U.S. patent application number 12/658452 was filed with the patent office on 2010-08-12 for methods and systems of using exosomes for determining phenotypes.
This patent application is currently assigned to Caris MPI, Inc.. Invention is credited to Michael Klass, Christine Kuslich, George Poste.
Application Number | 20100203529 12/658452 |
Document ID | / |
Family ID | 42170590 |
Filed Date | 2010-08-12 |
United States Patent
Application |
20100203529 |
Kind Code |
A1 |
Kuslich; Christine ; et
al. |
August 12, 2010 |
Methods and systems of using exosomes for determining
phenotypes
Abstract
Exosomes can be used for detecting biomarkers for diagnostic,
therapy-related or prognostic methods to identify phenotypes, such
as a condition or disease, for example, the stage or progression of
a disease. Cell-of-origin exosomes can be used in profiling of
physiological states or determining phenotypes. Biomarkers or
markers from cell-of-origin specific exosomes can be used to
determine treatment regimens for diseases, conditions, disease
stages, and stages of a condition, and can also be used to
determine treatment efficacy. Markers from cell-of-origin specific
exosomes can also be used to identify conditions of diseases of
unknown origin.
Inventors: |
Kuslich; Christine;
(Gilbert, AZ) ; Poste; George; (Cave Creek,
AZ) ; Klass; Michael; (Oro Valley, AZ) |
Correspondence
Address: |
WILSON SONSINI GODDRICH & ROSATI/ CARIS;LIFE SCIENCES
650 PAGE MILL ROAD
PALO ALTO
CA
94304
US
|
Assignee: |
Caris MPI, Inc.
Phoenix
AZ
|
Family ID: |
42170590 |
Appl. No.: |
12/658452 |
Filed: |
February 5, 2010 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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12591226 |
Nov 12, 2009 |
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12658452 |
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61114045 |
Nov 12, 2008 |
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61114058 |
Nov 12, 2008 |
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61114065 |
Nov 13, 2008 |
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61151183 |
Feb 9, 2009 |
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61278049 |
Oct 2, 2009 |
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61250454 |
Oct 9, 2009 |
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61253027 |
Oct 19, 2009 |
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Current U.S.
Class: |
435/6.12 ;
435/29 |
Current CPC
Class: |
C12Q 1/6811 20130101;
C12Q 1/6886 20130101; C12Q 1/6811 20130101; C12Q 1/6886 20130101;
G01N 33/57434 20130101; G01N 33/574 20130101; G01N 33/54326
20130101; G01N 33/57419 20130101; G01N 33/5023 20130101; C12Q
2600/112 20130101; G01N 33/57484 20130101; C12Q 2600/16 20130101;
G01N 33/6848 20130101; C12Q 2525/207 20130101; C12Q 2600/178
20130101; C12Q 2525/205 20130101 |
Class at
Publication: |
435/6 ;
435/29 |
International
Class: |
C12Q 1/68 20060101
C12Q001/68; C12Q 1/02 20060101 C12Q001/02 |
Claims
1. A method for determining a theranosis in a subject comprising:
(a) assessing a bio-signature for a microvesicle present in a
biological sample from a subject suffering a disorder, wherein said
assessing comprises assaying two or more polypeptides associated
with said microvesicle; and (b) determining whether said subject
may respond to a selected treatment based on said assessing in (a),
thereby determining a theranosis for said subject.
2. The method of claim 1, wherein said disorder is a cancer, an
autoimmune disorder or a cardiac disorder.
3. The method of claim 2, wherein said cancer is lung cancer,
breast cancer, or colon cancer.
4. The method of claim 1, wherein said assessing comprises
contacting said sample with at least three antibodies specific for
three different analytes.
5. The method of claim 1, wherein said microvesicle is assessed
with respect to at least one nucleic acid.
6. The method of claim 5, wherein said nucleic acid is DNA, mRNA,
microRNA, snoRNA, snRNA, rRNAs, tRNAs, siRNA, hnRNA, or shRNA.
7. The method of claim 5, wherein said nucleic acid is one or more
of miR-21, miR-205, miR-92, miR-147 or miR-574.
8. The method of claim 1, wherein said assessing comprises
multiplexed analysis of said microvesicle surface biomarkers.
9. The method of claim 8, wherein said assessing comprises
identifying at least one nucleic acid, peptide, protein, lipid,
antigen, carbohydrate, proteoglycan or a combination thereof.
10. The method of claim 1, wherein said determining comprises
obtaining a measure for an amount of said microvesicle.
11. The method of claim 8, wherein said assessing further comprises
multiplexed analysis of a plurality of nucleic acids in said
microvesicle.
12. The method of claim 11, wherein said plurality comprises at
least one microRNA in FIGS. 3-6, 19-24, 26-30, 32, 33, 36, 40-42,
47, 51, 53-57, and 60.
13. The method of claim 6, wherein said microRNA is selected from
miR-21, miR-205, miR-92, miR-147 or miR-574.
14. The method of claim 1, wherein said disorder is lung
cancer.
15. The method of claim 14, wherein said bio-signature comprises at
least one microRNA selected from miR-21, miR-205, miR-92, miR-147
or miR-574.
16. A method for determining biomarkers of a disorder in a subject
comprising: (a) assessing a bio-signature for a microvesicle
present in a biological sample from a subject suffering a disorder,
wherein said assessing comprises assaying two or more polypeptides
associated with said microvesicle; (b) determining whether one or
more biomarkers are present in said microvesicle; (c) comparing
said one or more biomarkers in said sample to a reference; and (d)
determining biomarkers of said disorder based on said
comparison.
17. The method of claim 16, wherein said disorder is a cancer, an
autoimmune disorder or a cardiac disorder.
18. The method of claim 17, wherein said cancer is lung cancer,
breast cancer, or colon cancer
19. The method of claim 16, wherein said assessing comprises
contacting said sample with at least three antibodies specific for
three different analytes.
20. The method of claim 16, wherein said one or biomarker is a
nucleic acid, peptide, protein, lipid, antigen, carbohydrate,
proteoglycan or a combination thereof.
21. The method of claim 20, wherein said nucleic acid is DNA, mRNA,
microRNA, snoRNA, snRNA, rRNAs, tRNAs, siRNA, hnRNA, or shRNA.
22. The method of claim 20, wherein the nucleic acid is one or more
of miR-21, miR-205, miR-92, miR-147 or miR-574.
23. The method of claim 16, wherein said assessing comprises
multiplexed analysis of surface markers of said microvesicle.
24. The method of claim 20, wherein said one or more biomarker
comprises at least one polypeptide and at least one nucleic
acid.
25. The method of claim 16, wherein said determining comprises
obtaining a measure for an amount of said microvesicle.
26. The method of claim 23, wherein said assessing further
comprises multiplexed analysis of a plurality of nucleic acids in
said microvesicle.
27. The method of claim 26, wherein said plurality comprises at
least one microRNA in FIGS. 3-6, 19-24, 26-30, 32, 33, 36, 40-42,
47, 51, 53-57, and 60.
28. The method of claim 27, wherein said microRNA is selected from
miR-21, miR-205, miR-92, miR-147 or miR-574.
29. The method of claim 16, wherein said disorder is lung
cancer.
30. The method of claim 29, wherein said bio-signature comprises at
least one microRNA selected from miR-21, miR-205, miR-92, miR-147
or miR-574.
Description
CROSS-REFERENCE
[0001] This application is a continuation of U.S. patent
application Ser. No. 12/591,226, filed Nov. 12, 2009, which claims
the benefit of U.S. Provisional Application Nos. 61/114,045, filed
Nov. 12, 2008; 61/114,058, filed Nov. 12, 2008; 61/114,065, filed
Nov. 13, 2008; 61/151,183, filed Feb. 9, 2009; 61/278,049, filed
Oct. 2, 2009; 61/250,454, filed Oct. 9, 2009; and 61/253,027 filed
Oct. 19, 2009, of which each is incorporated herein by reference in
its entirety. This application is also related to U.S. application
Ser. No. 12/609,847, filed Oct. 30, 2009, which claims the benefit
of U.S. Provisional Application Nos. 61/109,742, filed Oct. 30,
2008; 61/112,571, filed Nov. 7, 2008; 61/114,045, filed Nov. 12,
2008; 61/114,058, filed Nov. 12, 2008; 61/114,065, filed Nov. 13,
2008; 61/151,183, filed Feb. 9, 2009; 61/278,049, filed Oct. 2,
2009; 61/250,454, filed Oct. 9, 2009, and 61/253,027 filed Oct. 19,
2009, each of which is incorporated herein by reference in its
entirety.
BACKGROUND
[0002] A critical need for disease detection, prognostic
prediction, monitoring, and therapeutic decisions is improved assay
sensitivity and specificity. At present, biomarkers (proteins,
peptides, lipids, RNAs, DNA and modifications thereof for
disease-associated molecular alterations) for conditions and
diseases, such as cancer, rely almost exclusively on obtaining
samples from tissue to identify the condition or disease. Methods
to obtain these tissues of interest for analysis are often
invasive, costly and pose complication risks for the patient.
Furthermore, use of bodily fluids to isolate or detect biomarkers
often significantly dilutes a biomarker resulting in readouts that
lack requisite sensitivity. Additionally, most biomarkers are
produced in low or moderate amounts in normal tissues other than
the diseased tissue and thus this lack of specificity can also be
problematic.
[0003] The identification of specific biomarkers, such as DNA, RNA
and proteins can provide bio-signatures that are used for the
diagnosis, prognosis, or theranosis of a condition or disease.
Exosomes are a good source for assessing one or more biomarkers
that are present in or on the surface of an exosome. Furthermore,
identifying particular characteristics of an exosome (e.g., size,
surface antigens, cell-of-origin) can itself provide a diagnostic,
prognostic or theranostic readout.
[0004] The secretion of exosomes by cancerous cells, other diseased
cells, or at certain times of a physiological process (e.g.,
pregnancy), can be leveraged to aid in diagnosis as well as
individualized treatment decisions. Exosomes have been found in a
number of body fluids, including blood plasma, breast milk,
bronchoalveolar lavage fluid and urine. Exosomes also take part in
the communication between cells, as transport vehicles for
proteins, RNAs, DNAs, viruses, and prions.
[0005] The present inventions provide an improvement to prior art
assays. Products and process are provided for improved assay
sensitivity and specificity, allowing for disease detection,
prognostic prediction, disease monitoring, disease staging, and
therapeutic decision-making, as well as physiological state
identification. Products and processes include cell-of-origin
specific selection of exosomes and analysis of their protein
composition, RNA composition, DNA composition, lipid profile, and
relevant metabolic and/or epigenetic modifications of these
analytes. Also provided herein are methods of determining
biomarkers and bio-signatures for exosomes without prior
concentration or purification of the exosomes from a sample.
SUMMARY
[0006] Disclosed herein are methods and compositions for
characterizing a phenotype by analyzing an exosome. Characterizing
a phenotype for a subject or individual may include, but is not
limited to, the diagnosis of a disease or condition, the prognosis
of a disease or condition, the determination of a disease stage or
a condition stage, a drug efficacy, a physiological condition,
organ distress or organ rejection, disease or condition
progression, therapy-related association to a disease or condition,
or a specific physiological or biological state.
[0007] The method can include determining a bio-signature of an
exosome in a biological sample from a subject and characterizing a
phenotype in said subject based on the bio-signature.
Characterizing can also be based on determining the amount of
exosomes in a biological sample. The characterization of the
phenotype can be performed with at least 70, 80 or 90% sensitivity,
specificity, or both.
[0008] The exosome can be isolated or concentrated prior to
determining an exosomal bio-signature. The bio-signature can
comprise an expression level, presence, absence, mutation, copy
number variation, truncation, duplication, insertion, modification,
sequence variation, or molecular association of a biomarker. The
bio-signature can also comprise quantification of isolated
exosomes, temporal evaluation of the variation in exosomal
half-life, circulating exosomal half-life, exosomal metabolic
half-life, or the activity of an exosome.
[0009] The exosome can be a cell-of-origin specific exosome. The
exosome can be derived from a tumor or cancer cell. The
cell-of-origin for an exosome can be a lung, pancreas, stomach,
intestine, bladder, kidney, ovary, testis, skin, colorectal,
breast, prostate, brain, esophagus, liver, placenta, or fetal
cell.
[0010] One or more biomarkers of an exosome can be assessed for
characterizing a phenotype. The biomarker can be a nucleic acid,
peptide, protein, lipid, antigen, carbohydrate or proteoglycan,
such as DNA or RNA. The RNA can be mRNA, miRNA, snoRNA, snRNA,
rRNAs, tRNAs, siRNA, hnRNA, or shRNA. The biomarker can be an
antigen selected from FIG. 1, or a biomarker selected from a table
listed in FIG. 3-60. One or more biomarkers can be assessed and
used to characterize a phenotype. The bio-signature can comprise
one or more miRNAs selected from the group consisting of: miR-9,
miR-629, miR-141, miR-671-3p, miR-491, miR-182, miR-125a-3p,
miR-324-5p, miR-148b, and miR-222. The bio-signature can be used to
characterize a phenotype, such as prostate cancer. Other biomarkers
can be selected from the group consisting of: CD9, PSCA (prostate
stem cell antigen), TNFR, CD63, MFG-E8, EpCam, Rab, CD81, STEAP,
PCSA (prostate cell surface antigen), PSM (or PSMA, prostate
specific membrane antigen), 5T4, CD59, CD66, CD24 and B7H3.
Detecting a plurality of biomarkers can provide greater sensitivity
or specificity as compared to detecting less than a plurality of
biomarkers.
[0011] Methods of multiplexing, or multiplex analysis of, a
plurality of exosomes are also provided. Multiplexing a plurality
of exosomes can comprise applying said plurality of exosomes to a
plurality of particles, wherein each particle of a subset of the
plurality of particles is coupled to a different capture agent,
capturing a subset of said plurality of exosomes; and, detecting
one or more biomarkers of the captured exosomes. Multiplexing can
also be performed using an array, wherein the capture agents are
attached to an array instead of particles or beads.
[0012] Also provided herein are isolated exosomes. The isolated
exosome can comprise any one or more biomarkers disclosed herein,
such as a specific combination of biomarkers. Compositions
comprising the one or more isolated exosomes are also provided. The
composition can comprise a substantially enriched population of
exosomes. The population of exosomes can be substantially
homogeneous for one or more specific biomarkers, for a particular
bio-signature, or derived from a specific cell type.
[0013] Detection systems, microfluidic devices, and kits for
assessing one or more exosomes, such as for the isolation,
separation, or detection of one or more exosomes, are also
provided.
INCORPORATION BY REFERENCE
[0014] All publications and patent applications mentioned in this
specification are herein incorporated by reference to the same
extent as if each individual publication or patent application was
specifically and individually indicated to be incorporated by
reference.
BRIEF DESCRIPTION OF THE DRAWINGS
[0015] FIG. 1 (a)-(g) represents a table which lists exemplary
cancers by lineage, group comparisons of cells/tissue, and specific
disease states and antigens specific to those cancers, group
cell/tissue comparisons and specific disease states. Furthermore,
the antigen can be a biomarker. The one or more biomarkers can be
present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0016] FIG. 2 (a)-(f) represents a table which lists exemplary
cancers by lineage, group comparisons of cells/tissue, and specific
disease states and binding agents specific to those cancers, group
cell/tissue comparisons and specific disease states.
[0017] FIG. 3 (a)-(b) represents a table which lists exemplary
breast cancer biomarkers that can be derived and analyzed from
exosomes specific to breast cancer to create a breast cancer
specific exosome bio-signature. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0018] FIG. 4 (a)-(b) represents a table which lists exemplary
ovarian cancer biomarkers that can be derived from and analyzed
from exosomes specific to ovarian cancer to create an ovarian
cancer specific exosome bio-signature. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0019] FIG. 5 represents a table which lists exemplary lung cancer
biomarkers that can be derived from and analyzed from exosomes
specific to lung cancer to create a lung cancer specific exosome
bio-signature. Furthermore, the one or more biomarkers can be
present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0020] FIG. 6 (a)-(d) represents a table which lists exemplary
colon cancer biomarkers that can be derived from and analyzed from
exosomes specific to colon cancer to create a colon cancer specific
exosome bio-signature. Furthermore, the one or more biomarkers can
be present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0021] FIG. 7 represents a table which lists exemplary biomarkers
specific to an adenoma versus a hyperplastic polyp that can be
derived and analyzed from exosomes specific to adenomas versus
hyperplastic polyps. Furthermore, the one or more biomarkers can be
present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0022] FIG. 8 is a table which lists exemplary biomarkers specific
to inflammatory bowel disease (IBD) versus normal tissue that can
be derived and analyzed from exosomes specific to inflammatory
bowel disease versus normal tissue. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0023] FIG. 9(a)-(c) represents a table which lists exemplary
biomarkers specific to an adenoma versus colorectal cancer (CRC)
that can be derived and analyzed from exosomes specific to adenomas
versus colorectal cancer. Furthermore, the one or more biomarkers
can be present or absent, underexpressed or overexpressed, mutated,
or modified, such as epigentically modified or post-translationally
modified.
[0024] FIG. 10 represents a table which lists exemplary biomarkers
specific to IBD versus CRC that can be derived and analyzed from
exosomes specific to IBD versus CRC. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0025] FIG. 11 (a)-(b) represents a table which lists exemplary
biomarkers specific to CRC Dukes B versus Dukes C-D that can be
derived and analyzed from exosomes specific to CRC Dukes B versus
Dukes C-D. Furthermore, the one or more biomarkers can be present
or absent, underexpressed or overexpressed, mutated, or modified,
such as epigentically modified or post-translationally
modified.
[0026] FIG. 12(a)-(d) represents a table which lists exemplary
biomarkers specific to an adenoma with low grade dysplasia versus
an adenoma with high grade dysplasia that can be derived and
analyzed from exosomes specific to an adenoma with low grade
dysplasia versus an adenoma with high grade dysplasia. Furthermore,
the one or more biomarkers can be present or absent, underexpressed
or overexpressed, mutated, or modified, such as epigentically
modified or post-translationally modified.
[0027] FIG. 13(a)-(b) represents a table which lists exemplary
biomarkers specific to ulcerative colitis (UC) versus Crohn's
Disease (CD) that can be derived and analyzed from exosomes
specific to UC versus CD. Furthermore, the one or more biomarkers
can be present or absent, underexpressed or overexpressed, mutated,
or modified, such as epigentically modified or post-translationally
modified.
[0028] FIG. 14 represents a table which lists exemplary biomarkers
specific to a hyperplastic polyp versus normal tissue that can be
derived and analyzed from exosomes specific to a hyperplastic polyp
versus normal tissue. Furthermore, the one or more biomarkers can
be present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0029] FIG. 15 is a table which lists exemplary biomarkers specific
to an adenoma with low grade dysplasia versus normal tissue that
can be derived and analyzed from exosomes specific to an adenoma
with low grade dysplasia versus normal tissue. Furthermore, the one
or more biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0030] FIG. 16 is a table which lists exemplary biomarkers specific
to an adenoma versus normal tissue that can be derived and analyzed
from exosomes specific to an adenoma versus normal tissue.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0031] FIG. 17 represents a table which lists exemplary biomarkers
specific to CRC versus normal tissue that can be derived and
analyzed from exosomes specific to CRC versus normal tissue.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0032] FIG. 18 is a table which lists exemplary biomarkers specific
to benign prostatic hyperplasia that can be derived from and
analyzed from exosomes specific to benign prostatic hyperplasia.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0033] FIG. 19(a)-(c) represents a table which lists exemplary
prostate cancer biomarkers that can be derived from and analyzed
from exosomes specific to prostate cancer to create a prostate
cancer specific exosome bio-signature. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0034] FIG. 20(a)-(c) represents a table which lists exemplary
melanoma biomarkers that can be derived from and analyzed from
exosomes specific to melanoma to create a melanoma specific exosome
bio-signature. Furthermore, the one or more biomarkers can be
present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0035] FIG. 21(a)-(b) represents a table which lists exemplary
pancreatic cancer biomarkers that can be derived from and analyzed
from exosomes specific to pancreatic cancer to create a pancreatic
cancer specific exosome bio-signature. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0036] FIG. 22 is a table which lists exemplary biomarkers specific
to brain cancer that can be derived from and analyzed from exosomes
specific to brain cancer to create a brain cancer specific exosome
bio-signature. Furthermore, the one or more biomarkers can be
present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0037] FIG. 23(a)-(b) represents a table which lists exemplary
psoriasis biomarkers that can be derived from and analyzed from
exosomes specific to psoriasis to create a psoriasis specific
exosome bio-signature. Furthermore, the one or more biomarkers can
be present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0038] FIG. 24(a)-(c) represents a table which lists exemplary
cardiovascular disease biomarkers that can be derived from and
analyzed from exosomes specific to cardiovascular disease to create
a cardiovascular disease specific exosome bio-signature.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0039] FIG. 25 is a table which lists exemplary biomarkers specific
to hematological malignancies that can be derived from and analyzed
from exosomes specific to hematological malignancies to create a
specific exosome bio-signature for hematological malignancies.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0040] FIG. 26(a)-(b) represents a table which lists exemplary
biomarkers specific to B-Cell Chronic Lymphocytic Leukemias that
can be derived from and analyzed from exosomes specific to B-Cell
Chronic Lymphocytic Leukemias to create a specific exosome
bio-signature for B-Cell Chronic Lymphocytic Leukemias.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0041] FIG. 27 is a table which lists exemplary biomarkers specific
to B-Cell Lymphoma and B-Cell Lymphoma-DLBCL that can be derived
from and analyzed from exosomes specific to B-Cell Lymphoma and
B-Cell Lymphoma-DLBCL. Furthermore, the one or more biomarkers can
be present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0042] FIG. 28 represents a table which lists exemplary biomarkers
specific to B-Cell Lymphoma-DLBCL-germinal center-like and B-Cell
Lymphoma-DLBCL-activated B-cell-like and B-cell lymphoma-DLBCL that
can be derived from and analyzed from exosomes specific to B-Cell
Lymphoma-DLBCL-germinal center-like and B-Cell
Lymphoma-DLBCL-activated B-cell-like and B-cell lymphoma-DLBCL.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0043] FIG. 29 represents a table which lists exemplary Burkitt's
lymphoma biomarkers that can be derived from and analyzed from
exosomes specific to Burkitt's lymphoma to create a Burkitt's
lymphoma specific exosome bio-signature. Furthermore, the one or
more biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0044] FIG. 30(a)-(b) represents a table which lists exemplary
hepatocellular carcinoma biomarkers that can be derived from and
analyzed from exosomes specific to hepatocellular carcinoma to
create a specific exosome bio-signature for hepatocellular
carcinoma. Furthermore, the one or more biomarkers can be present
or absent, underexpressed or overexpressed, mutated, or modified,
such as epigentically modified or post-translationally
modified.
[0045] FIG. 31 is a table which lists exemplary biomarkers for
cervical cancer that can be derived from and analyzed from exosomes
specific to cervical cancer. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0046] FIG. 32 represents a table which lists exemplary biomarkers
for endometrial cancer that can be derived from and analyzed from
exosomes specific to endometrial cancer to create a specific
exosome bio-signature for endometrial cancer. Furthermore, the one
or more biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0047] FIG. 33(a)-(b) represents a table which lists exemplary
biomarkers for head and neck cancer that can be derived from and
analyzed from exosomes specific to head and neck cancer to create a
specific exosome bio-signature for head and neck cancer.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0048] FIG. 34 represents a table which lists exemplary biomarkers
for inflammatory bowel disease (IBD) that can be derived from and
analyzed from exosomes specific to IBD to create a specific exosome
bio-signature for IBD. Furthermore, the one or more biomarkers can
be present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0049] FIG. 35 is a table which lists exemplary biomarkers for
diabetes that can be derived from and analyzed from exosomes
specific to diabetes to create a specific exosome bio-signature for
diabetes. Furthermore, the one or more biomarkers can be present or
absent, underexpressed or overexpressed, mutated, or modified, such
as epigentically modified or post-translationally modified.
[0050] FIG. 36 is a table which lists exemplary biomarkers for
Barrett's Esophagus that can be derived from and analyzed from
exosomes specific to Barrett's Esophagus to create a specific
exosome bio-signature for Barrett's Esophagus. Furthermore, the one
or more biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0051] FIG. 37 is a table which lists exemplary biomarkers for
fibromyalgia that can be derived from and analyzed from exosomes
specific to fibromyalgia. Furthermore, the one or more biomarkers
can be present or absent, underexpressed or overexpressed, mutated,
or modified, such as epigentically modified or post-translationally
modified.
[0052] FIG. 38 represents a table which lists exemplary biomarkers
for stroke that can be derived from and analyzed from exosomes
specific to stroke to create a specific exosome bio-signature for
stroke. Furthermore, the one or more biomarkers can be present or
absent, underexpressed or overexpressed, mutated, or modified, such
as epigentically modified or post-translationally modified.
[0053] FIG. 39 is a table which lists exemplary biomarkers for
Multiple Sclerosis (MS) that can be derived from and analyzed from
exosomes specific to MS to create a specific exosome bio-signature
for MS. Furthermore, the one or more biomarkers can be present or
absent, underexpressed or overexpressed, mutated, or modified, such
as epigentically modified or post-translationally modified.
[0054] FIG. 40(a)-(b) represents a table which lists exemplary
biomarkers for Parkinson's Disease that can be derived from and
analyzed from exosomes specific to Parkinson's Disease to create a
specific exosome bio-signature for Parkinson's Disease.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0055] FIG. 41 represents a table which lists exemplary biomarkers
for Rheumatic Disease that can be derived from and analyzed from
exosomes specific to Rheumatic Disease to create a specific exosome
bio-signature for Rheumatic Disease. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0056] FIG. 42(a)-(b) represents a table which lists exemplary
biomarkers for Alzheimers Disease that can be derived from and
analyzed from exosomes specific to Alzheimers Disease to create a
specific exosome bio-signature for Alzheimers Disease. Furthermore,
the one or more biomarkers can be present or absent, underexpressed
or overexpressed, mutated, or modified, such as epigentically
modified or post-translationally modified.
[0057] FIG. 43 is a table which lists exemplary biomarkers for
Prion Diseases that can be derived from and analyzed from exosomes
specific to Prion Diseases to create a specific exosome
bio-signature for Prion Diseases. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0058] FIG. 44 represents a table which lists exemplary biomarkers
for sepsis that can be derived from and analyzed from exosomes
specific to sepsis to create a specific exosome bio-signature for
sepsis. Furthermore, the one or more biomarkers can be present or
absent, underexpressed or overexpressed, mutated, or modified, such
as epigentically modified or post-translationally modified.
[0059] FIG. 45 is a table which lists exemplary biomarkers for
chronic neuropathic pain that can be derived from and analyzed from
exosomes specific to chronic neuropathic pain. Furthermore, the one
or more biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0060] FIG. 46 is a table which lists exemplary biomarkers for
peripheral neuropathic pain that can be derived from and analyzed
from exosomes specific to peripheral neuropathic pain. Furthermore,
the one or more biomarkers can be present or absent, underexpressed
or overexpressed, mutated, or modified, such as epigentically
modified or post-translationally modified.
[0061] FIG. 47 represents a table which lists exemplary biomarkers
for Schizophrenia that can be derived from and analyzed from
exosomes specific to Schizophrenia to create a specific exosome
bio-signature for Schizophrenia. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0062] FIG. 48 is a table which lists exemplary biomarkers for
bipolar disorder or disease that can be derived from and analyzed
from exosomes specific to bipolar disorder to create a specific
exosome bio-signature for bipolar disorder. Furthermore, the one or
more biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0063] FIG. 49 is a table which lists exemplary biomarkers for
depression that can be derived from and analyzed from exosomes
specific to depression to create a specific exosome bio-signature
for depression. Furthermore, the one or more biomarkers can be
present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0064] FIG. 50 is a table which lists exemplary biomarkers for
gastrointestinal stromal tumor (GIST) that can be derived from and
analyzed from exosomes specific to GIST to create a specific
exosome bio-signature for GIST. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0065] FIG. 51(a)-(b) represent sa table which lists exemplary
biomarkers for renal cell carcinoma (RCC) that can be derived from
and analyzed from exosomes specific to RCC to create a specific
exosome bio-signature for RCC. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0066] FIG. 52 is a table which lists exemplary biomarkers for
cirrhosis that can be derived from and analyzed from exosomes
specific to cirrhosis to create a specific exosome bio-signature
for cirrhosis. Furthermore, the one or more biomarkers can be
present or absent, underexpressed or overexpressed, mutated, or
modified, such as epigentically modified or post-translationally
modified.
[0067] FIG. 53 is a table which lists exemplary biomarkers for
esophageal cancer that can be derived from and analyzed from
exosomes specific to esophageal cancer to create a specific exosome
bio-signature for esophageal cancer. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0068] FIG. 54 is a table which lists exemplary biomarkers for
gastric cancer that can be derived from and analyzed from exosomes
specific to gastric cancer to create a specific exosome
bio-signature for gastric cancer. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0069] FIG. 55 is a table which lists exemplary biomarkers for
autism that can be derived from and analyzed from exosomes specific
to autism to create a specific exosome bio-signature for autism.
Furthermore, the one or more biomarkers can be present or absent,
underexpressed or overexpressed, mutated, or modified, such as
epigentically modified or post-translationally modified.
[0070] FIG. 56 is a table which lists exemplary biomarkers for
organ rejection that can be derived from and analyzed from exosomes
specific to organ rejection to create a specific exosome
bio-signature for organ rejection. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0071] FIG. 57 is a table which lists exemplary biomarkers for
methicillin-resistant staphylococcus aureus that can be derived
from and analyzed from exosomes specific to methicillin-resistant
staphylococcus aureus to create a specific exosome bio-signature
for methicillin-resistant staphylococcus aureus. Furthermore, the
one or more biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0072] FIG. 58 is a table which lists exemplary biomarkers for
vulnerable plaque that can be derived from and analyzed from
exosomes specific to vulnerable plaque to create a specific exosome
bio-signature for vulnerable plaque. Furthermore, the one or more
biomarkers can be present or absent, underexpressed or
overexpressed, mutated, or modified, such as epigentically modified
or post-translationally modified.
[0073] FIG. 59(a)-(i) is a table which lists exemplary gene fusions
that can be derived from, or analyzed from exosomes. The gene
fusion can be biomarker, and can be present or absent,
underexpressed or overexpressed, or modified, such as epigentically
modified or post-translationally modified.
[0074] FIG. 60(a)-(b) is a table of genes and their associated
miRNAs, of which the gene, such as the mRNA of the gene, their
associated miRNAs, or any combination thereof, can be used as one
or more biomarkers that can be analyzed from exosomes. Furthermore,
the one or more biomarkers can be present or absent, underexpressed
or overexpressed, mutated, or modified.
[0075] FIG. 61 is a flow chart of an exemplary method disclosed
herein.
[0076] FIG. 62 illustrates a computer system that can be used in
some exemplary embodiments of the invention.
[0077] FIG. 63 illustrates results obtained from screening for
proteins on exosomes, which can be used a biomarkers for the
exosomes and antibodies to the proteins can be used as binding
agents. Examples of the proteins identified include Bcl-XL, ERCC1,
Keratin 15, CD81/TAPA-1, CD9, Epithelial Specific Antigen (ESA),
and Mast Cell Chymase. The one or more biomarkers can be present or
absent, underexpressed or overexpressed, mutated, or modified.
[0078] FIG. 64 illustrates a particle based method of isolating
exosomes. (A) is a schematic of a bead coated with a capture
antibody, which captures exosomes expressing that protein. In this
schematic, the capture antibody is for an exosomal protein that is
not specific for exosomes derived from cancer cells ("cancer
exosome"). The detection antibody binds to the captured exosome and
fluoresces a signal. The detection antibody in this example detects
an antigen that is associated with cancer exosomes. (B) is an
example of a screening scheme that can be performed by multiplexing
using the beads as shown in (A).
[0079] FIG. 65 depicts scanning electron micrographs (SEMs) of
EpCam conjugated beads that have been incubated with VCaP exosomes.
(A) A glass slide was coated with poly-L-lysine and incubated with
the bead solution. After attachment, the beads were (i) fixed
sequentially with glutaraldehyde and osmium tetroxide, 30 min per
fix step with a few washes in between; (ii) gradually dehydrated in
acetone, 20% increments, about 5-7 min per step; (iii)
critical-point dried; and (iv) sputter-coated with gold. (B) Left:
depicts a higher magnification of exosomes on an EpCam coated bead
as in (A). Right: depicts exosomes isolated by ultracentrifugation
and adhered to a poly-L-lysine coated glass slide and fixed and
stained as in (A).
[0080] FIG. 66 is a schematic of an exosome protein expression
patterns. Different proteins are typically not distributed evenly
or uniformly on exosome shell. Exosome-specific proteins are
typically more common, while cancer-specific proteins are less
common. Exosome capture can be more easily accomplished using a
more common, less cancer-specific protein, and cancer-specific
proteins used in the detection phase.
[0081] FIG. 67 illustrates the method of depicting the results
using the bead based method of detecting exosomes from a subject.
(A) For an individual patient, a graph of the bead enumeration and
signal intensity using a screening scheme as depicted in FIG. 64B,
where .about.100 capture beads are used for each capture/detection
combination assay per patient. For a given patient, the output
shows number of beads detected vs. intensity of signal. The number
of beads captured at a given intensity is an indication of how
frequently an exosome expresses the detection protein at that
intensity. The more intense the signal for a given bead, the
greater the expression of the detection protein. (B) is a
normalized graph obtained by combining normal patients into one
curve and cancer patients into another, and using bio-statistical
analysis to differentiate the curves. Data from each individual is
normalized to account for variation in the number of beads read by
the detection machine, added together, and then normalized again to
account for the different number of samples in each population.
[0082] FIG. 68 illustrates prostate cancer bio-signatures. (A) is a
histogram of intensity values collected from a multiplexing
experiment using the Luminex platform, where beads were
functionalized with CD63 antibody, incubated with exosomes purified
from patient plasma, and then labeled with a phycoerythrin (PE)
conjugated EpCam antibody. The darker shaded bars (blue) represent
the population from 12 normal subjects and the lighter shaded bars
(green) are from 7 stage 3 prostate cancer patients. (B) is a
normalized graph for each of the histograms shown in (A), as
described in FIG. 67. The distributions are of a Gaussian fit to
intensity values from the Luminex results of (A) for both prostate
patient samples and normal samples. (C) is an example of one of the
prostate bio-signatures shown in (B), the CD63 versus CD63
bio-signature (upper graph) where CD63 is used as the detector and
capture antibody. The lower three panels show the results of flow
cytometry on three prostate cancer cell lines (VCaP, LNcap, and
22RV1). Points above the horizontal line indicate beads that
captured exosomes with CD63 that contain B7H3. Beads to the right
of the vertical line indicate beads that have captured exosomes
with CD63 that have PSMA. Those beads that are above and to the
right of the lines have all three antigens. CD63 is a surface
protein that is associated with exosomes, PSMA is surface protein
that is associated with prostate cells, and B7H3 is a surface
protein that is associated with aggressive cancers (specifically
prostate, ovarian, and non-small-cell lung). The combination of all
three antigens together identifies exosomes that are from cancer
prostate cells. The majority of CD63 expressing prostate cancer
exosomes also have prostate-specific membrane antigen, PSMA, and
B7H3 (implicated in regulation of tumor cell migration and invasion
and an indicator of aggressive cancer as well as clinical outcome).
(D) is a prostate cancer exosome topography. The upper panels show
the results of capturing and labeling with CD63, CD9, and CD81 in
various combinations. Almost all points are in the upper right
quadrant indicating that these three markers are highly coupled. If
an exosome has one of them, it typically has all three. The lower
row depicts the results of capturing cell line exosomes with B7H3
and labeling with CD63 and PSMA. Both VCaP and 22RV1 show that most
exosomes captured with B7H3 also have CD63, and that there are two
populations, those with PSMA and those without. The presence of
B7H3 may be an indication of how aggressive the cancer is, as LNcap
does not have a high amount of B7H3 containing exosomes (not many
spots with CD63). LnCap is an earlier stage prostate cancer
analogue cell line.
[0083] FIG. 69: illustrates colon cancer bio-signatures. (A) shows
histograms of intensity values collected from various multiplexing
experiments using the Luminex platform, where beads were
functionalized with a capture antibody, incubated with exosomes
purified form patient plasma, and then labeled with a detector
antibody. The darker shaded bars (blue) represent the population
from normals and the lighter shaded bars (green) are from colon
cancer patients. (B) shows a normalized graph for each of the
histograms shown in (A). (C) shows a histogram of intensity values
collected from a Luminex experiment where beads where
functionalized with CD66 antibody (the capture antibody), incubated
with exosomes purified from patient plasma, and then labeled with a
PE conjugated EpCam antibody (the detector antibody). The red
population is from 6 normals and the green is from 21 colon cancer
patients. Data from each individual was normalized to account for
variation in the number of beads read by the Luminex machine, added
together, and then normalized again to account for the different
number of samples in each population.
[0084] FIG. 70 illustrates multiple detectors can increase the
signal of exosome detection. (A) Median intensity values are
plotted as a function of purified exosome concentration from the
VCaP cell line when labeled with a variety of prostate specific PE
conjugated antibodies. Exosomes captured with EpCam (left graphs)
or PCSA (right graphs) and the various proteins detected by the
detector antibody are listed to the right of each graph. In both
cases the combination of CD9 and CD63 gives the best increase in
signal over background (bottom graphs depicting percent increase).
The combination of CD9 and CD63 gave about 200% percent increase
over background. (B) further illustrates prostate cancer/prostate
exosome-specific marker multiplexing improves detection of prostate
cancer cell derived exosomes. Median intensity values are plotted
as a function of purified exosome concentration from the VCaP cell
line when labeled with a variety of prostate specific PE conjugated
antibodies. Exosomes captured with PCSA (left) and exosomes
captured with EpCam (right) are depicted. In both cases the
combination of B7H3 and PSMA gives the best increase in signal over
background.
[0085] FIG. 71 illustrates a colon cancer bio-signature for colon
cancer by stage, using CD63 detector and CD63 capture. The
histograms of intensities from exosomes captured with CD63 coated
beads and labeled with CD63 conjugated PE. There are 6 patients in
the control group (A), 4 in stage I (B), 5 in stage 11 (C), 8 in
stage III (D), and 4 stage 1V (E). Data from each individual was
normalized to account for variation in the number of beads read by
the Luminex machine, added together, and then normalized again to
account for the different number of samples in each population
(F).
[0086] FIG. 72: illustrates colon cancer bio-signature for colon
cancer by stage, using EpCam detector and CD9 capture. The
histograms of intensities are from exosomes captured with CD9
coated beads and labeled with EpCam. There are patients in the (A)
control group, (B) stage I, (C) stage II, (D) stage III, and (E)
stage 1V. Data from each individual was normalized to account for
variation in the number of beads read by the Luminex machine, added
together, and then normalized again to account for the different
number of samples in each population (F).
[0087] FIG. 73: illustrates (A) the sensitivity and specificity,
and the confidence level, for detecting prostate cancer using
antibodies to the listed proteins listed as the detector and
capture antibodies. CD63, CD9, and CD81 are general exosome markers
and EpCam is a cancer marker. The individual results are depicted
in (B) for EpCam versus CD63, with 99% confidence, 100% (n=8)
cancer patient samples were different from the Generalized Normal
Distribution and with 99% confidence, 77% (n=10) normal patient
samples were not different from the Generalized Normal
Distribution; (C) for CD81 versus CD63, with 99% confidence, 90%
(n=5) cancer patient samples were different from the Generalized
Normal Distribution; with 99% confidence, 77% (n=10) normal patient
samples were not different from the Generalized Normal
Distribution; (D) for CD63 versus CD63, with 99% confidence, 60%
(n=5) cancer patient samples were different from the Generalized
Normal Distribution; with 99% confidence, 80% (n=10) normal patient
samples were not different from the Generalized Normal
Distribution; (E) for CD9 versus CD63, with 99% confidence, 90%
(n=5) cancer patient samples were different from the Generalized
Normal Distribution; with 99% confidence, 77% (n=10) normal patient
samples were not different from the Generalized Normal
Distribution.
[0088] FIG. 74 illustrates (A) the sensitivity and the confidence
level for detecting colon cancer using antibodies to the listed
proteins listed as the detector and capture antibodies. CD63, CD9
are general exosome markers, EpCam is a cancer marker, and CD66 is
a colon marker. The individual results are depicted in (B) for
EpCam versus CD63, with 99% confidence, 95% (n=20) cancer patient
samples were different from the Generalized Normal Distribution;
with 99% confidence, 100% (n=6) normal patient samples were not
different from the Generalized Normal Distribution; (C) for EpCam
versus CD9, with 99% confidence, 90% (n=20) cancer patient samples
were different from the Generalized Normal Distribution; with 99%
confidence, 77% (n=6) normal patient samples were not different
from the Generalized Normal Distribution; (D) for CD63 versus CD63,
with 99% confidence, 60% (n=20) cancer patient samples were
different from the Generalized Normal Distribution; with 99%
confidence, 80% (n=6) normal patient samples were not different
from the Generalized Normal Distribution; (E) for CD9 versus CD63,
with 99% confidence, 90% (n=20) cancer patient samples were
different from the Generalized Normal Distribution; with 99%
confidence, 77% (n=6) normal patient samples were not different
from the Generalized Normal Distribution; (F) for CD66 versus CD9,
with 99% confidence, 90% (n=20) cancer patient samples were
different from the Generalized Normal Distribution; with 99%
confidence, 77% (n=6) normal patient samples were not different
from the Generalized Normal Distribution.
[0089] FIG. 75 illustrates the capture of prostate cancer
cells-derived exosomes from plasma with EpCam by assessing
TMPRSS2-ERG expression. (A) Graduated amounts of VCAP purified
exosomes were spiked into normal plasma. Exosomes were isolated
using Dynal beads with either EPCAM antibody or its isotype
control. RNA from the exosomes was isolated and the expression of
the TMPRSS2:ERG fusion transcript was measured using qRT-PCR. (B)
VCaP purified exosomes were spiked into normal plasma and then
incubated with Dynal magnetic beads coated with either the EpCam or
isotype control antibody. RNA was isolated directly from the Dynal
beads. Equal volumes of RNA from each sample were used for RT-PCR
and subsequent Taqman assays. (C) Cycle threshold (CT) differences
of the SPINK1 and GAPDH transcripts between 22RV1 exosomes captured
with EpCam and IgG2 isotype negative control beads. Higher CT
values indicate lower transcript expression.
[0090] FIG. 76: illustrates the top ten differentially expressed
microRNAs between VCaP prostate cancer cell derived exosomes and
normal plasma exosomes. VCAP cell line exosomes and exosomes from
normal plasma were isolated via ultracentrifugation followed by RNA
isolation. MicroRNAs were profiled using qRT-PCR analysis. Prostate
cancer cell line derived exosomes have higher levels (lower CT
values) of the indicated microRNAs as depicted in the bar graph (A)
and table (B).
[0091] FIG. 77 depicts a bar graph of miR-21 expression with CD9
bead capture. 1 ml of plasma from prostate cancer patients, 250
ng/ml of LNCaP, or normal purified exosomes was incubated with CD9
coated Dynal beads. The RNA was isolated from the beads and the
bead supernatant. One sample (#6) was also uncaptured for
comparison. MiR-21 expression was measured with qRT-PCR and the
mean CT values for each sample compared. CD9 capture improves the
detection of miR-21 in prostate cancer samples.
[0092] FIG. 78 depicts a bar graph of miR-141 expression with CD9
bead capture. The experiment was performed as in FIG. 77, with
miR-141 expression measured with qRT-PCR instead of miR-21.
[0093] FIG. 79 depicts a table of the sensitivity and specificity
for different prostate signatures. "Exosome" lists the threshold
value or reference value of exosome levels, "Prostate" lists the
threshold value or reference value used for prostate exosomes,
"Cancer-1," "Cancer-2," and "Cancer-3" lists the threshold values
or reference values for the three different bio-signatures for
prostate cancer, the "QC-1" and "QC-2" columns list the threshold
values or reference values for quality control, or reliability, and
the last four columns list the specificities and sensitivities for
benign prostate hyperplasia (BPH).
DETAILED DESCRIPTION
[0094] Disclosed herein are products and processes for
characterizing a phenotype of an individual by analyzing exosomes.
A phenotype can be any observable characteristic or trait of a
subject, such as a disease or condition, a disease stage or
condition stage, susceptibility to a disease or condition,
prognosis of a disease stage or condition, a physiological state;
or response to therapeutics. A phenotype can result from a
subject's gene expression as well as the influence of environmental
factors and the interactions between the two, as well as from
epigenetic modifications to nucleic acid sequences
[0095] A phenotype in a subject can be characterized by obtaining a
biological sample from said subject and analyzing one or more
exosomes from the sample. For example, characterizing a phenotype
for a subject or individual may include detecting a disease or
condition (including pre-symptomatic early stage detecting),
determining the prognosis, diagnosis, or theranosis of a disease or
condition, or determining the stage or progression of a disease or
condition. Characterizing a phenotype can also include identifying
appropriate treatments or treatment efficacy for specific diseases,
conditions, disease stages and condition stages, predictions and
likelihood analysis of disease progression, particularly disease
recurrence, metastatic spread or disease relapse. A phenotype can
also be a clinically distinct type or subtype of a condition or
disease, such as a cancer or tumor. Phenotype determination can
also be a determination of a physiological condition, or an
assessment of organ distress or organ rejection, such as
post-transplantation. The products and processes described herein
allow assessment of a subject on an individual basis, which can
provide benefits of more efficient and economical decisions in
treatment.
[0096] The phenotype can be a disease or condition such as listed
in Table 1. For example, the phenotype can be a tumor, neoplasm, or
cancer. A cancer detected or assessed by products or processes
described herein includes, but is not limited to, breast cancer,
ovarian cancer, lung cancer, colon cancer, hyperplastic polyp,
adenoma, colorectal cancer, high grade dysplasia, low grade
dysplasia, prostatic hyperplasia, prostate cancer, melanoma,
pancreatic cancer, brain cancer (such as a glioblastoma),
hematological malignancy, hepatocellular carcinoma, cervical
cancer, endometrial cancer, head and neck cancer, esophageal
cancer, gastrointestinal stromal tumor (GIST), renal cell carcinoma
(RCC) or gastric cancer. The colorectal cancer can be CRC Dukes B
or Dukes C-D. The hematological malignancy can be B-Cell Chronic
Lymphocytic Leukemia, B-Cell Lymphoma-DLBCL, B--Cell
Lymphoma-DLBCL-germinal center-like, B-Cell
Lymphoma-DLBCL-activated B-cell-like, and Burkitt's lymphoma. The
phenotype may also be a premalignant condition, such as Barrett's
Esophagus.
[0097] The phenotype can also be an inflammatory disease, immune
disease, or autoimmune disease. For example, the disease may be
inflammatory bowel disease (IBD), Crohn's disease (CD), ulcerative
colitis (UC), pelvic inflammation, vasculitis, psoriasis, diabetes,
autoimmune hepatitis, Multiple Sclerosis, Myasthenia Gravis, Type I
diabetes, Rheumatoid Arthritis, Psoriasis, Systemic Lupus
Erythematosis (SLE), Hashimoto's Thyroiditis, Grave's disease,
Ankylosing Spondylitis Sjogrens Disease, CREST syndrome,
Scleroderma, Rheumatic Disease, organ rejection, Primary Sclerosing
Cholangitis, or sepsis.
[0098] The phenotype can also be a cardiovascular disease, such as
atherosclerosis, congestive heart failure, vulnerable plaque,
stroke, or ischemia. The cardiovascular disease or condition can be
high blood pressure, stenosis, vessel occlusion or a thrombotic
event.
[0099] The phenotype can also be a neurological disease, such as
Multiple Sclerosis (MS), Parkinson's Disease (PD), Alzheimer's
Disease (AD), schizophrenia, bipolar disorder, depression, autism,
Prion Disease, Pick's disease, dementia, Huntington disease (HD),
Down's syndrome, cerebrovascular disease, Rasmussen's encephalitis,
viral meningitis, neurospsychiatric systemic lupus erythematosus
(NPSLE), amyotrophic lateral sclerosis, Creutzfeldt-Jacob disease,
Gerstmann-Straussler-Scheinker disease, transmissible spongiform
encephalopathy, ischemic reperfusion damage (e.g. stroke), brain
trauma, microbial infection, or chronic fatigue syndrome. The
phenotype may also be a condition such as fibromyalgia, chronic
neuropathic pain, or peripheral neuropathic pain.
[0100] The phenotype may also be an infectious disease, such as a
bacterial, viral or yeast infection. For example, the disease or
condition may be Whipple's Disease, Prion Disease, cirrhosis,
methicillin-resistant staphylococcus aureus, HIV, hepatitis,
syphilis, meningitis, malaria, tuberculosis, or influenza. Viral
proteins, such as HIV or HCV-like particles can be assessed in an
exosome, to characterize a viral condition.
[0101] The phenotype can also be a perinatal or pregnancy related
condition (e.g. preeclampsia or preterm birth), metabolic disease
or condition, such as a metabolic disease or condition associated
with iron metabolism. For example, hepcidin can be assayed in an
exosome to characterize an iron deficiency. The metabolic disease
or condition can also be diabetes, inflammation, or a perinatal
condition.
[0102] Subject
[0103] One or more phenotypes of a subject can be determined by
analyzing exosomes in a biological sample obtained from the
subject. A subject or patient can include, but is not limited to,
mammals such as bovine, avian, canine, equine, feline, ovine,
porcine, or primate animals (including humans and non-human
primates). A subject may also include mammals of importance due to
being endangered, such as Siberian tigers; or economic importance,
such as animals raised on farms for consumption by humans, or
animals of social importance to humans such as animals kept as pets
or in zoos. Examples of such animals include but are not limited
to: carnivores such as cats and dogs; swine including pigs, hogs
and wild boars; ruminants or ungulates such as cattle, oxen, sheep,
giraffes, deer, goats, bison, camels or horses. Also included are
birds that are endangered or kept in zoos, as well as fowl and more
particularly domesticated fowl, i.e. poultry, such as turkeys and
chickens, ducks, geese, guinea fowl. Also included are domesticated
swine and horses (including race horses). In addition, any animal
species connected to commercial activities are also included such
as those animals connected to agriculture and aquaculture and other
activities in which disease monitoring, diagnosis, and therapy
selection are routine practice in husbandry for economic
productivity and/or safety of the food chain.
[0104] The subject can have a pre-existing disease or condition,
such as cancer. Alternatively, the subject may not have any known
pre-existing condition. The subject may also be non-responsive to
an existing or past treatment, such as a treatment for cancer.
[0105] Samples
[0106] The biological sample obtained from the subject may be any
bodily fluid. For example, the biological sample can be peripheral
blood, sera, plasma, ascites, urine, cerebrospinal fluid (CSF),
sputum, saliva, bone marrow, synovial fluid, aqueous humor,
amniotic fluid, cerumen, breast milk, broncheoalveolar lavage
fluid, semen (including prostatic fluid), Cowper's fluid or
pre-ejaculatory fluid, female ejaculate, sweat, fecal matter, hair,
tears, cyst fluid, pleural and peritoneal fluid, pericardial fluid,
lymph, chyme, chyle, bile, interstitial fluid, menses, pus, sebum,
vomit, vaginal secretions, mucosal secretion, stool water,
pancreatic juice, lavage fluids from sinus cavities,
bronchopulmonary aspirates or other lavage fluids. A biological
sample may also include the blastocyl cavity, umbilical cord blood,
or maternal circulation which may be of fetal or maternal origin.
The biological sample may also be a tissue sample or biopsy, from
which exosomes may be obtained. For example, if the sample is a
solid sample, cells from the sample can be cultured and exosome
product induced (see for example, Example 1).
[0107] Table 1 provides a list of examples of diseases, conditions,
or biological states and a corresponding list of biological samples
from which exosomes may be analyzed.
TABLE-US-00001 TABLE 1 Examples of Biological Samples for Exosome
Analysis for Various Diseases. Conditions, or Biological States
Disease, Condition or Biological State Biological Samples
Cancers/neoplasms affecting the following tissue Blood, serum,
cerebrospinal fluid (CSF), urine, sputum, types/bodily systems:
breast, lung, ovarian, colon, rectal, ascites, synovial fluid,
semen, nipple aspirates, saliva, prostate, pancreatic, brain, bone,
connective tissue, glands, bronchoalveolar lavage fluid, tears,
oropharyngeal washes, skin, lymph, nervous system, endocrine, germ
cell, feces, peritoneal fluids, pleural effusion, sweat, tears,
genitourinary, hematologic/blood, bone marrow, muscle, aqueous
humor, pericardial fluid, lymph, chyme, chyle, eye, esophageal, fat
tissue, thyroid, pituitary, spinal cord, bile, stool water,
amniotic fluid, breast milk, pancreatic bile duct, heart, gall
bladder, bladder, testes, cervical, juice, cerumen, Cowper's fluid
or pre-ejaculatory fluid, endometrial, renal, ovarian,
digestive/gastrointestinal, female ejaculate, interstitial fluid,
menses, mucus, pus, stomach, head and neck, liver, leukemia, sebum,
vaginal lubrication, vomit respiratory/thorasic, cancers of unknown
primary Neurodegenerative/neurological disorders: Parkinson's
Blood, serum, CSF, urine disease, Alzheimer's Disease and multiple
sclerosis, Schizophrenia, and bipolar disorder, spasticity
disorders, epilepsy Cardiovascular Disease: atherosclerosis,
cardiomyopathy, Blood, serum, CSF, urine endocarditis, vunerable
plaques, infection Stroke: ischemic, intracerebral hemorrhage,
subarachnoid Blood, serum, CSF, urine hemorrhage, transient
ischemic attacks (TIA) Pain disorders: peripheral neuropathic pain
and chronic Blood, serum, CSF, urine neuropathic pain, and
fibromyalgia, Autoimmune disease: systemic and localized diseases,
Blood, serum, CSF, urine, synovial fluid rheumatic disease, Lupus,
Sjogren's syndrome Digestive system abnormalities: Barrett's
esophagus, Blood, serum, CSF, urine irritable bowel syndrome,
ulcerative colitis, Crohn's disease, Diverticulosis and
Diverticulitis, Celiac Disease Endocrine disorders: diabetes
mellitus, various forms of Blood, serum, CSF, urine Thyroiditis,,
adrenal disorders, pituitary disorders Diseases and disorders of
the skin: psoriasis Blood, serum, CSF, urine, synovial fluid, tears
Urological disorders: benign prostatic hypertrophy (BPH), Blood,
serum, urine polycystic kidney disease, interstitial cystitis
Hepatic disease/injury: Cirrhosis, induced hepatotoxicity Blood,
serum, urine (due to exposure to natural or synthetic chemical
sources) Kidney disease/injury: acute, sub-acute, chronic Blood,
serum, urine conditions, Podocyte injury, focal segmental
glomerulosclerosis Endometriosis Blood, serum, urine, vaginal
fluids Osteoporosis Blood, serum, urine, synovial fluid
Pancreatitis Blood, serum, urine, pancreatic juice Asthma Blood,
serum, urine, sputum, bronchiolar lavage fluid Allergies Blood,
serum, urine, sputum, bronchiolar lavage fluid Prion-related
diseases Blood, serum, CSF, urine Viral Infections: HIV/AIDS Blood,
serum, urine Sepsis Blood, serum, urine, tears, nasal lavage Organ
rejection/transplantation Blood, serum, urine, various lavage
fluids Differentiating conditions: adenoma versus hyperplastic
Blood, serum, urine, sputum, feces, colonic lavage fluid polyp,
irritable bowel syndrome (IBS) versus normal, classifying Dukes
stages A, B, C, and/or D of colon cancer, adenoma with low-grade
hyperplasia versus high- grade hyperplasia, adenoma versus normal,
colorectal cancer versus normal, IBS versus, ulcerative colitis
(UC) versus Crohn's disease (CD), Pregnancy related physiological
states, conditions, or Maternal serum, amniotic fluid, cord blood
affiliated diseases: genetic risk, adverse pregnancy outcomes
[0108] The biological samples may be obtained through a third
party, such as a party not performing the analysis of the exosome.
For example, the sample may be obtained through a clinician,
physician, or other health care manager of a subject from which the
sample is derived. Alternatively, the biological sample may
obtained by the same party analyzing the exosomes.
[0109] The volume of the biological sample used for analyzing an
exosome can be in the range of between 0.1-20 mL, such as less than
about 20, 15, 10, 9, 8, 7, 6, 5, 4, 3, 2, 1 or 0.1 mL.
[0110] Furthermore, analysis of one or more exosomes in a
biological sample can be used to determine whether an additional
biological sample should be obtained for analysis. For example,
analysis of one or more exosomes in a serum sample can be used to
determine whether a biopsy should be obtained.
Exosomes
[0111] The exosomes from a biological sample for analysis are used
to determine a phenotype. Exosomes are small vesicles that are
released into the extracellular environment from a variety of
different cells such as but not limited to, cells that originate
from, or are derived from, the ectoderm, endoderm, or mesoderm
including any such cells that have undergone genetic,
environmental, and/or any other variations or alterations (e.g.
Tumor cells or cells with genetic mutations). An exosome is
typically created intracellularly when a segment of the cell
membrane spontaneously invaginates and is ultimately exocytosed
(see for example, Keller et al., Immunol. Lett. 107 (2): 102-8
(2006)). Exosomes can have, but not be limited to, a diameter of
greater than about 10, 20, or 30 nm. They can have a diameter of
about 30-1000 nm, about 30-800 nm, about 30-200 nm, or about 30-100
nm. In some embodiments, the exosomes can have, but not be limited
to, a diameter of less than about 10,000 nm, 1000 nm, 800 nm, 500
nm, 200 nm, 100 nm or 50 nm. As used throughout, the term "about,"
when referring to a value or to an amount is meant to encompass
variations in some embodiments.+-.10% from the specified amount, as
such variations are appropriate.
[0112] Exosomes may also be referred to as microvesicles,
nanovesicles, vesicles, dexosomes, bleb, blebby, prostasomes,
microparticles, intralumenal vesicles, endosomal-like vesicles or
exocytosed vehicles. As used herein, exosomes can also include any
shed membrane bound particle that is derived from either the plasma
membrane or an internal membrane. Exosomes can also include
cell-derived structures bounded by a lipid bilayer membrane arising
from both herniated evagination (blebbing) separation and sealing
of portions of the plasma membrane or from the export of any
intracellular membrane-bounded vesicular structure containing
various membrane-associated proteins of tumor origin, including
surface-bound molecules derived from the host circulation that bind
selectively to the tumor-derived proteins together with molecules
contained in the exosome lumen, including but not limited to
tumor-derived microRNAs or intracellular proteins. Blebs and
blebbing are further described in Charras et al., Nature Reviews
Molecular and Cell Biology, Vol. 9, No. 11, p. 730-736 (2008).
Exosomes can also include membrane fragments. Circulating
tumor-derived exosomes (CTEs) as referenced herein are exosomes
that are shed into circulation or bodily fluids from tumor cells.
CTEs, as with cell-of-origin specific exosomes, typically have
unique biomarkers that permit their isolation from bodily fluids in
a highly specific manner.
[0113] Exosomes can be directly assayed from the biological
samples, such that the level of exosomes is determined or the one
or more biomarkers of the exosomes is determined without prior
isolation, purification, or concentration of the exosomes.
Alternatively, exosomes may be isolated, purified, or concentrated
from a sample prior to analysis.
Isolation of Exosomes
[0114] An exosome may be purified or concentrated prior to
analysis. Analysis of an exosome can include quantitiating the
amount one or more exosome populations of a biological sample. For
example, a heterogeneous population of exosomes can be quantitated,
or a homogeneous population of exosomes, such as a population of
exosomes with a particular biomarker profile, a particular
bio-signature, or derived from a particular cell type
(cell-of-origin specific exosomes) can be isolated from a
heterogeneous population of exosomes and quantitated. Analysis of
an exosome can also include detecting, quantitatively or
qualitatively, a particular biomarker profile or a bio-signature,
of an exosome, as described below.
[0115] An exosome can be stored and archived, such as in a
bio-fluid bank and retrieved for analysis as necessary. An exosome
may also be isolated from a biological sample that has been
previously harvested and stored from a living or deceased subject.
In addition, an exosome may be isolated from a biological sample
which has been collected as described in King et al., Breast Cancer
Res 7(5): 198-204 (2005). An exosome may be isolated from an
archived or stored sample. Alternatively, an exosome may be
isolated from a biological sample and analyzed without storing or
archiving of the sample. Furthermore, a third party may obtain or
store the biological sample, or obtain or store the exosomes for
analysis.
[0116] An enriched population of exosomes can be obtained from a
biological sample. For example, exosomes may be concentrated or
isolated from a biological sample using size exclusion
chromatography, density gradient centrifugation, differential
centrifugation, nanomembrane ultrafiltration, immunoabsorbent
capture, affinity purification, microfluidic separation, or
combinations thereof.
[0117] Size exclusion chromatography, such as gel permeation
columns, centrifugation or density gradient centrifugation, and
filtration methods can be used. For example, exosomes can be
isolated by differential centrifugation, anion exchange and/or gel
permeation chromatography (for example, as described in U.S. Pat.
Nos. 6,899,863 and 6,812,023), sucrose density gradients, organelle
electrophoresis (for example, as described in U.S. Pat. No.
7,198,923), magnetic activated cell sorting (MACS), or with a
nanomembrane ultrafiltration concentrator. Various combinations of
isolation or concentration methods can be used.
[0118] Highly abundant proteins, such as albumin and
immunoglobulin, may hinder isolation of exosomes from a biological
sample. For example, exosomes may be isolated from a biological
sample using a system that utilizes multiple antibodies that are
specific to the most abundant proteins found in blood. Such a
system can remove up to several proteins at once, thus unveiling
the lower abundance species such as cell-of-origin specific
exosomes.
[0119] This type of system can be used for isolation of exosomes
from biological samples such as blood, cerebrospinal fluid or
urine. The isolation of exosomes from a biological sample may also
be enhanced by high abundant protein removal methods as described
in Chromy et al. J. Proteome Res 2004; 3:1120-1127. In another
embodiment, the isolation of exosomes from a biological sample may
also be enhanced by removing serum proteins using glycopeptide
capture as described in Zhang et al, Mol Cell Proteomics 2005;
4:144-155. In addition, exosomes from a biological sample such as
urine may be isolated by differential centrifugation followed by
contact with antibodies directed to cytoplasmic or anti-cytoplasmic
epitopes as described in Pisitkun et al., Proc Natl Acad Sci USA,
2004; 101:13368-13373.
[0120] Isolation or enrichment of exosomes from biological samples
can also be enhanced by use of sonication (for example, by applying
ultrasound), or the use of detergents, other membrane-active
agents, or any combination thereof. For example, ultrasonic energy
can be applied to a potential tumor site, and without being bound
by theory, release of exosomes from the tissue can be increased,
allowing an enriched population of exosomes that can be analyzed or
assessed from a biological sample using one or more methods
disclosed herein.
Binding Agents
[0121] A binding agent is an agent that binds to an exosomal
component, such as a biomarker of an exosome. The binding agent can
be a capture agent. A capture agent captures the exosome by binding
to an exosomal target, such as a biomarker on the exosome. For
example, the capture agent can be a capture antibody that binds to
an antigen on the exosome. The capture agent can be coupled to a
substrate and used to isolate the exosome, such as described
herein.
[0122] A binding agent can be used after exosomes are concentrated
or isolated from a biological sample. For example, exosomes can
first be isolated from a biological sample before exosomes with a
specific biomarker are isolated using a binding agent for the
biomarker. Thus, exosomes with the specific biomarker is isolated
from a heterogeneous population of exosomes. Alternatively, a
binding agent may be used on a biological sample comprising
exosomes without a prior isolation step or concentration of
exosomes. For example, a binding agent is used to isolate an
exosome with a specific biomarker from a biological sample.
[0123] A binding agent can be DNA, RNA, monoclonal antibodies,
polyclonal antibodies, Fabs, Fab', single chain antibodies,
synthetic antibodies, aptamers (DNA/RNA), peptoids, zDNA, peptide
nucleic acids (PNAs), locked nucleic acids (LNAs), lectins,
synthetic or naturally occurring chemical compounds (including but
not limited to drugs, labeling reagents), dendrimers, or
combinations thereof. For example, the binding agent can be a
capture antibody.
[0124] In some instances, a single binding agent can be employed to
isolate an exosome. In other instances, a combination of different
binding agents may be employed to isolate an exosome. For example,
at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 25, 50, 75 or 100 different binding agents may be used
to isolate an exosome from a biological sample. Furthermore, the
one or more different binding agents for an exosome can form the
bio-signature of the exosome, further described below.
[0125] Different binding agents can also be used for multiplexing.
For example, isolation of more than one population of exosomes (for
example, exosomes from specific cell types) can be performed by
isolating each exosome population with a different binding agent.
Different binding agents can be bound to different particles,
wherein the different particles are labeled. In another embodiment,
an array comprising different binding agents can be used for
multiplex analysis, wherein the different binding agents are
differentially labeled or can be ascertained based on the location
of the binding agent on the array. Multiplexing can be accomplished
up to the resolution capability of the labels or detection method,
such as described below.
[0126] The binding agent can be an antibody. For example, an
exosome may be isolated using one or more antibodies specific for
one or more antigens present on the exosome. For example, an
exosome can have CD63 on its surface, and an antibody, or capture
antibody, for CD63 can be used to isolate the exosome.
Alternatively, an exosome derived from a tumor cell can express
EpCam, the exosome can be isolated using an antibody for EpCam and
CD63. Other antibodies for isolating exosomes can include an
antibody, or capture antibody, to CD9, PSCA, TNFR, CD63, B7H3,
MFG-E8, EpCam, Rab, CD81, STEAP, PCSA, PSMA, or 5T4.
[0127] The antibodies disclosed herein can be immunoglobulin
molecules or immunologically active portions of immunoglobulin
molecules, i.e., molecules that contain an antigen binding site
that specifically binds an antigen and synthetic antibodies. The
immunoglobulin molecules can be of any class (e.g., IgG, IgE, IgM,
IgD or IgA) or subclass of immunoglobulin molecule. Antibodies
include, but are not limited to, polyclonal, monoclonal,
bispecific, synthetic, humanized and chimeric antibodies, single
chain antibodies, Fab fragments and F(ab').sub.2 fragments, Fv or
Fv' portions, fragments produced by a Fab expression library,
anti-idiotypic (anti-Id) antibodies, or epitope-binding fragments
of any of the above. An antibody, or generally any molecule, "binds
specifically" to an antigen (or other molecule) if the antibody
binds preferentially to the antigen, and, e.g., has less than about
30%, 20%, 10%, 5% or 1% cross-reactivity with another molecule.
[0128] The binding agent can also be a polypeptide or peptide.
Polypeptide is used in its broadest sense and may include a
sequence of subunit amino acids, amino acid analogs, or
peptidomimetics. The subunits may be linked by peptide bonds. The
polypeptides may be naturally occurring, processed forms of
naturally occurring polypeptides (such as by enzymatic digestion),
chemically synthesized or recombinantly expressed. The polypeptides
for use in the methods of the present invention may be chemically
synthesized using standard techniques. The polypeptides may
comprise D-amino acids (which are resistant to L-amino
acid-specific proteases), a combination of D- and L-amino acids,
.beta. amino acids, or various other designer or non-naturally
occurring amino acids (e.g., (.beta.-methyl amino acids,
C.alpha.-methyl amino acids, and N.alpha.-methyl amino acids, etc.)
to convey special properties. Synthetic amino acids may include
ornithine for lysine, and norleucine for leucine or isoleucine. In
addition, the polypeptides can have peptidomimetic bonds, such as
ester bonds, to prepare polypeptides with novel properties. For
example, a polypeptide may be generated that incorporates a reduced
peptide bond, i.e., R.sub.1--CH.sub.2--NH--R.sub.2, where R.sub.1
and R.sub.2 are amino acid residues or sequences. A reduced peptide
bond may be introduced as a dipeptide subunit. Such a polypeptide
would be resistant to protease activity, and would possess an
extended half-live in vivo. Polypeptides can also include peptoids
(N-substituted glycines), in which the side chains are appended to
nitrogen atoms along the molecule's backbone, rather than to the
.alpha.-carbons, as in amino acids. Polypeptides and peptides are
intended to be used interchangeably throughout this application,
i.e. where the term peptide is used, it may also include
polypeptides and where the term polypeptides is used, it may also
include peptides.
[0129] An exosome may be isolated using a known binding agent. For
example, the binding agent can be an agent that binds exosomal
"housekeeping proteins," or general exosome biomarkers, such as
CD63, CD9, CD81, CD82, CD37, CD53, or Rab-5b. The binding agent can
also be an agent that binds to exosomes derived from specific cell
types, such as tumor cells (e.g. binding agent for EpCam) or
specific cell-of-origins, such as described below. For example, the
binding agent used to isolate an exosome may be a binding agent for
an antigen selected from FIG. 1. The binding agent for an exosome
can also be selected from those listed in FIG. 2. For example, the
binding agent can be for an antigen such as 5T4, B7H3, caveolin,
CD63, CD9, E-Cadherin, MFG-E8, PSCA, PSMA, Rab-5B, STEAP, TNFR1,
CD81, EpCam, CD59, or CD66. One or more binding agents, such as one
or more binding agents for two or more of the antigens, can be used
for isolating an exosome. The binding agent used can be selected
based on the desire of isolating exosomes derived from particular
cell types, or cell-of-origin specific exosomes.
[0130] A binding agent can also be linked directly or indirectly to
a solid surface or substrate. A solid surface or substrate can be
any physically separable solid to which a binding agent can be
directly or indirectly attached including, but not limited to,
surfaces provided by microarrays and wells, particles such as
beads, columns, optical fibers, wipes, glass and modified or
functionalized glass, quartz, mica, diazotized membranes (paper or
nylon), polyformaldehyde, cellulose, cellulose acetate, paper,
ceramics, metals, metalloids, semiconductive materials, quantum
dots, coated beads or particles, other chromatographic materials,
magnetic particles; plastics (including acrylics, polystyrene,
copolymers of styrene or other materials, polypropylene,
polyethylene, polybutylene, polyurethanes, TEFLON.TM., etc.),
polysaccharides, nylon or nitrocellulose, resins, silica or
silica-based materials including silicon and modified silicon,
carbon, metals, inorganic glasses, plastics, ceramics, conducting
polymers (including polymers such as polypyrole and polyindole);
micro or nanostructured surfaces such as nucleic acid tiling
arrays, nanotube, nanowire, or nanoparticulate decorated surfaces;
or porous surfaces or gels such as methacrylates, acrylamides,
sugar polymers, cellulose, silicates, or other fibrous or stranded
polymers. In addition, as is known the art, the substrate may be
coated using passive or chemically-derivatized coatings with any
number of materials, including polymers, such as dextrans,
acrylamides, gelatins or agarose. Such coatings can facilitate the
use of the array with a biological sample.
[0131] For example, an antibody used to isolate an exosome can be
bound to a solid substrate such as a well, such as commercially
available plates (e.g. from Nunc, Milan Italy). Each well can be
coated with the antibody. In some embodiments, the antibody used to
isolate an exosome can be bound to a solid substrate such as an
array. The array can have a predetermined spatial arrangement of
molecule interactions, binding islands, biomolecules, zones,
domains or spatial arrangements of binding islands or binding
agents deposited within discrete boundaries. Further, the term
array may be used herein to refer to multiple arrays arranged on a
surface, such as would be the case where a surface bore multiple
copies of an array. Such surfaces bearing multiple arrays may also
be referred to as multiple arrays or repeating arrays.
[0132] A binding agent can also be bound to particles such as beads
or microspheres. For example, an antibody specific for an exosomal
component can be bound to a particle, and the antibody-bound
particle is used to isolate exosomes from a biological sample. In
some embodiments, the microspheres may be magnetic or fluorescently
labeled. In addition, a binding agent for isolating exosomes can be
a solid substrate itself. For example, latex beads, such as
aldehyde/sulfate beads (Interfacial Dynamics, Portland, Oreg.) can
be used.
[0133] A binding agent bound to a magnetic bead can also be used to
isolate an exosome. For example, a biological sample such as serum
from a patient can be collected for colon cancer screening. The
sample can be incubated with anti-CCSA-3 (Colon Cancer-Specific
Antigen) coupled to magnetic microbeads. A low-density microcolumn
can be placed in the magnetic field of a MACS Separator and the
column is then washed with a buffer solution such as Tris-buffered
saline. The magnetic immune complexes can then be applied to the
column and unbound, non-specific material can be discarded. The
CCSA-3 selected exosomes can be recovered by removing the column
from the separator and placing it on a collection tube. A buffer
can be added to the column and the magnetically labeled exosomes
can be released by applying the plunger supplied with the column.
The isolated exosomes can be diluted in IgG elution buffer and the
complex can then be centrifuged to separate the microbeads from the
exosomes. The pelleted isolated cell-of-origin specific exosomes
can be resuspended in buffer such as phosphate-buffered saline and
quantitated. Alternatively, due to the strong adhesion force
between the antibody captured cell-of-origin specific exosomes and
the magnetic microbeads, a proteolytic enzyme such as trypsin can
be used for the release of captured exosomes without the need for
centrifugation. The proteolytic enzyme can be incubated with the
antibody captured cell-of-origin specific exosomes for at least a
time sufficient to release the exosomes.
[0134] A binding agent, such as an antibody, for isolating an
exosome is preferably contacted with the biological sample
comprising the exosome of interest for at least a time sufficient
for the binding agent to bind to an exosomal component. For
example, an antibody may be contacted with a biological sample for
various intervals ranging from seconds days, including but not
limited to, about 10 minutes, 30 minutes, 1 hour, 3 hours, 5 hours,
7 hours, 10 hours, 15 hours, 1 day, 3 days, 7 days or 10 days.
[0135] A binding agent, such as an antibody specific to an antigen
listed in FIG. 1, or a binding agent listed in FIG. 2, can be
labeled with, including but not limited to, a magnetic label, a
fluorescent moiety, an enzyme, a chemiluminescent probe, a metal
particle, a non-metal colloidal particle, a polymeric dye particle,
a pigment molecule, a pigment particle, an electrochemically active
species, semiconductor nanocrystal or other nanoparticles including
quantum dots or gold particles. The label can be, but not be
limited to, fluorophores, quantum dots, or radioactive labels. For
example, the label can be a radioisotope (radionuclides), such as
.sup.3H, .sup.11C, .sup.14C, .sup.18F, .sup.32P, .sup.35S,
.sup.64Cu, .sup.68Ga, .sup.86Y, .sup.99Tc, .sup.111In, .sup.123I,
.sup.124I, .sup.125I, .sup.131I, .sup.133Xe, .sup.177Lu,
.sup.211At, or .sup.213Bi. The label can be a fluorescent label,
such as a rare earth chelate (europium chelate), fluorescein type,
such as, but not limited to, FITC, 5-carboxyfluorescein, 6-carboxy
fluorescein; a rhodamine type, such as, but not limited to, TAMRA;
dansyl; Lissamine; cyanines; phycoerythrins; Texas Red; and analogs
thereof.
[0136] A binding agent can be directly or indirectly labeled, e.g.,
the label is attached to the antibody through biotin-streptavidin.
Alternatively, an antibody is not labeled, but is later contacted
with a second antibody that is labeled after the first antibody is
bound to an antigen of interest.
[0137] For example, various enzyme-substrate labels are available
or disclosed (see for example, U.S. Pat. No. 4,275,149). The enzyme
generally catalyzes a chemical alteration of a chromogenic
substrate that can be measured using various techniques. For
example, the enzyme may catalyze a color change in a substrate,
which can be measured spectrophotometrically. Alternatively, the
enzyme may alter the fluorescence or chemiluminescence of the
substrate. Examples of enzymatic labels include luciferases (e.g.,
firefly luciferase and bacterial luciferase; U.S. Pat. No.
4,737,456), luciferin, 2,3-dihydrophthalazinediones, malate
dehydrogenase, urease, peroxidase such as horseradish peroxidase
(HRP), alkaline phosphatase (AP), .beta.-galactosidase,
glucoamylase, lysozyme, saccharide oxidases (e.g., glucose oxidase,
galactose oxidase, and glucose-6-phosphate dehydrogenase),
heterocyclic oxidases (such as uricase and xanthine oxidase),
lactoperoxidase, microperoxidase, and the like. Examples of
enzyme-substrate combinations include, but are not limited to,
horseradish peroxidase (HRP) with hydrogen peroxidase as a
substrate, wherein the hydrogen peroxidase oxidizes a dye precursor
(e.g., orthophenylene diamine (OPD) or
3,3',5,5'-tetramethylbenzidine hydrochloride (TMB)); alkaline
phosphatase (AP) with para-nitrophenyl phosphate as chromogenic
substrate; and .beta.-D-galactosidase ((.beta.-D-Gal) with a
chromogenic substrate (e.g., p-nitrophenyl-(.beta.-D-galactosidase)
or fluorogenic substrate
4-methylumbelliferyl-.beta.-D-galactosidase.
[0138] Depending on the method of isolation used, the binding agent
may be linked to a solid surface or substrate, such as arrays,
particles, wells and other substrates described above. Methods for
direct chemical coupling of antibodies, to the cell surface are
known in the art, and may include, for example, coupling using
glutaraldehyde or maleimide activated antibodies. Methods for
chemical coupling using multiple step procedures include
biotinylation, coupling of trinitrophenol (TNP) or digoxigenin
using for example succinimide esters of these compounds.
Biotinylation can be accomplished by, for example, the use of
D-biotinyl-N-hydroxysuccinimide. Succinimide groups react
effectively with amino groups at pH values above 7, and
preferentially between about pH 8.0 and about pH 8.5. Biotinylation
can be accomplished by, for example, treating the cells with
dithiothreitol followed by the addition of biotin maleimide.
[0139] Flow Cytometry
[0140] Isolation of exosomes using particles such as beads or
microspheres can also be performed using flow cytometry. Flow
cytometry can be used for sorting microscopic particles suspended
in a stream of fluid. As particles pass through they can be
selectively charged and on their exit can be deflected into
separate paths of flow. It is therefore possible to separate
populations from an original mix, such as a biological sample, with
a high degree of accuracy and speed. Flow cytometry allows
simultaneous multiparametric analysis of the physical and/or
chemical characteristics of single cells flowing through an
optical/electronic detection apparatus. A beam of light, usually
laser light, of a single frequency (color) is directed onto a
hydrodynamically focused stream of fluid. A number of detectors are
aimed at the point where the stream passes through the light beam;
one in line with the light beam (Forward Scatter or FSC) and
several perpendicular to it (Side Scatter or SSC) and one or more
fluorescent detectors.
[0141] Each suspended particle passing through the beam scatters
the light in some way, and fluorescent chemicals in the particle
may be excited into emitting light at a lower frequency than the
light source. This combination of scattered and fluorescent light
is picked up by the detectors, and by analyzing fluctuations in
brightness at each detector (one for each fluorescent emission
peak), it is possible to deduce various facts about the physical
and chemical structure of each individual particle. FSC correlates
with the cell size and SSC depends on the inner complexity of the
particle, such as shape of the nucleus, the amount and type of
cytoplasmic granules or the membrane roughness. Some flow
cytometers have eliminated the need for fluorescence and use only
light scatter for measurement.
[0142] Flow cytometers can analyze several thousand particles every
second in "real time" and can actively separate out and isolate
particles having specified properties. They offer high-throughput
automated quantification, and separation, of the set parameters for
a high number of single cells during each analysis session. Modern
instruments have multiple lasers and fluorescence detectors, for
example up to 4 lasers and 18 fluorescence detectors, allowing
multiple labels to be used to more precisely specify a target
population by their phenotype.
[0143] The data resulting from flow-cytometers can be plotted in 1
dimension to produce histograms or seen in 2 dimensions as dot
plots or in 3 dimensions with newer software. The regions on these
plots can be sequentially separated by a series of subset
extractions which are termed gates. Specific gating protocols exist
for diagnostic and clinical purposes especially in relation to
hematology. The plots are often made on logarithmic scales. Because
different fluorescent dye's emission spectra overlap, signals at
the detectors have to be compensated electronically as well as
computationally. Fluorophores for labeling biomarkers may include
those described in Ormerod, Flow Cytometry 2nd ed.,
Springer-Verlag, New York (1999), and in Nida et al., Gynecologic
Oncology 2005; 4 889-894 which is incorporated herein by
reference.
[0144] Multiplexing
[0145] Different binding agents can be used for multiplexing
different exosome populations. Different exosome populations can be
isolated or detected using different binding agents. Each exosome
population in a biological sample can be labeled with a different
signaling label, such as fluorophores, quantum dots, or radioactive
labels, such as described above. The label can be directly
conjugated to a binding agent or indirectly used to detect a
binding agent. The number of populations detected in a multiplexing
assay is dependent on the resolution capability of the labels and
the summation of signals, as more than two differentially labeled
exosome populations that bind two or more affinity elements can
produce summed signals.
[0146] Multiplexing of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75 or 100 different exosome
populations may be performed. For example, one population of
exosomes specific to a cell-of-origin can be assayed along with a
second population of exosomes specific to a different
cell-of-origin, where each population is labeled with a different
label. Alternatively, a population of exosomes with a particular
biomarker or bio-signature can be assayed along with a second
population of exosomes with a different biomarker or
bio-signature.
[0147] In one embodiment, multiplex analysis is performed by
applying a plurality of exosomes comprising more than one
population of exosomes to a plurality of substrates, such as beads.
Each bead is coupled to one or more capture agents. The plurality
of beads is divided into subsets, where beads with the same capture
agent or combination of capture agents form a subset of beads, such
that each subset of beads has a different capture agent or
combination of capture agents than another subset of beads. The
beads can then be used to capture exosomes that comprises a
component that binds to the capture agent. The different subsets
can be used to capture different populations of exosomes. The
captured exosomes can then be analyzed by detecting one or more
biomarkers of the exosomes.
[0148] Flow cytometry can be used in combination with a
particle-based or bead based assay. Multiparametric immunoassays or
other high throughput detection assays using bead coatings with
cognate ligands and reporter molecules with specific activities
consistent with high sensitivity automation can be used. For
example, beads in each subset can be differentially labeled from
another subset. For example, in a particle based assay system, a
binding agent or capture agent for an exosome, such as a capture
antibody, can be immobilized on addressable beads or microspheres.
Each binding agent for each individual binding assay (such as an
immunoassay when the binding agent is an antibody) can be coupled
to a distinct type of microsphere (i.e., microbead) and the binding
assay reaction takes place on the surface of the microspheres.
Microspheres can be distinguished by different labels, for example,
a microsphere with a specific capture agent would have a different
signaling label as compared to another microsphere with a different
capture agent. For example, microspheres can be dyed with discrete
fluorescence intensities such that the fluorescence intensity of a
microsphere with a specific binding agent is different than that of
another microsphere with a different binding agent.
[0149] The microsphere can be labeled or dyed with at least 2
different labels or dyes. In some embodiments, the microsphere is
labeled with at least 3, 4, 5, 6, 7, 8, 9, or 10 different labels.
Different microspheres in a plurality of microspheres can have more
than one label or dye, wherein various subsets of the microspheres
have various ratios and combinations of the labels or dyes
permitting detection of different microspheres with different
binding agents. For example, the various ratios and combinations of
labels and dyes can permit different fluorescent intensities.
Alternatively, the various ratios and combinations maybe used to
generate different detection patters to identify the binding agent.
The microspheres can be labeled or dyed externally or may have
intrinsic fluorescence or signaling labels. Beads can be loaded
separately with their appropriate binding agents and thus,
different exosome populations can be isolated based on the
different binding agents on the differentially labeled microspheres
to which the different binding agents are coupled.
[0150] In another embodiment, multiplex analysis can be performed
using a planar substrate, wherein the said substrate comprises a
plurality of capture agents. The plurality of capture agents can
capture one or more populations of exosomes, and one or more
biomarkers of the captured exosomes detected. The planar substrate
can be a microarray or other substrate as further described
herein.
[0151] Novel Binding Agents
[0152] An exosome may be isolated using a binding agent for a novel
component of an exosome, such as an antibody for a novel antigen
specific to an exosome of interest. Novel antigens that are
specific to exosomes of interest may be isolated or identified
using different test compounds of known composition bound to a
substrate, such as an array or a plurality of particles, which can
allow a large amount of chemical/structural space to be adequately
sampled using only a small fraction of the space. The novel antigen
identified can also serve as a biomarker for the exosome. For
example, a novel antigen identified for a cell-of-origin specific
exosome can be a biomarker for that particular cell-of-origin
specific exosome.
[0153] A binding agent can be identified by screening either a
homogeneous or heterogeneous exosome population against test
compounds. Since the composition of each test compound on the
substrate surface is known, this constitutes a screen for affinity
elements. For example, a test compound array comprises test
compounds at specific locations on the substrate addressable
locations, and can be used to identify one or more binding agents
for an exosome. The test compounds can all be unrelated or related
based on minor variations of a core sequence or structure. The
different test compounds may include variants of a given test
compound (such as polypeptide isoforms), test compounds that are
structurally or compositionally unrelated, or a combination
thereof.
[0154] Test compounds can be peptoids, polysaccharides, organic
compounds, inorganic compounds, polymers, lipids, nucleic acids,
polypeptides, antibodies, proteins, polysaccharides, or other
compounds. The test compounds can be natural or synthetic. The test
compounds can comprise or consist of linear or branched
heteropolymeric compounds based on any of a number of linkages or
combinations of linkages (e.g., amide, ester, ether, thiol, radical
additions, metal coordination, etc.), dendritic structures,
circular structures, cavity structures or other structures with
multiple nearby sites of attachment that serve as scaffolds upon
which specific additions are made. These test compounds can be
spotted on the substrate or synthesized in situ, using standard
methods in the art. In addition, the test compounds can be spotted
or synthesized in situ in combinations in order to detect useful
interactions, such as cooperative binding.
[0155] The test compounds can be polypeptides with known amino acid
sequences, thus, detection a test compound binding with an exosome
can lead to identification of a polypeptide of known amino sequence
that can be used as a binding agent. For example, a homogenous
population of exosomes can be applied to a spotted array on a slide
containing between a few and 1,000,000 test polypeptides having a
length of variable amino acids. The polypeptides can be attached to
the surface through the C-terminus. The sequence of the
polypeptides can be generated randomly from 19 amino acids,
excluding cysteine. The binding reaction can include a non-specific
competitor, such as excess bacterial proteins labeled with another
dye such that the specificity ratio for each polypeptide binding
target can be determined. The polypeptides with the highest
specificity and binding can be selected. The identity of the
polypeptide on each spot is known, and thus can be readily
identified. Once the novel antigens specific to the homogeneous
exosome population, such as a cell-of-origin specific exosome is
identified, such cell-of-origin specific exosomes may subsequently
be isolated using such antigens in methods described hereafter.
[0156] Arrays can also be used for identifying antibodies for
isolating exosomes. Test antibodies can be attached to an array and
screened against a heterogeneous population of exosomes to identify
antibodies that can be used to isolate, and identify, an exosome. A
homogeneous population of exosomes, such as cell-of-origin specific
exosomes, can also be screened with an antibody array. Other than
identifying antibodies to isolate the homogeneous population of
exosomes, one or more protein biomarkers specific to the homogenous
exosome population can be identified. Commercially available
platforms with test antibodies pre-selected, or custom selection of
test antibodies attached to the array, can be used. For example, an
antibody array from Full Moon Biosystems can be screened using
prostate cancer cell derived exosomes, identifying antibodies to
Bcl-XL, ERCC1, Keratin 15, CD81/TAPA-1, CD9, Epithelial Specific
Antigen (ESA), and Mast Cell Chymase as binding agents (see for
example, FIG. 63), and the proteins identified can be used as
biomarkers for the exosomes.
[0157] An antibody or synthetic antibody to be used as a binding
agent can also be identified through a peptide array. Another
method is the use of synthetic antibody generation through antibody
phage display. M13 bacteriophage libraries of antibodies (e.g.
Fabs) are displayed on the surfaces of phage particles as fusions
to a coat protein. Each phage particle displays a unique antibody
and also encapsulates a vector that contains the encoding DNA.
Highly diverse libraries can be constructed and represented as
phage pools, which can be used in antibody selection for binding to
immobilized antigens. Antigen-binding phages are retained by the
immobilized antigen, and the nonbinding phages are removed by
washing. The retained phage pool can be amplified by infection of
an Escherichia coli host and the amplified pool can be used for
additional rounds of selection to eventually obtain a population
that is dominated by antigen-binding clones. At this stage,
individual phase clones can be isolated and subjected to DNA
sequencing to decode the sequences of the displayed antibodies.
Through the use of phase display and other methods known in the
art, high affinity designer antibodies for exosomes can be
generated.
[0158] Bead-based assays can also be used to identify novel binding
agents to isolate exosomes. A test antibody or peptide can be
conjugated to a particle. For example, a bead can be conjugated to
an antibody or peptide and used to detect and quantify the proteins
expressed on the surface of a population of exosomes in order to
discover and specifically select for novel antibodies that can
target exosomes from specific tissue or tumor types. Any molecule
of organic origin can be successfully conjugated to a polystyrene
bead through use of a commercially available kit according to
manufacturer's instructions. Each bead set can be colored a certain
detectable wavelength and each can be linked to a known antibody or
peptide which can be used to specifically measure which beads are
linked to exosomal proteins matching the epitope of previously
conjugated antibodies or peptides. The beads can be dyed with
discrete fluorescence intensities such that each bead with a
different intensity has a different binding agent as described
above.
[0159] For example, a purified exosome preparation can be diluted
in assay buffer to an appropriate concentration according to
empirically determined dynamic range of assay. A sufficient volume
of coupled beads can be prepared and approximately 1 .mu.l of the
antibody-coupled beads can be aliqouted into a well and adjusted to
a final volume of approximately 50 .mu.l. Once the
antibody-conjugated beads have been added to a vacuum compatible
plate, the beads can be washed to ensure proper binding conditions:
An appropriate volume of exosomal preparation can then be added to
each well being tested and the mixture incubated, such as for 15-18
hours. A sufficient volume of detection antibodies using detection
antibody diluent solution can be prepared and incubated with the
mixture for 1 hour or for as long as necessary. The beads can then
be washed before the addition of detection antibody (biotin
expressing) mixture composed of streptavidin phycoereythin. The
beads can then be washed and vacuum aspirated several times before
analysis on a suspension array system using software provided with
an instrument. The identity of antigens that can be used to
selectively extract the exosomes can then be elucidated from the
analysis.
[0160] Assays using imaging systems can be utilized to detect and
quantify proteins expressed on the surface of an exosome in order
to discover and specifically select for and enrich exosomes from
specific tissue or tumor types. Antibodies, peptides or cells
conjugated to multiple well multiplex carbon coated plates can be
used. Simultaneous measurement of many analytes in a well can be
achieved through the use of capture antibodies arrayed on the
patterned carbon working surface. Analytes can then be detected
with antibodies labeled with reagents in electrode wells with an
enhanced electro-chemiluminescent plate. Any molecule of organic
origin can be successfully conjugated to the carbon coated plate.
Proteins expressed on the surface of exosomes can be identified
from this assay and can be used as targets to specifically select
for and enrich exosomes from specific tissue or tumor types.
[0161] The binding agent can also be a novel aptamer. An aptamer
for a target can be identified using systematic evolution of
ligands by exponential enrichment (SELEX) (Tuerk & Gold,
Science 249:505-510, 1990; Ellington & Szostak, Nature
346:818-822, 1990), such as described in U.S. Pat. No. 5,270,163. A
library of nucleic acids can be contacted with a target exosome,
and those nucleic acids specifically bound to the target are
partitioned from the remainder of nucleic acids in the library
which do not specifically bind the target. The partitioned nucleic
acids are amplified to yield a ligand-enriched pool. Multiple
cycles of binding, partitioning, and amplifying (i.e., selection)
result in identification of one or more aptamers with the desired
activity. Another method for identifying an aptamer to isolate
exosomes is described in U.S. Pat. No. 6,376,19, which describes
increasing or decreasing frequency of nucleic acids in a library by
their binding to a chemically synthesized peptide. Modified
methods, such as Laser SELEX or deSELEX as described in U.S. Patent
Publication No. 20090264508 can also be used.
[0162] Microfluidics
[0163] The methods for isolating or identifying exosomes can be
used in combination with microfluidic devices. The methods of
isolating exosomes disclosed herein can be performed using
microfluidic devices. Microfluidic devices, which may also be
referred to as "lab-on-a-chip" systems, biomedical
micro-electro-mechanical systems (bioMEMs), or multicomponent
integrated systems, can be used for isolating, and analyzing,
exosomes. Such systems miniaturize and compartmentalize processes
that allow for binding of exosomes, detection of exosomal
biomarkers, and other processes.
[0164] A microfluidic device can also be used for isolation of an
exosome through size differential or affinity selection. For
example, a microfluidic device can use one more channels for
isolating an exosome from a biological sample based on size, or by
using one or more binding agents for isolating an exosome, from a
biological sample. A biological sample can be introduced into one
or more microfluidic channels, which selectively allows the passage
of exosomes. The selection can be based on a property of the
exosomes, for example, size, shape, deformability, biomarker
profile, or bio-signature.
[0165] Alternatively, a heterogeneous population of exosomes can be
introduced into a microfluidic device, and one or more different
homogeneous populations of exosomes can be obtained. For example,
different channels can have different size selections or binding
agents to select for different exosome populations. Thus, a
microfluidic device can isolate a plurality of exosomes, wherein at
least a subset of the plurality of exosomes comprises a different
bio-signature from another subset of said plurality of exosomes.
For example, the microfluidic device can isolate at least 2, 3, 4,
5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90, or 100
different subsets of exosomes, wherein each subset of exosomes
comprises a different bio-signature.
[0166] In some embodiments, the microfluidic device can comprise
one or more channels that permit further enrichment or selection of
exosomes. A population of exosomes that has been enriched after
passage through a first channel can be introduced into a second
channel, which allows the passage of the desired exosome population
to be further enriched, such as through binding agents present in
the second channel.
[0167] Array-based assays and bead-based assays can be used with
microfluidic device. For example, the binding agent can be coupled
to beads and the binding reaction between the beads and exosomes
can be performed in a microfluidic device. Multiplexing can also be
performed using a microfluidic device. Different compartments can
comprise different binding agents for different populations of
exosomes, where each population is of a different cell-of-origin
specific exosome population or each population has a different
bio-signature. The hybridization reaction between the microspheres
and exosomes can be performed in a microfluidic device and the
reaction mixture can be delivered to a detection device. The
detection device, such as a dual or multiple laser detection system
can be part of the microfluidic system and can use a laser to
identify each bead or microsphere by its color-coding, and another
laser can detect the hybridization signal associated with each
bead.
[0168] Examples of microfluidic devices that may be used, or
adapted for use with exosomes, include but are not limited to those
described in U.S. Pat. Nos. 7,591,936, 7,581,429, 7,579,136,
7,575,722, 7,568,399, 7,552,741, 7,544,506, 7,541,578, 7,518,726,
7,488,596, 7,485,214, 7,467,928, 7,452,713, 7,452,509, 7,449,096,
7,431,887, 7,422,725, 7,422,669, 7,419,822, 7,419,639, 7,413,709,
7,411,184, 7,402,229, 7,390,463, 7,381,471, 7,357,864, 7,351,592,
7,351,380, 7,338,637, 7,329,391, 7,323,140, 7,261,824, 7,258,837,
7,253,003, 7,238,324, 7,238,255, 7,233,865, 7,229,538, 7,201,881,
7,195,986, 7,189,581, 7,189,580, 7,189,368, 7,141,978, 7,138,062,
7,135,147, 7,125,711, 7,118,910, and 7,118,661.
Cell-of-Origin and Disease-Specific Exosomes
[0169] The bindings agents disclosed herein can be used to isolate
a heterogeneous population of exosomes from a sample or can be used
to isolate or identify a homogeneous population of exosomes, such
as cell-of-origin specific exosomes or exosomes with specific
bio-signatures. A homogeneous population of exosomes, such as
cell-of-origin specific exosomes, can be analyzed and used to
characterize a phenotype for a subject. Cell-of-origin specific
exosomes are exosomes derived from specific cell types, which can
include, but are not limited to, cells of a specific tissue, cells
from a specific tumor of interest or a diseased tissue of interest,
circulating tumor cells, or cells of maternal or fetal origin. The
exosomes may be derived from tumor cells or lung, pancreas,
stomach, intestine, bladder, kidney, ovary, testis, skin,
colorectal, breast, prostate, brain, esophagus, liver, placenta, or
fetal cells. The isolated exosomes can also be from a particular
sample type, such as urinary exosomes.
[0170] Cell-of-origin specific exosomes from a biological sample
can be isolated using one or more binding agents that are specific
to a cell-of-origin. Exosomes for analysis of a disease or
condition can be isolated using one or more binding agents specific
for biomarkers for that disease or condition.
[0171] The exosomes can be concentrated prior to isolation of
cell-of-origin specific exosomes, such as through centrifugation,
chromatography, or filtration, as described above, to produce a
heterogeneous population of exosomes prior to isolation of
cell-of-origin specific exosomes. Alternatively, the exosomes are
not concentrated, or the biological sample is not enriched for
exosomes, prior to isolation of cell-of-origin exosomes.
[0172] FIG. 61 illustrates a flowchart which depicts one method 100
for isolating or identifying cell-of-origin specific exosomes.
First, a biological sample is obtained from a subject in step 102.
The sample can be obtained from a third party or from the same
party performing the analysis. Next, cell-of-origin specific
exosomes are isolated from the biological sample in step 104. The
isolated cell-of-origin specific exosomes are then analyzed in step
106 and a biomarker or bio-signature for a particular phenotype is
identified in step 108. The method may be used for a number of
phenotypes. In some embodiments, prior to step 104, exosomes are
concentrated or isolated from a biological sample to product a
heterogeneous population of exosomes. For example, heterogeneous
population of exosomes may be isolated using centrifugation,
chromatography, filtration, or other methods as described above,
prior to use of one or more binding agents specific for isolating
or identifying exosomes derived from specific cell types, or
cell-of-origin specific exosomes.
[0173] Cell-of-origin specific exosomes can be isolated from a
biological sample of a subject by employing one or more binding
agents that bind with high specificity to the cell-of-origin
specific exosomes. In some instances, a single binding agent can be
employed to isolate cell-of-origin specific exosomes. In other
instances, a combination of binding agents may be employed to
isolate cell-of-origin specific exosomes. For example, at least 2,
3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
25, 50, 75, or 100 different binding agents may be used to isolate
cell-of-origin exosomes. Therefore, an exosome population (e.g.,
exosomes having the same binding agent profile) can be identified
by utilizing a single or a plurality of binding agents.
[0174] One or more binding agents can be selected based on their
specificity for a target antigen(s) that is specific to a
cell-of-origin, tumor or disease. Non-limiting examples of antigens
which may be used singularly, or in combination, to isolate a
cell-of-origin specific exosome, disease specific exosome, or tumor
specific exosome is shown in FIG. 1 and are also described below.
The antigen may be membrane bound antigens which are accessible to
binding agents. The antigen can also be a biomarker for the
phenotype.
[0175] Breast Cancer
[0176] An exosome derived from a breast cancer cell can be isolated
using a binding agent (e.g., antibody), that is specific for an
antigen that is associated with a cell of breast cancer origin
(e.g., cells of glandular or stromal origin). An exosome derived
from a breast cancer cell can be isolated using an antigen
including, but not limited to, BCA-225, hsp70, MART1, ER, VEGFA,
Class III b-tubulin, HER2/neu (for Her2+BC), GPR30, ErbB4 (JM)
isoform, MPR8, MISIIR, fragments thereof, any combination thereof,
or any combination of antigens that are specific for a breast
cancer cell.
[0177] Ovarian Cancer
[0178] An exosome derived from an ovarian cancer cell can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of ovarian cancer origin
including, but not limited to, CA125, VEGFR2, HER2, MISIIR, VEGFA,
CD24, fragments thereof, any combination thereof, or any
combination of antigens that is specific for an ovarian cancer
cell.
[0179] Lung Cancer
[0180] An exosome derived from a lung cancer cell can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for a cell of lung cancer origin including, but not
limited to, CYFRA21-1, TPA-M, TPS, CEA, SCC-Ag, XAGE-1b, HLA Class
1, TA-MUC1, KRAS, hENT1, kinin B1 receptor, kinin B2 receptor,
TSC403, HTI56, DC-LAMP, fragments thereof, any combination thereof,
or any combination of antigens that is specific for a lung cancer
cell.
[0181] Colon Cancer
[0182] An exosome derived from a colon cancer cell can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for a cell of colon cancer origin including, but not
limited to, CEA, MUC2, GPA33, CEACAM5, ENFB1, CCSA-3, CCSA-4,
ADAM10, CD44, NG2, ephrin B1, plakoglobin, galectin 4, RACK1,
tetraspanin-8, FASL, A33, CEA, EGFR, dipeptidase 1, PTEN,
Na(+)-dependent glucose transporter, UDP-glucuronosyltransferase
1A, fragments thereof, any combination thereof, or any combination
of antigens that is specific for a colon cancer cell.
[0183] Prostate Cancer
[0184] An exosome derived from a prostate cancer cell can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of prostate cancer origin
including, but not limited to, PSA, TMPRSS2, FASLG, TNFSF10, PSMA,
NGEP, Il-7RI, CSCR4, CysLT1R, TRPM8, Kv1.3, TRPV6, TRPM8, PSGR,
MISIIR, galectin-3, PCA3, TMPRSS2:ERG, fragments thereof, any
combination thereof, or any combination of antigens that is
specific for a prostate cancer cell.
[0185] Brain Cancer
[0186] An exosome derived from brain cancer cell can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for a cell of brain cancer origin including, but not
limited to, PRMT8, BDNF, EGFR, DPPX, Elk, Densin-180, BAI2, BAI3,
fragments thereof, any combination thereof, or any combination of
antigens that is specific for a brain cancer cell.
[0187] Blood Cancer
[0188] An exosome derived from a hematological malignancy cell can
be isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of hematological malignancy
origin including, but not limited to, CD44, CD58, CD31, CD11a,
CD49d, GARP, BTS, Raftlin, fragments thereof, any combination
thereof, or any combination of antigens that is specific for a
hematological malignancy cell.
[0189] Melanoma
[0190] An exosome derived from a melanoma cell can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for a cell of melanoma origin including, but not
limited to, DUSP1, TYRP1, SILV, MLANA, MCAM, CD63, Alix, hsp70,
meosin, p120 catenin, PGRL, syntaxin binding protein 1 &2,
caveolin, fragments thereof, any combination thereof, or any
combination of antigens that is specific for a melanoma cell.
[0191] Liver Cancer
[0192] An exosome derived from a hepatocellular carcinoma cell can
be isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of hepatocellular carcinoma
origin including, but not limited to, HBxAg, HBsAg, NLT, fragments
thereof, any combination thereof, or any combination of antigens
that is specific for a hepatocellular carcinoma cell.
[0193] Cervical Cancer
[0194] An exosome derived from a cervical cancer cell can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of cervical cancer origin
including, but not limited to, MCT-1, MCT-2, MCT-4, fragments
thereof, any combination thereof, or any combination of antigens
that is specific for a cervical cancer cell.
[0195] Endometrial Cancer
[0196] An exosome derived from an endometrial cancer cell can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of endometrial cancer origin
including, but not limited to, Alpha V Beta 6 integrin, fragments
thereof, any combination thereof, or any combination of antigens
that is specific for an endometrial cancer cell.
[0197] Psoriasis
[0198] An exosome for characterizing psoriasis can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for psoriasis including, but not limited to, flt-1, VPF
receptors, kdr, fragments thereof, any combination thereof, or any
combination of antigens that is specific to psoriasis.
[0199] Autoimmune Disease
[0200] An exosome for characterizing an autoimmune disease can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for an autoimmune disease including, but
not limited to, Tim-2, fragments thereof, or any combination of
antigens that is specific to an autoimmune disease.
[0201] Irritable Bowel Disease
[0202] An exosome for characterizing irritable bowel disease (IBD)
or syndrome (IBS) can be isolated using an antibody, or any other
binding agent, for an antigen that is specific for IBD or IBS
including, but not limited to, IL-16, IL-1beta, IL-12, TNF-alpha,
interferon-gamma, IL-6, Rantes, 11-12, MCP-1, 5HT, fragments
thereof, or any combination of antigens that is specific to IBD or
IBS.
[0203] Diabetes
[0204] An exosome derived from a pancreatic cell can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for a cell of pancreatic origin including, but not
limited to, IL-6, CRP, RBP4, fragments thereof, any combination
thereof, or any combination of antigens that is specific for a
pancreatic cell.
[0205] Barrett's Esophagus
[0206] An exosome for characterizing Barrett's Esophagus can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for Barrett's Esophagus including, but not
limited to, p53, MUC1, MUC6, fragments thereof, any combination
thereof, or any combination of antigens that is specific to
Barrett's Esophagus.
[0207] Fibromyalgia
[0208] An exosome for characterizing fibromyalgia can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for fibromyalgia including, but not limited to,
neopterin, gp130, fragments thereof, any combination thereof, or
any combination of antigens that is specific to fibromyalgia.
[0209] Prostatic Hyperplasia
[0210] An exosome derived from a benign prostatic hyperplasia (BPH)
cell can be isolated using an antibody, or any other binding agent,
for an antigen that is specific for a cell of BPH origin including,
but not limited to, KIA1, intact fibronectin, fragments thereof,
any combination thereof, or any combination of antigens that is
specific for a BPH cell.
[0211] Multiple Sclerosis
[0212] An exosome for characterizing multiple sclerosis (MS) can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for MS including, but not limited to, B7,
B7-2, CD-95 (fas), Apo-1/Fas, fragments thereof, any combination
thereof, or any combination of antigens that is specific to MS.
[0213] Parkinson's Disease
[0214] An exosome for characterizing Parkinson's disease can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for Parkinson's disease including, but not
limited to, PARK2, ceruloplasmin, VDBP, tau, DJ-1, fragments
thereof, any combination thereof, or any combination of antigens
that is specific to Parkinson's disease.
[0215] Rheumatic Disease
[0216] An exosome for characterizing rheumatic disease can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for rheumatic disease including, but not
limited to, Citrulinated fibrin a-chain, CD5 antigen-like
fibrinogen fragment D, CD5 antigen-like fibrinogen fragment B, TNF
alpha, fragments thereof, any combination thereof, or any
combination of antigens that is specific to rheumatic disease.
[0217] Alzheimer's Disease
[0218] An exosome derived from a neuron of a patient suffering from
Alzheimer's disease can be further isolated using an antibody, or
any other binding agent, for an antigen that including, but not
limited to, APP695, APP751 or APP770, BACE1, cystatin C, amyloid
.beta., T-tau, complement factor H or alpha-2-macroglobulin,
fragments thereof, any combination thereof, or any combination of
antigens that are specific for Alzheimer's.
[0219] Head and Neck Cancer
[0220] An exosome derived from a head and neck cancer cell can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of head and neck cancer origin
including, but not limited to, EGFR, EphB4 or Ephrin B2, fragments
thereof, any combination thereof, or any combination of antigens
that is specific for a head and neck cancer cell.
[0221] Gastrointestinal Stromal Tumor
[0222] An exosome derived from a gastrointestinal stromal tumor
(GIST) cell can be isolated using an antibody, or any other binding
agent, for an antigen that is specific for a cell of GIST origin
including, but not limited to, c-kit PDGFRA, NHE-3, fragments
thereof, any combination thereof, or any combination of antigens
that is specific for a GIST cell.
[0223] Renal Cell Carcinoma
[0224] An exosome derived from a renal cell carcinomas (RCC) cell
can be isolated using an antibody, or any other binding agent, for
an antigen that is specific for a cell of RCC origin including, but
not limited to, c PDGFRA, VEGF, HIF 1 alpha, fragments thereof, any
combination thereof, or any combination of antigens that is
specific for a RCC cell.
[0225] Schizophrenia
[0226] An exosome for characterizing schizophrenia can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for schizophrenia including, but not limited to, ATP5B,
ATP5H, ATP6V1B, DNM1, fragments thereof, any combination thereof,
or any combination of antigens that is specific to
schizophrenia.
[0227] Peripheral Neuropathic Pain
[0228] An exosome derived from a nerve cell of a patient suffering
from peripheral neuropathic pain can be isolated using an antibody,
or any other binding agent, for an antigen that is specific for
peripheral neuropathic pain including, but not limited to, OX42,
ED9, fragments thereof, any combination thereof, or any combination
of antigens that is specific for peripheral neuropathic pain.
[0229] Chronic Neuropathic Pain
[0230] An exosome derived from a nerve cell of a patient suffering
from chronic neuropathic pain can be isolated using an antibody, or
any other binding agent, for an antigen that is specific for
chronic neuropathic pain including, but not limited to, chemokine
receptor (CCR2/4), fragments thereof, or any combination of
antigens that is specific for chronic neuropathic pain.
[0231] Prion Disease
[0232] An exosome derived from a cell of a patient suffering from
prion disease can be isolated using an antibody, or any other
binding agent, for an antigen that is specific for prion disease
including, but not limited to, PrPSc, 14-3-3 zeta, S-100, AQP4,
fragments thereof, or any combination of antigens that is specific
for prion disease.
[0233] Stroke
[0234] An exosome for characterizing stroke can be isolated using
an antibody, or any other binding agent, for an antigen that is
specific for stroke including, but not limited to, S-100, neuron
specific enolase, PARK7, NDKA, ApoC-I, ApoC-III, SAA or AT-III
fragment, Lp-PLA2, hs-CRP, fragments thereof, any combination
thereof, or any combination of antigens that is specific to
stroke.
[0235] Cardiovascular Disease
[0236] An exosome for characterizing a cardiovascular disease can
be isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cardiovascular disease including,
but not limited to, FATP6, fragments thereof, or any combination of
antigens that is specific to a cardiovascular disease or cardiac
cell.
[0237] Esophageal Cancer
[0238] An exosome derived from an esophageal cancer cell can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for a cell of esophageal cancer origin
including, but not limited to, CaSR, fragments thereof, or any
combination of antigens that is specific for an esophageal cancer
cell.
[0239] Tuberculosis
[0240] An exosome for characterizing tuberculosis (TB) can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for TB including, but not limited to,
antigen 60, HSP, Lipoarabinomannan, Sulfolipid, antigen of acylated
trehalose family, DAT, TAT, Trehalose 6,6-dimycolate (cord-factor)
antigen, fragments thereof, any combination thereof, or any
combination of antigens that is specific to TB.
[0241] HIV
[0242] An exosome for characterizing HIV can be isolated using an
antibody, or any other binding agent, for an antigen that is
specific for HIV including, but not limited to, gp41, gp120,
fragments thereof, any combination thereof, or any combination of
antigens that is specific to HIV.
[0243] Autism
[0244] An exosome for characterizing autism can be isolated using
an antibody, or any other binding agent, for an antigen that is
specific for autism including, but not limited to, VIP, PACAP,
CGRP, NT3, fragments thereof, any combination thereof, or any
combination of antigens that is specific to autism.
[0245] Asthma
[0246] An exosome for characterizing asthma can be isolated using
an antibody, or any other binding agent, for an antigen that is
specific for asthma including, but not limited to, YKL-40,
S-nitrosothiols, SSCA2, PAI, amphiregulin, periostin, fragments
thereof, any combination thereof, or any combination of antigens
that is specific to asthma.
[0247] Lupus
[0248] An exosome for characterizing lupus can be isolated using an
antibody, or any other binding agent, for an antigen that is
specific for lupus including, but not limited to, TNFR, fragments
thereof, or any combination of antigens that is specific to
lupus.
[0249] Cirrhosis
[0250] An exosome for characterizing cirrhosis can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for cirrhosis including, but not limited to, NLT,
HBsAg, fragments thereof, any combination thereof, or any
combination of antigens that is specific to cirrhosis.
[0251] Influenza
[0252] An exosome for characterizing influenza can be isolated
using an antibody, or any other binding agent, for an antigen that
is specific for influenza including, but not limited to,
hemagglutinin, neurominidase, fragments thereof, any combination
thereof, or any combination of antigens that is specific to
influenza.
[0253] Vulnerable Plaque
[0254] An exosome for characterizing vulnerable plaque can be
isolated using an antibody, or any other binding agent, for an
antigen that is specific for vulnerable plaque including, but not
limited to, Alpha v. Beta 3 integrin, MMP9, fragments thereof, any
combination thereof, or any combination of antigens that is
specific to vulnerable plaque.
[0255] A cell-of-origin specific exosome may be isolated using
novel binding agents, using methods as described above.
Furthermore, a cell-of-origin specific exosome can also be isolated
from a biological sample using isolation methods based on cellular
binding partners or binding agents of such exosomes. Such cellular
binding partners can include but are not limited to peptides,
proteins, RNA, DNA, apatmers, cells or serum-associated proteins
that only bind to such exosomes when one or more specific
biomarkers are present. Isolation of a cell-of-origin specific
exosome can be carried out with a single binding partner or binding
agent, or a combination of binding partners or binding agents whose
singular application or combined application results in
cell-of-origin specific isolation. Non-limiting examples of such
binding agents are provided in FIG. 2. For example, an exosome for
characterizing breast cancer can be isolated with one or more
binding agents including, but not limited to, estrogen,
progesterone, Herceptin (Trastuzumab), CCND1, MYC PNA, IGF-1 PNA,
MYC PNA, SC4 aptamer (Ku), AII-7 aptamer (ERB2), Galectin-3,
mucin-type O-glycans, L-PHA, Galectin-9, or any combination
thereof.
[0256] A binding agent may also be used for isolating the
cell-of-origin specific exosome based on i) the presence of
antigens specific for cell-of-origin specific exosomes cells, ii)
the absence of markers specific for cell-of-origin specific
exosomes, or iii) expression levels of biomarkers specific for
cell-of-origin specific exosomes. A heterogeneous population of
exosomes is applied to a surface coated with specific binding
agents designed to rule out or identify the cell-of-origin
characteristics of the exosomes. Various binding agents, such as
antibodies, can be arrayed on a solid surface or substrate and the
heterogeneous population of exosomes is allowed to contact the
solid surface or substrate for a sufficient time to allow
interactions to take place. Specific binding or non-binding to
given antibody locations on the array surface or substrate can then
serve to identify antigen specific characteristics of the exosome
population that are specific to a given cell-of-origin.
[0257] A cell-of-origin specific exosome can be enriched or
isolated using one or more binding agents using a magnetic capture
method, fluorescence activated cell sorting or laser cytometry as
described above. Magnetic capture methods can include, but are not
limited to, the use of magnetically activated cell sorter (MACS)
microbeads or magnetic columns. Examples of immunoaffinity and
magnetic particle methods that can be used is described in U.S.
Pat. No. 4,551,435, 4,795,698, 4,925,788, 5,108,933, 5,186,827,
5,200,084 or 5,158,871. A cell-of-origin specific exosome can also
be isolated following the general methods described in U.S. Pat.
No. 7,399,632, by using combination of antigens specific to an
exosome.
[0258] Any other method for isolating or otherwise enriching the
cell-of-origin specific exosomes with respect to a biological
sample may also be used in combination with the present invention.
For example, size exclusion chromatography such as gel permeation
columns, centrifugation or density gradient centrifugation, and
filtration methods can be used in combination with the antigen
selection methods described herein. The cell-of-origin specific
exosomes may also be isolated following the methods described in
Koga et al., Anticancer Research, 25:3703-3708 (2005), Taylor et
al., Gynecologic Oncology, 110:13-21 (2008), Nanjee et al., Clin
Chem, 2000; 46:207-223 or U.S. Pat. No. 7,232,653.
Exosome Assessment
[0259] A phenotype can be characterized for a subject by analyzing
a biological sample from the subject and determining the level,
amount, or concentration of one or more populations of exosomes in
the sample. An exosome can be purified or concentrated prior to
determining the amount of exosomes. Alternatively, the amount of
exosomes can be directly assayed from a sample, without prior
purification or concentration. The exosomes can be cell-of-origin
specific exosomes or exosomes with a specific biomarker or
combination of biomarkers. The amount of exosomes can be used to
characterize a phenotype, such as a diagnosis, theranosis or
prognosis of a condition or disease. The amount may be used to
determine a physiological or biological state, such as pregnancy or
the stage of pregnancy. The amount of exosomes can also be used to
determine treatment efficacy, stage of a disease or condition, or
progression of a disease or condition. For example, the amount of
exosomes can be proportional to an increase in disease stage or
progression.
[0260] The exosomes can be evaluated by comparing the level of
exosomes with a reference level or value of exosomes. The reference
value can be particular to physical or temporal endpoint. For
example, the reference value can be from the same subject from whom
a sample is assessed for an exosome, or the reference value can be
from a representative population of samples (e.g., samples from
normal subjects not exhibiting a symptom of disease). Therefore, a
reference value can provide a threshold measurement which is
compared to a subject sample's readout for one or more exosome
populations assayed in a given sample. Such reference values may be
set according to data pooled from groups of sample corresponding to
a particular cohort, including but not limited to age (e.g.,
newborns, infants, adolescents, young, middle-aged adults, seniors
and adults of varied ages), racial/ethnic groups, normal versus
diseased subjects, smoker v. non-smoker, subject receiving therapy
versus untreated subject, different time points of treatment for a
particular individual or group of subjects similarly diagnosed or
treated or combinations thereof.
[0261] A reference value may be based on samples assessed from the
same subject so to provide individualized tracking. Frequent
testing of a patient may provide better comparisons to the
reference values previously established for a particular patient
and would allow a physician to more accurately assess the patient's
disease stage or progression, and to inform a better decision for
treatment. The reduced intraindividual variance of exosomes levels
would allow a more specific and individualized threshold to be
defined for the patient. Temporal intrasubject variation allows
each individual to serve as a longitudinal control for optimum
analysis of disease or physiological state.
[0262] Reference values can be established for unaffected
individuals (of varying ages, ethnic backgrounds and sexes) without
a particular phenotype by determining the amount of exosomes in an
unaffected individual. For example, a reference value for a
reference population can be utilized as a baseline for detection of
one or more exosome populations in a test subject. If a sample from
a subject has a level or value that is similar to the reference,
the subject can be identified to not have the disease, or of having
a low likelihood of developing a disease.
[0263] Alternatively, reference values or levels can be established
for individuals with a particular phenotype by determining the
amount of one or more populations of exosomes in an individual with
the phenotype. In addition, an index of values can be generated for
a particular phenotype. For example, different disease stages can
have different values, such as obtained from individuals with the
different disease stages. A subject's value can be compared to the
index and a diagnosis or prognosis of the disease can be
determined, such as the disease stage or progression. In other
embodiments, an index of values is generated for therapeutic
efficacies. For example, the level of exosomes of individuals with
a particular disease can be generated and noted what treatments
were effective for the individual. The levels can be used to
generate values of which is a subject's value is compared, and a
treatment or therapy can be selected for the individual.
[0264] For example, a reference value can be determined for
individuals unaffected with a particular cancer, by isolating
exosomes with an antigen that specifically targets for the
particular cancer. For example, individuals with varying stages of
colorectal cancer and noncancerous polyps can be surveyed using the
same techniques described for unaffected individuals and the levels
of circulating exosomes for each group defined as means.+-.standard
deviations from at least two separate experiments performed in
triplicate. Comparisons between these groups can be made using
statistical applications such as one-way ANOVA, followed by Tukey's
multiple comparisons post-test comparing each population.
[0265] Reference values can also be established for disease
recurrence monitoring (or exacerbation phase in MS), or for
therapeutic response monitoring.
[0266] The values can be a quantitative or qualitative value. The
values can be a direct measurement of the level of exosomes
(example, mass per volume), or an indirect measure, such as the
amount of a specific exosomal marker. The values can be a
quantitative, such as a numerical value. In other embodiments, the
value is qualitiative, such as no exosomes, low level of exosomes,
medium level, or high level of exosomes, or variations thereof.
[0267] The reference values can be stored in a database and used as
a reference for the diagnosis, prognosis, or theranosis of a
disease or condition based on the level or amount of exosomes, such
as total amount of exosomes, or the amount of a specific population
of exosomes, such as cell-of-origin specific exosomes or exosomes
with one or more specific biomarkers.
[0268] Exosome levels may be characterized using mass spectrometry
or flow cytometry. Analysis may also be carried out on exosomes by
immunocytochemical staining, Western blotting, electrophoresis,
chromatography or x-ray crystallography in accordance with
procedures well known in the art. Exosomes may be characterized and
quantitatively measured using flow cytometry as described in
Clayton et al., Journal of Immunological Methods 2001; 163-174,
which is herein incorporated by reference in its entirety. Exosome
levels may be determined using binding agents as described above.
For example, a binding agent to exosomes can be labeled and the
label detected and used to determine the amount of exosomes in a
sample. The binding agent can be bound to a substrate, such as
arrays or particles, such as described above. Alternatively, the
exosomes may be labeled directly.
[0269] Electrophoretic tags or eTags can also be used to determine
the amount of exosomes. eTags are small fluorescent molecules
linked to nucleic acids or antibodies and are designed to bind one
specific nucleic acid sequence or protein, respectively. After the
eTag binds its target, an enzyme is used to cleave the bound eTag
from the target. The signal generated from the released eTag,
called a "reporter," is proportional to the amount of target
nucleic acid or protein in the sample. The eTag reporters can be
identified by capillary electrophoresis. The unique charge-to-mass
ratio of each eTag reporter--that is, its electrical charge divided
by its molecular weight--makes it show up as a specific peak on the
capillary electrophoresis readout. Thus by targeting a specific
biomarker of an exosome with an eTag, the amount or level of
exosomes can be determined.
[0270] The exosome levels can determined from a heterogeneous
population of exosomes, such as the total population of exosomes in
a sample. Alternatively, the exosomes level is determined from a
homogenous population, or substantially homogenous population of
exosomes, such as the level of specific cell-of-origin exosomes,
such as exosomes from prostate cancer cells. In yet other
embodiments, the level is determined for exosomes with a particular
biomarker or combination of biomarkers, such as a biomarker
specific for prostate cancer. Determining the level of exosome can
be performed in conjunction with determining the biomarker or
combination of biomarkers of an exosome. Alternatively, determining
the amount of exosome may be performed prior to or subsequent to
determining the biomarker or combination of biomarkers of the
exosomes.
[0271] Determining the amount of exosomes can be assayed in a
multiplexed manner. For example, determining the amount of more
than one population of exosomes, such as different cell-of-origin
specific exosomes or exosomes with different biomarkers or
combination of biomarkers, can be performed, such as those
disclosed herein.
[0272] Specificity and Sensitivity
[0273] The level of exosomes as determined using one or more
processes disclosed herein can be used to characterize a phenotype
with increased sensitivity and the specificity. The sensitivity can
be determined by: (number of true positives)/(number of true
positives+number of false negatives). The specificity can be
determined by: (number of true negatives)/(number of true
negatives+number of false positives).
[0274] The level of exosomes as determined using one or more
processes disclosed herein can be used to characterize a phenotype
with at least 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, or 70%
sensitivity, such as with at least 71, 72, 73, 74, 75, 76, 77, 78,
79, 80, 81, 82, 83, 84, 85, 86, or 87% sensitivity. For example,
the phenotype can be characterized with at least 87.1, 87.2, 87.3,
87.4, 87.5, 87.6, 87.7, 87.8, 87.9, 88.0, or 89% sensitivity, such
as with at least 90% sensitivity. The phenotype can be
characterized with at least 91, 92, 93, 94, 95, 96, 97, 98, 99 or
100% sensitivity.
[0275] The phenotype of a subject can also be characterized with at
least 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83, 84,
85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, or 97% specificity,
such as with at least 97.1, 97.2, 97.3, 97.4, 97.5, 97.6, 97.7,
97.8, 97.8, 97.9, 98.0, 98.1, 98.2, 98.3, 98.4, 98.5, 98.6, 98.7,
98.8, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6, 99.7, 99.8,
99.9 or 100% specificity.
[0276] The phenotype can also be characterized with at least 70%
sensitivity and at least 80, 90, 95, 99, or 100% specificity; at
least 75% sensitivity and at least 80, 90, 95, 99, or 100%
specificity; at least 80% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; at least 85% sensitivity and at least 80,
85, 90, 95, 99, or 100% specificity; at least 86% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; at least 87%
sensitivity and at least 80, 85, 90, 95, 99, or 100% specificity;
at least 88% sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity; at least 89% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; at least 90% sensitivity and at least 80,
85, 90, 95, 99, or 100% specificity; at least 95% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; at least 99%
sensitivity and at least 80, 85, 90, 95, 99, or 100% specificity;
or at least 100% sensitivity and at least 80, 85, 90, 95, 99, or
100% specificity.
[0277] Furthermore, the confidence level for determining the
specificity, sensitivity, or both, may be with at least 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99% confidence.
Bio-Signatures
[0278] A bio-signature of an exosome from a subject can be used to
characterize a phenotype. A bio-signature can reflect the
particular antigens or biomarkers that are present on an exosome.
In addition, a bio-signature can also reflect one or more
biomarkers that are carried in an exosome. Alternatively, a
bio-signature can comprise a combination of one or more antigens or
biomarkers that are present on an exosome with one or more
biomarkers that are detected in the exosome.
[0279] The exosome can be purified or concentrated prior to
determining the bio-signature of the exosome. Alternatively, the
bio-signature of the exosome can be directly assayed from a sample,
without prior purification or concentration. An exosome can also be
isolated prior to assaying. For example, a cell-of-origin specific
exosome can be isolated and its bio-signature determined. The
bio-signature is used to determine a diagnosis, prognosis, or
theranosis of a disease or condition. Therefore, a bio-signature
can also be used to determine treatment efficacy, stage of a
disease or condition, or progression of a disease or condition.
Furthermore, a bio-signature may be used to determine a
physiological state, such as pregnancy.
[0280] An exosomal characteristic in and of itself can be assessed
to determine a bio-signature. The exosomal characteristic can be
used to diagnose, detect or determine a disease stage or
progression, the therapeutic implications of a disease or
condition, or characterize a physiological state. An exosomal
characteristic can include, but is not limited to, the level or
amount of exosomes, temporal evaluation of the variation in
exosomal half-life, circulating exosomal half-life or exosomal
metabolic half-life, or the activity of an exosome.
[0281] In addition, a bio-signature can also correspond to an
expression level, presence, absence, mutation, variant, copy number
variation, truncation, duplication, modification, or molecular
association of one or more biomarkers. A biomarker may be any
exosomal component and can form its own signature. For example, the
biomarker may be the RNA content of the exosome, such that the RNA
signature includes one or more RNA species, such as, but not
limited to, mRNA, miRNA, snoRNA, snRNA, rRNAs, tRNAs, siRNA, hnRNA,
shRNA, or a combination thereof. Therefore, an exosome can be
assayed to determine a RNA signature.
[0282] Other biomarkers include, but are not limited to, one or
more proteins or peptides (e.g., providing a protein signature),
nucleic acids (e.g. RNA signature as described, or a DNA
signature), lipids (e.g. lipid signature), or combinations thereof.
In some embodiments, the bio-signature can also comprise the type
or amount of drug or drug metabolite present in an exosome (e.g.
drug signature), as such drug may be taken by a subject from which
the biological sample is obtained from, resulting in an exosome
carrying such drug, or metabolites of such drug.
[0283] An RNA signature or DNA signature can also include a
mutational, epigenetic modification, or genetic variant analysis of
the RNA or DNA present in the exosome. In addition, a protein
signature can include, but is not limited to, the mutation,
modification, overexpression, underexpression, presence or absence
of antigens, peptides, proteins or combinations thereof.
[0284] A bio-signature of an exosome can comprise one or more miRNA
signatures combined with one or more additional signatures
including, but not limited to, an mRNA signature, DNA signature,
protein signature, peptide signature, antigen signature, or any
combination thereof. For example, the bio-signature can comprise
one or more miRNA biomarkers with one or more DNA biomarkers, one
or more mRNA biomarkers, one or more snoRNA biomarkers, one or more
protein biomarkers, one or more peptide biomarkers, one or more
antigen biomarkers, one or more antigen biomarkers, one or more
lipid biomarkers, or any combination thereof.
[0285] A bio-signature can comprise a combination of one or more
antigens or binding agents (such as ability to bind one or more
binding agents), such as listed in FIGS. 1 and 2, respectively. The
bio-signature can further comprise one or more other biomarkers,
such as, but not limited to, miRNA, DNA (e.g. single stranded DNA,
complementary DNA, or noncoding DNA), or mRNA. For example, the
bio-signature of an exosome can comprise a combination of one or
more antigens, such as shown in FIG. 1, one or more binding agents,
such as shown in FIG. 2, and one or more biomarkers for a condition
or disease, such as listed in FIGS. 3-60. The bio-signature can
comprise one or more biomarkers, for example miRNA, with one or
more antigens specific for a cancer cell (for example, as shown in
FIG. 1).
[0286] An exosome can have a bio-signature that is specific to the
cell-of-origin and, as such, can be utilized to derive
disease-specific or biological state specific diagnostic,
prognostic or therapy-related bio-signatures representative of the
cell-of-origin. An exosome may also have a bio-signature that is
specific to a given disease or physiological condition that may be
different from the bio-signature of the cell-of-origin, but no less
important to the diagnosis, prognosis, staging, therapy-related
determinations or physiological state characterization.
[0287] The bio-signature of an exosome, such as a cell-of-origin
specific exosome described herein, can be used clinically in making
decisions concerning treatment modalities, including therapeutic
intervention, diagnostic criteria such as disease staging, disease
monitoring, and disease stratification, and surveillance for
detection, metastasis or recurrence or progression of disease. The
bio-signature of an exosome, such as an isolated cell-of-origin
specific exosome can further be used clinically to make treatment
decisions, including whether to perform surgery or what treatment
standards should be utilized along with surgery (e.g., either
pre-surgery or post-surgery).
[0288] An exosome bio-signature can also be used in therapy related
diagnostics to provide tests useful to diagnose a disease or choose
the correct treatment regimen, as well as monitor a subject's
response. Therapy related tests are useful to predict and assess
drug response in individual subjects, i.e., to provide personalized
medicine. Therapy related tests are also useful to select a subject
for treatment who is particularly likely to benefit from the
treatment or to provide an early and objective indication of
treatment efficacy in an individual subject. For example, a
treatment can be altered without the great expense of delaying
beneficial treatment as well as the great financial cost of
administering an ineffective drug(s).
[0289] Therapy related diagnostics are also useful in clinical
diagnosis and management of a variety of diseases and disorders,
which include, but are not limited to cardiovascular disease,
cancer, infectious diseases, sepsis, neurological diseases, central
nervous system related diseases, endovascular related diseases, and
autoimmune related diseases or the prediction of drug toxicity,
drug resistance or drug response. Therapy related tests may be
developed in any suitable diagnostic testing format, which include,
but are not limited to, e.g., immunohistochemical tests, clinical
chemistry, immunoassay, cell-based technologies, nucleic acid tests
or body imaging methods. Therapy related tests can further include
but are not limited to, testing that aids in the determination of
therapy, testing that monitors for therapeutic toxicity, or
response to therapy testing. For example, a bio-signature can
determine whether a particular disease or condition is resistant to
a drug, and therefore, a physician need not waste valuable time
with hit-and-miss treatment. Instead, to obtain early validation of
a drug choice or treatment regimen, a bio-signature is determined
for an exosome obtained from a subject, which then determines
whether the particular subject's disease has the biomarker
associated with drug resistance. Therefore, such a determination
enables doctors to devote critical time as well as the patient's
financial resources to effective treatments.
[0290] Moreover, an exosome bio-signature may be used to assess
whether a subject is afflicted with disease, is at risk for
developing disease or to assess the stage or progression of the
disease. For example, a bio-signature can be used to assess whether
a subject has prostate cancer (for example, FIGS. 68, 73) or colon
cancer (for example, FIGS. 69, 74). Furthermore, a bio-signature
can be used to determine a stage of a disease or condition, such as
colon cancer (for example, FIGS. 71, 72).
[0291] Furthermore, determining the amount of exosomes, such a
heterogeneous population of exosomes, and the amount of one or more
homogeneous population of exosomes, such as a population of
exosomes with the same bio-signature, can be used to characterize a
phenotype. For example, determination of the total amount of
exosomes in a sample (i.e. not cell-type specific) and determining
the presence of one or more different cell-of-origin specific
exosomes (such as cell-of-origin specific exosomes) can be used to
characterize a phenotype. Threshold values, or reference values or
amounts can be determined based on comparisons of normal subjects
and subjects with the phenotype of interest, as further described
below, and criteria based on the threshold or reference values
determined. The different criteria can be used to characterize a
phenotype.
[0292] For example, one criterion can be based on the amount of a
heterogeneous population of exosomes in a sample. If the amount is
lower than a threshold value or reference value, the criterion is
met. Alternatively, the criterion can be based on whether the
amount of exosomes is higher than a threshold or reference value.
Another criterion can be the amount of exosomes with a specific
bio-signature or biomarker. If the amount of exosomes with the
specific bio-signature or biomarker is lower, or higher, than a
threshold or reference value, the criterion is met. A criterion can
also be based on the amount of exosomes derived from a particular
cell type. If the amount is lower, or higher, than a threshold or
reference value, the criterion is met. Another criterion can be
based on whether the amount of exosomes derived from a cancer cell
or comprising one or more cancer specific biomarkers. If the amount
is lower, or higher, than a threshold or reference value, the
criterion is met. A criterion can also be the reliability of the
result, such as meeting a quality control measure or value.
[0293] A phenotype for a subject can be characterized based on
meeting at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 criteria. For
example, for the characterizing of a cancer, a number of different
criteria can be used: 1) if the amount of exosomes in a sample from
a subject is higher than a reference value; 2) if the amount of a
cell type (ie. derived from a specific tissue or organ) specific
exosomes is higher than a reference value; and 3) if the amount of
exosomes with one or more cancer specific biomarkers is higher than
a reference value, the subject is diagnosed with a cancer. The
method can further include a quality control measure, such that the
results are provided for the subject if the samples meet the
quality control measure.
[0294] A bio-signature can be determined by comparing the amount of
exosomes, the structure of an exosome, (using transmission electron
microscopy, see for example, Hansen et al., Journal of Biomechanics
31, Supplement 1: 134-134(1) (1998), or scanning electron
microscopy), or any other exosomal characteristic. Various
combinations of methods and techniques or analyzing one or more
exosomes can be used to determine a phenotype for a subject.
[0295] An exosome characteristic can include, but is not limited to
the presence or absence, copy number, expression level, or activity
level of a biomarker. The presence of a mutation (e.g., mutations
which affect activity of the biomarker, such as substitution,
deletion, or insertion mutations), variant, or post-translation
modification of a biomarker, such as a protein biomarker, can
include, but not be limited to, acylation, acetylation,
phosphorylation, ubiquitination, deacetylation, alkylation,
methylation, amidation, biotinylation, gamma-carboxylation,
glutamylation, glycosylation, glycyation, hydroxylation, covalent
attachment of heme moiety, iodination, isoprenylation, lipoylation,
prenylation, GPI anchor formation, myristoylation, farnesylation,
geranylgeranylation, covalent attachment of nucleotides or
derivatives thereof, ADP-ribosylation, flavin attachment,
oxidation, palmitoylation, pegylation, covalent attachment of
phosphatidylinositol, phosphopantetheinylation, polysialylation,
pyroglutamate formation, racemization of proline by prolyl
isomerase, tRNA-mediation addition of amino acids such as
arginylation, sulfation, the addition of a sulfate group to a
tyrosine, or selenoylation of the biomarker can also be an exosomal
characteristic.
[0296] The methods described above can be used to identify an
exosome bio-signature that is associated with a disease, condition
or physiological state.
[0297] The bio-signature can also be utilized to determine if a
subject is afflicted with cancer or is at risk for developing
cancer. A subject at risk of developing cancer can include those
who may be predisposed or who have pre-symptomatic early stage
disease.
[0298] A bio-signature can also be utilized to provide a diagnostic
or theranostic determination for other diseases including but not
limited to autoimmune diseases, inflammatory bowel diseases,
Alzheimer's disease, Parkinson's disease, Multiple Sclerosis,
sepsis or pancreatitis or any disease, conditions or symptoms
listed in FIGS. 3-58.
[0299] The bio-signature can also be used to identify a given
pregnancy state from the peripheral blood, umbilical cord blood, or
amniotic fluid (e.g. miRNA signature specific to Downs Syndrome) or
adverse pregnancy outcome such as pre-eclampsia, pre-term birth,
premature rupture of membranes, intrauterine growth restriction or
recurrent pregnancy loss. The bio-signature can also be used to
indicate the health of the mother, the fetus at all developmental
stages, the pre-implantation embryo or a newborn.
[0300] A bio-signature can be utilized for pre-symptomatic
diagnosis. Furthermore, the bio-signature can be utilized to detect
disease, determine disease stage or progression, determine the
recurrence of disease, identify treatment protocols, determine
efficacy of treatment protocols or evaluate the physiological
status of individuals related to age and environmental
exposure.
[0301] Monitoring the bio-signature of an exosome can also be used
to identify toxic exposures in a subject including, but not limited
to, situations of early exposure or exposure to an unknown or
unidentified toxic agent. Without being bound by any one specific
theory for mechanism of action, exosomes are shed from damaged
cells and in the process compartmentalize specific contents of the
cell including both membrane components and engulfed cytoplasmic
contents. Cells exposed to toxic agents/chemicals may increase
exosome shedding to expel toxic agents or metabolites thereof, thus
resulting in increased exosome levels. Thus, monitoring an exosome
and/or bio-signature allows assessment of an individual's response
to potential toxic agent(s).
[0302] Furthermore, an exosome can be used to identify states of
drug-induced toxicity or the organ injured, by detecting one or
more specific antigen, binding agent, biomarker, or any combination
thereof of the exosome. Therefore, the exosome, or exosome
bio-signature can be used to monitor an individual for acute,
chronic, or occupational exposures to any number of toxic agents
including, but not limited to, drugs, antibiotics, industrial
chemicals, toxic antibiotic metabolites, herbs, household
chemicals, and chemicals produced by other organisms, either
naturally occurring or synthetic in nature.
[0303] In addition, an exosome bio-signature can be used to
identify conditions or diseases, including cancers of unknown
origin, also known as cancers of unknown primary (CUP). For
example, an exosome may be isolated from a biological sample as
previously described to arrive at a heterogeneous population of
exosomes. The heterogeneous population of exosomes can then be
applied to surfaces coated with specific binding agents designed to
rule out or identify antigen specific characteristics of the
exosome population that are specific to a given cell-of-origin.
Further, as described above, the bio-signature of a specific
cell-of-origin exosome can correlate with the cancerous state of
cells. Compounds that inhibit cancer in a subject may cause a
change, e.g., a change in bio-signature of specific cell-of-origin
exosome, which can be monitored by serial isolation of a
cell-of-origin exosome over time and treatment course.
[0304] Alternatively, an exosome bio-signature can be used to
assess the efficacy of a therapy, e.g., chemotherapy, radiation
therapy, surgery, or any other therapeutic approach useful for
inhibiting cancer in a subject. In addition, an exosome
bio-signature can be used in a screening assay to identify
candidate or test compounds or agents (e.g., proteins, peptides,
peptidomimetics, peptoids, small molecules or other drugs) that
have a modulatory effect on the bio-signature of a specific
cell-of-origin exosome. Compounds identified via such screening
assays may be useful, for example, for modulating, e.g.,
inhibiting, ameliorating, treating, or preventing conditions or
diseases.
[0305] For example, a bio-signature for an exosome can be obtained
from a patient who is undergoing successful treatment for a
particular cancer. Cells from a cancer patient not being treated
with the same drug can be cultured and exosomes from the cultures
obtained for determining bio-signatures. The cells can be treated
with test compounds and the bio-signature of the exosomes from the
cultures can be compared to the bio-signature of the exosomes
obtained from the patient undergoing successful treatment. The test
compounds that results in exosome bio-signatures that are similar
to those of the patient undergoing successful treatment can be
selected for further studies.
[0306] The bio-signature of a specific cell-of-origin exosome can
also be used to monitor the influence of an agent (e.g., drug
compounds) on the bio-signature in clinical trials. Monitoring an
exosome bio-signature can also be used in a method of assessing the
efficacy of a test compound, such as a test compound for inhibiting
cancer cells.
[0307] An exosome bio-signature can also be used to determine the
effectiveness of a particular therapeutic intervention
(pharmaceutical or non-pharmaceutical) and to alter the
intervention to 1) reduce the risk of developing adverse outcomes,
2) enhance the effectiveness of the intervention or 3) identify
resistant states. Thus, in addition to diagnosing or confirming the
presence of or risk for developing a disease, condition or a
syndrome, the methods and compositions disclosed herein also
provide a system for optimizing the treatment of a subject having
such a disease, condition or syndrome. For example, a
therapy-related approach to treating a disease, condition or
syndrome by integrating diagnostics and therapeutics to improve the
real-time treatment of a subject can be determined by identifying
the bio-signature of an exosome.
[0308] Tests that identify an exosome bio-signature can be used to
identify which patients are most suited to a particular therapy,
and provide feedback on how well a drug is working, so as to
optimize treatment regimens. For example, in pregnancy-induced
hypertension and associated conditions, therapy-related diagnostics
can flexibly monitor changes in important parameters (e.g.,
cytokine and/or growth factor levels) over time, to optimize
treatment.
[0309] Within the clinical trial setting of investigational agents
as defined by the FDA, MDA, EMA, USDA, and EMEA, therapy-related
diagnostics as determined by a bio-signature disclosed herein, can
provide key information to optimize trial design, monitor efficacy,
and enhance drug safety. For instance, for trial design,
therapy-related diagnostics can be used for patient stratification,
determination of patient eligibility (inclusion/exclusion),
creation of homogeneous treatment groups, and selection of patient
samples that are optimized to a matched case control cohort. Such
therapy-related diagnostic can therefore provide the means for
patient efficacy enrichment, thereby minimizing the number of
individuals needed for trial recruitment. For example, for
efficacy, therapy-related diagnostics are useful for monitoring
therapy and assessing efficacy criteria. Alternatively, for safety,
therapy-related diagnostics can be used to prevent adverse drug
reactions or avoid medication error and monitor compliance with the
therapeutic regimen.
[0310] Therefore, an exosomal bio-signature can be used to monitor
drug efficacy, determine response or resistance to a given drug,
and thereby enhance drug safety. For example, in colon cancer,
exosomes are typically shed from colon cancer cells and can be
isolated from the peripheral blood and used to isolate one or more
biomarkers (e.g., KRAS mRNA). In the case of mRNA biomarkers, the
mRNA can be reverse transcribed into cDNA and sequenced (e.g., by
Sanger sequencing) to determine if there are mutations present that
confer resistance to a drug (e.g., cetuximab or panitumimab).
[0311] In another example, exosomes that are specifically shed from
lung cancer cells are isolated from a biological sample and used to
isolate a lung cancer biomarker, e.g., EGFR mRNA. The EGFR mRNA is
processed to cDNA and sequenced to determine if there are EGFR
mutations present that show resistance or response to specific
drugs or treatments for lung cancer.
[0312] One or more exosome bio-signatures can be grouped so that
information obtained about the set of bio-signatures in a
particular group provides a reasonable basis for making a
clinically relevant decision, such as but not limited to a
diagnosis, prognosis, or management of treatment, such as treatment
selection.
[0313] As with most diagnostic markers, it is often desirable to
use the fewest number of markers sufficient to make a correct
medical judgment. This prevents a delay in treatment pending
further analysis as well inappropriate use of time and
resources.
[0314] Also disclosed herein are methods of conducting
retrospective analysis on samples (e.g., serum and tissue biobanks)
for the purpose of correlating qualitative and quantitative
properties, such as exosome bio-signatures, with clinical outcomes
in terms of disease state, disease stage, progression, prognosis;
therapeutic efficacy or selection; or physiological conditions.
Furthermore, methods and compositions disclosed herein are utilized
for conducting prospective analysis on a sample (e.g., serum and/or
tissue collected from individuals in a clinical trial) for the
purpose of correlating qualitative and quantitative exosome
bio-signatures with clinical outcomes in terms of disease state,
disease stage, progression, prognosis; therapeutic efficacy or
selection; or physiological conditions can also be performed. As
used herein, exosome bio-signatures can be to cell-of-origin
specific exosomes. Furthermore, bio-signatures can be determined
based on an exosome surface marker profile and/or exosome contents
(e.g., biomarkers).
[0315] An exosome bio-signature can comprise at least 2, 3, 4, 5,
6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 40,
50, 75, or 100 characteristics. A bio-signature with more than one
exosomal characteristic, such as at least 2, 3, 4, 5, 6, 7, 8, 9,
10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 40, 50, 75, or
100 characteristics, may provide higher sensitivity, specificity,
or both, in determining a phenotype. For example, assessing a
plurality of exosomal characteristics can provide increased
sensitivity, specificity, or both, as compared to assessing less
than a plurality of exosomal characteristics.
[0316] A bio-signature comprising more than one exosomal
characteristic can be used to characterize a phenotype with at
least 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, or 70% sensitivity,
such as with at least 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81,
82, 83, 84, 85, 86, or 87% sensitivity. For example, the phenotype
can be characterized with at least 87.1, 87.2, 87.3, 87.4, 87.5,
87.6, 87.7, 87.8, 87.9, 88.0, or 89% sensitivity, such as at least
90% sensitivity. The phenotype can be characterized with at least
91, 92, 93, 94, 95, 96, 97, 98, 99 or 100% sensitivity.
[0317] The bio-signature can be used to characterize a phenotype of
a subject with at least 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80,
81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, or
97% specificity, such as with at least 97.1, 97.2, 97.3, 97.4,
97.5, 97.6, 97.7, 97.8, 97.8, 97.9, 98.0, 98.1, 98.2, 98.3, 98.4,
98.5, 98.6, 98.7, 98.8, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5,
99.6, 99.7, 99.8, 99.9 or 100% specificity.
[0318] The phenotype can also be characterized using a
bio-signature with at least 70% sensitivity and at least 80, 90,
95, 99, or 100% specificity; at least 75% sensitivity and at least
80, 90, 95, 99, or 100% specificity; at least 80% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; at least 85%
sensitivity and at least 80, 85, 90, 95, 99, or 100% specificity;
at least 86% sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity; at least 87% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; at least 88% sensitivity and at least 80,
85, 90, 95, 99, or 100% specificity; at least 89% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; at least 90%
sensitivity and at least 80, 85, 90, 95, 99, or 100% specificity;
at least 95% sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity; at least 99% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; or at least 100% sensitivity and at least
80, 85, 90, 95, 99, or 100% specificity.
[0319] Furthermore, the confidence level for determining the
specificity, sensitivity, or both, may be with at least 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99% confidence.
Bio-Signatures: Exosomal Biomarkers
[0320] An exosome bio-signature can comprise one or more
biomarkers. An exosomal biomarker can be any component present in
an exosome or on the exosome, such as any nucleic acid (e.g. RNA or
DNA); protein, peptide, polypeptide, antigen, lipid, carbohydrate,
or proteoglycan.
[0321] The bio-signature can include the presence or absence,
expression level, mutational state, genetic variant state, or any
modification (such as epigentic modification, post-translation
modification) of a biomarker (e.g. any one or more biomarker listed
in FIGS. 1, 3-60). The expression level of a biomarker can be
compared to a control or reference, to determine the overexpression
or underexpression (or upregulation or downregulation) of a
biomarker in a sample. The control or reference level can be the
amount of a biomarker, such as a miRNA in a control sample, such as
a sample from a subject that does not have or exhibit the condition
or disease, and further described below.
[0322] The nucleic acid can be any RNA or DNA species. For example,
the biomarker can be mRNA, miRNA, small nucleolar RNAs (snoRNA),
small nuclear RNAs (snRNA), ribosomal RNAs (rRNA), heterogeneous
nuclear RNA (hnRNA), ribosomal RNAS (rRNA), siRNA, transfer RNAs
(tRNA), or shRNA. The DNA can be double-stranded DNA, single
stranded DNA, complementary DNA, or noncoding DNA.
[0323] In addition, the biomarker can be a polypeptide, peptides or
protein, such as the modification state, truncations, mutations,
expression level (such as overexpression or underexpression as
compared to a reference level), and post-translational
modifications, such as described above.
[0324] An exosome bio-signature may include a number of the same
type of biomarkers (e.g., two different mRNAs, each corresponding
to a different gene) or one or more of different types of
biomarkers (e.g. mRNAs, miRNAs, proteins, peptides, ligands, and
antigens).
[0325] One or more exosome bio-signatures can comprise at least one
biomarker selected from those listed in FIGS. 1, 3-60. A specific
cell-of-origin bio-signature may include one or more biomarkers.
FIGS. 3-58 depict tables which lists a number of disease or
condition specific biomarkers that can be derived and analyzed from
an exosome. The biomarker can also beCD24, midkine, hepcidin,
TMPRSS2-ERG, PCA-3, PSA, EGFR, EGFRvIII, BRAF variant, MET, cKit,
PDGFR, Wnt, beta-catenin, K-ras, H-ras, N-ras, Raf, N-myc, c-myc,
IGFR, PI3K, Akt, BRCA1, BRCA2, PTEN, VEGFR-2, VEGFR-1, Tie-2,
TEM-1, CD276, HER-2, HER-3, or HER-4. The biomarker can also be
annexin V, CD63, Rab-5b, or caveolin, or a miRNA, such as let-7a;
miR-15b; miR-16; miR-19b; miR-21; miR-26a; miR-27a; miR-92; miR-93;
miR-320 or miR-20. The biomarker can also be of any gene or
fragment thereof as disclosed in PCT Publication No. WO2009/100029,
such as those listed in Tables 3-15.
[0326] Other biomarkers useful for assessment in methods and
compositions disclosed herein can include those associated with
conditions or physiological states as disclosed in Rajendran et
al., Proc Natl Acad Sci USA 2006; 103:11172-11177, Taylor et al.,
Gynecol Oncol 2008; 110:13-21, Zhou et al., Kidney Int 2008;
74:613-621, Buning et al., Immunology 2008, Prado et al. J Immunol
2008; 181:1519-1525, Vella et al. (2008) Vet Immunol Immunopathol
124(3-4): 385-93, Gould et al. (2003). Proc Natl Acad Sci USA
100(19): 10592-7, Fang et al. (2007). PLoS Biol 5(6): e158, Chen,
B. J. and R. A. Lamb (2008). Virology 372(2): 221-32, Bhatnagar, S,
and J. S. Schorey (2007). J Biol Chem 282(35): 25779-89, Bhatnagar
et al. (2007) Blood 110(9): 3234-44, Yuyama, et al. (2008). J
Neurochem 105(1): 217-24, Gomes et al. (2007). Neurosci Lett.
428(1): 43-6, Nagahama et al. (2003). Autoimmunity 36(3): 125-31,
Taylor, D. D., S. Akyol, et al. (2006). J Immunol 176(3): 1534-42,
Peche, et al. (2006). Am J Transplant 6(7): 1541-50, lero, M., M.
Valenti, et al. (2008). Cell Death and Differentiation 15: 80-88,
Gesierich, S., I. Berezoversuskiy, et al. (2006), Cancer Res
66(14): 7083-94, Clayton, A., A. Turkes, et al. (2004). Faseb J
18(9): 977-9, Skriner., K. Adolph, et al. (2006). Arthritis Rheum
54(12): 3809-14, Brouwer, R., G. J. Pruijn, et al. (2001).
Arthritis Res 3(2): 102-6, Kim, S. H., N. Bianco, et al. (2006).
Mol Ther 13(2): 289-300, Evans, C. H., S. C. Ghivizzani, et al.
(2000). Clin Orthop Relat Res (379 Suppl): S300-7, Zhang, H. G., C.
Liu, et al. (2006). J Immunol 176(12): 7385-93, Van Niel, G., J.
Mallegol, et al. (2004). Gut 52: 1690-1697, Fiasse, R. and O. Dewit
(2007). Expert Opinion on Therapeutic Patents 17(12):
1423-1441(19).
[0327] A biomarker that can be derived and analyzed from an exosome
includes, but is not limited to, the presence or absence,
expression level, mutations (for example genetic mutations, such as
deletions, translocations, duplications, nucleotide or amino acid
substitutions, and the like) of miRNA (miR) and miRNA*nonsense
(miR*), and other RNAs (including, but not limited to, mRNA,
preRNA, preRNA, hnRNA, snRNA, siRNA, shRNA), DNA, proteins,
peptides, and ligands. Any epigenetic modulation or copy number
variation of a biomarker can also be analyzed. A miRNA biomarker
includes not only its miRNA and microRNA*nonsense, but its
precursor molecules: pri-microRNAs (pri-miRs) and pre-microRNAs
(pre-miRs) are also included as biomarkers. The sequence of a miRNA
can be obtained from publicly available databases such as
http://www.mirbase.org/, http://www.microrna.org/, or any others
available.
[0328] The one or more biomarkers analyzed from an exosome can be
indicative of a particular tissue or cell of origin, disease, or
physiological state, as further described below. Furthermore, the
presence, absence or expression level of one or more of the
biomarkers described herein can be correlated to a phenotype of a
subject, including a disease, condition, prognosis or drug
efficacy. The specific biomarker and bio-signature set forth below
constitute non-inclusive examples for each of the diseases,
condition comparisons, conditions, and/or physiological states.
Furthermore, the one or more biomarker assessed for a phenotype can
be a cell-of-origin specific exosome, such as those described
above.
[0329] The one or more miRNAs used to characterize a phenotype may
be selected from those disclosed in PCT Publication No.
WO2009/036236. For example, one or more miRNAs listed in Tables
I-VI (FIGS. 6-11) can be used to characterize colon adenocarcinoma,
colorectal cancer, prostate cancer, lung cancer, breast cancer,
b-cell lymphoma, pancreatic cancer, diffuse large BCL cancer, CLL,
bladder cancer, renal cancer, hypoxia-tumor, uterine leiomyomas,
ovarian cancer, hepatitis C virus-associated hepatocellular
carcinoma, ALL, Alzheimer's disease, myelofibrosis, myelofibrosis,
polycythemia vera, thrombocythemia, HIV, or HIV-I latency, as
further described herein.
[0330] The one or more miRNAs can be detected in plasma exosomes.
The one or more miRNAs can be miR-223, miR-484, miR-191, miR-146a,
miR-016, miR-026a, miR-222, miR-024, miR-126, and miR-32. One or
more miRNAs can also be detected in PBMC. The one or more miRNAs
can be miR-223, miR-150, miR-146b, miR-016, miR-484, miR-146a,
miR-191, miR-026a, miR-019b, or miR-020a. The one or more miRNAs
can be used to characterize a particular disease or condition. For
example, for the disease bladder cancer, one or more miRNAs can be
detected, such as miR-223, miR-26b, miR-221, miR-103-1, miR-185,
miR-23b, miR-203, miR-17-5p, miR-23a, miR-205 or any combination
thereof. The one or more miRNAs may be upregulated or
overexpressed.
[0331] In some embodiments, the one or more miRNAs is used to
characterize hypoxia-tumor. The one or more miRNA may be miR-23,
miR-24, miR-26, miR-27, miR-103, miR-107, miR-181, miR-210, or
miR-213, and may be upregulated. One or more miRNAs can also be
used to characterize uterine leiomyomas. For example, the one or
more miRNAs used to characterize a uterine leiomyoma may be a let-7
family member, miR-21, miR-23b, miR-29b, or miR-197. The miRNA can
be upregulated.
[0332] Myelofibrosis can also be characterized by one or more
miRNAs, such as miR-190, which can be upregulated; miR-31, miR-150
and miR-95, which can be downregulated, or any combination thereof.
Furthermore, myelofibrosis, polycythemia vera or thrombocythemia
can also be characterized by detecting one or more miRNAs, such as,
but not limited to, miR-34a, miR-342, miR-326, miR-105, miR-149,
miR-147, or any combination thereof. The one or more miRNAs may be
down-regulated.
[0333] Other examples of phenotypes that can be characterized by
assessing an exosome for one or more biomarkers are further
described herein.
[0334] The one or more biomarkers can be detected by a probe. A
probe can comprise of an oligonucleotide, such as DNA or RNA, an
aptamer, monoclonal antibody, polyclonal antibody, Fabs, Fab',
single chain antibody, synthetic antibody, peptoid, zDNA, peptide
nucleic acid (PNA), locked nucleic acid (LNA), lectin, synthetic or
naturally occurring chemical compound (including but not limited to
a drug or labeling reagent), dendrimer, or any combination thereof.
The probe can be directly detected, for example by being directly
labeled, or be indirectly detected, such as through a labeing
reagent. The probe can selectively hybridize to a biomarker. For
example, a probe that is an oligonucleotide can selectively
hybridize to a miRNA biomarker.
[0335] Breast Cancer
[0336] Breast cancer specific biomarkers can include one or more
(for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed miRs,
underexpressed miRs, mRNA, genetic mutations, proteins, ligands,
peptides, snoRNA, or any combination thereof, such as listed in
FIG. 3.
[0337] One or more breast cancer specific biomarker can be assessed
to provide a breast cancer specific exosome bio-signature. For
example, the bio-signature can comprise one or more overexpressed
miRs, including but not limited to, miR-21, miR-155, miR-206,
miR-122a, miR-210, miR-21, miR-21, miR-155, miR-206, miR-122a,
miR-210, or miR-21, or any combination thereof.
[0338] The bio-signature can also comprise one or more
underexpressed miRs such as, but not limited to, let-7, miR-10b,
miR-125a, miR-125b, miR-145, miR-143, miR-145, miR-16, let-7,
let-7, let-7, miR-10b, miR-125a, miR-125b, or miR-145, or any
combination thereof.
[0339] The mRNAs that may be analyzed can include, but are not
limited to, ER, PR, HER2, MUC1, or EGFR, or any combination
thereof. Mutations including, but not limited to, those related to
KRAS, B-Raf, or CYP2D6, or any combination thereof can also be used
as specific biomarkers from exosomes for breast cancer. In
addition, a protein, ligand, or peptide that can be used as
biomarkers from exosomes that are specific to breast cancer
includes, but are not limited to, hsp70, MART-1, TRP, HER2, hsp70,
MART-1, TRP, HER2, ER, PR, Class III b-tubulin, or VEGFA, or any
combination thereof. Furthermore the snoRNA that can be used as an
exosomal biomarker for breast cancer include, but are not limited
to, GAS5. The gene fusion ETV6-NTRK3 can also be used a biomarker
for breast cancer.
[0340] Also provided herein is an isolated exosome comprising one
or more breast cancer specific biomarkers, such as ETV6-NTRK3, or
biomarkers listed in FIG. 3 and in FIG. 1 for breast cancer. A
composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more breast cancer
specific biomarkers, such as ETV6-NTRK3, or biomarkers listed in
FIG. 3 and in FIG. 1 for breast cancer. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for breast
cancer specific exosomes or exosomes comprising one or more breast
cancer specific biomarkers, such as ETV6-NTRK3, or biomarkers
listed in FIG. 3 and in FIG. 1 for breast cancer.
[0341] One or more breast cancer specific biomarkers, such as
ETV6-NTRK3, or biomarkers listed in FIG. 3 and in FIG. 1 for breast
cancer can also be detected by one or more systems disclosed
herein, for characterizing a breast cancer. For example, a
detection system can comprise one or more probes to detect one or
more breast cancer specific biomarkers, such as ETV6-NTRK3, or
biomarkers listed in FIG. 3 and in FIG. 1 for breast cancer, of one
or more exosomes of a biological sample.
[0342] Ovarian Cancer
[0343] Ovarian cancer specific biomarkers from exosomes can include
one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 4, and can be used to create a ovarian
cancer specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-200a, miR-141, miR-200c, miR-200b, miR-21,
miR-141, miR-200a, miR-200b, miR-200c, miR-203, miR-205, miR-214,
miR-199'', or miR-215, or any combination thereof. The
bio-signature can also comprise one or more underexpressed miRs
such as, but not limited to, miR-199a, miR-140, miR-145, miR-100,
miR-let-7 cluster, or miR-125b-1, or any combination thereof. The
one or more mRNAs that may be analyzed can include, but are not
limited to, ERCC1, ER, TOPO1, TOP2A, AR, PTEN, HER2/neu, CD24 or
EGFR, or any combination thereof.
[0344] A biomarker mutation for ovarian cancer that can be assessed
in an exosome includes, but is not limited to, a mutation of KRAS,
mutation of B-Raf, or any combination of mutations specific for
ovarian cancer. The protein, ligand, or peptide that can be
assessed in an exosome can include, but is not limited to, VEGFA,
VEGFR2, or HER2, or any combination thereof. Furthermore, an
exosome isolated or assayed can be ovarian cancer cell specific, or
derived from ovarian cancer cells.
[0345] Also provided herein is an isolated exosome comprising one
or more ovarian cancer specific biomarkers, such as CD24, those
listed in FIG. 4 and in FIG. 1 for ovarian cancer. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more ovarian cancer specific biomarkers,
such as CD24, those listed in FIG. 4 and in FIG. 1 for ovarian
cancer. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for ovarian cancer specific exosomes or
exosomes comprising one or more ovarian cancer specific biomarkers,
such as CD24, those listed in FIG. 4 and in FIG. 1 for ovarian
cancer.
[0346] One or more ovarian cancer specific biomarkers, such as
CD24, those listed in FIG. 4 and in FIG. 1 for ovarian cancer can
also be detected by one or more systems disclosed herein, for
characterizing an ovarian cancer. For example, a detection system
can comprise one or more probes to detect one or more ovarian
cancer specific biomarkers, such as CD24, those listed in FIG. 4
and in FIG. 1 for ovarian cancer, of one or more exosomes of a
biological sample.
[0347] Lung Cancer
[0348] Lung cancer specific biomarkers from exosomes can include
one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 5, and can be used to create a lung cancer
specific exosome bio-signature.
[0349] The bio-signature can comprise one or more overexpressed
miRs, such as, but not limited to, miR-21, miR-205, miR-221
(protective), let-7a (protective), miR-137 (risky), miR-372
(risky), or miR-122a (risky), or any combination thereof. The
bio-signature can comprise one or more upregulated or overexpressed
miRNAs, such as miR-17-92, miR-19a, miR-21, miR-92, miR-155,
miR-191, miR-205 or miR-210; one or more downregulated or
underexpressed miRNAs, such as miR-let-7, or any combination
thereof.
[0350] The one or more mRNAs that may be analyzed can include, but
are not limited to, EGFR, PTEN, RRM1, RRM2, ABCB1, ABCG2, LRP,
VEGFR2, VEGFR3, class III b-tubulin, or any combination
thereof.
[0351] A biomarker mutation for lung cancer that can be assessed in
an exosome includes, but is not limited to, a mutation of EGFR,
KRAS, B-Raf, UGT1A1, or any combination of mutations specific for
lung cancer. The protein, ligand, or peptide that can be assessed
in an exosome can include, but is not limited to, KRAS, hENT1, or
any combination thereof.
[0352] The biomarker can also be midkine (MK or MDK). Furthermore,
an exosome isolated or assayed can be lung cancer cell specific, or
derived from lung cancer cells.
[0353] Also provided herein is an isolated exosome comprising one
or more lung cancer specific biomarkers, such as RLF-MYCL1,
TGF-ALK, or CD74-ROS1, or those listed in FIG. 5 and in FIG. 1 for
lung cancer. A composition comprising the isolated exosome is also
provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more lung
cancer specific biomarkers, such as RLF-MYCL1, TGF-ALK, or
CD74-ROS1, or those listed in FIG. 5 and in FIG. 1 for lung cancer.
The composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for lung cancer specific exosomes or exosomes
comprising one or more lung cancer specific biomarkers, such as
RLF-MYCL1, TGF-ALK, or CD74-ROS1, or those listed in FIG. 5 and in
FIG. 1 for lung cancer.
[0354] One or more lung cancer specific biomarkers, such as
RLF-MYCL1, TGF-ALK, or CD74-ROS1, or those listed in FIG. 5 and in
FIG. 1 for lung cancer can also be detected by one or more systems
disclosed herein, for characterizing a lung cancer. For example, a
detection system can comprise one or more probes to detect one or
more lung cancer specific biomarkers, such as RLF-MYCL1, TGF-ALK,
or CD74-ROS1, or those listed in FIG. 5 and in FIG. 1 for lung
cancer, of one or more exosomes of a biological sample.
[0355] Colon Cancer
[0356] Colon cancer specific biomarkers from exosomes can include
one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 6, and can be used to create a colon cancer
specific exosome bio-signature. For example, the bio-signature can
comprise one or more overexpressed miRs, such as, but not limited
to, miR-24-1, miR-29b-2, miR-20a, miR-10a, miR-32, miR-203,
miR-106a, miR-17-5p, miR-30c, miR-223, miR-126, miR-128b, miR-21,
miR-24-2, miR-99b, miR-155, miR-213, miR-150, miR-107, miR-191,
miR-221, miR-20a, miR-510, miR-92, miR-513, miR-19a, miR-21,
miR-20, miR-183, miR-96, miR-135b, miR-31, miR-21, miR-92, miR-222,
miR-181b, miR-210, miR-20a, miR-106a, miR-93, miR-335, miR-338,
miR-133b, miR-346, miR-106b, miR-153a, miR-219, miR-34a, miR-99b,
miR-185, miR-223, miR-211, miR-135a, miR-127, miR-203, miR-212,
miR-95, or miR-17-5p, or any combination thereof. The bio-signature
can also comprise one or more underexpressed miRs such as miR-143,
miR-145, miR-143, miR-126, miR-34b, miR-34c, let-7, miR-9-3,
miR-34a, miR-145, miR-455, miR-484, miR-101, miR-145, miR-133b,
miR-129, miR-124a, miR-30-3p, miR-328, miR-106a, miR-17-5p,
miR-342, miR-192, miR-1, miR-34b, miR-215, miR-192, miR-301,
miR-324-5p, miR-30a-3p, miR-34c, miR-331, or miR-148b, or any
combination thereof.
[0357] The one or more biomarker can be an upregulated or
overexpressed miRNA, such as miR-20a, miR-21, miR-106a, miR-181b or
miR-203, for characterizing a colon adenocarcinoma. The one or more
biomarker can be used to characterize a colorectal cancer, such as
an upregulated or overexpressed miRNA selected from the group
consisting of: miR-19a, miR-21, miR-127, miR-31, miR-96, miR-135b
and miR-183, a downregulated or underexpressed miRNA, such as
miR-30c, miR-133a, mir143, miR-133b or miR-145, or any combination
thereof.
[0358] The one or more mRNAs that may be analyzed can include, but
are not limited to, EFNB1, ERCC1, HER2, VEGF, or EGFR, or any
combination thereof. A biomarker mutation for colon cancer that can
be assessed in an exosome includes, but is not limited to, a
mutation of EGFR, KRAS, VEGFA, B-Raf, APC, or p53, or any
combination of mutations specific for colon cancer. The protein,
ligand, or peptide that can be assessed in an exosome can include,
but is not limited to, AFRs, Rabs, ADAM10, CD44, NG2, ephrin-B1,
MIF, b-catenin, Junction, plakoglobin, glalectin-4, RACK1,
tetrspanin-8, FasL, TRAIL, A33, CEA, EGFR, dipeptidase 1, hsc-70,
tetraspanins, ESCRT, TS, PTEN, or TOPO1, or any combination
thereof. Furthermore, an exosome isolated or assayed can be colon
cancer cell specific, or derived from colon cancer cells.
[0359] Also provided herein is an isolated exosome comprising one
or more colon cancer specific biomarkers, such as listed in FIG. 6
and in FIG. 1 for colon cancer. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more colon cancer specific biomarkers, such as
listed in FIG. 6 and in FIG. 1 for colon cancer. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
colon cancer specific exosomes or exosomes comprising one or more
colon cancer specific biomarkers, such as listed in FIG. 6 and in
FIG. 1 for colon cancer.
[0360] One or more colon cancer specific biomarkers, such as listed
in FIG. 6 and in FIG. 1 for colon cancer can also be detected by
one or more systems disclosed herein, for characterizing a colon
cancer. For example, a detection system can comprise one or more
probes to detect one or more colon cancer specific biomarkers, such
as listed in FIG. 6 and in FIG. 1 for colon cancer, of one or more
exosomes of a biological sample.
[0361] Adenoma Versus Hyperplastic Polyp
[0362] Adenoma versus hyperplastic polyp specific biomarkers from
exosomes can include one or more (for example, 2, 3, 4, 5, 6, 7, 8,
or more) overexpressed miRs, underexpressed miRs, mRNAs, genetic
mutations, proteins, ligands, peptides, or any combination thereof,
such as listed in FIG. 7, and can be used to create an adenoma
versus hyperplastic polyp specific exosome bio-signature. For
example, the one or more mRNAs that may be analyzed can include,
but are not limited to, ABCA8, KIAA1199, GCG, MAMDC2, C2orf32,
229670_at, IGF1, PCDH7, PRDX6, PCNA, COX2, or MUC6, or any
combination thereof.
[0363] A biomarker mutation to distinguish for adenoma versus
hyperplastic polyp that can be assessed in an exosome includes, but
is not limited to, a mutation of KRAS, mutation of B-Raf, or any
combination of mutations specific for distinguishing between
adenoma versus hyperplastic polyp. The protein, ligand, or peptide
that can be assessed in an exosome can include, but is not limited
to, hTERT.
[0364] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between an adenoma
and a hyperplastic polyp, such as listed in FIG. 7. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more specific biomarkers for
distinguishing between an adenoma and a hyperplastic polyp, such as
listed in FIG. 7. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for having one or more specific
biomarkers for distinguishing between an adenoma and a hyperplastic
polyp, such as listed in FIG. 7.
[0365] One or more specific biomarkers for distinguishing between
an adenoma and a hyperplastic polyp, such as listed in FIG. 7 can
also be detected by one or more systems disclosed herein, for
distinguishing between an adenoma and a hyperplastic polyp. For
example, a detection system can comprise one or more probes to
detect one or more specific biomarkers for distinguishing between
an adenoma and a hyperplastic polyp, such as listed in FIG. 7, of
one or more exosomes of a biological sample.
[0366] Irritable Bowel Disease (IBD)
[0367] IBD versus normal biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 8, and can be used to create a IBD versus normal
specific exosome bio-signature. For example, the one or more mRNAs
that may be analyzed can include, but are not limited to, REG1A,
MMP3, or any combination thereof.
[0368] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between IBD and a
normal sample, such as listed in FIG. 8. A composition comprising
the isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more specific biomarkers for distinguishing
between IBD and a normal sample, such as listed in FIG. 8. The
composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for having one or more specific biomarkers for
distinguishing between IBD and a normal sample, such as listed in
FIG. 8.
[0369] One or more specific biomarkers for distinguishing between
IBD and a normal sample, such as listed in FIG. 8 can also be
detected by one or more systems disclosed herein, for
distinguishing between IBD and a normal sample. For example, a
detection system can comprise one or more probes to detect one or
more specific biomarkers for distinguishing between IBD and a
normal sample, such as listed in FIG. 8, of one or more exosomes of
a biological sample.
[0370] Adenoma Versus Colorectal Cancer (CRC)
[0371] Adenoma versus CRC specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 9, and can be used to create a Adenoma
versus CRC specific exosome bio-signature. For example, the one or
more mRNAs that may be analyzed can include, but are not limited
to, GREM1, DDR2, GUCY1A3, TNS1, ADAMTS1, FBLN1, FLJ38028, RDX,
FAM129A, ASPN, FRMD6, MCC, RBMS1, SNA12, MEIS1, DOCK10, PLEKHC1,
FAM126A, TBC1D9, VWF, DCN, ROBO1, MSRB3, LATS2, MEF2C, IGFBP3,
GNB4, RCN3, AKAP12, RFTN1, 226834_at, COL5A1, GNG2, NR3C1*,
SPARCL1, MAB21L2, AXIN2, 236894_at, AEBP1, AP1S2, C10orf56, LPHN2,
AKT3, FRMD6, COL15A1, CRYAB, COL14A1, LOC286167, QKI, WWTR1, GNG11,
PAPPA, or ELDT1, or any combination thereof.
[0372] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between an adenoma
and a CRC, such as listed in FIG. 9. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more specific biomarkers for distinguishing
between an adenoma and a CRC, such as listed in FIG. 9. The
composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for having one or more specific biomarkers for
distinguishing between an adenoma and a CRC, such as listed in FIG.
9.
[0373] One or more specific biomarkers for distinguishing between
an adenoma and a CRC, such as listed in FIG. 9 can also be detected
by one or more systems disclosed herein, for distinguishing between
an adenoma and a CRC. For example, a detection system can comprise
one or more probes to detect one or more specific biomarkers for
distinguishing between an adenoma and a CRC, such as listed in FIG.
9, of one or more exosomes of a biological sample.
[0374] IBD Versus CRC
[0375] IBD versus CRC specific biomarkers from exosomes can include
one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 10, and can be used to create a IBD versus
CRC specific exosome bio-signature. For example, the one or more
mRNAs that may be analyzed can include, but are not limited to,
227458_at, INDO, CXCL9, CCR2, CD38, RARRES3, CXCL10, FAM26F, TNIP3,
NOS2A, CCRL1, TLR8, IL18BP, FCRL5, SAMD9L, ECGF1, TNFSF13B, GBPS,
or GBP1, or any combination thereof.
[0376] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between IBD and a
CRC, such as listed in FIG. 10. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more specific biomarkers for distinguishing
between IBD and a CRC, such as listed in FIG. 10. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
having one or more specific biomarkers for distinguishing between
IBD and a CRC, such as listed in FIG. 10.
[0377] One or more specific biomarkers for distinguishing between
IBD and a CRC, such as listed in FIG. 10 can also be detected by
one or more systems disclosed herein, for distinguishing between
IBD and a CRC. For example, a detection system can comprise one or
more probes to detect one or more specific biomarkers for
distinguishing between IBD and a CRC, such as listed in FIG. 10, of
one or more exosomes of a biological sample.
[0378] CRC Dukes B Versus Dukes C-D
[0379] CRC Dukes B versus Dukes C-D specific biomarkers from
exosomes can include one or more (for example, 2, 3, 4, 5, 6, 7, 8,
or more) overexpressed miRs, underexpressed miRs, mRNAs, genetic
mutations, proteins, ligands, peptides, snoRNA, or any combination
thereof, such as listed in FIG. 11, and can be used to create a CRC
D-B versus C-D specific exosome bio-signature. For example, the one
or more mRNAs that may be analyzed can include, but are not limited
to, TMEM37*, IL33, CA4, CCDC58, CLIC6, VERSUSNL1, ESPN, APCDD1,
C13orf18, CYP4X1, ATP2A3, LOC646627, MUPCDH, ANPEP, C1orf115,
HSD3B2, GBA3, GABRB2, GYLTL1B, LYZ, SPC25, CDKN2B, FAM89A, MOGAT2,
SEMA6D, 229376_at, TSPAN5, IL6R, or SLC26A2, or any combination
thereof.
[0380] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between CRC Dukes B
and a CRC Dukes C-D, such as listed in FIG. 11. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more specific biomarkers for
distinguishing between CRC Dukes B and a CRC Dukes C-D, such as
listed in FIG. 11. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for having one or more specific
biomarkers for distinguishing between CRC Dukes B and a CRC Dukes
C-D, such as listed in FIG. 11.
[0381] One or more specific biomarkers for distinguishing between
CRC Dukes B and a CRC Dukes C-D, such as listed in FIG. 11 can also
be detected by one or more systems disclosed herein, for
distinguishing between CRC Dukes B and a CRC Dukes C-D. For
example, a detection system can comprise one or more probes to
detect one or more specific biomarkers for distinguishing between
CRC Dukes B and a CRC Dukes C-D, such as listed in FIG. 11, of one
or more exosomes of a biological sample.
[0382] Adenoma with Low Grade Dysplasia Versus Adenoma with High
Grade Dysplasia
[0383] Adenoma with low grade dysplasia versus adenoma with high
grade dysplasia specific biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 12, and can be used to create an adenoma low grade
dysplasia versus adenoma high grade dysplasia specific exosome
bio-signature. For example, the one or mRNAs that may be analyzed
can include, but are not limited to, SI, DMBT1, CFI*, AQP1, APOD,
TNFRSF17, CXCL10, CTSE, IGHA1, SLC9A3, SLC7A1, BATF2, SOCS1, DOCK2,
NOS2A, HK2, CXCL2, IL15RA, POU2AF1, CLEC3B, ANI3BP, MGC13057, LCK*,
C4BPA, HOXC6, GOLT1A, C2orf32, IL10RA, 240856_at, SOCS3, MEIS3P1,
HIPK1, GLS, CPLX1, 236045_x_at, GALC, AMN, CCDC69, CCL28, CPA3,
TRIB2, HMGA2, PLCL2, NR3C1, EIF5A, LARP4, RP5-1022P6.2, PHLDB2,
FKBP1B, INDO, CLDN8, CNTN3, PBEF1, SLC16A9, CDC25B, TPSB2, PBEF1,
ID4, GJB5, CHN2, LIMCH1, or CXCL9, or any combination thereof.
[0384] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between adenoma with
low grade dysplasia and adenoma with high grade dysplasia, such as
listed in FIG. 12. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more specific
biomarkers for distinguishing between adenoma with low grade
dysplasia and adenoma with high grade dysplasia, such as listed in
FIG. 12. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for having one or more specific
biomarkers for distinguishing between adenoma with low grade
dysplasia and adenoma with high grade dysplasia, such as listed in
FIG. 12.
[0385] One or more specific biomarkers for distinguishing between
adenoma with low grade dysplasia and adenoma with high grade
dysplasia, such as listed in FIG. 12 can also be detected by one or
more systems disclosed herein, for distinguishing between adenoma
with low grade dysplasia and adenoma with high grade dysplasia. For
example, a detection system can comprise one or more probes to
detect one or more specific biomarkers for distinguishing between
adenoma with low grade dysplasia and adenoma with high grade
dysplasia, such as listed in FIG. 12, of one or more exosomes of a
biological sample.
[0386] Ulcerative Colitis (UC) Versus Crohn's Disease (CD)
[0387] Ulcerative colitis (UC) versus Crohn's disease (CD) specific
biomarkers from exosomes can include one or more (for example, 2,
3, 4, 5, 6, 7, 8, or more) overexpressed miRs, underexpressed miRs,
mRNAs, genetic mutations, proteins, ligands, peptides, snoRNA, or
any combination thereof, such as listed in FIG. 13, and can be used
to create a UC versus CD specific exosome bio-signature. For
example, the one or more mRNAs that may be analyzed can include,
but are not limited to, IFITM1, IFITM3, STAT1, STAT3, TAP1, PSME2,
PSMB8, HNF4G, KLF5, AQP8, APT2B1, SLC16A, MFAP4, CCNG2, SLC44A4,
DDAH1, TOB1, 231152_at, MKNK1, CEACAM7*, 1562836_at, CDC42SE2,
PSD3, 231169_at, IGL@*, GSN, GPM6B, CDV3*, PDPK1, ANP32E, ADAM9,
CDH1, NLRP2, 215777_at, OSBPL1, VNN1, RABGAP1L, PHACTR2, ASH1L,
213710_s_at, CDH1, NLRP2, 215777_at, OSBPL1, VNN1, RABGAP1L,
PHACTR2, ASH1, 213710_s_at, ZNF3, FUT2, IGHA1, EDEM1, GPR171,
229713_at, LOC643187, FLVCR1, SNAP23*, ETNK1, LOC728411, POSTN,
MUC12, HOXA5, SIGLEC1, LARP5, PIGR, SPTBN1, UFM1, C6orf62, WDR90,
ALDH1A3, F2RL1, IGHV1-69, DUOX2, RAB5A, or CP, or any combination
thereof can also be used as specific biomarkers from exosomes for
UC versus CD.
[0388] A biomarker mutation for distinguishing UC versus CD that
can be assessed in an exosome includes, but is not limited to, a
mutation of CARD15, or any combination of mutations specific for
distinguishing UC versus CD. The protein, ligand, or peptide that
can be assessed in an exosome can include, but is not limited to,
(P)ASCA.
[0389] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between UC and CD,
such as listed in FIG. 13. A composition comprising the isolated
exosome is also provided. Accordingly, in some embodiments, the
composition comprises a population of exosomes comprising one or
more specific biomarkers for distinguishing between UC and CD, such
as listed in FIG. 13. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for having one or more specific
biomarkers for distinguishing between UC and CD, such as listed in
FIG. 13.
[0390] One or more specific biomarkers for distinguishing between
UC and CD, such as listed in FIG. 13 can also be detected by one or
more systems disclosed herein, for distinguishing between UC and
CD. For example, a detection system can comprise one or more probes
to detect one or more specific biomarkers for distinguishing
between UC and CD, such as listed in FIG. 13, of one or more
exosomes of a biological sample.
[0391] Hyperplastic Polyp
[0392] Hyperplastic polyp versus normal specific biomarkers from
exosomes can include one or more (for example, 2, 3, 4, 5, 6, 7, 8,
or more) overexpressed miRs, underexpressed miRs, mRNAs, genetic
mutations, proteins, ligands, peptides, snoRNA, or any combination
thereof, such as listed in FIG. 14, and can be used to create a
hyperplastic polyp versus normal specific exosome bio-signature.
For example, the one or more mRNAs that may be analyzed can
include, but are not limited to, SLC6A14, ARHGEF10, ALS2, IL1RN,
SPRy4, PTGER3, TRIM29, SERPINB5, 1560327 at, ZAK, BAG4, TRIB3, TTL,
FOXQ1, or any combination.
[0393] Also provided herein is an isolated exosome comprising one
or more hyperplastic polyp specific biomarkers, such as listed in
FIG. 14. A composition comprising the isolated exosome is also
provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more
hyperplastic polyp specific biomarkers, such as listed in FIG. 14.
The composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for hyperplastic polyp specific exosomes or exosomes
comprising one or more hyperplastic polyp specific biomarkers, such
as listed in FIG. 14.
[0394] One or more hyperplastic polyp specific biomarkers, such as
listed in FIG. 14 can also be detected by one or more systems
disclosed herein, for characterizing a hyperplastic polyp. For
example, a detection system can comprise one or more probes to
detect one or more listed in FIG. 14. One or more hyperplastic
specific biomarkers, such as listed in FIG. 14, of one or more
exosomes of a biological sample.
[0395] Adenoma with Low Grade Dysplasia Versus Normal
[0396] Adenoma with low grade dysplasia versus normal specific
biomarkers from exosomes can include one or more (for example, 2,
3, 4, 5, 6, 7, 8, or more) overexpressed miRs, underexpressed miRs,
mRNAs, genetic mutations, proteins, ligands, peptides, snoRNA, or
any combination thereof, such as listed in FIG. 15, and can be used
to create an adenoma low grade dysplasia versus normal specific
exosome bio-signature. For example, the RNAs that may be analyzed
can include, but are not limited to, UGT2A3, KLK11, KIAA1199,
FOXQ1, CLDN8, ABCA8, or PYY, or any combination thereof and can be
used as specific biomarkers from exosomes for Adenoma low grade
dysplasia versus normal. Furthermore, the snoRNA that can be used
as an exosomal biomarker for adenoma low grade dysplasia versus
normal can include, but is not limited to, GAS5.
[0397] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between adenoma with
low grade dysplasia and normal, such as listed in FIG. 15. A
composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more specific biomarkers
for distinguishing between adenoma with low grade dysplasia and
normal, such as listed in FIG. 15. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for having one
or more specific biomarkers for distinguishing between adenoma with
low grade dysplasia and normal, such as listed in FIG. 15.
[0398] One or more specific biomarkers for distinguishing between
adenoma with low grade dysplasia and normal, such as listed in FIG.
15 can also be detected by one or more systems disclosed herein,
for distinguishing between adenoma with low grade dysplasia and
normal. For example, a detection system can comprise one or more
probes to detect one or more specific biomarkers for distinguishing
between adenoma with low grade dysplasia and normal, such as listed
in FIG. 15, of one or more exosomes of a biological sample.
[0399] Adenoma Versus Normal
[0400] Adenoma versus normal specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 16, and can be used to create an Adenoma
versus normal specific exosome bio-signature. For example, the one
or more mRNAs that may be analyzed can include, but are not limited
to, KIAA1199, FOXQ1, or CA7, or any combination thereof. The
protein, ligand, or peptide that can be used as a biomarker from
exosomes that is specific to adenoma versus. normal can include,
but is not limited to, Clusterin.
[0401] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between adenoma and
normal, such as listed in FIG. 16. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more specific biomarkers for distinguishing
between adenoma and normal, such as listed in FIG. 16. The
composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for having one or more specific biomarkers for
distinguishing between adenoma and normal, such as listed in FIG.
16.
[0402] One or more specific biomarkers for distinguishing between
adenoma and normal, such as listed in FIG. 16 can also be detected
by one or more systems disclosed herein, for distinguishing between
adenoma and normal. For example, a detection system can comprise
one or more probes to detect one or more specific biomarkers for
distinguishing between adenoma and normal, such as listed in FIG.
16, of one or more exosomes of a biological sample.
[0403] CRC Versus Normal
[0404] CRC versus normal specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 17, and can be used to create a CRC versus
normal specific exosome bio-signature. For example, the one or
mRNAs that may be analyzed can include, but are not limited to,
VWF, IL8, CHI3L1, S100A8, GREM1, or ODC, or any combination thereof
and can be used as specific biomarkers from exosomes for CRC versus
normal.
[0405] A biomarker mutation for CRC versus normal that can be
assessed in an exosome includes, but is not limited to, a mutation
of KRAS, BRAF, APC, MSH2, or MLH1, or any combination of mutations
specific for distinguishing between CRC versus normal. The protein,
ligand, or peptide that can be assessed in an exosome can include,
but is not limited to, cytokeratin 13, calcineurin, CHK1, clathrin
light chain, phospho-ERK, phospho-PTK2, or MDM2, or any combination
thereof.
[0406] Also provided herein is an isolated exosome comprising one
or more specific biomarkers for distinguishing between CRC and
normal, such as listed in FIG. 17. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more specific biomarkers for distinguishing
between CRC and normal, such as listed in FIG. 17. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
having one or more specific biomarkers for distinguishing between
CRC and normal, such as listed in FIG. 17.
[0407] One or more specific biomarkers for distinguishing between
CRC and normal, such as listed in FIG. 17 can also be detected by
one or more systems disclosed herein, for distinguishing between
CRC and normal. For example, a detection system can comprise one or
more probes to detect one or more specific biomarkers for
distinguishing between CRC and normal, such as listed in FIG. 17,
of one or more exosomes of a biological sample.
[0408] Benign Prostatic Hyperplasia (BPH)
[0409] Benign prostatic hyperplasia (BPH) specific biomarkers from
exosomes can include one or more (for example, 2, 3, 4, 5, 6, 7, 8,
or more) overexpressed miRs, underexpressed miRs, mRNAs, genetic
mutations, proteins, ligands, peptides, snoRNA, or any combination
thereof, such as listed in FIG. 18, and can be used to create a BPH
specific exosome bio-signature. The protein, ligand, or peptide
that can be assessed in an exosome can include, but is not limited
to, intact fibronectin.
[0410] Also provided herein is an isolated exosome comprising one
or more BPH specific biomarkers, such as listed in FIG. 18 and in
FIG. 1 for BPH. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more BPH
specific biomarkers, such as listed in FIG. 18 and in FIG. 1 for
BPH. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for BPH specific exosomes or exosomes
comprising one or more BPH specific biomarkers, such as listed in
FIG. 18 and in FIG. 1 for BPH.
[0411] One or more BPH specific biomarkers, such as listed in FIG.
18 and in FIG. 1 for BPH, can also be detected by one or more
systems disclosed herein, for characterizing a BPH. For example, a
detection system can comprise one or more probes to detect one more
BPH specific biomarkers, such as listed in FIG. 18 and in FIG. 1
for BPH, of one or more exosomes of a biological sample.
[0412] Prostate Cancer
[0413] Prostate cancer specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 19, and can be used to create a prostate
cancer specific exosome bio-signature. For example, a bio-signature
for prostate cancer can comprise miR-9, miR-21, miR-141, miR-370,
miR-200b, miR-210, miR-155, or miR-196a. In some embodiments, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-202, miR-210, miR-296, miR-320, miR-370,
miR-373, miR-498, miR-503, miR-184, miR-198, miR-302c, miR-345,
miR-491, miR-513, miR-32, miR-182, miR-31, miR-26a-1/2, miR-200c,
miR-375, miR-196a-1/2, miR-370, miR-425, miR-425, miR-194-1/2,
miR-181a-1/2, miR-34b, let-71, miR-188, miR-25, miR-106b, miR-449,
miR-99b, miR-93, miR-92-1/2, miR-125a, or miR-141, or any
combination thereof.
[0414] The bio-signature can also comprise one or more
underexpressed miRs such as, but not limited to, let-7a, let-7b,
let-7c, let-7d, let-7g, miR-16, miR-23a, miR-23b, miR-26a, miR-92,
miR-99a, miR-103, miR-125a, miR-125b, miR-143, miR-145, miR-195,
miR-199, miR-221, miR-222, miR-497, let-7f, miR-19b, miR-22,
miR-26b, miR-27a, miR-27b, miR-29a, miR-29b, miR-30.sub.--5p,
miR-30c, miR-100, miR-141, miR-148a, miR-205, miR-520h, miR-494,
miR-490, miR-133a-1, miR-1-2, miR-218-2, miR-220, miR-128a,
miR-221, miR-499, miR-329, miR-340, miR-345, miR-410, miR-126,
miR-205, miR-7-1/2, miR-145, miR-34a, miR-487, or let-7b, or any
combination thereof. The bio-signature can comprise upregulated or
overexpressed miR-21, downregulated or underexpressed miR-15a,
miR-16-1, miR-143 or miR-145, or any combination thereof.
[0415] The one or more mRNAs that may be analyzed can include, but
are not limited to, AR, PCA3, or any combination thereof and can be
used as specific biomarkers from exosomes for prostate cancer.
[0416] The protein, ligand, or peptide that can be assessed in an
exosome can include, but is not limited to, FASLG or TNFSF10 or any
combination thereof. Furthermore, an exosome isolated or assayed
can be prostate cancer cell specific, or derived from prostate
cancer cells. Furthermore, the snoRNA that can be used as an
exosomal biomarker for prostate cancer can include, but is not
limited to, U50. Examples of prostate cancer bio-signatures are
further described below.
[0417] Also provided herein is an isolated exosome comprising one
or more prostate cancer specific biomarkers, such as ACSL3-ETV1,
C15ORF21-ETV1, FLJ35294-ETV1, HERV-ETV1, TMPRSS2-ERG,
TMPRSS2-ETV1/4/5, TMPRSS2-ETV4/5, SLC5A3-ERG, SLC5A3-ETV1,
SLC5A3-ETV5 or KLK2-ETV4, or those listed in FIGS. 19, 60 and in
FIG. 1 for prostate cancer. A composition comprising the isolated
exosome is also provided. Accordingly, in some embodiments, the
composition comprises a population of exosomes comprising one or
more prostate cancer specific biomarkers such as ACSL3-ETV1,
C15ORF21-ETV1, FLJ35294-ETV1, HERV-ETV1, TMPRSS2-ERG,
TMPRSS2-ETV1/4/5, TMPRSS2-ETV4/5, SLC5A3-ERG, SLC5A3-ETV1,
SLC5A3-ETV5 or KLK2-ETV4, or those listed in FIGS. 19, 60 and in
FIG. 1 for prostate cancer. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for prostate
cancer specific exosomes or exosomes comprising one or more
prostate cancer specific biomarkers, such as ACSL3-ETV1,
C15ORF21-ETV1, FLJ35294-ETV1, HERV-ETV1, TMPRSS2-ERG,
TMPRSS2-ETV1/4/5, TMPRSS2-ETV4/5, SLC5A3-ERG, SLC5A3-ETV1,
SLC5A3-ETV5 or KLK2-ETV4, or those listed in FIGS. 19, 60 and in
FIG. 1 for prostate cancer.
[0418] One or more prostate cancer specific biomarkers, such as
ACSL3-ETV1, C15ORF21-ETV1, FLJ35294-ETV1, HERV-ETV1, TMPRSS2-ERG,
TMPRSS2-ETV1/4/5, TMPRSS2-ETV4/5, SLC5A3-ERG, SLC5A3-ETV1,
SLC5A3-ETV5 or KLK2-ETV4, or those listed in FIGS. 19, 60 and in
FIG. 1 for prostate cancer can also be detected by one or more
systems disclosed herein, for characterizing a prostate cancer. For
example, a detection system can comprise one or more probes to
detect one or more prostate cancer specific biomarkers, such as
ACSL3-ETV1, C15ORF21-ETV1, FLJ35294-ETV1, HERV-ETV1, TMPRSS2-ERG,
TMPRSS2-ETV1/4/5, TMPRSS2-ETV4/5, SLC5A3-ERG, SLC5A3-ETV1,
SLC5A3-ETV5 or KLK2-ETV4, or those listed in FIGS. 19, 60 and in
FIG. 1 for prostate cancer, of one or more exosomes of a biological
sample.
[0419] Melanoma
[0420] Melanoma specific biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 20, and can be used to create a melanoma specific
exosome bio-signature. For example, the bio-signature can comprise
one or more overexpressed miRs, such as, but not limited to,
miR-19a, miR-144, miR-200c, miR-211, miR-324-5p, miR-331, or
miR-374, or any combination thereof. The bio-signature can also
comprise one or more underexpressed miRs such as, but not limited
to, miR-9, miR-15a, miR-17-3p, miR-23b, miR-27a, miR-28, miR-29b,
miR-30b, miR-31, miR-34b, miR-34c, miR-95, miR-96, miR-100,
miR-104, miR-105, miR-106a, miR-107, miR-122a, miR-124a, miR-125b,
miR-127, miR-128a, miR-128b, miR-129, miR-135a, miR-135b, miR-137,
miR-138, miR-139, miR-140, miR-141, miR-149, miR-154, miR-154#3,
miR-181a, miR-182, miR-183, miR-184, miR-185, miR-189, miR-190,
miR-199, miR-199b, miR-200a, miR-200b, miR-204, miR-213, miR-215,
miR-216, miR-219, miR-222, miR-224, miR-299, miR-302a, miR-302b,
miR-302c, miR-302d, miR-323, miR-325, let-7a, let-7b, let-7d,
let-7e, or let-7g, or any combination thereof.
[0421] The one or more mRNAs that may be analyzed can include, but
are not limited to, MUM-1, beta-catenin, or Nop/5/Sik, or any
combination thereof and can be used as specific biomarkers from
exosomes for melanoma.
[0422] A biomarker mutation for melanoma that can be assessed in an
exosome includes, but is not limited to, a mutation of CDK4 or any
combination of mutations specific for melanoma. The protein,
ligand, or peptide that can be assessed in an exosome can include,
but is not limited to, DUSP-1, Alix, hsp70, Gib2, Gia, moesin,
GAPDH, malate dehydrogenase, p120 catenin, PGRL, syntaxin-binding
protein 1 & 2, septin-2, or WD-repeat containing protein 1, or
any combination thereof. The snoRNA that can be used as an exosomal
biomarker for melanoma include, but are not limited to, H/ACA
(U1071), SNORA11D, or any combination thereof. Furthermore, an
exosome isolated or assayed can be melanoma cell specific, or
derived from melanoma cells.
[0423] Also provided herein is an isolated exosome comprising one
or more melanoma specific biomarkers, such as listed in FIG. 20 and
in FIG. 1 for melanoma. A composition comprising the isolated
exosome is also provided. Accordingly, in some embodiments, the
composition comprises a population of exosomes comprising one or
more melanoma specific biomarkers, such as listed in FIG. 20 and in
FIG. 1 for melanoma. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for melanoma specific exosomes or
exosomes comprising one or more melanoma specific biomarkers, such
as listed in FIG. 20 and in FIG. 1 for melanoma.
[0424] One or more melanoma specific biomarkers, such as listed in
FIG. 20 and in FIG. 1 for melanoma can also be detected by one or
more systems disclosed herein, for characterizing a melanoma. For
example, a detection system can comprise one or more probes to
detect one or more cancer specific biomarkers, such as listed in
FIG. 20 and in FIG. 1 for melanoma, of one or more exosomes of a
biological sample.
[0425] Pancreatic Cancer
[0426] Pancreatic cancer specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 21, and can be used to create a pancreatic
cancer specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-221, miR-181a, miR-155, miR-210, miR-213,
miR-181b, miR-222, miR-181b-2, miR-21, miR-181b-1, miR-220,
miR-181d, miR-223, miR-100-1/2, miR-125a, miR-143, miR-10a,
miR-146, miR-99, miR-100, miR-199a-1, miR-10b, miR-199a-2, miR-221,
miR-181a, miR-155, miR-210, miR-213, miR-181b, miR-222, miR-181b-2,
miR-21, miR-181b-1, miR-181c, miR-220, miR-181d, miR-223,
miR-100-1/2, miR-125a, miR-143, miR-10a, miR-146, miR-99, miR-100,
miR-199a-1, miR-10b, miR-199a-2, miR-107, miR-103, miR-103-2,
miR-125b-1, miR-205, miR-23a, miR-221, miR-424, miR-301, miR-100,
miR-376a, miR-125b-1, miR-21, miR-16-1, miR-181a, miR-181c, miR-92,
miR-15, miR-155, let-7f-1, miR-212, miR-107, miR-024-1/2, miR-18a,
miR-31, miR-93, miR-224, or let-7d, or any combination thereof.
[0427] The bio-signature can also comprise one or more
underexpressed miRs such as, but not limited to, miR-148a,
miR-148b, miR-375, miR-345, miR-142, miR-133a, miR-216, miR-217 or
miR-139, or any combination thereof. The one or more mRNAs that may
be analyzed can include, but are not limited to, PSCA, Mesothelin,
or Osteopontin, or any combination thereof and can be used as
specific biomarkers from exosomes for pancreatic cancer.
[0428] A biomarker mutation for pancreatic cancer that can be
assessed in an exosome includes, but is not limited to, a mutation
of KRAS, CTNNLB1, AKT, NCOA3, or B-RAF, or any combination of
mutations specific for pancreatic cancer. The biomarker can also be
BRCA2, PALB2, or p16. Furthermore, an exosome isolated or assayed
can be pancreatic cancer cell specific, or derived from pancreatic
cancer cells.
[0429] Also provided herein is an isolated exosome comprising one
or more pancreatic cancer specific biomarkers, such as listed in
FIG. 21. A composition comprising the isolated exosome is also
provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more
pancreatic cancer specific biomarkers, such as listed in FIG. 21.
The composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for pancreatic cancer specific exosomes or exosomes
comprising one or more pancreatic cancer specific biomarkers, such
as listed in FIG. 21.
[0430] One or more pancreatic cancer specific biomarkers, such as
listed in FIG. 21, can also be detected by one or more systems
disclosed herein, for characterizing a pancreatic cancer. For
example, a detection system can comprise one or more probes to
detect one or more pancreatic cancer specific biomarkers, such as
listed in FIG. 21, of one or more exosomes of a biological
sample.
[0431] Brain Cancer
[0432] Brain cancer (including, but not limited to, gliomas,
glioblastomas, meinigiomas, acoustic neuroma/schwannomas,
medulloblastoma) specific biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 22, and can be used to create a brain cancer
specific exosome bio-signature. For example, the bio-signature can
comprise one or more overexpressed miRs, such as, but not limited
to miR-21, miR-10b, miR-130a, miR-221, miR-125b-1, miR-125b-2,
miR-9-2, miR-21, miR-25, or miR-123, or any combination
thereof.
[0433] The bio-signature can also comprise one or more
underexpressed miRs such as, but not limited to, miR-128a,
miR-181c, miR-181a, or miR-181b, or any combination thereof. The
one or more mRNAs that may be analyzed include, but are not limited
to, MGMT, which can be used as specific biomarker from exosomes for
brain cancer. The protein, ligand, or peptide that can be assessed
in an exosome can include, but is not limited to, EGFR.
[0434] Also provided herein is an isolated exosome comprising one
or more brain cancer specific biomarkers, such as GOPC-ROS1, or
those listed in FIG. 22 and in FIG. 1 for brain cancer. A
composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more brain cancer specific
biomarkers, such as GOPC-ROS1, or those listed in FIG. 22 and in
FIG. 1 for brain cancer. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for brain
cancer specific exosomes or exosomes comprising one or more brain
cancer specific biomarkers, such as GOPC-ROS1, or those listed in
FIG. 22. and in FIG. 1 for brain cancer.
[0435] One or more brain cancer specific biomarkers, such as listed
in FIG. 22 and in FIG. 1 for brain cancer, can also be detected by
one or more systems disclosed herein, for characterizing a brain
cancer. For example, a detection system can comprise one or more
probes to detect one or more brain cancer specific biomarkers, such
as GOPC-ROS1, or those listed in FIG. 22 and in FIG. 1 for brain
cancer, of one or more exosomes of a biological sample.
[0436] Psoriasis
[0437] Psoriasis specific biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 23, and can be used to create a psoriasis specific
exosome bio-signature. For example, the bio-signature can comprise
one or more overexpressed miRs, such as, but not limited to,
miR-146b, miR-20a, miR-146a, miR-31, miR-200a, miR-17-5p,
miR-30e-5p, miR-141, miR-203, miR-142-3p, miR-21, or miR-106a, or
any combination thereof. The bio-signature can also comprise one or
more underexpressed miRs such a, but not limited to, miR-125b,
miR-99b, miR-122a, miR-197, miR-100, miR-381, miR-518b, miR-524,
let-7e, miR-30c, miR-365, miR-133b, miR-10a, miR-133a, miR-22,
miR-326, or miR-215, or any combination thereof.
[0438] The one or more mRNAs that may be analyzed can include, but
are not limited to, IL-20, VEGFR-1, VEGFR-2, VEGFR-3, or EGR1, or
any combination thereof and can be used as specific biomarkers from
exosomes for psoriasis. A biomarker mutation for psoriasis that can
be assessed in an exosome includes, but is not limited to, a
mutation of MGST2, or any combination of mutations specific for
psoriasis.
[0439] Also provided herein is an isolated exosome comprising one
or more psoriasis specific biomarkers, such as listed in FIG. 23
and in FIG. 1 for psoriasis. A composition comprising the isolated
exosome is also provided. Accordingly, in some embodiments, the
composition comprises a population of exosomes comprising one or
more psoriasis specific biomarkers, such as listed in FIG. 23 and
in FIG. 1 for psoriasis. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for psoriasis
specific exosomes or exosomes comprising one or more psoriasis
specific biomarkers, such as listed in FIG. 23 and in FIG. 1 for
psoriasis.
[0440] One or more psoriasis specific biomarkers, such as listed in
FIG. 23 and in FIG. 1 for psoriasis, can also be detected by one or
more systems disclosed herein, for characterizing psoriasis. For
example, a detection system can comprise one or more probes to
detect one or more psoriasis specific biomarkers, such as listed in
FIG. 23 and in FIG. 1 for psoriasis, of one or more exosomes of a
biological sample.
[0441] Cardiovascular Disease (CVD)
[0442] CVD specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 24, and can be used to create a CVD specific exosome
bio-signature. For example, the bio-signature can comprise one or
more overexpressed miRs, such as, but not limited to, miR-195,
miR-208, miR-214, let-7b, let-7c, let-7e, miR-15b, miR-23a, miR-24,
miR-27a, miR-27b, miR-93, miR-99b, miR-100, miR-103, miR-125b,
miR-140, miR-145, miR-181a, miR-191, miR-195, miR-199a, miR-320,
miR-342, miR-451, or miR-499, or any combination thereof.
[0443] The bio-signature can also comprise one or more
underexpressed miRs such as, but not limited to, miR-1, miR-10a,
miR-17-5p, miR-19a, miR-19b, miR-20a, miR-20b, miR-26b, miR-28,
miR-30e-5p, miR-101, miR-106a, miR-126, miR-222, miR-374, miR-422b,
or miR-423, or any combination thereof. The mRNAs that may be
analyzed can include, but are not limited to, MRP14, CD69, or any
combination thereof and can be used as specific biomarkers from
exosomes for CVD.
[0444] A biomarker mutation for CVD that can be assessed in an
exosome includes, but is not limited to, a mutation of MYH7, SCN5A,
or CHRM2, or any combination of mutations specific for CVD.
[0445] The protein, ligand, or peptide that can be assessed in an
exosome can include, but is not limited to, CK-MB, cTnI (cardiac
troponin), CRP, BPN, IL-6, MCSF, CD40, CD40L, or any combination
thereof. Furthermore, an exosome isolated or assayed can be a CVD
cell specific, or derived from cardiac cells.
[0446] Also provided herein is an isolated exosome comprising one
or more CVD specific biomarkers, such as listed in FIG. 24 and in
FIG. 1 for CVD. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more CVD
specific biomarkers, such as listed in FIG. 24 and in FIG. 1 for
CVD. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for CVD specific exosomes or exosomes
comprising one or more CVD specific biomarkers, such as listed in
FIG. 24 and in FIG. 1 for CVD.
[0447] One or more CVD specific biomarkers, such as listed in FIG.
24 and in FIG. 1 for CVD, can also be detected by one or more
system's disclosed herein, for characterizing a CVD. For example, a
detection system can comprise one or more probes to detect one or
more CVD specific biomarkers, such as listed in FIG. 24 and in FIG.
1 for CVD, of one or more exosomes of a biological sample.
[0448] Blood Cancers
[0449] Hematological malignancies specific biomarkers from exosomes
can include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 25, and can be used to create a
hematological malignancies specific exosome bio-signature. For
example, the one or more mRNAs that may be analyzed can include,
but are not limited to, HOX11, TAL1, LY1, LMO1, or LMO2, or any
combination thereof and can be used as specific biomarkers from
exosomes for hematological malignancies.
[0450] A biomarker mutation for a blood cancer that can be assessed
in an exosome includes, but is not limited to, a mutation of c-kit,
PDGFR, or ABL, or any combination of mutations specific for
hematological malignancies.
[0451] Also provided herein is an isolated exosome comprising one
or more blood cancer specific biomarkers, such as listed in FIG. 25
and in FIG. 1 for blood cancer. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more blood cancer specific biomarkers, such as
listed in FIG. 25 and in FIG. 1 for blood cancer. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
blood cancer specific exosomes or exosomes comprising one or more
blood cancer specific biomarkers, such as listed in FIG. 25 and in
FIG. 1 for blood cancer.
[0452] One or more blood cancer specific biomarkers, such as listed
in FIG. 25 and in FIG. 1 for blood cancer, can also be detected by
one or more systems disclosed herein, for characterizing a blood
cancer. For example, a detection system can comprise one or more
probes to detect one or more blood cancer specific biomarkers, such
as listed in FIG. 25 and in FIG. 1 for blood cancer, of one or more
exosomes of a biological sample.
[0453] The one or more blood cancer specific biomarkers can also be
a gene fusion selected from the group consisting of: TTL-ETV6,
CDK6-MLL, CDK6-TLX3, ETV6-FLT3, ETV6-RUNX1, ETV6-TTL, MLL-AFF1,
MLL-AFF3, MLL-AFF4, MLL-GAS7, TCBA1-ETV6, TCF3-PBX1 or TCF3-TFPT,
for acute lymphocytic leukemia (ALL); BCL11B-TLX3, IL2-TNFRFS17,
NUP214-ABL1, NUP98-CCDC28A, TAL1-STIL, or ETV6-ABL2, for T-cell
acute lymphocytic leukemia (T-ALL); ATIC-ALK, KIAA1618-ALK,
MSN-ALK, MYH9-ALK, NPM1-ALK, TGF-ALK or TPM3-ALK, for anaplastic
large cell lymphoma (ALCL); BCR-ABL1, BCR-JAK2, ETV6-EVI1, ETV6-MN1
or ETV6-TCBA1, for chronic myelogenous leukemia (CML); CBFB-MYH11,
CHIC2-ETV6, ETV6-ABL1, ETV6-ABL2, ETV6-ARNT, ETV6-CDX2, ETV6-HLXB9,
ETV6-PER1, MEF2D-DAZAP1, AML-AFF1, MLL-ARHGAP26, MLL-ARHGEF12,
MLL-CASC5, MLL-CBL, MLL-CREBBP, MLL-DAB21P, MLL-ELL, MLL-EP300,
MLL-EPS15, MLL-FNBP1, MLL-FOXO3A, MLL-GMPS, MLL-GPHN, MLL-MLLT1,
MLL-MLLT11, MLL-MLLT3, MLL-MLLT6, MLL-MYO1F, MLL-PICALM, MLL-SEPT2,
MLL-SEPT6, MLL-SORBS2, MYST3-SORBS2, MYST-CREBBP, NPM1-MLF1,
NUP98-HOXA13, PRDM16-EVI1, RABEP1-PDGFRB, RUNX1-EVI1, RUNX1-MDS1,
RUNX1-RPL22, RUNX1-RUNX1T1, RUNX1-SH3D19, RUNX1-USP42,
RUNX1-YTHDF2, RUNX1-ZNF687, or TAF15-ZNF-384, for AML; CCND1-FSTL3,
for chronic lymphocytic leukemia (CLL); and FLIP1-PDGFRA,
FLT3-ETV6, KIAA1509-PDGFRA, PDE4DIP-PDGFRB, NIN-PDGFRB,
TP53BP1-PDGFRB, or TPM3-PDGFRB, for hyper eosinophilia/chronic
eosinophilia.
[0454] The one or more biomarkers for CLL can also include one or
more of the following upregulated or overexpressed miRNAs, such as
miR-23b, miR-24-1, miR-146, miR-155, miR-195, miR-221, miR-331,
miR-29a, miR-195, miR-34a, or miR-29c; one or more of the following
downregulated or underexpressed miRs, such as miR-15a, miR-16-1,
miR-29 or miR-223, or any combination thereof.
[0455] The one or more biomarkers for ALL can also include one or
more of the following upregulated or overexpressed miRNAs, such as
miR-128b, miR-204, miR-218, miR-331, miR-181b-1, miR-17-92; or any
combination thereof.
[0456] B-Cell Chronic Lymphocytic Leukemia (B-CLL)
[0457] B-CLL specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 26, and can be used to create a B-CLL specific
exosome bio-signature. For example, the bio-signature can comprise
one or more overexpressed miRs, such as, but not limited to,
miR-183-prec, miR-190, miR-24-1-prec, miR-33, miR-19a, miR-140,
miR-123, miR-10b, miR-15b-prec, miR-92-1, miR-188, miR-154,
miR-217, miR-101, miR-141-prec, miR-153-prec, miR-196-2, miR-134,
miR-141, miR-132, miR-192, or miR-181b-prec, or any combination
thereof.
[0458] The bio-signature can also comprise one or more
underexpressed miRs such as, but not limited to, miR-213, miR-220,
or any combination thereof. The one or more mRNAs that may be
analyzed can include, but are not limited to, ZAP70, AdipoR1, or
any combination thereof and can be used as specific biomarkers from
exosomes for B-CLL. A biomarker mutation for B-CLL that can be
assessed in an exosome includes, but is not limited to, a mutation
of IGHV, P53, ATM, or any combination of mutations specific for
B-CLL.
[0459] Also provided herein is an isolated exosome comprising one
or more B-CLL specific biomarkers, such as BCL3-MYC, MYC-BTG1,
BCL7A-MYC, BRWD3-ARHGAP20 or BTG1-MYC, or those listed in FIG. 26.
A composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more B-CLL specific
biomarkers, such as BCL3-MYC, MYC-BTG1, BCL7A-MYC, BRWD3-ARHGAP20
or BTG1-MYC, or those listed in FIG. 26. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for B-CLL
specific exosomes or exosomes comprising one or more B-CLL specific
biomarkers, such as BCL3-MYC, MYC-BTG1, BCL7A-MYC, BRWD3-ARHGAP20
or BTG1-MYC, or those listed in FIG. 26.
[0460] One or more B-CLL specific biomarkers, such as BCL3-MYC,
MYC-BTG1, BCL7A-MYC, BRWD3-ARHGAP20 or BTG1-MYC, or those listed in
FIG. 26, can also be detected by one or more systems disclosed
herein, for characterizing a B-CLL. For example, a detection system
can comprise one or more probes to detect one or more B-CLL
specific biomarkers, such as BCL3-MYC, MYC-BTG1, BCL7A-MYC,
BRWD3-ARHGAP20 or BTG1-MYC, or those listed in FIG. 26, of one or
more exosomes of a biological sample.
[0461] B-Cell Lymphoma
[0462] B-cell lymphome specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 27, and can be used to create a B-cell
lymphoma specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-17-92 polycistron, miR-155, miR-210, or
miR-21, miR-19a, miR-92, miR-142 miR-155, miR-221 miR-17-92,
miR-21, miR-191, miR-205, or any combination thereof. Furthermore
the snoRNA that can be used as an exosomal biomarker for B-cell
lymphoma can include, but is not limited to, U50.
[0463] Also provided herein is an isolated exosome comprising one
or more B-cell lymphoma specific biomarkers, such as listed in FIG.
27. A composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more B-cell lymphoma
specific biomarkers, such as listed in FIG. 27. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for B-cell
lymphoma specific exosomes or exosomes comprising one or more
B-cell lymphoma specific biomarkers, such as listed in FIG. 27.
[0464] One or more B-cell lymphoma specific biomarkers, such as
listed in FIG. 27, can also be detected by one or more systems
disclosed herein, for characterizing a B-cell lymphoma. For
example, a detection system can comprise one or more probes to
detect one or more B-cell lymphoma specific biomarkers, such as
listed in FIG. 27, of one or more exosomes of a biological
sample.
[0465] Diffuse Large B-Cell Lymphoma (DLBCL)
[0466] DLBCL specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 28, and can be used to create a DLBCL specific
exosome bio-signature. For example, the bio-signature can comprise
one or more overexpressed miRs, such as, but not limited to,
miR-17-92, miR-155, miR-210, or miR-21, or any combination thereof.
The one or more mRNAs that may be analyzed can include, but are not
limited to, A-myb, LMO2, JNK3, CD10, bcl-6, Cyclin D2, IRF4, Flip,
or CD44, or any combination thereof and can be used as specific
biomarkers from exosomes for DLBCL.
[0467] Also provided herein is an isolated exosome comprising one
or more DLBCL specific biomarkers, such as CITTA-BCL6, CLTC-ALK,
IL21R-BCL6, PIM1-BCL6, TFCR-BCL6, IKZF1-BCL6 or SEC31A-ALK, or
those listed in FIG. 28. A composition comprising the isolated
exosome is also provided. Accordingly, in some embodiments, the
composition comprises a population of exosomes comprising one or
more DLBCL specific biomarkers, such as CITTA-BCL6, CLTC-ALK,
IL21R-BCL6, PIM1-BCL6, TFCR-BCL6, IKZF1-BCL6 or SEC31A-ALK, or
those listed in FIG. 28. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for DLBCL
specific exosomes or exosomes comprising one or more DLBCL specific
biomarkers, such as CITTA-BCL6, CLTC-ALK, IL21R-BCL6, PIM1-BCL6,
TFCR-BCL6, IKZF1-BCL6 or SEC31A-ALK, or those listed in FIG.
28.
[0468] One or more DLBCL specific biomarkers, such as CITTA-BCL6,
CLTC-ALK, IL21R-BCL6, PIM1-BCL6, TFCR-BCL6, IKZF1-BCL6 or
SEC31A-ALK, or those listed in FIG. 28, can also be detected by one
or more systems disclosed herein, for characterizing a DLBCL. For
example, a detection system can comprise one or more probes to
detect one or more DLBCL specific biomarkers, such as CITTA-BCL6,
CLTC-ALK, IL21R-BCL6, PIM 1-BCL6, TFCR-BCL6, IKZF1-BCL6 or
SEC31A-ALK, or those listed in FIG. 28, of one or more exosomes of
a biological sample.
[0469] Burkitt's Lymphoma
[0470] Burkitt's lymphoma specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 29, and can be used to create a Burkitt's
lymphoma specific exosome bio-signature. For example, the
bio-signature can also comprise one or more underexpressed miRs
such as, but not limited to, pri-miR-155, or any combination
thereof. The one or more mRNAs that may be analyzed can include,
but are not limited to, MYC, TERT, NS, NP, MAZ, RCF3, BYSL, IDE3,
CDC7, TCL1A, AUTS2, MYBL1, BMP7, ITPR3, CDC2, BACK2, TTK, MME,
ALOX5, or TOP1, or any combination thereof and can be used as
specific biomarkers from exosomes for Burkitt's lymphoma. The
protein, ligand, or peptide that can be assessed in an exosome can
include, but is not limited to, BCL6, KI-67, or any combination
thereof.
[0471] Also provided herein is an isolated exosome comprising one
or more Burkitt's lymphoma specific biomarkers, such as IGH-MYC,
LCP1-BCL6, or those listed in FIG. 29. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more Burkitt's lymphoma specific biomarkers, such
as IGH-MYC, LCP1-BCL6, or those listed in FIG. 29. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
Burkitt's lymphoma specific exosomes or exosomes comprising one or
more Burkitt's lymphoma specific biomarkers, such as IGH-MYC,
LCP1-BCL6, or those listed in FIG. 29.
[0472] One or more Burkitt's lymphoma specific biomarkers, such as
IGH-MYC, LCP1-BCL6, or those listed in FIG. 29, can also be
detected by one or more systems disclosed herein, for
characterizing a Burkitt's lymphoma. For example, a detection
system can comprise one or more probes to detect one or more
Burkitt's lymphoma specific biomarkers, such as IGH-MYC, LCP1-BCL6,
or those listed in FIG. 29, of one or more exosomes of a biological
sample.
[0473] Hepatocellular Carcinoma
[0474] Hepatocellular carcinoma specific biomarkers from exosomes
can include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 30 and can be used to create a
hepatocellular carcinoma specific exosome bio-signature. For
example, the bio-signature can comprise one or more overexpressed
miRs, such as, but not limited to, miR-221. The bio-signature can
also comprise one or more underexpressed miRs such as, but not
limited to, let-7a-1, let-7a-2, let-7a-3, let-7b, let-7c, let-7d,
let-7e, let-7f-2, let-fg, miR-122a, miR-124a-2, miR-130a, miR-132,
miR-136, miR-141, miR-142, miR-143, miR-145, miR-146, miR-150,
miR-155(BIC), miR-181a-1, miR-181a-2, miR-181c, miR-195,
miR-199a-1-5p, miR-199a-2-5p, miR-199b, miR-200b, miR-214, miR-223,
or pre-miR-594, or any combination thereof. The one or more mRNAs
that may be analyzed can include, but are not limited to,
FAT10.
[0475] The one or more biomarkers of a bio-signature can also be
used to characterize hepatitis C virus-associated hepatocellular
carcinoma. The one or more biomarkers can be a miRNA, such as an
overexpressed or underexpressed miRNA. For example, the upregulated
or overexpressed miRNA can be miR-122, miR-100, or miR-10a and the
downregulated miRNA can be miR-198 or miR-145.
[0476] Also provided herein is an isolated exosome comprising one
or more hepatocellular carcinoma specific biomarkers, such as
listed in FIG. 30 and in FIG. 1 for hepatocellular carcinoma. A
composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more hepatocellular
carcinoma specific biomarkers, such as listed in FIG. 30 and in
FIG. 1 for hepatocellular carcinoma. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for
hepatocellular carcinoma specific exosomes or exosomes comprising
one or more hepatocellular carcinoma specific biomarkers, such as
listed in FIG. 30 and in FIG. 1 for hepatocellular carcinoma.
[0477] One or more hepatocellular carcinoma specific biomarkers,
such as listed in FIG. 30 and in FIG. 1 for hepatocellular
carcinoma, can also be detected by one or more systems disclosed
herein, for characterizing a hepatocellular carcinoma. For example,
a detection system can comprise one or more probes to detect one or
more hepatocellular carcinoma specific biomarkers, such as listed
in FIG. 30 and in FIG. 1 for hepatocellular carcinoma, of one or
more exosomes of a biological sample.
[0478] Cervical Cancer
[0479] Cervical cancer specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 31, and can be used to create a cervical
cancer specific exosome bio-signature. For example, the one or more
mRNAs that may be analyzed can include, but are not limited to, HPV
E6, HPV E7, or p53, or any combination thereof and can be used as
specific biomarkers from exosomes for cervical cancer.
[0480] Also provided herein is an isolated exosome comprising one
or more cervical cancer specific biomarkers, such as listed in FIG.
31 and in FIG. 1 for cervical cancer. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more cervical cancer specific biomarkers, such as
listed in FIG. 31 and in FIG. 1 for cervical cancer. The
composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for cervical cancer specific exosomes or exosomes
comprising one or more cervical cancer specific biomarkers, such as
listed in FIG. 31 and in FIG. 1 for cervical cancer.
[0481] One or more cervical cancer specific biomarkers, such as
listed in FIG. 31 and in FIG. 1 for cervical cancer, can also be
detected by one or more systems disclosed herein, for
characterizing a cervical cancer. For example, a detection system
can comprise one or more probes to detect one or more cervical
cancer specific biomarkers, such as listed in FIG. 31 and in FIG. 1
for cervical cancer, of one or more exosomes of a biological
sample.
[0482] Endometrial Cancer
[0483] Endometrial cancer specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 32 and can be used to create a endometrial
cancer specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-185, miR-106a, miR-181a, miR-210, miR-423,
miR-103, miR-107, or let-7c, or any combination thereof. The
bio-signature can also comprise one or more underexpressed miRs
such as, but not limited to, miR-71, miR-221, miR-193, miR-152, or
miR-30c, or any combination thereof.
[0484] A biomarker mutation for endometrial cancer that can be
assessed in an exosome includes, but is not limited to, a mutation
of PTEN, K-RAS, B-catenin, p53, Her2/neu, or any combination of
mutations specific for endometrial cancer. The protein, ligand, or
peptide that can be assessed in an exosome can include, but is not
limited to, NLRP7, AlphaV Beta6 integrin, or any combination
thereof.
[0485] Also provided herein is an isolated exosome comprising one
or more endometrial cancer specific biomarkers, such as listed in
FIG. 32 and in FIG. 1 for endometrial cancer. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more endometrial cancer specific
biomarkers, such as listed in FIG. 32 and in FIG. 1 for endometrial
cancer. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for endometrial cancer specific exosomes
or exosomes comprising one or more endometrial cancer specific
biomarkers, such as listed in FIG. 32 and in FIG. 1 for endometrial
cancer.
[0486] One or more endometrial cancer specific biomarkers, such as
listed in FIG. 32 and in FIG. 1 for endometrial cancer, can also be
detected by one or more systems disclosed herein, for
characterizing a endometrial cancer. For example, a detection
system can comprise one or more probes to detect one or more
endometrial cancer specific biomarkers, such as listed in FIG. 32
and in FIG. 1 for endometrial cancer, of one or more exosomes of a
biological sample.
[0487] Head and Neck Cancer
[0488] Head and neck cancer specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 33, and can be used to create a head and
neck cancer specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-21, let-7, miR-18, miR-29c, miR-142-3p,
miR-155, miR-146b, miR-205, or miR-21, or any combination thereof.
The bio-signature can also comprise one or more underexpressed miRs
such as, but not limited to, miR-494. The one or more mRNAs that
may be analyzed include, but are not limited to, HPV E6, HPV E7,
p53, IL-8, SAT, H3FA3, or EGFR, or any combination thereof and can
be used as specific biomarkers from exosomes for head and neck
cancer.
[0489] A biomarker mutation for head and neck cancer that can be
assessed in an exosome includes, but is not limited to, a mutation
of GSTM1, GSTT1, GSTP1, OGG1, XRCC1, XPD, RAD51, EGFR, p53, or any
combination of mutations specific for head and neck cancer. The
protein, ligand, or peptide that can be assessed in an exosome can
include, but is not limited to, EGFR, EphB4, or EphB2, or any
combination thereof.
[0490] Also provided herein is an isolated exosome comprising one
or more head and neck cancer specific biomarkers, such as
CHCHD7-PLAG1, CTNNB1-PLAG1, FHIT-HMGA2, HMGA2-NFIB, LIFR-PLAG1, or
TCEA1-PLAG1, or those listed in FIG. 33 and in FIG. 1 for head and
neck cancer. A composition comprising the isolated exosome is also
provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more head and
neck cancer specific biomarkers, such as CHCHD7-PLAG1,
CTNNB1-PLAG1, FHIT-HMGA2, HMGA2-NFIB, LIFR-PLAG1, or TCEA1-PLAG1,
or those listed in FIG. 33 and in FIG. 1 for head and neck cancer.
The composition can comprise a substantially enriched population of
exosomes, wherein the population of exosomes is substantially
homogeneous for head and neck cancer specific exosomes or exosomes
comprising one or more head and neck cancer specific biomarkers,
such as CHCHD7-PLAG1, CTNNB1-PLAG1, FHIT-HMGA2, HMGA2-NFIB,
LIFR-PLAG1, or TCEA1-PLAG1, or those listed in FIG. 33 and in FIG.
1 for head and neck cancer.
[0491] One or more head and neck cancer specific biomarkers, such
as listed in FIG. 33 and in FIG. 1 for head and neck cancer, can
also be detected by one or more systems disclosed herein, for
characterizing a head and neck cancer. For example, a detection
system can comprise one or more probes to detect one or more head
and neck cancer specific biomarkers, such as CHCHD7-PLAG1,
CTNNB1-PLAG1, FHIT-HMGA2, HMGA2-NFIB, LIFR-PLAG1, or TCEA1-PLAG1,
or those listed in FIG. 33 and in FIG. 1 for head and neck cancer,
of one or more exosomes of a biological sample.
[0492] Inflammatory Bowel Disease (IBD)
[0493] IBD specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 34, and can be used to create a IBD specific exosome
bio-signature. The one or more mRNAs that may be analyzed can
include, but are not limited to, Trypsinogen IV, SERT, or any
combination thereof and can be used as specific biomarkers from
exosomes for IBD.
[0494] A biomarker mutation for IBD that can be assessed in an
exosome can include, but is not limited to, a mutation of CARD15 or
any combination of mutations specific for IBD. The protein, ligand,
or peptide that can be assessed in an exosome can include, but is
not limited to, II-16, II-1beta, II-12, TNF-alpha, interferon
gamma, 11-6, Rantes, MCP-1, Resistin, or 5-HT, or any combination
thereof.
[0495] Also provided herein is an isolated exosome comprising one
or more IBD specific biomarkers, such as listed in FIG. 34 and in
FIG. 1 for IBD. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more IBD
specific biomarkers, such as listed in FIG. 34 and in FIG. 1 for
IBD. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for IBD specific exosomes or exosomes
comprising one or more IBD specific biomarkers, such as listed in
FIG. 34 and in FIG. 1 for IBD.
[0496] One or more IBD specific biomarkers, such as listed in FIG.
34 and in FIG. 1 for IBD, can also be detected by one or more
systems disclosed herein, for characterizing a IBD. For example, a
detection system can comprise one or more probes to detect one or
more IBD specific biomarkers, such as listed in FIG. 34 and in FIG.
1 for IBD, of one or more exosomes of a biological sample.
[0497] Diabetes
[0498] Diabetes specific biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 35, and can be used to create a diabetes specific
exosome bio-signature. For example, the one or more mRNAs that may
be analyzed can include, but are not limited to, 11-8, CTSS, ITGB2,
HLA-DRA, CD53, PLAG27, or MMP9, or any combination thereof and can
be used as specific biomarkers from exosomes for diabetes. The
protein, ligand, or peptide that can be assessed in an exosome can
include, but is not limited to, RBP4.
[0499] Also provided herein is an isolated exosome comprising one
or more diabetes specific biomarkers, such as listed in FIG. 35 and
in FIG. 1 for diabetes. A composition comprising the isolated
exosome is also provided. Accordingly, in some embodiments, the
composition comprises a population of exosomes comprising one or
more diabetes specific biomarkers, such as listed in FIG. 35 and in
FIG. 1 for diabetes. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for diabetes specific exosomes or
exosomes comprising one or more diabetes specific biomarkers, such
as listed in FIG. 35 and in FIG. 1 for diabetes.
[0500] One or more diabetes specific biomarkers, such as listed in
FIG. 35 and in FIG. 1 for diabetes, can also be detected by one or
more systems disclosed herein, for characterizing a diabetes. For
example, a detection system can comprise one or more probes to
detect one or more diabetes specific biomarkers, such as listed in
FIG. 35 and in FIG. 1 for diabetes, of one or more exosomes of a
biological sample.
[0501] Barrett's Esophagus
[0502] Barrett's Esophagus specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 36, and can be used to create a Barrett's
Esophagus specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-21, miR-143, miR-145, miR-194, or miR-215,
or any combination thereof. The one or more mRNAs that may be
analyzed include, but are not limited to, S100A2, S100A4, or any
combination thereof and can be used as specific biomarkers from
exosomes for Barrett's Esophagus.
[0503] A biomarker mutation for Barrett's Esophagus that can be
assessed in an exosome includes, but is not limited to, a mutation
of p53 or any combination of mutations specific for Barrett's
Esophagus. The protein, ligand, or peptide that can be assessed in
an exosome can include, but is not limited to, p53, MUC1, MUC2, or
any combination thereof.
[0504] Also provided herein is an isolated exosome comprising one
or more Barrett's Esophagus specific biomarkers, such as listed in
FIG. 36 and in FIG. 1 for Barrett's Esophagus. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more Barrett's Esophagus specific
biomarkers, such as listed in FIG. 36 and in FIG. 1 for Barrett's
Esophagus. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for Barrett's Esophagus specific exosomes
or exosomes comprising one or more Barrett's Esophagus specific
biomarkers, such as listed in FIG. 36 and in FIG. 1 for Barrett's
Esophagus.
[0505] One or more Barrett's Esophagus specific biomarkers, such as
listed in FIG. 36 and in FIG. 1 for Barrett's Esophagus, can also
be detected by one or more systems disclosed herein, for
characterizing a Barrett's Esophagus. For example, a detection
system can comprise one or more probes to detect one or more
Barrett's Esophagus specific biomarkers, such as listed in FIG. 36
and in FIG. 1 for Barrett's Esophagus, of one or more exosomes of a
biological sample.
[0506] Fibromyalgia
[0507] Fibromyalgia specific biomarkers from exosomes can include
one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 37, and can be used to create a fibromyalgia
specific exosome bio-signature. The one or more mRNAs that may be
analyzed can include, but are not limited to, NR2D which can be
used as a specific biomarker from exosomes for fibromyalgia.
[0508] Also provided herein is an isolated exosome comprising one
or more fibromyalgia specific biomarkers, such as listed in FIG. 37
and in FIG. 1 for fibromyalgia. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more fibromyalgia specific biomarkers, such as
listed in FIG. 37 and in FIG. 1 for fibromyalgia. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
fibromyalgia specific exosomes or exosomes comprising one or more
fibromyalgia specific biomarkers, such as listed in FIG. 37 and in
FIG. 1 for fibromyalgia.
[0509] Stroke
[0510] Stroke specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 38, and can be used to create a stroke specific
exosome bio-signature. For example, the one or more mRNAs that may
be analyzed can include, but are not limited to, MMP9, S100-P,
S100A12, SI00A9, coag factor V, ArginaseI, CA-IV, monocarboxylic
acid transporter, ets-2, EIF2alpha, cytoskeleton associated protein
4, N-formylpeptide receptor, Ribonuclease2, N-acetylneuraminate
pyruvate lyase, BCL-6, or Glycogen phosphorylase, or any
combination thereof and can be used as specific biomarkers from
exosomes for stroke.
[0511] Also provided herein is an isolated exosome comprising one
or more stroke specific biomarkers, such as listed in FIG. 38 and
in FIG. 1 for stroke. A composition comprising the isolated exosome
is also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more stroke
specific biomarkers, such as listed in FIG. 38 and in FIG. 1 for
stroke. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for stroke specific exosomes or exosomes
comprising one or more stroke specific biomarkers, such as listed
in FIG. 38 and in FIG. 1 for stroke.
[0512] One or more stroke specific biomarkers, such as listed in
FIG. 38 and in FIG. 1 for stroke, can also be detected by one or
more systems disclosed herein, for characterizing a stroke. For
example, a detection system can comprise one or more probes to
detect one or more stroke specific biomarkers, such as listed in
FIG. 38 and in FIG. 1 for stroke, of one or more exosomes of a
biological sample.
[0513] Multiple Sclerosis (MS)
[0514] MS specific biomarkers from exosomes can include one or more
(for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed miRs,
underexpressed miRs, mRNAs, genetic mutations, proteins, ligands,
peptides, snoRNA, or any combination thereof, such as listed in
FIG. 39, and can be used to create a MS specific exosome
bio-signature. For example, the one or more mRNAs that may be
analyzed can include, but are not limited to, IL-6, IL-17, PAR-3,
IL-17, T1/ST2, JunD, 5-LO, LTA4H, MBP, PLP, or alpha-beta
crystallin, or any combination thereof and can be used as specific
biomarkers from exosomes for MS.
[0515] Also provided herein is an isolated exosome comprising one
or more MS specific biomarkers, such as listed in FIG. 39 and in
FIG. 1 for MS. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more MS
specific biomarkers, such as listed in FIG. 39 and in FIG. 1 for
MS. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for MS specific exosomes or exosomes
comprising one or more MS specific biomarkers, such as listed in
FIG. 39 and in FIG. 1 for MS.
[0516] One or more MS specific biomarkers, such as listed in FIG.
39 and in FIG. 1 for MS, can also be detected by one or more
systems disclosed herein, for characterizing a MS. For example, a
detection system can comprise one or more probes to detect one or
more MS specific biomarkers, such as listed in FIG. 39 and in FIG.
1 for MS, of one or more exosomes of a biological sample.
[0517] Parkinson's Disease
[0518] Parkinson's disease specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 40, and can be used to create a Parkinson's
disease specific exosome bio-signature. For example, the
bio-signature can include, but is not limited to, one or more
underexpressed miRs such as miR-133b. The one or more mRNAs that
may be analyzed can include, but are not limited to Nurr1, BDNF,
TrkB, gstm1, or 5100 beta, or any combination thereof and can be
used as specific biomarkers from exosomes for Parkinson's
disease.
[0519] A biomarker mutation for Parkinson's disease that can be
assessed in an exosome includes, but is not limited to, a mutation
of FGF20, alpha-synuclein, FGF20, NDUFV2, FGF2, CALB1, B2M, or any
combination of mutations specific for Parkinson's disease. The
protein, ligand, or peptide that can be assessed in an exosome can
include, but is not limited to, apo-H, Ceruloplasmin, BDNF, IL-8,
Beta2-microglobulin, apoAII, tau, ABeta1-42, DJ-1, or any
combination thereof.
[0520] Also provided herein is an isolated exosome comprising one
or more Parkinson's disease specific biomarkers, such as listed in
FIG. 40 and in FIG. 1 for Parkinson's disease A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more Parkinson's disease specific
biomarkers, such as listed in FIG. 40 and in FIG. 1 for Parkinson's
disease. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for Parkinson's disease specific exosomes
or exosomes comprising one or more Parkinson's disease specific
biomarkers, such as listed in FIG. 40 and in FIG. 1 for Parkinson's
disease.
[0521] One or more Parkinson's disease specific biomarkers, such as
listed in FIG. 40 and in FIG. 1 for Parkinson's disease, can also
be detected by one or more systems disclosed herein, for
characterizing a Parkinson's disease. For example, a detection
system can comprise one or more probes to detect one or more
Parkinson's disease specific biomarkers, such as listed in FIG. 40
and in FIG. 1 for Parkinson's disease, of one or more exosomes of a
biological sample.
[0522] Rheumatic Disease
[0523] Rheumatic disease specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 41, and can be used to create a rheumatic
disease specific exosome bio-signature. For example, the
bio-signature can also comprise one or more underexpressed miRs
such as, but not limited to, miR-146a, miR-155, miR-132, miR-16, or
miR-181, or any combination thereof. The one or more mRNAs that may
be analyzed can include, but are not limited to, HOXD10, HOXD11,
HOXD13, CCL8, LIM homeobox2, or CENP-E, or any combination thereof
and can be used as specific biomarkers from exosomes for rheumatic
disease. The protein, ligand, or peptide that can be assessed in an
exosome can include, but is not limited to, TNF.alpha..
[0524] Also provided herein is an isolated exosome comprising one
or more rheumatic disease specific biomarkers, such as listed in
FIG. 41 and in FIG. 1 for rheumatic disease. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more rheumatic disease specific
biomarkers, such as listed in FIG. 41 and in FIG. 1 for rheumatic
disease. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for rheumatic disease specific exosomes
or exosomes comprising one or more rheumatic disease specific
biomarkers, such as listed in FIG. 41 and in FIG. 1 for rheumatic
disease.
[0525] One or more rheumatic disease specific biomarkers, such as
listed in FIG. 41 and in FIG. 1 for rheumatic disease, can also be
detected by one or more systems disclosed herein, for
characterizing a rheumatic disease. For example, a detection system
can comprise one or more probes to detect one or more rheumatic
disease specific biomarkers, such as listed in FIG. 41 and in FIG.
1 for rheumatic disease, of one or more exosomes of a biological
sample.
[0526] Alzheimer's Disease
[0527] Alzheimer's disease specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 42, and can be used to create a Alzheimers
disease specific exosome bio-signature. For example, the
bio-signature can also comprise one or more underexpressed miRs
such as miR-107, miR-29a, miR-29b-1, or miR-9, or any combination
thereof. The bio-signature can also comprise one or more
overexpressed miRs such as miR-128 or any combination thereof.
[0528] The one or more mRNAs that may be analyzed can include, but
are not limited to, HIF-1.alpha., BACE1, Reelin, CHRNA7, or
3Rtau/4Rtau, or any combination thereof and can be used as specific
biomarkers from exosomes for Alzheimer's disease.
[0529] A biomarker mutation for Alzheimer's disease that can be
assessed in an exosome includes, but is not limited to, a mutation
of APP, presenilin1, presenilin2, APOE4, or any combination of
mutations specific for Alzheimer's disease. The protein, ligand, or
peptide that can be assessed in an exosome can include, but is not
limited to, BACE1, Reelin, Cystatin C, Truncated Cystatin C,
Amyloid Beta, C3a, t-Tau, Complement factor H, or
alpha-2-macroglobulin, or any combination thereof.
[0530] Also provided herein is an isolated exosome comprising one
or more Alzheimer's disease specific biomarkers, such as listed in
FIG. 42 and in FIG. 1 for Alzheimer's disease. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more Alzheimer's disease specific
biomarkers, such as listed in FIG. 42 and in FIG. 1 for Alzheimer's
disease. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for Alzheimer's disease specific exosomes
or exosomes comprising one or more Alzheimer's disease specific
biomarkers, such as listed in FIG. 42 and in FIG. 1 for Alzheimer's
disease.
[0531] One or more Alzheimer's disease specific biomarkers, such as
listed in FIG. 42 and in FIG. 1 for Alzheimer's disease, can also
be detected by one or more systems disclosed herein, for
characterizing a Alzheimer's disease. For example, a detection
system can comprise one or more probes to detect one or more
Alzheimer's disease specific biomarkers, such as listed in FIG. 42
and in FIG. 1 for Alzheimer's disease, of one or more exosomes of a
biological sample.
[0532] Prion Disease
[0533] Prion specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 43, and can be used to create a prion specific
exosome bio-signature. For example, the one or more mRNAs that may
be analyzed can include, but are not limited to, Amyloid B4, App,
IL-1R1, or SOD1, or any combination thereof and can be used as
specific biomarkers from exosomes for a prion. The protein, ligand,
or peptide that can be assessed in an exosome can include, but is
not limited to, PrP(c), 14-3-3, NSE, S-100, Tau, AQP-4, or any
combination thereof.
[0534] Also provided herein is an isolated exosome comprising one
or more prion disease specific biomarkers, such as listed in FIG.
43 and in FIG. 1 for prion disease. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more prion disease specific biomarkers, such as
listed in FIG. 43 and in FIG. 1 for prion disease. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
prion disease specific exosomes or exosomes comprising one or more
prion disease specific biomarkers, such as listed in FIG. 43 and in
FIG. 1 for prion disease.
[0535] One or more prion disease specific biomarkers, such as
listed in FIG. 43 and in FIG. 1 for prion disease, can also be
detected by one or more systems disclosed herein, for
characterizing a prion disease. For example, a detection system can
comprise one or more probes to detect one or more prion disease
specific biomarkers, such as listed in FIG. 43 and in FIG. 1 for
prion disease, of one or more exosomes of a biological sample.
[0536] Sepsis
[0537] Sepsis specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 44, and can be used to create a sepsis specific
exosome bio-signature. For example, the one or more mRNAs that may
be analyzed can include, but are not limited to, 15-Hydroxy-PG
dehydrogenase (up), LAIR1 (up), NFKB1A (up), TLR2, PGLYPR1, TLR4,
MD2, TLR5, IFNAR2, IRAK2, IRAK3, IRAK4, PI3K, PI3KCB, MAP2K6,
MAPK14, NFKB1A, NFKB1, IL1R1, MAP2K1IP1, MKNK1, FAS, CASP4,
GADD45B, SOCS3, TNFSF10, TNFSF13B, OSM, HGF, or IL18R1, or any
combination thereof and can be used as specific biomarkers from
exosomes for sepsis.
[0538] Also provided herein is an isolated exosome comprising one
or more sepsis specific biomarkers, such as listed in FIG. 44. A
composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more sepsis specific
biomarkers, such as listed in FIG. 44. The composition can comprise
a substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for sepsis
specific exosomes or exosomes comprising one or more sepsis
specific biomarkers, such as listed in FIG. 44.
[0539] One or more sepsis specific biomarkers, such as listed in
FIG. 44, can also be detected by one or more systems disclosed
herein, for characterizing a sepsis. For example, a detection
system can comprise one or more probes to detect one or more sepsis
specific biomarkers, such as listed in FIG. 44, of one or more
exosomes of a biological sample.
[0540] Chronic Neuropathic Pain
[0541] Chronic neuropathic pain (CNP) specific biomarkers from
exosomes can include one or more (for example, 2, 3, 4, 5, 6, 7, 8,
or more) overexpressed miRs, underexpressed miRs, mRNAs, genetic
mutations, proteins, ligands, peptides, snoRNA, or any combination
thereof, such as listed in FIG. 45, and can be used to create a CNP
specific exosome bio-signature. For example, the one or more mRNAs
that may be analyzed can include, but are not limited to, ICAM-1
(rodent), CGRP (rodent), TIMP-1 (rodent), CLR-1 (rodent), HSP-27
(rodent), FABP (rodent), or apolipoprotein D (rodent), or any
combination thereof and can be used as specific biomarkers from
exosomes for CNP. The protein, ligand, or peptide that can be
assessed in an exosome can include, but is not limited to,
chemokines, chemokine receptors (CCR2/4), or any combination
thereof.
[0542] Also provided herein is an isolated exosome comprising one
or more chronic neuropathic pain specific biomarkers, such as
listed in FIG. 45 and in FIG. 1 for chronic neuropathic pain. A
composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more chronic neuropathic
pain specific biomarkers, such as listed in FIG. 45 and in FIG. 1
for chronic neuropathic pain. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for chronic
neuropathic pain specific exosomes or exosomes comprising one or
more chronic neuropathic pain specific biomarkers, such as listed
in FIG. 45 and in FIG. 1 for chronic neuropathic pain.
[0543] One or more chronic neuropathic pain specific biomarkers,
such as listed in FIG. 45 and in FIG. 1 for chronic neuropathic
pain, can also be detected by one or more systems disclosed herein,
for characterizing a chronic neuropathic pain. For example, a
detection system can comprise one or more probes to detect one or
more chronic neuropathic pain specific biomarkers, such as listed
in FIG. 45 and in FIG. 1 for chronic neuropathic pain, of one or
more exosomes of a biological sample.
[0544] Peripheral Neuropathic Pain
[0545] Peripheral neuropathic pain (PNP) specific biomarkers from
exosomes can include one or more (for example, 2, 3, 4, 5, 6, 7, 8,
or more) overexpressed miRs, underexpressed miRs, mRNAs, genetic
mutations, proteins, ligands, peptides, snoRNA, or any combination
thereof, such as listed in FIG. 46, and can be used to create a PNP
specific exosome bio-signature. For example, the protein, ligand,
or peptide that can be assessed in an exosome can include, but is
not limited to, OX42, ED9, or any combination thereof.
[0546] Also provided herein is an isolated exosome comprising one
or more peripheral neuropathic pain specific biomarkers, such as
listed in FIG. 46 and in FIG. 1 for peripheral neuropathic pain. A
composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more peripheral
neuropathic pain specific biomarkers, such as listed in FIG. 46 and
in FIG. 1 for peripheral neuropathic pain. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for
peripheral neuropathic pain specific exosomes or exosomes
comprising one or more peripheral neuropathic pain specific
biomarkers, such as listed in FIG. 46 and in FIG. 1 for peripheral
neuropathic pain.
[0547] One or more peripheral neuropathic pain specific biomarkers,
such as listed in FIG. 46 and in FIG. 1 for peripheral neuropathic
pain, can also be detected by one or more systems disclosed herein,
for characterizing a peripheral neuropathic pain. For example, a
detection system can comprise one or more probes to detect one or
more peripheral neuropathic pain specific biomarkers, such as
listed in FIG. 46 and in FIG. 1 for peripheral neuropathic pain, of
one or more exosomes of a biological sample.
[0548] Schizophrenia
[0549] Schizophrenia specific biomarkers from exosomes can include
one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 47, and can be used to create a
schizophrenia specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-181b. The bio-signature can also comprise
one or more underexpressed miRs such as, but not limited to, miR-7,
miR-24, miR-26b, miR-29b, miR-30b, miR-30e, miR-92, or miR-195, or
any combination thereof.
[0550] The one or more mRNAs that may be analyzed can include, but
are not limited to, IFITM3, SERPINA3, GLS, or ALDH7A1BASP1, or any
combination thereof and can be used as specific biomarkers from
exosomes for schizophrenia. A biomarker mutation for schizophrenia
that can be assessed in an exosome includes, but is not limited to,
a mutation of to DISC1, dysbindin, neuregulin-1, seratonin 2a
receptor, NURR1, or any combination of mutations specific for
schizophrenia.
[0551] The protein, ligand, or peptide that can be assessed in an
exosome can include, but is not limited to, ATP5B, ATP5H, ATP6V1B,
DNM1, NDUFV2, NSF, PDHB, or any combination thereof.
[0552] Also provided herein is an isolated exosome comprising one
or more schizophrenia specific biomarkers, such as listed in FIG.
47 and in FIG. 1 for schizophrenia. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more schizophrenia specific biomarkers, such as
listed in FIG. 47 and in FIG. 1 for schizophrenia. The composition
can comprise a substantially enriched population of exosomes,
wherein the population of exosomes is substantially homogeneous for
schizophrenia specific exosomes or exosomes comprising one or more
schizophrenia specific biomarkers, such as listed in FIG. 47 and in
FIG. 1 for schizophrenia.
[0553] One or more schizophrenia specific biomarkers, such as
listed in FIG. 47 and in FIG. 1 for schizophrenia, can also be
detected by one or more systems disclosed herein, for
characterizing a schizophrenia. For example, a detection system can
comprise one or more probes to detect one or more schizophrenia
specific biomarkers, such as listed in FIG. 47 and in FIG. 1 for
schizophrenia, of one or more exosomes of a biological sample.
[0554] Bipolar Disease
[0555] Bipolar disease specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 48, and can be used to create a bipolar
disease specific exosome bio-signature. For example, the one or
more mRNAs that may be analyzed can include, but are not limited
to, FGF2, ALDH7A1, AGXT2L1, AQP4, or PCNT2, or any combination
thereof and can be used as specific biomarkers from exosomes for
bipolar disease. A biomarker mutation for bipolar disease that can
be assessed in an exosome includes, but is not limited to, a
mutation of Dysbindin, DAOA/G30, DISC1, neuregulin-1, or any
combination of mutations specific for bipolar disease.
[0556] Also provided herein is an isolated exosome comprising one
or more bipolar disease specific biomarkers, such as listed in FIG.
48. A composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more bipolar disease
specific biomarkers, such as listed in FIG. 48. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for bipolar
disease specific exosomes or exosomes comprising one or more
bipolar disease specific biomarkers, such as listed in FIG. 48.
[0557] One or more bipolar disease specific biomarkers, such as
listed in FIG. 48, can also be detected by one or more systems
disclosed herein, for characterizing a bipolar disease. For
example, a detection system can comprise one or more probes to
detect one or more bipolar disease specific biomarkers, such as
listed in FIG. 48, of one or more exosomes of a biological
sample.
[0558] Depression
[0559] Depression specific biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 49, and can be used to create a depression specific
exosome bio-signature. For example, the one or more mRNAs that may
be analyzed can include, but are not limited to, FGFR1, FGFR2,
FGFR3, or AQP4, or any combination thereof can also be used as
specific biomarkers from exosomes for depression.
[0560] Also provided herein is an isolated exosome comprising one
or more depression specific biomarkers, such as listed in FIG. 49.
A composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more depression specific
biomarkers, such as listed in FIG. 49. The composition can comprise
a substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for depression
specific exosomes or exosomes comprising one or more depression
specific biomarkers, such as listed in FIG. 49.
[0561] One or more depression specific biomarkers, such as listed
in FIG. 49, can also be detected by one or more systems disclosed
herein, for characterizing a depression. For example, a detection
system can comprise one or more probes to detect one or more
depression specific biomarkers, such as listed in FIG. 49, of one
or more exosomes of a biological sample.
[0562] Gastrointestinal Stromal Tumor (GIST)
[0563] GIST specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 50, and can be used to create a GIST specific
exosome bio-signature. For example, the one or more mRNAs that may
be analyzed can include, but are not limited to, DOG-1, PKC-theta,
KIT, GPR20, PRKCQ, KCNK3, KCNH2, SCG2, TNFRSF6B, or CD34, or any
combination thereof and can be used as specific biomarkers from
exosomes for GIST.
[0564] A biomarker mutation for GIST that can be assessed in an
exosome includes, but is not limited to, a mutation of PKC-theta or
any combination of mutations specific for GIST. The protein,
ligand, or peptide that can be assessed in an exosome can include,
but is not limited to, PDGFRA, c-kit, or any combination
thereof.
[0565] Also provided herein is an isolated exosome comprising one
or more GIST specific biomarkers, such as listed in FIG. 50 and in
FIG. 1 for GIST. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more GIST
specific biomarkers, such as listed in FIG. 50 and in FIG. 1 for
GIST. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for GIST specific exosomes or exosomes
comprising one or more GIST specific biomarkers, such as listed in
FIG. 50 and in FIG. 1 for GIST.
[0566] One or more GIST specific biomarkers, such as listed in FIG.
50 and in FIG. 1 for GIST, can also be detected by one or more
systems disclosed herein, for characterizing a GIST. For example, a
detection system can comprise one or more probes to detect one or
more GIST specific biomarkers, such as listed in FIG. 50 and in
FIG. 1 for GIST, of one or more exosomes of a biological
sample.
[0567] Renal Cell Carcinoma
[0568] Renal cell carcinoma specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 51, and can be used to create a renal cell
carcinoma specific exosome bio-signature. For example, the
bio-signature can also comprise one or more underexpressed miRs
such as, but not limited to, miR-141, miR-200c, or any combination
thereof. The one or more upregulated or overexpressed miRNA can be
miR-28, miR-185, miR-27, miR-let-7f-2, or any combination
thereof.
[0569] The one or more mRNAs that may be analyzed can include, but
are not limited to, laminin receptor 1, betaig-h3, Galectin-1, a-2
Macroglobulin, Adipophilin, Angiopoietin 2, Caldesmon 1, Class II
MHC-associated invariant chain (CD74), Collagen IV-al, Complement
component, Complement component 3, Cytochrome P450, subfamily IIJ
polypeptide 2, Delta sleep-inducing peptide, Fc g receptor 111a
(CD16), HLA-B, HLA-DRa, HLA-DRb, HLA-SB, IFN-induced transmembrane
protein 3, IFN-induced transmembrane protein 1, or Lysyl Oxidase,
or any combination thereof and can be used as specific biomarkers
from exosomes for renal cell carcinoma.
[0570] A biomarker mutation for renal cell carcinoma that can be
assessed in an exosome includes, but is not limited to, a mutation
of VHL or any combination of mutations specific renal cell
carcinoma.
[0571] The protein, ligand, or peptide that can be assessed in an
exosome can include, but is not limited to, IF1 alpha, VEGF,
PDGFRA, or any combination thereof.
[0572] Also provided herein is an isolated exosome comprising one
or more RCC specific biomarkers, such as ALPHA-TFEB, NONO-TFE3,
PRCC-TFE3, SFPQ-TFE3, CLTC-TFE3, or MALAT1-TFEB, or those listed in
FIG. 51 and in FIG. 1 for RCC. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more RCC specific biomarkers, such as ALPHA-TFEB,
NONO-TFE3, PRCC-TFE3, SFPQ-TFE3, CLTC-TFE3, or MALAT1-TFE, or those
listed in FIG. 51 and in FIG. 1 for RCC. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for RCC
specific exosomes or exosomes comprising one or more RCC specific
biomarkers, such as ALPHA-TFEB, NONO-TFE3, PRCC-TFE3, SFPQ-TFE3,
CLTC-TFE3, or MALAT1-TFE, or those listed in FIG. 51 and in FIG. 1
for RCC.
[0573] One or more RCC specific biomarkers, such as ALPHA-TFEB,
NONO-TFE3, PRCC-TFE3, SFPQ-TFE3, CLTC-TFE3, or MALAT1-TFE, or those
listed in FIG. 51 and in FIG. 1 for RCC, can also be detected by
one or more systems disclosed herein, for characterizing a RCC. For
example, a detection system can comprise one or more probes to
detect one or more RCC specific biomarkers, such as ALPHA-TFEB,
NONO-TFE3, PRCC-TFE3, SFPQ-TFE3, CLTC-TFE3, or MALAT1-TFE, or those
listed in FIG. 51 and in FIG. 1 for RCC, of one or more exosomes of
a biological sample.
[0574] Cirrhosis
[0575] Cirrhosis specific biomarkers from exosomes can include one
or more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 52, and can be used to create a cirrhosis specific
exosome bio-signature. The one or more mRNAs that may be analyzed
include, but are not limited to, NLT, which can be used as
aspecific biomarker from exosomes for cirrhosis.
[0576] The protein, ligand, or peptide that can be assessed in an
exosome can include, but is not limited to, NLT, HBsAG, AST,
YKL-40, Hyaluronic acid, TIMP-1, alpha 2 macroglobulin,
a-1-antitrypsin P1Z allele, haptoglobin, or acid phosphatase ACP
AC, or any combination thereof.
[0577] Also provided herein is an isolated exosome comprising one
or more cirrhosis specific biomarkers, such as those listed in FIG.
52 and in FIG. 1 for cirrhosis. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more cirrhosis specific biomarkers, such as those
listed in FIG. 52 and in FIG. 1 for cirrhosis. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for
cirrhosis specific exosomes or exosomes comprising one or more
cirrhosis specific biomarkers, such as those listed in FIG. 52 and
in FIG. 1 for cirrhosis.
[0578] One or more cirrhosis specific biomarkers, such as those
listed in FIG. 52 and in FIG. 1 for cirrhosis, can also be detected
by one or more systems disclosed herein, for characterizing
cirrhosis. For example, a detection system can comprise one or more
probes to detect one or more cirrhosis specific biomarkers, such as
those listed in FIG. 52 and in FIG. 1 for cirrhosis, of one or more
exosomes of a biological sample.
[0579] Esophageal Cancer
[0580] Esophageal cancer specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 53, and can be used to create a esophageal
cancer specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-192, miR-194, miR-21, miR-200c, miR-93,
miR-342, miR-152, miR-93, miR-25, miR-424, or miR-151, or any
combination thereof. The bio-signature can also comprise one or
more underexpressed miRs such as, but not limited to, miR-27b,
miR-205, miR-203, miR-342, let-7c, miR-125b, miR-100, miR-152,
miR-192, miR-194, miR-27b, miR-205, miR-203, miR-200c, miR-99a,
miR-29c, miR-140, miR-103, or miR-107, or any combination thereof.
The one or more mRNAs that may be analyzed include, but are not
limited to, MTHFR and can be used as specific biomarkers from
exosomes for esophageal cancer.
[0581] Also provided herein is an isolated exosome comprising one
or more esophageal cancer specific biomarkers, such as listed in
FIG. 53 and in FIG. 1 for esophageal cancer. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more esophageal cancer specific
biomarkers, such as listed in FIG. 53 and in FIG. 1 for esophageal
cancer. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for esophageal cancer specific exosomes
or exosomes comprising one or more esophageal cancer specific
biomarkers, such as listed in FIG. 53 and in FIG. 1 for esophageal
cancer.
[0582] One or more esophageal cancer specific biomarkers, such as
listed in FIG. 53 and in FIG. 1 for esophageal cancer, can also be
detected by one or more systems disclosed herein, for
characterizing a esophageal cancer. For example, a detection system
can comprise one or more probes to detect one or more esophageal
cancer specific biomarkers, such as listed in FIG. 53 and in FIG. 1
for esophageal cancer, of one or more exosomes of a biological
sample.
[0583] Gastric Cancer
[0584] Gastric cancer specific biomarkers from exosomes can include
one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 54, and can be used to create a gastric
cancer specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-106a, miR-21, miR-191, miR-223, miR-24-1,
miR-24-2, miR-107, miR-92-2, miR-214, miR-25, or miR-221, or any
combination thereof. The bio-signature can also comprise one or
more underexpressed miRs such as, but not limited to, let-7a.
[0585] The one or more mRNAs that may be analyzed include, but are
not limited to, RRM2, EphA4, or survivin, or any combination
thereof and can be used as specific biomarkers from exosomes for
gastric cancer. A biomarker mutation for gastric cancer that can be
assessed in an exosome includes, but is not limited to, a mutation
of APC or any combination of mutations specific for gastric cancer.
The protein, ligand, or peptide that can be assessed in an exosome
can include, but is not limited to EphA4.
[0586] Also provided herein is an isolated exosome comprising one
or more gastric cancer specific biomarkers, such as listed in FIG.
54. A composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more gastric cancer
specific biomarkers, such as listed in FIG. 54. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for gastric
cancer specific exosomes or exosomes comprising one or more gastric
cancer specific biomarkers, such as listed in FIG. 54.
[0587] One or more gastric cancer specific biomarkers, such as
listed in FIG. 54, can also be detected by one or more systems
disclosed herein, for characterizing a gastric cancer. For example,
a detection system can comprise one or more probes to detect one or
more gastric cancer specific biomarkers, such as listed in FIG. 54,
of one or more exosomes of a biological sample.
[0588] Autism
[0589] Autism specific biomarkers from exosomes can include one or
more (for example, 2, 3, 4, 5, 6, 7, 8, or more) overexpressed
miRs, underexpressed miRs, mRNAs, genetic mutations, proteins,
ligands, peptides, snoRNA, or any combination thereof, such as
listed in FIG. 55, and can be used to create an autism specific
exosome bio-signature. For example, the bio-signature can comprise
one or more overexpressed miRs, such as, but not limited to,
miR-484, miR-21, miR-212, miR-23a, miR-598, miR-95, miR-129,
miR-431, miR-7, miR-15a, miR-27a, miR-15b, miR-148b, miR-132, or
miR-128, or any combination thereof. The bio-signature can also
comprise one or more underexpressed miRs such as, but not limited
to, miR-93, miR-106a, miR-539, miR-652, miR-550, miR-432, miR-193b,
miR-181d, miR-146b, miR-140, miR-381, miR-320a, or miR-106b, or any
combination thereof. The protein, ligand, or peptide that can be
assessed in an exosome can include, but is not limited to, GM1,
GD1a, GD1b, or GT1b, or any combination thereof.
[0590] Also provided herein is an isolated exosome comprising one
or more autism specific biomarkers, such as listed in FIG. 55 and
in FIG. 1 for autism. A composition comprising the isolated exosome
is also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more autism
specific biomarkers, such as listed in FIG. 55 and in FIG. 1 for
autism. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for autism specific exosomes or exosomes
comprising one or more autism specific biomarkers, such as listed
in FIG. 55 and in FIG. 1 for autism.
[0591] One or more autism specific biomarkers, such as listed in
FIG. 55 and in FIG. 1 for autism, can also be detected by one or
more systems disclosed herein, for characterizing a autism. For
example, a detection system can comprise one or more probes to
detect one or more autism specific biomarkers, such as listed in
FIG. 55 and in FIG. 1 for autism, of one or more exosomes of a
biological sample.
[0592] Organ Rejection
[0593] Organ rejection specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 56, and can be used to create an organ
rejection specific exosome bio-signature. For example, the
bio-signature can comprise one or more overexpressed miRs, such as,
but not limited to, miR-658, miR-125a, miR-320, miR-381, miR-628,
miR-602, miR-629, or miR-125a, or any combination thereof. The
bio-signature can also comprise one or more underexpressed miRs
such as, but not limited to, miR-324-3p, miR-611, miR-654,
miR-330_MM1, miR-524, miR-17-3p_MM1, miR-483, miR-663, miR-5,6-5p,
miR-326, miR-197_MM2, or miR-346, or any combination thereof. The
protein, ligand, or peptide that can be assessed in an exosome can
include, but is not limited to, matix metalloprotein-9, proteinase
3, or HNP, or any combinations thereof. The biomarker can be a
member of the matrix metalloproteinases.
[0594] Also provided herein is an isolated exosome comprising one
or more organ rejection specific biomarkers, such as listed in FIG.
56. A composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more organ rejection
specific biomarkers, such as listed in FIG. 56. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for organ
rejection specific exosomes or exosomes comprising one or more
organ rejection specific biomarkers, such as listed in FIG. 56.
[0595] One or more organ rejection specific biomarkers, such as
listed in FIG. 56, can also be detected by one or more systems
disclosed herein, for characterizing a organ rejection. For
example, a detection system can comprise one or more probes to
detect one or more organ rejection specific biomarkers, such as
listed in FIG. 56, of one or more exosomes of a biological
sample.
[0596] Methicillin-Resistant Staphylococcus aureus
[0597] Methicillin-resistant Staphylococcus aureus specific
biomarkers from exosomes can include one or more (for example, 2,
3, 4, 5, 6, 7, 8, or more) overexpressed miRs, underexpressed miRs,
mRNAs, genetic mutations, proteins, ligands, peptides, snoRNA, or
any combination thereof, such as listed in FIG. 57, and can be used
to create a methicillin-resistant Staphylococcus aureus specific
exosome bio-signature.
[0598] The one or more mRNAs that may be analyzed include, but are
not limited to, TSST-1 which can be used as a specific biomarker
from exosomes for methicillin-resistant Staphylococcus aureus. A
biomarker mutation for methicillin-resistant Staphylococcus aureus
that can be assessed in an exosome includes, but is not limited to,
a mutation of mecA, Protein A SNPs, or any combination of mutations
specific for methicillin-resistant Staphylococcus aureus. The
protein, ligand, or peptide that can be assessed in an exosome can
include, but is not limited to, ETA, ETB, TSST-1, or leukocidins,
or any combination thereof.
[0599] Also provided herein is an isolated exosome comprising one
or more methicillin-resistant Staphylococcus aureus specific
biomarkers, such as listed in FIG. 57. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more methicillin-resistant Staphylococcus aureus
specific biomarkers, such as listed in FIG. 57. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for
methicillin-resistant Staphylococcus aureus specific exosomes or
exosomes comprising one or more methicillin-resistant
Staphylococcus aureus specific biomarkers, such as listed in FIG.
57.
[0600] One or more methicillin-resistant Staphylococcus aureus
specific biomarkers, such as listed in FIG. 57, can also be
detected by one or more systems disclosed herein, for
characterizing a methicillin-resistant Staphylococcus aureus. For
example, a detection system can comprise one or more probes to
detect one or more methicillin-resistant Staphylococcus aureus
specific biomarkers, such as listed in FIG. 57, of one or more
exosomes of a biological sample.
[0601] Vulnerable Plaque
[0602] Vulnerable plaque specific biomarkers from exosomes can
include one or more (for example, 2, 3, 4, 5, 6, 7, 8, or more)
overexpressed miRs, underexpressed miRs, mRNAs, genetic mutations,
proteins, ligands, peptides, snoRNA, or any combination thereof,
such as listed in FIG. 58, and can be used to create a vulnerable
plaque specific exosome bio-signature. The protein, ligand, or
peptide that can be assessed in an exosome can include, but is not
limited to, IL-6, MMP-9, PAPP-A, D-dimer, fibrinogen, Lp-PLA2,
SCD40L, Il-18, oxLDL, GPx-1, MCP-1, P1GF, or CRP, or any
combination thereof.
[0603] Also provided herein is an isolated exosome comprising one
or more vulnerable plaque specific biomarkers, such as listed in
FIG. 58 and in FIG. 1 for vulnerable plaque. A composition
comprising the isolated exosome is also provided. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more vulnerable plaque specific
biomarkers, such as listed in FIG. 58 and in FIG. 1 for vulnerable
plaque. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for vulnerable plaque specific exosomes
or exosomes comprising one or more vulnerable plaque specific
biomarkers, such as listed in FIG. 58 and in FIG. 1 for vulnerable
plaque.
[0604] One or more vulnerable plaque specific biomarkers, such as
listed in FIG. 58 and in FIG. 1 for vulnerable plaque, can also be
detected by one or more systems disclosed herein, for
characterizing a vulnerable plaque. For example, a detection system
can comprise one or more probes to detect one or more vulnerable
plaque specific biomarkers, such as listed in FIG. 58 and in FIG. 1
for vulnerable plaque, of one or more exosomes of a biological
sample.
[0605] Autoimmune Disease
[0606] Also provided herein is an isolated exosome comprising one
or more autoimmune disease specific biomarkers, such as listed in
FIG. 1 for autoimmune disease. A composition comprising the
isolated exosome is also provided. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more autoimmune disease specific biomarkers, such
as listed in FIG. 1 for autoimmune disease. The composition can
comprise a substantially enriched population of exosomes, wherein
the population of exosomes is substantially homogeneous for
autoimmune disease specific exosomes or exosomes comprising one or
more autoimmune disease specific biomarkers, such as listed in FIG.
1 for autoimmune disease.
[0607] One or more autoimmune disease specific biomarkers, such as
listed in FIG. 1 for autoimmune disease, can also be detected by
one or more systems disclosed herein, for characterizing a
autoimmune disease. For example, a detection system can comprise
one or more probes to detect one or more autoimmune disease
specific biomarkers, such as listed in FIG. 1 for autoimmune
disease, of one or more exosomes of a biological sample.
[0608] Tuberculosis (TB)
[0609] Also provided herein is an isolated exosome comprising one
or more TB disease specific biomarkers, such as listed in FIG. 1
for TB disease. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more TB
disease specific biomarkers, such as listed in FIG. 1 for TB
disease. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for TB disease specific exosomes or
exosomes comprising one or more TB disease specific biomarkers,
such as listed in FIG. 1 for TB disease.
[0610] One or more TB disease specific biomarkers, such as listed
in FIG. 1 for TB disease, can also be detected by one or more
systems disclosed herein, for characterizing a TB disease. For
example, a detection system can comprise one or more probes to
detect one or more TB disease specific biomarkers, such as listed
in FIG. 1 for TB disease, of one or more exosomes of a biological
sample.
[0611] HIV
[0612] Also provided herein is an isolated exosome comprising one
or more HIV disease specific biomarkers, such as listed in FIG. 1
for HIV disease. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more HIV
disease specific biomarkers, such as listed in FIG. 1 for HIV
disease. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for HIV disease specific exosomes or
exosomes comprising one or more HIV disease specific biomarkers,
such as listed in FIG. 1 for HIV disease.
[0613] One or more HIV disease specific biomarkers, such as listed
in FIG. 1 for HIV disease, can also be detected by one or more
systems disclosed herein, for characterizing a HIV disease. For
example, a detection system can comprise one or more probes to
detect one or more HIV disease specific biomarkers, such as listed
in FIG. 1 for HIV disease, of one or more exosomes of a biological
sample.
[0614] The one or more biomarker can also be a miRNA, such as an
upregulated or overexpressed miRNA. The upregulated miRNA can be
miR-29a, miR-29b, miR-149, miR-378 or miR-324-5p. One or more
biomarkers can also be used to characterize HIV-1 latency, such as
by assessing one or more miRNAs. The miRNA can be miR-28, miR-125b,
miR-150, miR-223 and miR-382, and upregulated.
[0615] Asthma
[0616] Also provided herein is an isolated exosome comprising one
or more asthma disease specific biomarkers, such as listed in FIG.
1 for asthma disease. A composition comprising the isolated exosome
is also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more asthma
disease specific biomarkers, such as listed in FIG. 1 for asthma
disease. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for asthma disease specific exosomes or
exosomes comprising one or more asthma disease specific biomarkers,
such as listed in FIG. 1 for asthma disease.
[0617] One or more asthma disease specific biomarkers, such as
listed in FIG. 1 for asthma disease, can also be detected by one or
more systems disclosed herein, for characterizing a asthma disease.
For example, a detection system can comprise one or more probes to
detect one or more asthma disease specific biomarkers, such as
listed in FIG. 1 for asthma disease, of one or more exosomes of a
biological sample.
[0618] Lupus
[0619] Also provided herein is an isolated exosome comprising one
or more lupus disease specific biomarkers, such as listed in FIG. 1
for lupus disease. A composition comprising the isolated exosome is
also provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more lupus
disease specific biomarkers, such as listed in FIG. 1 for lupus
disease. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for lupus disease specific exosomes or
exosomes comprising one or more lupus disease specific biomarkers,
such as listed in FIG. 1 for lupus disease.
[0620] One or more lupus disease specific biomarkers, such as
listed in FIG. 1 for lupus disease, can also be detected by one or
more systems disclosed herein, for characterizing a lupus disease.
For example, a detection system can comprise one or more probes to
detect one or more lupus disease specific biomarkers, such as
listed in FIG. 1 for lupus disease, of one or more exosomes of a
biological sample.
[0621] Influenza
[0622] Also provided herein is an isolated exosome comprising one
or more influenza disease specific biomarkers, such as listed in
FIG. 1 for influenza disease. A composition comprising the isolated
exosome is also provided. Accordingly, in some embodiments, the
composition comprises a population of exosomes comprising one or
more influenza disease specific biomarkers, such as listed in FIG.
1 for influenza disease. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for influenza
disease specific exosomes or exosomes comprising one or more
influenza disease specific biomarkers, such as listed in FIG. 1 for
influenza disease.
[0623] One or more influenza disease specific biomarkers, such as
listed in FIG. 1 for influenza disease, can also be detected by one
or more systems disclosed herein, for characterizing a influenza
disease. For example, a detection system can comprise one or more
probes to detect one or more influenza disease specific biomarkers,
such as listed in FIG. 1 for influenza disease, of one or more
exosomes of a biological sample.
[0624] Thyroid Cancer
[0625] Also provided herein is an isolated exosome comprising one
or more thyroid cancer specific biomarkers, such as AKAP-BRAF,
CCDC6-RET, ERC1-RETM, GOLGA5-RET, HOOK3-RET, HRH4-RET, KTN1-RET,
NCOA4-RET, PCM1-RET, PRKARA1A-RET, RFG-RET, RFG9-RET, Ria-RET,
TGF-NTRK1, TPM3-NTRK1, TPM3-TPR, TPR-MET, TPR-NTRK1, TRIM24-RET,
TRIM27-RET or TRIM33-RET, characteristic of papillary thyroid
carcinoma; or PAX8-PPARy, characteristic of follicular thyroid
cancer. A composition comprising the isolated exosome is also
provided. Accordingly, in some embodiments, the composition
comprises a population of exosomes comprising one or more thyroid
cancer specific biomarkers, such as listed in FIG. 1 for thyroid
cancer. The composition can comprise a substantially enriched
population of exosomes, wherein the population of exosomes is
substantially homogeneous for thyroid cancer specific exosomes or
exosomes comprising one or more thyroid cancer specific biomarkers,
such as listed in FIG. 1 for thyroid cancer.
[0626] One or more thyroid cancer specific biomarkers, such as
listed in FIG. 1 for thyroid cancer, can also be detected by one or
more systems disclosed herein, for characterizing a thyroid cancer.
For example, a detection system can comprise one or more probes to
detect one or more thyroid cancer specific biomarkers, such as
listed in FIG. 1 for thyroid cancer, of one or more exosomes of a
biological sample.
[0627] Gene Fusions
[0628] The one or more biomarkers assessed of an exosome can be a
gene fusion, such as one or more listed in FIG. 59. A fusion gene
is a hybrid gene created by the juxtaposition of two previously
separate genes. This can occur by chromosomal translocation or
inversion, deletion or via trans-splicing. The resulting fusion
gene can cause abnormal temporal and spatial expression of genes,
such as leading to abnormal expression of cell growth factors,
angiogenesis factors, tumor promoters or other factors contributing
to the neoplastic transformation of the cell and the creation of a
tumor. Such fusion genes can be oncogenic due to the juxtaposition
of: 1) a strong promoter region of one gene next to the coding
region of a cell growth factor, tumor promoter or other gene
promoting oncogenesis leading to elevated gene expression, or 2)
due to the fusion of coding regions of two different genes, giving
rise to a chimeric gene and thus a chimeric protein with abnormal
activity.
[0629] An example of a fusion gene is BCR-ABL, a characteristic
molecular aberration in .about.90% of chronic myelogenous leukemia
(CML) and in a subset of acute leukemias (Kurzrock et al., Annals
of Internal Medicine 2003; 138(10): 819-830). The BCR-ABL results
from a translocation between chromosomes 9 and 22. The
translocation brings together the 5' region of the BCR gene and the
3' region of ABL1, generating a chimeric BCR-ABL1 gene, which
encodes a protein with constitutively active tyrosine kinase
activity (Mittleman et al., Nature Reviews Cancer 2007;
7(4):233-245). The aberrant tyrosine kinase activity leads to
de-regulated cell signaling, cell growth and cell survival,
apoptosis resistance and growth factor independence, all of which
contribute to the pathophysiology of leukemia (Kurzrock et al.,
Annals of Internal Medicine 2003; 138(10):819-830).
[0630] Another fusion gene is IGH-MYC, a defining feature of
.about.80% of Burkitt's lymphoma (Ferry et al. Oncologist 2006;
11(4):375-83). The causal event for this is a translocation between
chromosomes 8 and 14, bringing the c-Myc oncogene adjacent to the
strong promoter of the immunoglobin heavy chain gene, causing c-myc
overexpression (Mittleman et al., Nature Reviews Cancer 2007;
7(4):233-245). The c-myc rearrangement is a pivotal event in
lymphomagenesis as it results in a perpetually proliferative state.
It has wide ranging effects on progression through the cell cycle,
cellular differentiation, apoptosis, and cell adhesion (Ferry et
al. Oncologist 2006; 11(4):375-83).
[0631] A number of recurrent fusion genes have been catalogued in
the Mittleman database
(http://cgap.nci.nih.gov/Chromosomes/Mitelman) and can be assess in
an exosome and used to characterize a phenotype. The gene fusion
can be used to characterize a hematological malignancy or
epithelial tumor. For example, TMPRSS2-ERG, TMPRSS2-ETV and
SLC45A3-ELK4 fusions can be detected and used to characterize
prostate cancer; and ETV6-NTRK3 and ODZ4-NRG 1 for breast
cancer.
[0632] Furthermore, assessing the presence or absence, or
expression level of a fusion gene can be used to diagnosis a
phenotype such as a cancer as well as a monitoring a therapeutic
response to selecting a treatment. For example, the presence of the
BCR-ABL fusion gene is a characteristic not only for the diagnosis
of CML, but is also the target of the Novartis drug Imatinib
mesylate (Gleevec), a receptor tyrosine kinase inhibitor, for the
treatment of CML. Imatinib treatment has led to molecular responses
(disappearance of BCR-ABL+blood cells) and improved
progression-free survival in BCR-ABL+CML patients (Kantarjian et
al., Clinical Cancer Research 2007; 13(4):1089-1097).
[0633] Assessing an exosome for the presence, absence, or
expression level of a gene fusion can be of a heterogeneous
population of exosomes. Alternatively, the exosome can be derived
from a specific cell type, such as cell-or-origin specific
exosomes, as described above.
[0634] Breast Cancer
[0635] To characterize a breast cancer, an exosome can be assessed
for one or more breast cancer specific fusions, including, but not
limited to, ETV6-NTRK3. The exosome can be derived from breast
cancer cells.
[0636] Lung Cancer
[0637] To characterize a lung cancer, an exosome can be assessed
for one or more lung cancer specific fusions, including, but not
limited to, RLF-MYCL1, TGF-ALK, or CD74-ROS1. The exosome can be
derived from lung cancer cells.
[0638] Prostate Cancer
[0639] To characterize a prostate cancer, an exosome can be
assessed for one or more prostate cancer specific fusions,
including, but not limited to, ACSL3-ETV1, C15ORF21-ETV1,
FLJ35294-ETV1, HERV-ETV1, TMPRSS2-ERG, TMPRSS2-ETV1/4/5,
TMPRSS2-ETV4/5, SLC5A3-ERG, SLC5A3-ETV1, SLC5A3-ETV5 or KLK2-ETV4.
The exosome can be derived from prostate cancer cells.
[0640] Brain Cancer
[0641] To characterize a brain cancer, an exosome can be assessed
for one or more brain cancer specific fusions, including, but not
limited to, GOPC-ROS1. The exosome can be derived from brain cancer
cells.
[0642] Head and Neck Cancer
[0643] To characterize ahead and neck cancer, an exosome can be
assessed for one or more head and neck cancer specific fusions,
including, but not limited to, CHCHD7-PLAG1, CTNNB1-PLAG1,
FHIT-HMGA2, HMGA2-NFIB, LIFR-PLAG1, or TCEA1-PLAG1. The exosome can
be derived from head and neck cancer cells.
[0644] Renal Cell Carcinoma (RCC)
[0645] To characterize a RCC, an exosome can be assessed for one or
more RCC specific fusions, including, but not limited to,
ALPHA-TFEB, NONO-TFE3, PRCC-TFE3, SFPQ-TFE3, CLTC-TFE3, or
MALAT1-TFEB. The exosome can be derived from RCC cells.
[0646] Thyroid Cancer
[0647] To characterize a thyroid cancer, an exosome can be assessed
for one or more thyroid cancer specific fusions, including, but not
limited to, AKAP9-BRAF, CCDC6-RET, ERC1-RETM, GOLGA5-RET,
HOOK3-RET, HRH4-RET, KTN1-RET, NCOA4-RET, PCM1-RET, PRKARA1A-RET,
RFG-RET, RFG9-RET, R1a--RET, TGF-NTRK1, TPM3-NTRK1, TPM3-TPR,
TPR-MET, TPR-NTRK1, TRIM24-RET, TRIM27-RET or TRIM33-RET,
characteristic of papillary thyroid carcinoma; or PAX8-PPARy,
characteristic of follicular thyroid cancer. The exosome can be
derived from thyroid cancer cells.
[0648] Blood Cancers
[0649] To characterize a blood cancer, an exosome can be assessed
for one or more blood cancer specific fusions, including, but not
limited to, TTL-ETV6, CDK6-MLL, CDK6-TLX3, ETV6-FLT3, ETV6-RUNX1,
ETV6-TTL, MLL-AFF1, MLL-AFF3, MLL-AFF4, MLL-GAS7, TCBA1-ETV6,
TCF3-PBX1 or TCF3-TFPT, characteristic of acute lymphocytic
leukemia (ALL); BCL11B-TLX3, IL2-TNFRFS17, NUP214-ABL1,
NUP98-CCDC28A, TALI-STIL, or ETV6-ABL2, characteristic of T-cell
acute lymphocytic leukemia (T-ALL); ATIC-ALK, KIAA1618-ALK,
MSN-ALK, MYH9-ALK, NPM1-ALK, TGF-ALK or TPM3-ALK, characteristic of
anaplastic large cell lymphoma (ALCL); BCR-ABL1, BCR-JAK2,
ETV6-EVI1, ETV6-MN1 or ETV6-TCBA1, characteristic of chronic
myelogenous leukemia (CML); CBFB-MYH11, CHIC2-ETV6, ETV6-ABL1,
ETV6-ABL2, ETV6-ARNT, ETV6-CDX2, ETV6-HLXB9, ETV6-PER1,
MEF2D-DAZAP1, AML-AFF1, MLL-ARHGAP26, MLL-ARHGEF12, MLL-CASC5,
MLL-CBL, MLL-CREBBP, MLL-DAB21P, MLL-ELL, MLL-EP300, MLL-EPS15,
MLL-FNBP1, MLL-FOXO3A, MLL-GMPS, MLL-GPHN, MLL-MLLT1, MLL-MLLT11,
MLL-MLLT3, MLL-MLLT6, MLL-MYO1F, MLL-PICALM, MLL-SEPT2, MLL-SEPT6,
MLL-SORBS2, MYST3-SORBS2, MYST-CREBBP, NPM1-MLF1, NUP98-HOXA13,
PRDM16-EVI1, RABEP1-PDGFRB, RUNX1-EVI1, RUNX1-MDS1, RUNX1-RPL22,
RUNX1-RUNX1T1, RUNX1-SH3D19, RUNX1-USP42, RUNX1-YTHDF2,
RUNX1-ZNF687, or TAF15-ZNF-384, characteristic of AML; CCND1-FSTL3,
characteristic of chronic lymphocytic leukemia (CLL); BCL3-MYC,
MYC-BTG1, BCL7A-MYC, BRWD3-ARHGAP20 or BTG1-MYC, characteristic of
B-cell chronic lymphocytic leukemia (B-CLL); CITTA-BCL6, CLTC-ALK,
IL21R-BCL6, PIM1-BCL6, TFCR-BCL6, IKZF1-BCL6 or SEC31A-ALK,
characteristic of diffuse large B-cell lymphomas (DLBCL);
FLIP1-PDGFRA, FLT3-ETV6, KIAA1509-PDGFRA, PDE4DIP-PDGFRB,
NIN-PDGFRB, TP53BP1-PDGFRB, or TPM3-PDGFRB, characteristic of hyper
eosinophilia/chronic eosinophilia; IGH-MYC or LCP1-BCL6,
characteristic of Burkitt's lymphoma. The exosome can be derived
from blood cancer cells.
[0650] Also provided herein is an isolated exosome comprising one
or more gene fusions as disclosed herein, such as listed in FIG.
59. A composition comprising the isolated exosome is also provided.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more gene fusions, such as
listed in FIG. 59. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
gene fusions, such as listed in FIG. 59.
[0651] Also provided herein is a detection system for detecting one
or more gene fusions, such as gene fusions listed in FIG. 59. For
example, a detection system can comprise one or more probes to
detect one or more gene fusions listed in FIG. 59. Detection of the
one or more gene fusions can be used to characterize a cancer.
[0652] Gene-Associated mRNA Biomarkers
[0653] The one or more biomarkers assessed can also include one or
more genes selected from the group consisting of PFKFB3, RHAMM
(HMMR), cDNA FLJ42103, ASPM, CENPF, NCAPG, Androgen Receptor, EGFR,
HSP90, SPARC, DNMT3B, GART, MGMT, SSTR3, and TOP2B. The microRNA
that interacts with the one or more genes can also be a biomarker
(see for example, FIG. 60). Furthermore, the one or more biomarkers
can be used to characterize prostate cancer.
[0654] Also provided herein is an isolated exosome comprising one
or more one or more biomarkers consisting of PFKFB3, RHAMM (HMMR),
cDNA FLJ42103, ASPM, CENPF, NCAPG, Androgen Receptor, EGFR, HSP90,
SPARC, DNMT3B, GART, MGMT, SSTR3, and TOP2B; or the microRNA that
interacts with the one or more genes (see for example, FIG. 60).
Also provided is a composition comprising the isolated exosome.
Accordingly, in some embodiments, the composition comprises a
population of exosomes comprising one or more biomarkers consisting
of PFKFB3, RHAMM (HMMR), cDNA FLJ42103, ASPM, CENPF, NCAPG,
Androgen Receptor, EGFR, HSP90, SPARC, DNMT3B, GART, MGMT, SSTR3,
and TOP2B; or the microRNA that interacts with the one or more
genes, such as listed in FIG. 60. The composition can comprise a
substantially enriched population of exosomes, wherein the
population of exosomes is substantially homogeneous for exosomes
comprising one or more biomarkers consisting of PFKFB3, RHAMM
(HMMR), cDNA FLJ42103, ASPM, CENPF, NCAPG, Androgen Receptor, EGFR,
HSP90, SPARC, DNMT3B, GART, MGMT, SSTR3, and TOP2B; or the microRNA
that interacts with the one or more genes, such as listed in FIG.
60.
[0655] One or more prostate cancer specific biomarkers, such as
listed in FIG. 60 can also be detected by one or more systems
disclosed herein. For example, a detection system can comprise one
or more probes to detect one or more prostate cancer specific
biomarkers, such as listed in FIG. 60, of one or more exosomes of a
biological sample.
[0656] The miRNA that interacts with PFKFB3 can be miR-513a-3p,
miR-128, miR-488, miR-539, miR-658, miR-524-5p, miR-1258, miR-150,
miR-216b, miR-377, miR-135a, miR-26a, miR-548a-5p, miR-26b,
miR-520d-5p, miR-224, miR-1297, miR-1197, miR-182, miR-452,
miR-509-3-5p, miR-548m, miR-625, miR-509-5p, miR-1266, miR-135b,
miR-190b, miR-496, miR-616, miR-621, miR-650, miR-105, miR-19a,
miR-346, miR-620, miR-637, miR-651, miR-1283, miR-590-3p, miR-942,
miR-1185, miR-577, miR-602, miR-1305, miR-220c, miR-1270, miR-1282,
miR-432, miR-491-5p, miR-548n, miR-765, miR-768-3p or miR-924, and
can be used as a biomarker.
[0657] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with PFKFB3. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with PFKFB3. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with PFKFB3. Furthermore, the one or more
miRNA that interacts with PFKFB3 can also be detected by one or
more systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with PFKFB3 of one or more exosomes of a biological
sample.
[0658] The miRNA that interacts with RHAMM can be miR-936, miR-656,
miR-105, miR-361-5p, miR-194, miR-374a, miR-590-3p, miR-186,
miR-769-5p, miR-892a, miR-380, miR-875-3p, miR-208a, miR-208b,
miR-586, miR-125a-3p, miR-630, miR-374b, miR-411, miR-629,
miR-1286, miR-1185, miR-16, miR-200b, miR-671-5p, miR-95, miR-421,
miR-496, miR-633, miR-1243, miR-127-5p, miR-143, miR-15b, miR-200c,
miR-24 or miR-34c-3p.
[0659] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with RHAMM. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with RHAMM. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with RHAMM. Furthermore, the one or more miRNA
that interacts with RHAMM can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with RHAMM of one or more exosomes of a biological
sample.
[0660] The miRNA that interacts with CENPF can be miR-30c, miR-30b,
miR-190, miR-508-3p, miR-384, miR-512-5p, miR-548p, miR-297,
miR-520f, miR-376a, miR-1184, miR-577, miR-708, miR-205, miR-376b,
miR-520g, miR-520h, miR-519d, miR-596, miR-768-3p, miR-340,
miR-620, miR-539, miR-567, miR-671-5p, miR-1183, miR-129-3p,
miR-636, miR-106a, miR-1301, miR-17, miR-20a, miR-570, miR-656,
miR-1263, miR-1324, miR-142-5p, miR-28-5p, miR-302b, miR-452,
miR-520d-3p, miR-548o, miR-892b, miR-302d, miR-875-3p, miR-106b,
miR-1266, miR-1323, miR-20b, miR-221, miR-520e, miR-664, miR-920,
miR-922, miR-93, miR-1228, miR-1271, miR-30e, miR-483-3p,
miR-509-3-5p, miR-515-3p, miR-519e, miR-520b, miR-520c-3p or
miR-582-3p.
[0661] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with CENPF. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with CENPF. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with CENPF. Furthermore, the one or more miRNA
that interacts with CENPF can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with CENPF of one or more exosomes of a biological
sample.
[0662] The miRNA that interacts with NCAPG can be miR-876-5p,
miR-1260, miR-1246, miR-548c-3p, miR-1224-3p, miR-619, miR-605,
miR-490-5p, miR-186, miR-448, miR-129-5p, miR-188-3p, miR-516b,
miR-342-3p, miR-1270, miR-548k, miR-654-3p, miR-1290, miR-656,
miR-34b, miR-520g, miR-1231, miR-1289, miR-1229, miR-23a, miR-23b,
miR-616 or miR-620.
[0663] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with NCAPG. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with NCAPG. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with NCAPG. Furthermore, the one or more miRNA
that interacts with NCAPG can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with NCAPG of one or more exosomes of a biological
sample.
[0664] The miRNA that interacts with Androgen Receptor can be
miR-124a, miR-130a, miR-130b, miR-143, miR-149, miR-194, miR-29b,
miR-29c, miR-301, miR-30a-5p, miR-30d, miR-30e-5p, miR-337,
miR-342, miR-368, miR-488, miR-493-5p, miR-506, miR-512-5p,
miR-644, miR-768-5p or miR-801.
[0665] The miRNA that interacts with EGFR can be miR-105, miR-128a,
miR-128b, miR-140, miR-141, miR-146a, miR-146b, miR-27a, miR-27b,
miR-302a, miR-302d, miR-370, miR-548c, miR-574, miR-587 or
miR-7.
[0666] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with AR. Also provided is
a composition comprising the isolated exosome. Accordingly, in some
embodiments, the composition comprises a population of exosomes
comprising one or more biomarkers consisting of miRNA that
interacts with AR. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with AR. Furthermore, the one or more miRNA
that interacts with AR can also be detected by one or more systems
disclosed herein. For example, a detection system can comprise one
or more probes to detect one or more one or more miRNA that
interacts with AR of one or more exosomes of a biological
sample.
[0667] The miRNA that interacts with HSP90 can be miR-1,
miR-513a-3p, miR-548d-3p, miR-642, miR-206, miR-450b-3p, miR-152,
miR-148a, miR-148b, miR-188-3p, miR-23a, miR-23b, miR-578, miR-653,
miR-1206, miR-192, miR-215, miR-181b, miR-181d, miR-223, miR-613,
miR-769-3p, miR-99a, miR-100, miR-454, miR-548n, miR-640, miR-99b,
miR-150, miR-181a, miR-181c, miR-522, miR-624, miR-130a, miR-130b,
miR-146, miR-148a, miR-148b, miR-152, miR-181a, miR-181b, miR-181c,
miR-204, miR-206, miR-211, miR-212, miR-215, miR-223, miR-23a,
miR-23b, miR-301, miR-31, miR-325, miR-363, miR-566, miR-9 or
miR-99b.
[0668] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with HSP90. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with HSP90. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with HSP90. Furthermore, the one or more miRNA
that interacts with HSP90 can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with HSP90 of one or more exosomes of a biological
sample.
[0669] The miRNA that interacts with SPARC can be miR-768-5p,
miR-203, miR-196a, miR-569, miR-187, miR-641, miR-1275, miR-432,
miR-622, miR-296-3p, miR-646, miR-196b, miR-499-5p, miR-590-5p,
miR-495, miR-625, miR-1244, miR-512-5p, miR-1206, miR-1303,
miR-186, miR-302d, miR-494, miR-562, miR-573, miR-10a, miR-203,
miR-204, miR-211, miR-29, miR-29b, miR-29c, miR-339, miR-433,
miR-452, miR-515-5p, miR-517a, miR-517b, miR-517c, miR-592 or
miR-96.
[0670] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with SPARC. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with SPARC. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with SPARC. Furthermore, the one or more miRNA
that interacts with SPARC can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with SPARC of one or more exosomes of a biological
sample.
[0671] The miRNA that interacts with DNMT3B can be miR-618,
miR-1253, miR-765, miR-561, miR-330-5p, miR-326, miR-188, miR-203,
miR-221, miR-222, miR-26a, miR-26b, miR-29a, miR-29b, miR-29c,
miR-370, miR-379, miR-429, miR-519e, miR-598, miR-618 or
miR-635.
[0672] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with DNMT3B. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with DNMT3B. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with DNMT3B. Furthermore, the one or more
miRNA that interacts with DNMT3B can also be detected by one or
more systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with DNMT3B of one or more exosomes of a biological
sample.
[0673] The miRNA that interacts with GART can be miR-101, miR-141,
miR-144, miR-182, miR-189, miR-199a, miR-199b, miR-200a, miR-200b,
miR-202, miR-203, miR-223, miR-329, miR-383, miR-429, miR-433,
miR-485-5p, miR-493-5p, miR-499, miR-519a, miR-519b, miR-519c,
miR-569, miR-591, miR-607, miR-627, miR-635, miR-636 or
miR-659.
[0674] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with GART. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with GART. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with GART. Furthermore, the one or more miRNA
that interacts with GART can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with GART of one or more exosomes of a biological
sample.
[0675] The miRNA that interacts with MGMT can be miR-122a,
miR-142-3p, miR-17-3p, miR-181a, miR-181b, miR-181c, miR-181d,
miR-199b, miR-200a, miR-217, miR-302b, miR-32, miR-324-3p, miR-34a,
miR-371, miR-425-5p, miR-496, miR-514, miR-515-3p, miR-516-3p,
miR-574, miR-597, miR-603, miR-653, miR-655, miR-92, miR-92b or
miR-99a.
[0676] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with MGMT. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with MGMT. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with MGMT. Furthermore, the one or more miRNA
that interacts with MGMT can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with MGMT of one or more exosomes of a biological
sample.
[0677] The miRNA that interacts with SSTR3 can be miR-125a,
miR-125b, miR-133a, miR-133b, miR-136, miR-150, miR-21, miR-380-5p,
miR-504, miR-550, miR-671, miR-766 or miR-767-3p.
[0678] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with SSTR3. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with SSTR3. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with SSTR3. Furthermore, the one or more miRNA
that interacts with SSTR3 can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with SSTR3 of one or more exosomes of a biological
sample.
[0679] The miRNA that interacts with TOP2B can be miR-548f,
miR-548a-3p, miR-548g, miR-513a-3p, miR-548c-3p, miR-101, miR-653,
miR-548d-3p, miR-575, miR-297, miR-576-3p, miR-548b-3p, miR-624,
miR-548n, miR-758, miR-1253, miR-1324, miR-23b, miR-320a, miR-320b,
miR-1183, miR-1244, miR-23a, miR-451, miR-568, miR-1276, miR-548e,
miR-590-3p, miR-1, miR-101, miR-126, miR-129, miR-136, miR-140,
miR-141, miR-144, miR-147, miR-149, miR-18, miR-181b, miR-181c,
miR-182, miR-184, miR-186, miR-189, miR-191, miR-19a, miR-19b,
miR-200a, miR-206, miR-210, miR-218, miR-223, miR-23a, miR-23b,
miR-24, miR-27a, miR-302, miR-30a, miR-31, miR-320, miR-323,
miR-362, miR-374, miR-383, miR-409-3p, miR-451, miR-489,
miR-493-3p, miR-514, miR-542-3p, miR-544, miR-548a, miR-548b,
miR-548c, miR-548d, miR-559, miR-568, miR-575, miR-579, miR-585,
miR-591, miR-598, miR-613, miR-649, miR-651, miR-758, miR-768-3p or
miR-9.
[0680] Also provided herein is an isolated exosome comprising one
or more one or more miRNA that interacts with TOP2B. Also provided
is a composition comprising the isolated exosome. Accordingly, in
some embodiments, the composition comprises a population of
exosomes comprising one or more biomarkers consisting of miRNA that
interacts with TOP2B. The composition can comprise a substantially
enriched population of exosomes, wherein the population of exosomes
is substantially homogeneous for exosomes comprising one or more
miRNA that interacts with TOP2B. Furthermore, the one or more miRNA
that interacts with TOP2B can also be detected by one or more
systems disclosed herein. For example, a detection system can
comprise one or more probes to detect one or more one or more miRNA
that interacts with TOP2B of one or more exosomes of a biological
sample.
Bio-Signatures: Biomarker Detection
[0681] Bio-signatures can be detected qualitatively or
quantitatively. Exosome levels may be characterized as described
above. Analysis of exosomes can comprise detecting the level of
exosomes in combination with determining the biomarkers of the
exosomes. Determining the level or amount of exosome can be
performed in conjunction with determining the biomarkers of the
exosome. Alternatively, determining the amount of exosome may be
performed prior to or subsequent to determining the biomarkers of
the exosomes. Methods for analyzing biomarkers of tissues or cells
can be used to analyze the biomarkers associated with or contained
in exosomes.
[0682] For example, biomarkers can be detected by microarray
analysis, PCR (including PCR-based methods such as RT-PCR, qPCR and
the like), hybridization with allele-specific probes, enzymatic
mutation detection, ligation chain reaction (LCR), oligonucleotide
ligation assay (OLA), flow-cytometric heteroduplex analysis,
chemical cleavage of mismatches, mass spectrometry, nucleic acid
sequencing, single strand conformation polymorphism (SSCP),
denaturing gradient gel electrophoresis (DGGE), temperature
gradient gel electrophoresis (TGGE), restriction fragment
polymorphisms, serial analysis of gene expression (SAGE), or any
combinations thereof. The biomarker, such as a nucleic acid, can be
amplified prior to detection. Biomarkers can also be detected by
immunoblot, immunoprecipitation, ELISA, RIA, flow cytometry, or
electron microscopy.
[0683] One method of detecting biomarkers can include purifying or
isolating a heterogeneous exosome population from a biological
sample, as described above, and performing a sandwich assay. An
exosome in the population can be captured with a primary antibody,
such as an antibody bound to a substrate, for example an array,
well, or particle. The captured or bound exosome can be detected
with a detection antibody. For example, the detection antibody can
be for an antigen of the exosome. The detection antibody can be
directly labeled and detected. Alternatively, an enzyme linked
secondary antibody can react with the detection antibody. A
detection reagent or detection substrate is added and the reaction
can be detected, such as described in PCT Publication No.
WO2009092386. The primary antibody can be an anti-Rab 5b antibody
and the detection antibody anti-CD63 or anti-caveolin-1.
Alternatively, the capture antibody can be an antibody to CD9,
PSCA, TNFR, CD63, B7H3, MFG-E8, EpCam, Rab, CD81, STEAP, PCSA,
PSMA, or 5T4. The detection antibody can be an antibody to CD63,
CD9, CD81, B7H3, or EpCam.
[0684] In some embodiments, the capture agent binds or targets
EpCam, and the one or more biomarkers detected on the exosome is
CD9, CD63, or both CD9 and CD63. In other embodiments, the capture
agent targets PCSA, and the one or more biomarkers detected on the
captured exosome is B7H3, PSMA, or both B7H3 and PSMA. In yet other
embodiments, the capture agent targets CD63 and the one or more
biomarkers detected on the exosome is CD81, CD83, CD9, CD63, or any
combination thereof. The different capture agent and biomarker
combinations can be used to characterize a phenotype, such as
prostate cancer or colon cancer. For example, capturing one or more
exosomes can be performed with a capture agent targeting EpCam and
detection of CD9 and CD63; a capture agent targeting PCSA and
detection of B7H3 and PSMA; or a capture agent of CD63 and
detection of CD81; can be used to characterize prostate cancer. A
capture agent targeting CD63 and detection of CD63, or a capture
agent targeting CD9 and detecting CD63, can be used to characterize
colon cancer.
[0685] Other methods can include the use of a planar substrate such
as an array (i.e., biochip or microarray), with immobilized
molecules as capture agents, which can facilitate the detection of
a particular bio-signature of exosomes. The arrays can be provided
as part of a kit for assaying exosomes. Molecules that identify the
biomarkers described above and shown in FIG. 3-60, as well as
antigens in FIG. 1 can be included in a custom array for detection
and diagnosis of diseases including presymtomatic diseases. Arrays
comprising biomolecules that specifically identify selected
biomarkers can be used to develop a database of information using
data provided in the present specification. Additional biomolecules
that identify bio-signatures which lead to improved cross-validated
error rates in multivariate prediction models (e.g., logistic
regression, discriminant analysis, or regression tree models) can
be included in a custom array.
[0686] Customized array(s) provide an opportunity to study the
biology of a disease, condition or syndrome and profile exosomes
that are shed in defined physiological states. Standard p values of
significance (0.05) can be chosen to exclude or include additional
specific biomolecules on the microarray that identify particular
biomarkers.
[0687] A planar array can generally contain addressable locations
(e.g., pads, addresses, or micro-locations) of biomolecules in an
array format. The size of the array will depend on the composition
and end use of the array. Arrays containing from about 2 different
molecules to many thousands can be made. Generally, the array can
comprise from two to as many as 100,000 or more molecules,
depending on the end use of the array and the method of
manufacture. A microarray can generally comprise at least one
biomolecule that identifies or captures a biomarker present in a
bio-signature of specific cell-of-origin exosomes. In some
embodiments, the compositions of the invention may not be in an
array format; that is, for some embodiments, compositions
comprising a single biomolecule may be made as well. In addition,
in some arrays, multiple substrates may be used, either of
different or identical compositions. Thus, for example, large
planar arrays may comprise a plurality of smaller substrates.
[0688] An array of the present invention encompasses any means for
detecting a biomarker. For example, microarrays can be biochips
that provide high-density immobilized arrays of recognition
molecules (e.g., antibodies), where biomarker binding is monitored
indirectly (e.g., via fluorescence). In addition, an array can be
of a format that involves the capture of proteins by biochemical or
intermolecular interaction, coupled with direct detection by mass
spectrometry (MS).
[0689] Arrays and microarrays that can be used to detect the
biomarkers of a bio-signature of exosomes can be made according to
the methods described in U.S. Pat. Nos. 6,329,209; 6,365,418;
6,406,921; 6,475,808; and 6,475,809, and U.S. patent application
Ser. No. 10/884,269, each of which is herein incorporated by
reference in its entirety. New arrays, to detect specific
selections of sets of biomarkers described herein can also be made
using the methods described in these patents. Furthermore,
commercially available microarrays, such as for protein or nucleic
acid detection can also be used, such as from Affymetrix (Santa
Clara, Calif.), Illumina (San Diego, Calif.), Agilent (Santa Clara,
Calif.), Exiqon (Denmark), or Invitrogen (Carlsbad, Calif.).
[0690] In many embodiments, immobilized molecules, or molecules to
be immobilized, are proteins or peptides. One or more types of
proteins may be immobilized on a surface. In certain embodiments,
the proteins are immobilized using methods and materials that
minimize the denaturing of the proteins, that minimize alterations
in the activity of the proteins, or that minimize interactions
between the protein and the surface on which they are
immobilized.
[0691] Surfaces useful may be of any desired shape (form) and size.
Non-limiting examples of surfaces include chips, continuous
surfaces, curved surfaces, flexible surfaces, films, plates,
sheets, tubes, or the like. Surfaces can have areas ranging from
approximately a square micron to approximately 500 cm.sup.2. The
area, length, and width of surfaces according to the present
invention may be varied according to the requirements of the assay
to be performed. Considerations may include, for example, ease of
handling, limitations of the material(s) of which the surface is
formed, requirements of detection systems, requirements of
deposition systems (e.g., arrayers), or the like.
[0692] In certain embodiments, it is desirable to employ a physical
means for separating groups or arrays of binding islands or
immobilized biomolecules: such physical separation facilitates
exposure of different groups or arrays to different solutions of
interest. Therefore, in certain embodiments, arrays are situated
within microwell plates having any number of wells. In such
embodiments, the bottoms of the wells may serve as surfaces for the
formation of arrays, or arrays may be formed on other surfaces and
then placed into wells. In certain embodiments, such as where a
surface without wells is used, binding islands may be formed or
molecules may be immobilized on a surface and a gasket having holes
spatially arranged so that they correspond to the islands or
biomolecules may be placed on the surface. Such a gasket is
preferably liquid tight. A gasket may be placed on a surface at any
time during the process of making the array and may be removed if
separation of groups or arrays is no longer necessary.
[0693] The immobilized molecules can bind to exosomes present in a
biological sample overlying the immobilized molecules.
Alternatively, the immobilized molecules modify or are modified by
molecules present in exosomes overlying the immobilized
molecules.
[0694] Modifications or binding of molecules in solution or
immobilized on an array may be detected using detection techniques
known in the art. Examples of such techniques include immunological
techniques such as competitive binding assays and sandwich assays;
fluorescence detection using instruments such as confocal scanners,
confocal microscopes, or CCD-based systems and techniques such as
fluorescence, fluorescence polarization (FP), fluorescence resonant
energy transfer (FRET), total internal reflection fluorescence
(TIRF), fluorescence correlation spectroscopy (FCS);
colorimetric/spectrometric techniques; surface plasmon resonance,
by which changes in mass of materials adsorbed at surfaces may be
measured; techniques using radioisotopes, including conventional
radioisotope binding and scintillation proximity assays (SPA); mass
spectroscopy, such as matrix-assisted laser desorption/ionization
mass spectroscopy (MALDI) and MALDI-time of flight (TOF) mass
spectroscopy; ellipsometry, which is an optical method of measuring
thickness of protein films; quartz crystal microbalance (QCM), a
very sensitive method for measuring mass of materials adsorbing to
surfaces; scanning probe microscopies, such as AFM and SEM; and
techniques such as electrochemical, impedance, acoustic, microwave,
and IR/Raman detection. See, e.g., Mere L, et al., "Miniaturized
FRET assays and microfluidics: key components for
ultra-high-throughput screening," Drug Discovery Today 4(8):363-369
(1999), and references cited therein; Lakowicz J R, Principles of
Fluorescence Spectroscopy, 2nd Edition, Plenum Press (1999), or
Jain K K: Integrative Omics, Pharmacoproteomics, and Human Body
Fluids. In: Thongboonkerd V, ed., ed. Proteomics of Human Body
Fluids: Principles, Methods and Applications. Volume 1: Totowa,
N.J.: Humana Press, 2007, each of which is herein incorporated by
reference in its entirety.
[0695] Microarray technology can be combined with mass spectroscopy
(MS) analysis and other tools. Electrospray interface to a mass
spectrometer can be integrated with a capillary in microfluidics
devices. For example, one commercially available system contains
eTag reporters that are fluorescent labels with unique and
well-defined electrophoretic mobilities; each label is coupled to
biological or chemical probes via cleavable linkages. The distinct
mobility address of each eTag reporter allows mixtures of these
tags to be rapidly deconvoluted and quantitated by capillary
electrophoresis. This system allows concurrent gene expression,
protein expression, and protein function analyses from the same
sample Jain K K: Integrative Omics, Pharmacoproteomics, and Human
Body Fluids. In: Thongboonkerd V, ed., ed. Proteomics of Human Body
Fluids Principles, Methods and Applications. Volume 1: Totowa,
N.J.: Humana Press, 2007, which is herein incorporated by reference
in its entirety.
[0696] These biochips can include components for microfluidic or
nanofluidic assays. Microfluidic devices can be used for isolating
exosomes, such as described herein, in combination with analyzing
the exosomes, such as determining bio-signatures. Such systems
miniaturize and compartmentalize processes that allow for capturing
of exosomes, detection of exosomal biomarkers, and other processes.
The microfluidic devices can utilize detection reagents in at least
one aspect of the system, and such detection reagents may be used
to detect one or more biomarkers of exosomes. For example, the
device can detect biomarkers on the isolated exosomes or bound
exosomes. One or more biomarkers of a sample of isolated exosomes
can be detected through the use of a microfluidic device. For
example, various probes, antibodies, proteins, or other binding
agents can be used to detect a biomarker. The detection agents may
be immobilized in different compartments of the microfluidic device
or be entered into a hybridization or detection reaction through
various channels of the device.
[0697] An exosome in a microfluidic device may be lysed and the
contents, such as proteins or nucleic acids, such as DNA or RNA
(such as miRNA, mRNA) can be detected within a microfluidic device.
The nucleic acid may be amplified prior to detection, or directly
detected, within the microfluidic device. Thus microfluidic systems
can also be used for multiplexing detection of various
biomarkers.
[0698] Novel nanofabrication techniques are opening up the
possibilities for biosensing applications that rely on fabrication
of high-density, precision arrays, e.g., nucleotide-based chips and
protein arrays otherwise know as heterogeneous nanoarrays.
Nanofluidics allows a further reduction in the quantity of fluid
analyte in a microchip to nanoliter levels, and the chips used here
are referred to as nanochips. (See, e.g., Unger M et al.,
Biotechniques 1999; 27(5):1008-14, Kartalov E P et al.,
Biotechniques 2006; 40(1):85-90, each of which are herein
incorporated by reference in their entireties.) Commercially
available nanochips currently provide simple one step assays such
as total cholesterol, total protein or glucose assays that can be
run by combining sample and reagents, mixing and monitoring of the
reaction. Gel-free analytical approaches based on liquid
chromatography (LC) and nanoLC separations (Cutillas et al.
Proteomics, 2005; 5:101-112 and Cutillas et al., Mol Cell
Proteomics 2005; 4:1038-1051, each of which is herein incorporated
by reference in its entirety) can be used in combination with the
nanochips.
[0699] Arrays suitable for identifying a disease, condition or a
syndrome or physiological status may be included in kits. Such kits
may also include, as non-limiting examples, reagents useful for
preparing molecules for immobilization onto binding islands or
areas of an array, reagents useful for detecting binding of
exosomes or exosomal components to immobilized molecules, and
instructions for use.
[0700] Further provided herein is a rapid detection device that
facilitates the detection of a particular bio-signature of exosomes
in a biological sample. The device can integrate biological sample
preparation with polymerase chain reaction (PCR) on a chip. The
device can facilitate the detection of a particular bio-signature
of exosomes in a biological sample, and an example is provided as
described in Pipper et al., Angewandte Chemie, 47(21), p. 3900-3904
(2008), which is herein incorporated by reference in its entirety.
The bio-signatures of the exosomes can be incorporated using
micro-/nano-electrochemical system (MEMS/NEMS) sensors and oral
fluid for diagnostic applications as described in Li et al., Adv
Dent Res 18(1): 3-5 (2005), which is herein incorporated by
reference in its entirety.
[0701] As an alternative to planar arrays, assays using particles,
such as bead based assays as described herein, can be used in
combination with flow cytometry. Multiparametric assays or other
high throughput detection assays using bead coatings with cognate
ligands and reporter molecules with specific activities consistent
with high sensitivity automation can be used. In bead based assay
systems, the binding agents, such as an antibody for exosomes, can
be immobilized on addressable microspheres. Each binding agent for
each individual binding assay is coupled to a distinct type of
microsphere (i.e., microbead) and the assay reaction takes place on
the surface of the microspheres, such as depicted in FIG. 64A. A
binding agent for an exosome, such as a capture antibody is coupled
to a bead. Dyed microspheres with discrete fluorescence intensities
are loaded separately with their appropriate binding agent or
capture probes. The different bead sets carrying different binding
agents can be pooled as necessary to generate custom bead arrays.
Bead arrays are then incubated with the sample in a single reaction
vessel to perform the assay. Examples of microfluidic devices that
may be used, or adapted for use with exosomes, include but are not
limited to those described herein.
[0702] Product formation of the biomarker with their immobilized
capture molecules or binding agents can be detected with a
fluorescence based reporter system (see for example, FIG. 64A). The
biomarker can either be labeled directly by a fluorophore or
detected by a second fluorescently labeled capture biomolecule. The
signal intensities derived from captured biomarkers are measured in
a flow cytometer. The flow cytometer first identifies each
microsphere by its individual color code. For example, distinct
beads can be dyed with discrete fluorescence intensities such that
each bead with a different intensity has a different binding agent.
The beads can be labeled or dyed with at least 2 different labels
or dyes. In some embodiments, the beads are labeled with at least
3, 4, 5, 6, 7, 8, 9, or 10 different labels. The beads with more
than one label or dye can also have various ratios and combinations
of the labels or dyes. The beads can be labeled or dyed externally
or may have intrinsic fluorescence or signaling labels.
[0703] The amount of captured biomarkers on each individual bead
can be measured by the second color fluorescence specific for the
bound target. This allows multiplexed quantitation of multiple
targets from a single sample within the same experiment.
Sensitivity, reliability and accuracy are compared, or can be
improved to standard microtiter ELISA procedures. An advantage of
bead-based systems is the individual coupling of the capture
biomolecule, or binding agent for an exosome, to distinct
microspheres, which provides multiplexing. For example, as depicted
in FIG. 64B, a combination of 5 different biomarkers to be detected
(detected by antibodies to antigens such as CD63, CD9, CD81, B7H3,
and EpCam) and 20 biomarkers for which to capture the exosome
(using capture antibodies, such as antibodies to CD9, PSCA, TNFR,
CD63, B7H3, MFG-E8, EpCam, Rab, CD81, STEAP, PCSA, PSMA, and 5T4)
can result in 100 combinations to be detected. Thus, captured
exosomes can be detected using detection agents, such as
antibodies. The detection agents can be labeled directly or
indirectly, such as described above.
[0704] Multiplexing of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75 or 100 different
biomarkers may be performed. For example, an assay of a
heterogeneous population of exosomes can be performed with a
plurality of particles that are differentially labeled. There can
be at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 25, 50, 75 or 100 differentially labeled particles. The
particles may be externally labeled, such as with a tag, or they
may be intrinsically labeled. Each differentially labeled particle
can be coupled to a capture agent, such as a binding agent, for an
exosome, resulting in capture of an exosome. Biomarkers of the
captured exosomes can then be detected by a plurality of binding
agents. The binding agent can be directly labeled and thus,
detected. Alternatively, the binding agent is labeled by a
secondary agent. For example, the binding agent may be an antibody
for a biomarker on the exosome. The binding agent is linked to
biotin. A secondary agent comprises streptavidin linked to a
reporter and can be added to detect the biomarker. In some
embodiments, the captured exosomes are assayed for at least 2, 3,
4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25,
50, 75 or 100 different biomarkers. For example, as depicted in
FIG. 70, multiple detectors, i.e. detection of multiple biomarkers
of a captured exosome, can increase the signal obtained, permitted
increased sensitivity, specificity or both, and the use of smaller
amounts of samples.
[0705] ELISA based methods, so sandwich assay can also be used to
detect biomarkers on an exosome. A binding agent or capture agent
can be bound to a well, for example an antibody to an exosomal
antigen. Biomarkers on the captured exosome can be detected based
on the methods described herein.
[0706] Peptide or protein biomakers can be analyzed by mass
spectrometry or flow cytometry. Proteomic analysis of exosomes may
also be carried out on exosomes by immunocytochemical staining,
Western blotting, electrophoresis, chromatography or x-ray
crystallography in accordance with procedures well known in the
art. In other embodiments, the protein bio-signatures of exosomes
may be analyzed using 2 D differential gel electrophoresis as
described in, Chromy et al. J Proteome Res, 2004; 3:1120-1127,
which is herein incorporated by reference in its entirety, or with
liquid chromatography mass spectrometry as described in Zhang et
al. Mol Cell Proteomics, 2005; 4:144-155, which is herein
incorporated by reference in its entirety. Exosomes may be
subjected to activity-based protein profiling described for
example, in Berger et al., Am J Pharmacogenomics, 2004; 4:371-381,
which is in incorporated by reference in its entirety. In other
embodiments, exosomes may be profiled using nanospray liquid
chromatography-tandem mass spectrometry as described in Pisitkun et
al., Proc Natl Acad Sci USA, 2004; 101:13368-13373, which is herein
incorporated by reference in its entirety. In another embodiment,
the exosomes may be profiled using tandem mass spectrometry (MS)
such as liquid chromatography/MS/MS (LC-MS/MS) using for example a
LTQ and LTQ-FT ion trap mass spectrometer. Protein identification
can be determined and relative quantitation can be assessed by
comparing spectral counts as described in Smalley et al., J
Proteome Res, 2008; 7:2088-2096, which is herein incorporated by
reference in its entirety.
[0707] Protein expression of exosomes can also be identified, such
as following the isolation of cell-of-origin specific exosomes,
such exosomes can be resuspended in buffer, centrifuged at
100.times.g for example, for 3 minutes using a cytocentrifuge on
adhesive slides in preparation for immunocytochemical staining. The
cytospins can be air-dried overnight and stored at--80.degree. C.
until staining. Slides can then be fixed and blocked with
serum-free blocking reagent. The slides can then be incubated with
a specific antibody to detect the expression of a protein of
interest. In some embodiments, the exosomes are not purified,
isolated or concentrated prior to protein expression analysis.
[0708] Exosomes, such as isolated cell-of-origin specific exosomes
can be characterized by analysis of metabolite markers or
metabolites, which can also form a bio-signature for exosomes.
Various metabolite-oriented approaches have been described such as
metabolite target analyses, metabolite profiling, or metabolic
fingerprinting, see for example, Denkert et al., Molecular Cancer
2008; 7: 4598-4617, Ellis et al., Analyst 2006; 8: 875-885, Kuhn et
al., Clinical Cancer Research 2007; 24: 7401-7406, Fiehn O., Comp
Funct Genomics 2001; 2:155-168, Fancy et al., Rapid Commun Mass
Spectrom 20(15): 2271-80 (2006), Lindon et al., Pharm Res, 23(6):
1075-88 (2006), Holmes et al., Anal Chem. 2007 Apr. 1;
79(7):2629-40. Epub 2007 February 27. Erratum in: Anal Chem. 2008
Aug. 1; 80(15):6142-3, Stanley et al., Anal Biochem. 2005 Aug. 15;
343(2):195-202., Lehtimaki et al., J Biol. Chem. 2003 Nov. 14;
278(46):45915-23, each of which is herein incorporated by reference
in its entirety.
[0709] Peptides from exosomes can be analyzed by systems described
in Jain K K: Integrative Omics, Pharmacoproteomics, and Human Body
Fluids. In: Thongboonkerd V. ed., ed. Proteomics of Human Body
Fluids: Principles, Methods and Applications. Volume 1: Totowa,
N.J.: Humana Press, c2007., 2007, which is herein incorporated by
reference in its entirety. This system can generate sensitive
molecular fingerprints of proteins present in a body fluid as well
as in exosomes. Commercial applications which include the use of
chromatography/mass spectroscopy and reference libraries of all
stable metabolites in the human body, for example Paradigm
Genetic's Human Metabolome Project, may be used to determine the
metabolite bio-signature of exosomes, such as isolated
cell-of-origin specific exosomes. Other methods for analyzing a
metabolic profile can include methods and devices described in U.S.
Pat. No. 6,683,455 (Metabometrix), U.S. Patent Application
Publication Nos. 20070003965 and 20070004044 (Biocrates Life
Science), each of which is herein incorporated by reference in its
entirety. Other proteomic profiling techniques are described in
Kennedy, Toxicol Lett 120:379-384 (2001), Berven et al., Curr Pharm
Biotechnol 7(3): 147-58 (2006), Conrads et al., Expert Rev
Proteomics 2(5): 693-703, Decramer et al., World J Urol 25(5):
457-65 (2007), Decramer et al., Mol Cell Proteomics 7(10): 1850-62
(2008), Decramer et al., Contrib Nephrol, 160: 127-41 (2008),
Diamandis, J Proteome Res 5(9): 2079-82 (2006), Immler et al.,
Proteomics 6(10): 2947-58 (2006), Khan et al., J Proteome Res
5(10): 2824-38 (2006), Kumar et al., Biomarkers 11(5): 385-405
(2006), Noble et al., Breast Cancer Res Treat 104(2): 191-6 (2007),
Omenn, Dis Markers 20(3): 131-4 (2004), Powell et al., Expert Rev
Proteomics 3(1): 63-74 (2006), Rai et al., Arch Pathol Lab Med,
126(12): 1518-26 (2002), Ramstrom et al., Proteomics, 3(2): 184-90
(2003), Tammen et al., Breast Cancer Res Treat, 79(1): 83-93
(2003), Theodorescu et al., Lancet Oncol, 7(3): 230-40 (2006), or
Zurbig et al., Electrophoresis, 27(11): 2111-25 (2006).
[0710] For analysis of mRNAs, miRNAs or other small RNAs, the total
RNA can be first isolated from exosomes using any other known
methods for isolating nucleic acids such as methods described in
U.S. Patent Application Publication No. 2008132694, which is herein
incorporated by reference in its entirety. These include, but are
not limited to, kits for performing membrane based RNA
purification, which are commercially available. Generally, kits are
available for the small-scale (30 mg or less) preparation of RNA
from cells and tissues, for the medium scale (250 mg tissue)
preparation of RNA from cells and tissues, and for the large scale
(1 g maximum) preparation of RNA from cells and tissues. Other
commercially available kits for effective isolation of small
RNA-containing total RNA are available.
[0711] Alternatively, RNA can be isolated using the method
described in U.S. Pat. No. 7,267,950, which is herein incorporated
by reference in its entirety. U.S. Pat. No. 7,267,950 describes a
method of extracting RNA from biological systems (cells, cell
fragments, organelles, tissues, organs, or organisms) in which a
solution containing RNA is contacted with a substrate to which RNA
can bind and RNA is withdrawn from the substrate by applying
negative pressure. Alternatively, RNA may be isolated using the
method described in U.S. Patent Application No. 20050059024, which
is herein incorporated by reference in its entirety, which
describes the isolation of small RNA molecules. Other methods are
described in U.S. Patent Application No. 20050208510, 20050277121,
20070238118, each of which is incorporated by reference in its
entirety.
[0712] In one embodiment, mRNA expression analysis can be carried
out on mRNAs from exosomes isolated from a sample. In some
embodiments, the exosomes are cell-of-origin specific exosomes.
Expression patterns generated from these exosomes can be indicative
of a given disease state, disease stage, therapy related signature,
or physiological condition. Once the total RNA has been isolated,
cDNA can be synthesized and either qRT-PCR assays (e.g. Applied
Biosystem's Taqman.RTM. assays) for specific mRNA targets can be
performed according to manufacturer's protocol, or an expression
microarray can be performed to look at highly multiplexed sets of
expression markers in one experiment. Methods for establishing gene
expression profiles include determining the amount of RNA that is
produced by a gene that can code for a protein or peptide. This is
accomplished by quantitative reverse transcriptase PCR (qRT-PCR),
competitive RT-PCR, real time RT-PCR, differential display RT-PCR,
Northern Blot analysis or other related tests. While it is possible
to conduct these techniques using individual PCR reactions, it is
also possible to amplify complementary DNA (cDNA) or complementary
RNA (cRNA) produced from mRNA and analyze it via microarray.
[0713] The level of a miRNA product in a sample can be measured
using any technique that is suitable for detecting mRNA expression
levels in a biological sample, including but not limited to
Northern blot analysis, RT-PCR, qRT-PCR, in situ hybridization or
microarray analysis. For example, using gene specific primers and
target cDNA, qRT-PCR enables sensitive and quantitative miRNA
measurements of either a small number of target miRNAs (via
singleplex and multiplex analysis) or the platform can be adopted
to conduct high throughput measurements using 96-well or 384-well
plate formats. See for example, Ross J S et al, Oncologist. 2008
May; 13(5):477-93, which is herein incorporated by reference in its
entirety. A number of different array configurations and methods
for microarray production are known to those of skill in the art
and are described in U.S. patents such as: U.S. Pat. Nos.
5,445,934; 5,532,128; 5,556,752; 5,242,974; 5,384,261; 5,405,783;
5,412,087; 5,424,186; 5,429,807; 5,436,327; 5,472,672; 5,527,681;
5,529,756; 5,545,531; 5,554,501; 5,561,071; 5,571,639; 5,593,839;
5,599,695; 5,624,711; 5,658,734; or 5,700,637; each of which is
herein incorporated by reference in its entirety. Other methods of
profiling miRNAs are described in Taylor et al., Gynecol Oncol.
2008 July; 110(1):13-21, Gilad et al, PLoS ONE. 2008 Sep. 5;
3(9):e3148, Lee et al., Annu Rev Pathol. 2008 September 25 and
Mitchell et al, Proc Natl Acad Sci USA. 2008 Jul. 29;
105(30):10513-8, Shen R et al, BMC Genomics. 2004 Dec. 14; 5(1):94,
Mina L et al, Breast Cancer Res Treat. 2007 June; 103(2):197-208,
Zhang L et al, Proc Natl Acad Sci USA. 2008 May 13; 105(19):7004-9,
Ross J S et al, Oncologist. 2008 May; 13(5):477-93, Schetter A J et
al, JAMA. 2008 Jan. 30; 299(4):425-36, Staudt L M, N Engl J Med
2003; 348:1777-85, Mulligan G et al, Blood. 2007 Apr. 15;
109(8):3177-88. Epub 2006 Dec. 21, McLendon R et al, Nature. 2008
Oct. 23; 455(7216):1061-8, and U.S. Pat. Nos. 5,538,848, 5,723,591,
5,876,930, 6,030,787, 6,258,569, and 5,804,375, each of which is
herein incorporated by reference.
[0714] Microarray technology allows for the measurement of the
steady-state mRNA or miRNA levels of thousands of transcripts or
miRNAs simultaneously thereby presenting a powerful tool for
identifying effects such as the onset, arrest, or modulation of
uncontrolled cell proliferation. Two microarray technologies, such
as cDNA arrays and oligonucleotide arrays can be used. The product
of these analyses are typically measurements of the intensity of
the signal received from a labeled probe used to detect a cDNA
sequence from the sample that hybridizes to a nucleic acid sequence
at a known location on the microarray. Typically, the intensity of
the signal is proportional to the quantity of cDNA, and thus mRNA
or miRNA, expressed in the sample cells. A large number of such
techniques are available and useful. Methods for determining gene
expression can be found in U.S. Pat. No. 6,271,002 to Linsley, et
al.; U.S. Pat. No. 6,218,122 to Friend, et al.; U.S. Pat. No.
6,218,114 to Peck et al.; or U.S. Pat. No. 6,004,755 to Wang, et
al., each of which is herein incorporated by reference in its
entirety.
[0715] Analysis of the expression levels is conducted by comparing
such intensities. This can be performed by generating a ratio
matrix of the expression intensities of genes in a test sample
versus those in a control sample. The control sample may be used as
a reference, and different references to account for age, ethnicity
and sex may be used. Different references can be used for different
conditions or diseases, as well as different stages of diseases or
conditions, as well as for determining therapeutic efficacy.
[0716] For instance, the gene expression intensities of mRNA or
miRNAs isolated from exosomes derived from a diseased tissue can be
compared with the expression intensities generated from exosomes
isolated from normal tissue of the same type (e.g., diseased breast
tissue sample versus. normal breast tissue sample). A ratio of
these expression intensities indicates the fold-change in gene
expression between the test and control samples. Alternatively, if
exosomes are not normally present in from normal tissues (e.g.
breast) then absolute quantitation methods, as is known in the art,
can be used to define the number of miRNA molecules present without
the requirement of miRNA or mRNA isolated from exosomes derived
from normal tissue.
[0717] Gene expression profiles can also be displayed in a number
of ways. The most common method is to arrange raw fluorescence
intensities or ratio matrix into a graphical dendogram where
columns indicate test samples and rows indicate genes. The data is
arranged so genes that have similar expression profiles are
proximal to each other. The expression ratio for each gene is
visualized as a color. For example, a ratio less than one
(indicating down-regulation) may appear in the blue portion of the
spectrum while a ratio greater than one (indicating up-regulation)
may appear as a color in the red portion of the spectrum.
Commercially available computer software programs are available to
display such data.
[0718] mRNAs or miRNAs that are considered differentially expressed
can be either over expressed or under expressed in patients with a
disease relative to disease free individuals. Over and under
expression are relative terms meaning that a detectable difference
(beyond the contribution of noise in the system used to measure it)
is found in the amount of expression of the mRNAs or miRNAs
relative to some baseline. In this case, the baseline is the
measured mRNA/miRNA expression of a non-diseased individual. The
mRNA/miRNA of interest in the diseased cells can then be either
over or under expressed relative to the baseline level using the
same measurement method. Diseased, in this context, refers to an
alteration of the state of a body that interrupts or disturbs, or
has the potential to disturb, proper performance of bodily
functions as occurs with the uncontrolled proliferation of cells.
Someone is diagnosed with a disease when some aspect of that
person's genotype or phenotype is consistent with the presence of
the disease. However, the act of conducting a diagnosis or
prognosis includes the determination of disease/status issues such
as determining the likelihood of relapse or metastasis and therapy
monitoring. In therapy monitoring, clinical judgments are made
regarding the effect of a given course of therapy by comparing the
expression of genes over time to determine whether the mRNA/miRNA
expression profiles have changed or are changing to patterns more
consistent with normal tissue.
[0719] Levels of over and under expression are distinguished based
on fold changes of the intensity measurements of hybridized
microarray probes. A 2.times. difference is preferred for making
such distinctions or a p-value less than 0.05. That is, before an
mRNA/miRNA is said to be differentially expressed in
diseased/relapsing versus normal/non-relapsing cells, the diseased
cell is found to yield at least 2 times more, or 2 times less
intensity than the normal cells. The greater the fold difference,
the more preferred is use of the gene as a diagnostic or prognostic
tool. mRNA/miRNAs selected for the expression profiles of the
instant invention have expression levels that result in the
generation of a signal that is distinguishable from those of the
normal or non-modulated genes by an amount that exceeds background
using clinical laboratory instrumentation.
[0720] Statistical values can be used to confidently distinguish
modulated from non-modulated mRNA/miRNA and noise. Statistical
tests find the mRNA/miRNA most significantly different between
diverse groups of samples. The Student's t-test is an example of a
robust statistical test that can be used to find significant
differences between two groups. The lower the p-value, the more
compelling the evidence that the gene is showing a difference
between the different groups. Nevertheless, since microarrays
measure more than one mRNA/miRNA at a time, tens of thousands of
statistical tests may be performed at one time. Because of this,
one is unlikely to see small p-values just by chance and
adjustments for this using a Sidak correction as well as a
randomization/permutation experiment can be made. A p-value less
than 0.05 by the t-test is evidence that the gene is significantly
different. More compelling evidence is a p-value less then 0.05
after the Sidak correction is factored in. For a large number of
samples in each group, a p-value less than 0.05 after the
randomization/permutation test is the most compelling evidence of a
significant difference.
[0721] In one embodiment, a method of generating a posterior
probability score to enable diagnostic, prognostic,
therapy-related, or physiological state specific bio-signature
scores can be arrived at by obtaining mRNA or miRNA (biomarker)
expression data from a statistically significant number of patient
exosomes, such as cell-of-origin specific exosomes; applying linear
discrimination analysis to the data to obtain selected biomarkers;
and applying weighted expression levels to the selected biomarkers
with discriminate function factor to obtain a prediction model that
can be applied as a posterior probability score. Other analytical
tools can also be used to answer the same question such as,
logistic regression and neural network approaches.
[0722] For instance, the following can be used for linear
discriminant analysis:
[0723] where,
I(p.sub.si.sub.d)=The log base 2 intensity of the probe set
enclosed in parenthesis. d(cp)=The discriminant function for the
disease positive class d(C.sub.N)=The discriminant function for the
disease negative class
P(.sub.CP)=The posterior p-value for the disease positive class
P(.sub.CN)=The posterior p-value for the disease negative class
[0724] Numerous other well-known methods of pattern recognition are
available. The following references provide some examples: Weighted
Voting: Golub et al. (1999); Support Vector Machines: Su et al.
(2001); and Ramaswamy et al. (2001); K-nearest Neighbors: Ramaswamy
(2001); and Correlation Coefficients: van 't Veer et al. (2002),
all of which are herein incorporated by reference in their
entireties.
[0725] Bio-signature portfolios, further described below, can be
established such that the combination of biomarkers in the
portfolio exhibit improved sensitivity and specificity relative to
individual biomarkers or randomly selected combinations of
biomarkers. In one embodiment, the sensitivity of the bio-signature
portfolio can be reflected in the fold differences, for example,
exhibited by a transcript's expression in the diseased state
relative to the normal state. Specificity can be reflected in
statistical measurements of the correlation of the signaling of
transcript expression with the condition of interest. For example,
standard deviation can be a used as such a measurement. In
considering a group of biomarkers for inclusion in a bio-signature
portfolio, a small standard deviation in expression measurements
correlates with greater specificity. Other measurements of
variation such as correlation coefficients can also be used in this
capacity.
[0726] Another parameter that can be used to select mRNA/miRNA that
generate a signal that is greater than that of the non-modulated
mRNA/miRNA or noise is the use of a measurement of absolute signal
difference. The signal generated by the modulated mRNA/miRNA
expression is at least 20% different than those of the normal or
non-modulated gene (on an absolute basis). It is even more
preferred that such mRNA/miRNA produce expression patterns that are
at least 30% different than those of normal or non-modulated
mRNA/miRNA.
[0727] MiRNA can also be detected and measured by amplification
from a biological sample and measured using methods described in
U.S. Pat. No. 7,250,496, U.S. Application Publication Nos.
20070292878, 20070042380 or 20050222399 and references cited
therein, each of which is herein incorporated by reference in its
entirety.
[0728] Peptide nucleic acids (PNAs) which are a new class of
synthetic nucleic acid analogs in which the phosphate-sugar
polynucleotide backbone is replaced by a flexible pseudo-peptide
polymer may be utilized in analysis of bio-signatures of exosomes.
PNAs are capable of hybridizing with high affinity and specificity
to complementary RNA and DNA sequences and are highly resistant to
degradation by nucleases and proteinases. Peptide nucleic acids
(PNAs) are an attractive new class of probes with applications in
cytogenetics for the rapid in situ identification of human
chromosomes and the detection of copy number variation (CNV).
Multicolor peptide nucleic acid-fluorescence in situ hybridization
(PNA-FISH) protocols have been described for the identification of
several human CNV-related disorders and infectious diseases. PNAs
can also be utilized as molecular diagnostic tools to
non-invasively measure oncogene mRNAs with tumor targeted
radionuclide-PNA-peptide chimeras. Methods of using PNAs are
described further in Pellestor F et al., Curr Pharm Des. 2008;
14(24):2439-44, Tian X et al, Ann N Y Acad. Sci. 2005 November,
1059:106-44, Paulasova P and Pellestor F, Annales de Genetique, 47
(2004) 349-358, Stender H. Expert Rev Mol. Diagn. 2003 September;
3(5):649-55. Review, Vigneault et al., Nature Methods, 5(9),
777.+-.779 (2008), each reference is herein incorporated by
reference in its entirety. These methods can be used to screen the
genetic materials isolated from exosomes. When applying these
techniques to cell-of-origin specific exosomes they can be used to
identify a given molecular signal that directly pertains to the
cell of origin.
[0729] In addition, mutational analysis may be carried out for
mRNAs and DNA that are identified from the exosomes. For mutational
analysis of targets or biomarkers that are of RNA origin, the RNA
(mRNA, miRNA or other) can be reverse transcribed into cDNA and
subsequently sequenced or assayed for known SNPs (by Taqman SNP
assays, for example), or single nucleotide mutations, as well as
using sequencing to look for insertions or deletions to determine
mutations present in the cell-of-origin. Muliplexed ligation
dependent probe amplification (MLPA) could alternatively be used
for the purpose of identifying CNV in small and specific areas of
interest. For example, once the total RNA has been obtained from
isolated colon cancer-specific exosomes, cDNA can be synthesized
and primers specific for exons 2 and 3 of the KRAS gene can be used
to amplify these two exons containing codons 12, 13 and 61 of the
KRAS gene. The same primers used for PCR amplification can be used
for Big Dye Terminator sequence analysis on the ABI 3730 to
identify mutations in exons 2 and 3 of KRAS. Mutations in these
codons are known to confer resistance to drugs such as Cetuximab
and Panitumimab. Methods of conducting mutational analysis are
described in Maheswaran S et al., Jul. 2, 2008
(10.1056/NEJMoa0800668) and Orita, M et al, PNAS 1989, (86):
2766-70, each of which is herein incorporated by reference in its
entirety. Other methods of conducting mutational analysis can
include miRNA sequencing. Applications for identifying and
profiling miRNAs can be done by cloning techniques and the use of
capillary DNA sequencing or "next-generation" sequencing
technologies. The new sequencing technologies currently available
allow the identification of low-abundance miRNAs or those
exhibiting modest expression differences between samples, which may
not be detected by hybridization-based methods. Such new sequencing
technologies include the massively parallel signature sequencing
(MPSS) methodology described in Nakano et al. 2006, Nucleic Acids
Res. 2006; 34:D731D735. doi: 10.1093/nar/gkj077, the Roche/454
platform described in Margulies et al. 2005, Nature. 2005; 437:376
380 or the Illumina sequencing platform described in Berezikov et
al. Nat. Genet. 2006b; 38:1375-1377, each of which is incorporated
by reference in its entirety.
[0730] Additional methods to determine bio-signatures include
assaying biomarkers by allele-specific PCR which include specific
primers to amplify and discriminate between two alleles of a gene
simultaneously, single-strand conformation polymorphism (SSCP)
which involves the electrophoretic separation of single-stranded
nucleic acids based on subtle differences in sequence and DNA and
RNA aptamers. DNA and RNA aptamers are short oligonucleotide
sequences that can be selected from random pools based on their
ability to bind a particular molecule with high affinity. Methods
of using aptamers are described in Ulrich H et al, Comb Chem High
Throughput Screen. 2006 September; 9(8):619-32, Ferreira C S et al,
Anal Bioanal Chem. 2008 February; 390(4):1039-50, Ferreira C S et
al, Tumour Biol. 2006; 27(6):289-301, each of which is herein
incorporated by reference in its entirety.
[0731] Exosome biomarkers can also be detected using fluorescence
in situ hybridization (FISH). Methods of using FISH to detect and
localize specific DNA sequences, localize specific mRNAs within
tissue samples or identify chromosomal abnormalities are described
in Shaffer D R et al, Clin Cancer Res. 2007 Apr. 1; 13(7):2023-9,
Cappuzo F et al, Journal of Thoracic Oncology, Volume 2, Number 5,
May 2007, Moroni M et al., Lancet Oncol. 2005 May; 6(5):279-86,
each of which is herein incorporated by reference in its
entirety.
Bio-Signature: Binding Agents
[0732] Bio-signatures of exosomes can comprise binding agents for
exosomes. The binding agent can be DNA, RNA, aptamers, monoclonal
antibodies, polyclonal antibodies, Fabs, Fab', single chain
antibodies, synthetic antibodies, aptamers (DNA/RNA), peptoids,
zDNA, peptide nucleic acids (PNAs), locked nucleic acids (LNAs),
lectins, synthetic or naturally occurring chemical compounds
(including but not limited to drugs, labeling reagents).
[0733] Binding agents can used to isolate exosomes by binding to
exosomal components, as described above. The binding agents can be
used to detect the exosomes, such as for detecting cell-of-origin
specific exosomes. A binding agent or multiple binding agents can
themselves form a binding agent profile that provides a
bio-signature for an exosome. One or more binding agents can be
selected from FIG. 2. For example, if an exosome population is
detected or isolated using two, three or four binding agents in a
differential detection or isolation of an exosome from a
heterogeneous population of exosomes, the particular binding agent
profile for the exosome population provides a bio-signature for the
particular exosome population.
[0734] As an illustrative example, an exosome for analysis for lung
cancer can be detected with one or more binding agents including,
but not limited to, SCLC specific aptamer HCA 12, SCLC specific
aptamer HCC03, SCLC specific aptamer HCH07, SCLC specific aptamer
HCH01, A-p50 aptamer (NF-KB), Cetuximab, Panitumumab, Bevacizumab,
L19 Ab, F16 Ab, anti-CD45 (anti-ICAM-1, aka UV3), or L2G7 Ab
(anti-HGF), or any combination thereof.
[0735] An exosome for analysis for colon cancer can be detected
with one or more binding agents including, but not limited to,
angiopoietin 2 specific aptamer, beta-catenin aptamer, TCF1
aptamer, anti-Derlin1 ab, anti-RAGE, mAbgb3.1, Galectin-3,
Cetuximab, Panitumumab, Matuzumab, Bevacizumab, or Mac-2, or any
combination thereof.
[0736] An exosome for analysis for adenoma versus colorectal cancer
(CRC) can be detected with one or more binding agents including,
but not limited to, Complement C3, histidine-rich glycoprotein,
kininogen-1, or Galectin-3, or any combination thereof.
[0737] An exosome for analysis for adenoma with low grade
hyperplasia versus adenoma with high grade hyperplasia can be
detected with a binding agent such as, but not limited to,
Galectin-3 or any combination of binding agents specific for this
comparison.
[0738] An exosome for analysis for CRC versus normal state can be
detected with one or more binding agents including, but not limited
to, anti-ODC mAb, anti-CEA mAb, or Mac-2, or any combination
thereof.
[0739] An exosome for analysis for prostate cancer can be detected
with one or more binding agents including, but not limited to, PSA,
PSMA, TMPRSS2, mAB 5D4, XPSM-A9, XPSM-A 10, Galectin-3, E-selectin,
Galectin-1, or E4 (IgG2a kappa), or any combination thereof.
[0740] An exosome for analysis for melanoma can be detected with
one or more binding agents including, but not limited to,
Tremelimumab (anti-CTLA4), Ipilimumumab (anti-CTLA4), CTLA-4
aptamers, STAT-3 peptide aptamers, Galectin-1, Galectin-3, or PNA,
or any combination thereof.
[0741] An exosome for analysis for pancreatic cancer can be
detected with one or more binding agents including, but not limited
to, H38-15 (anti-HGF) aptamer, H38-21(anti-HGF) aptamer, Matuzumab,
Cetuximanb, or Bevacizumab, or any combination thereof.
[0742] An exosome for analysis for brain cancer can be detected
with one or more binding agents including, but not limited to,
aptamer III.1 (pigpen) and/or TTA1 (Tenascin-C) aptamer, or any
combination thereof.
[0743] An exosome for analysis for psoriasis can be detected with
one or more binding agents including, but not limited to,
E-selectin, ICAM-1, VLA-4, VCAM-1, alphaEbeta7, or any combination
thereof.
[0744] An exosome for analysis for cardiovascular disease (CVD) can
be detected with one or more binding agents including, but not
limited to, RB007 (factor 1.times.A aptamer), ARC1779 (anti VWF)
aptamer, or LOX1, or any combination thereof.
[0745] An exosome for analysis for hematological malignancies can
be detected with one or more binding agents including, but not
limited to, anti-CD20 and/or anti-CD52, or any combination
thereof.
[0746] An exosome for analysis for B-cell chronic lymphocytic
leukemias can be detected with one or more binding agents
including, but not limited to, Rituximab, Alemtuzumab, Apt48
(BCL6), R0-60, or D-R15-8, or any combination thereof.
[0747] An exosome for analysis for B-cell lymphoma can be detected
with one or more binding agents including, but not limited to,
Ibritumomab, Tositumomab, Anti-CD20 Antibodies, Alemtuzumab,
Galiximab, Anti-CD40 Antibodies, Epratuzumab, Lumiliximab, Hu1D10,
Galectin-3, or Apt48, or any combination thereof.
[0748] An exosome for analysis for Burkitt's lymphoma can be
detected with one or more binding agents including, but not limited
to, TD05 aptamer, IgM mAB (38-13), or any combination thereof.
[0749] An exosome for analysis for cervical cancer can be detected
with one or more binding agents including, but not limited to,
Galectin-9 and/or HPVE7 aptamer, or any combination thereof.
[0750] An exosome for analysis for endometrial cancer can be
detected with one or more binding agents including, but not limited
to, Galectin-1 or any combinations of binding agents specific for
endometrial cancer.
[0751] An exosome for analysis for head and neck cancer can be
detected with one or more binding agents including, but not limited
to, (111)In-cMAb U36, anti-LOXL4, U36, BIWA-1, BIWA-2, BIWA-4, or
BIWA-8, or any combination thereof.
[0752] An exosome for analysis for IBD can be detected with one or
more binding agents including, but not limited to, ACCA
(anti-glycan Ab), ALCA(anti-glycan Ab), or AMCA (anti-glycan Ab),
or any combination thereof.
[0753] An exosome for analysis for diabetes can be detected with
one or more binding agents including, but not limited to, RBP4
aptamer or any combination of binding agents specific for
diabetes.
[0754] An exosome for analysis for fibromyalgia can be detected
with one or more binding agents including, but not limited to,
L-selectin or any combination of binding agents specific for
fibromyalgia.
[0755] An exosome for analysis for multiple sclerosis (MS) can be
detected with one or more binding agents including, but not limited
to, Natalizumab (Tysabri) or any combination of binding agents
specific for MS.
[0756] In addition, An exosome for analysis for rheumatic disease
can be detected with one or more binding agents including, but not
limited to, Rituximab (anti-CD20 Ab) and/or Keliximab (anti-CD4
Ab), or any combination of binding agents specific for rheumatic
disease.
[0757] An exosome for analysis for Alzheimer disease can be
detected with one or more binding agents including, but not limited
to, TH14-BACE1 aptapers, S10-BACE1 aptapers, anti-Abeta,
Bapineuzumab (AAB-001)-Elan, LY2062430 (anti-amyloid beta Ab)-Eli
Lilly, or BACE1-Anti sense, or any combination thereof.
[0758] An exosome for analysis for Prion specific diseases can be
detected with one or more binding agents including, but not limited
to, rhuPrP(c) aptamer, DP7 aptamer, Thioaptamer 97, SAF-93 aptamer,
15B3 (anti-PrPSc Ab), monoclonal anti PrPSc antibody P1:1, 1.5D7,
1.6F4 Abs, mab 14D3, mab 4F2, mab 8G8, or mab 12F10, or any
combination thereof.
[0759] An exosome for analysis for sepsis can be detected with one
or more binding agents including, but not limited to, HA-1A mAb,
E-5 mAb, TNF-alpha MAb, Afelimomab, or E-selectin, or any
combination thereof.
[0760] An exosome for analysis for schizophrenia can be detected
with one or more binding agents including, but not limited to,
L-selectin and/or N-CAM, or any combination of binding agents
specific for schizophrenia.
[0761] An exosome for analysis for depression can be detected with
one or more binding agents including, but not limited to, GPIb or
any combination of binding agents specific for depression.
[0762] An exosome for analysis for GIST can be detected with one or
more binding agents including, but not limited to, ANTI-DOG1 Ab or
any combination of binding agents specific for GIST.
[0763] An exosome for analysis for esophageal cancer can be
detected with one or more binding agents including, but not limited
to, CaSR binding agent or any combination of binding agents
specific for esophageal cancer.
[0764] An exosome for analysis for gastric cancer can be detected
with one or more binding agents including, but not limited to,
Calpain nCL-2 binding agent and/or drebrin binding agent, or any
combination of binding agents specific for gastric cancer.
[0765] An exosome for analysis for COPD can be detected with one or
more binding agents including, but not limited to, CXCR3 binding
agent, CCR5 binding agent, or CXCR6 binding agent, or any
combination of binding agents specific for COPD.
[0766] An exosome for analysis for asthma can be detected with one
or more binding agents including, but not limited to, VIP binding
agent, PACAP binding agent, CGRP binding agent, NT3 binding agent,
YKL-40 binding agent, S-nitrosothiols, SCCA2 binding agent, PAI
binding agent, amphiregulin binding agent, or Periostin binding
agent, or any combination of binding agents specific for
asthma.
[0767] An exosome for analysis for vulnerable plaque can be
detected with one or more binding agents including, but not limited
to, Gd-DTPA-g-mimRGD (Alpha v Beta 3 integrin binding peptide), or
MMP-9 binding agent, or any combination of binding agents specific
for vulnerable plaque.
[0768] An exosome for analysis for ovarian cancer can be detected
with one or more binding agents including, but not limited to, (90)
Y-muHMFG1 binding agent and/or OC125 (anti-CA125 antibody), or any
combination of binding agents specific for ovarian cancer.
[0769] The binding agent can be for a general exosome marker, or
"housekeeping protein" or antigen, such as CD9, CD63, or CD81. For
example, the binding agent can be an antibody for CD9, CD63, or
CD81. The binding agent can also be for other exosomal proteins,
such as for prostate specific exosomes, or cancer specific
exosomes, such as PCSA, PSMA, EpCam, B7H3, or STEAP. For example,
the binding agent can be an antibody for PCSA, PSMA, EpCam, B7H3,
or STEAP.
[0770] Furthermore, additional cellular binding partners or binding
agents may be identified by any conventional methods known in the
art, or as described herein, and may additionally be used as a
diagnostic, prognostic or therapy-related marker.
Bio-Signatures: Prostate Cancer, Colon Cancer and Ovarian
Cancer
[0771] Prostate Cancer
[0772] An exosome bio-signature can be used to characterize
prostate cancer. As described above, a bio-signature for prostate
cancer can comprise a binding agent associated with prostate cancer
(for example, as shown in FIG. 2), and one or more additional
biomarkers, such as shown in FIG. 19. For example, a bio-signature
for prostate cancer can comprise a binding agent to PSA, PSMA,
TMPRSS2, mAB 5D4, XPSM-A9, XPSM-A10, Galectin-3, E-selectin,
Galectin-1, E4 (IgG2a kappa), or any combination thereof, with one
or more additional biomarkers, such as one or more miRNA, one or
more DNA, one or more additional peptide, protein, or antigen
associated with prostate cancer, such as, but not limited to, those
shown in FIG. 19.
[0773] A bio-signature for prostate cancer can comprise an antigen
associated with prostate cancer (for example, as shown in FIG. 1),
and one or more additional biomarkers, such as shown in FIG. 19. A
bio-signature for prostate cancer can comprise one or more antigens
associated with prostate cancer, such as, but not limited to, KIA1,
intact fibronectin, PSA, TMPRSS2, FASLG, TNFSF10, PSMA, NGEP,
IL-7R1, CSCR4, CysLT1R, TRPM8, Kv1.3, TRPV6, TRPM8, PSGR, MISIIR,
or any combination thereof. The bio-signature for prostate cancer
can comprise one or more of the aforementioned antigens and one or
more additional biomarkers, such as, but not limited to miRNA,
mRNA, DNA, or any combination thereof.
[0774] A bio-signature for prostate cancer can also comprise one or
more antigens associated with prostate cancer, such as, but not
limited to, KIA1, intact fibronectin, PSA, TMPRSS2, FASLG, TNFSF10,
PSMA, NGEP, IL-7R1, CSCR4, CysLT1R, TRPM8, Kv1.3, TRPV6, TRPM8,
PSGR, MISIIR, or any combination thereof, and one or more miRNA
biomarkers, such as, but not limited to, miR-202, miR-210, miR-296,
miR-320, miR-370, miR-373, miR-498, miR-503, miR-184, miR-198,
miR-302c, miR-345, miR-491, miR-513, miR-32, miR-182, miR-31,
miR-26a-1/2, miR-200c, miR-375, miR-196a-1/2, miR-370, miR-425,
miR-425, miR-194-1/2, miR-181a-1/2, miR-34b, let-71, miR-188,
miR-25, miR-106b, miR-449, miR-99b, miR-93, miR-92-1/2, miR-125a,
miR-141, let-7a, let-7b, let-7c, let-7d, let-7g, miR-16, miR-23a,
miR-23b, miR-26a, miR-92, miR-99a, miR-103, miR-125a, miR-125b,
miR-143, miR-145, miR-195, miR-199, miR-221, miR-222, miR-497,
let-7f, miR-19b, miR-22, miR-26b, miR-27a, miR-27b, miR-29a,
miR-29b, miR-30.sub.--5p, miR-30c, miR-100, miR-141, miR-148a,
miR-205, miR-520h, miR-494, miR-490, miR-133a-1, miR-1-2,
miR-218-2, miR-220, miR-128a, miR-221, miR-499, miR-329, miR-340,
miR-345, miR-410, miR-126, miR-205, miR-7-1/2, miR-145, miR-34a,
miR-487, or let-7b, or any combination thereof.
[0775] Furthermore, the miRNA for a prostate cancer bio-signature
can be a miRNA that interacts with PFKFB3, RHAMM (HMMR), cDNA
FLJ42103, ASPM, CENPF, NCAPG, Androgen Receptor, EGFR, HSP90,
SPARC, DNMT3B, GART, MGMT, SSTR3, TOP2B, or any combination
thereof, such as those described herein and depicted in FIG. 60.
The miRNA can also be miR-9, miR-629, miR-141, miR-671-3p, miR-491,
miR-182, miR-125a-3p, miR-324-5p, miR-148B, miR-222, or any
combination thereof.
[0776] The bio-signature for prostate cancer can comprise one or
more antigens associated with prostate cancer, such as, but not
limited to, KIA1, intact fibronectin, PSA, TMPRSS2, FASLG, TNFSF10,
PSMA, NGEP, IL-7R1, CSCR4, CysLT1R, TRPM8, Kv1.3, TRPV6, TRPM8,
PSGR, MISIIR, or any combination thereof, and one or more
additional biomarkers such as, but not limited to, the
aforementioned miRNAs, mRNAs (such as, but not limited to, AR or
PCA3), snoRNA (such as, but not limited to, U50) or any combination
thereof.
[0777] The bio-signature can also comprise one or more gene
fusions, such as ACSL3-ETV 1, C15ORF21-ETV1, FLJ35294-ETV1,
HERV-ETV 1, TMPRSS2-ERG, TMPRSS2-ETV 1/4/5, TMPRSS2-ETV4/5,
SLC5A3-ERG, SLC5A3-ETV1, SLC5A3-ETV5 or KLK2-ETV4.
[0778] An exosome can be isolated and assayed for one or more miRNA
and one or more antigens associated with prostate cancer to provide
a diagnostic, prognostic or theranostic profile, such as the stage
of the cancer, the efficacy of the cancer, or other characteristics
of the cancer. Alternatively, the exosome can be directly assayed
from a sample, such that the exosomes are not purified or
concentrated prior to assaying for one or more miRNA or antigens
associated with prostate cancer.
[0779] As depicted in FIG. 68, a prostate cancer bio-signature can
comprise assaying EpCam, CD63, CD81, CD9, or any combination
thereof, of an exosome. The prostate cancer bio-signature can
comprise detection of EpCam, CD9, CD63, CD81, PCSA or any
combination thereof. For example, the prostate cancer bio-signature
can comprise EpCam, CD9, CD63 and CD81 or PCSA, CD9, CD63 and CD81
(see for example, FIG. 70A). The prostate cancer bio-signature can
also comprise PCSA, PSMA, B7H3, or any combination thereof (see for
example, FIG. 70B).
[0780] Furthermore, assessing a plurality of biomarkers can provide
increased sensitivity, specificity, or signal intensity, as
compared to assessing less than a plurality of biomarkers. For
example, assessing PSMA and B7H3 can provide increased sensitivity
in detection as compared to assessing PSMA or B7H3 alone. Assessing
CD9 and CD63 can provide increased sensitivity in detection as
compared to assessing CD or CD63 alone.
[0781] Prostate cancer can also be characterized based on meeting
at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 criteria. For example, a
number of different criteria can be used: 1) if the amount of
exosomes in a sample from a subject is higher than a reference
value; 2) if the amount of prostate cell derived exosomes is higher
than a reference value; and 3) if the amount of exosomes with one
or more cancer specific biomarkers is higher than a reference
value, the subject is diagnosed with prostate cancer. The method
can further include a quality control measure, such that the
subject is diagnosed with prostate cancer if the determination of
the other criteria
[0782] The prostate cancer can be characterizing using one or more
processes disclosed herein with at least 60, 61, 62, 63, 64, 65,
66, 67, 68, 69, or 70% sensitivity. The prostate cancer can be
characterized with at least 80, 81, 82, 83, 84, 85, 86, or 87%
sensitivity. For example, the prostate cancer can be characterized
with at least 87.1, 87.2, 87.3, 87.4, 87.5, 87.6, 87.7, 87.8, 87.9,
88.0, or 89% sensitivity, such as with at least 90% sensitivity,
such as at least 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100%
sensitivity.
[0783] The prostate cancer of a subject can also be characterized
with at least 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82,
83, 84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, or 97%
specificity, such as with at least 97.1, 97.2, 97.3, 97.4, 97.5,
97.6, 97.7, 97.8, 97.8, 97.9, 98.0, 98.1, 98.2, 98.3, 98.4, 98.5,
98.6, 98.7, 98.8, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6,
99.7, 99.8, 99.9 or 100% specificity.
[0784] The prostate cancer can also be characterized with at least
70% sensitivity and at least 80, 90, 95, 99, or 100% specificity;
at least 80% sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity; at least 85% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; at least 86% sensitivity and at least 80,
85, 90, 95, 99, or 100% specificity; at least 87% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; at least 88%
sensitivity and at least 80, 85, 90, 95, 99, or 100% specificity;
at least 89% sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity; at least 90% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; at least 95% sensitivity and at least 80,
85, 90, 95, 99, or 100% specificity; at least 99% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; or at least 100%
sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity.
[0785] Furthermore, the confidence level for determining the
specificity, sensitivity, or both, may be with at least 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99% confidence.
[0786] Colon Cancer
[0787] A colon cancer bio-signature can comprise any one or more
antigens for colon cancer as listed in FIG. 1, any one or more
binding agents associated with isolating an exosome for
characterizing colon cancer (for example, as shown in FIG. 2), any
one or more additional biomarkers, such as shown in FIG. 6.
[0788] The bio-signature can comprise one or more miRNA selected
from the group consisting of miR-24-1, miR-29b-2, miR-20a, miR-10a,
miR-32, miR-203, miR-106a, miR-17-5p, miR-30c, miR-223, miR-126,
miR-128b, miR-21, miR-24-2, miR-99b, miR-155, miR-213, miR-150,
miR-107, miR-191, miR-221, miR-20a, miR-510, miR-92, miR-513,
miR-19a, miR-21, miR-20, miR-183, miR-96, miR-135b, miR-31, miR-21,
miR-92, miR-222, miR-181b, miR-210, miR-20a, miR-106a, miR-93,
miR-335, miR-338, miR-133b, miR-346, miR-106b, miR-153a, miR-219,
miR-34a, miR-99b, miR-185, miR-223, miR-211, miR-135a, miR-127,
miR-203, miR-212, miR-95, or miR-17-5p, or any combination thereof.
The bio-signature can also comprise one or more underexpressed miRs
such as miR-143, miR-145, miR-143, miR-126, miR-34b, miR-34c,
let-7, miR-9-3, miR-34a, miR-145, miR-455, miR-484, miR-101,
miR-145, miR-133b, miR-129, miR-124a, miR-30-3p, miR-328, miR-106a,
miR-17-5p, miR-342, miR-192, miR-1, miR-34b, miR-215, miR-192,
miR-301, miR-324-5p, miR-30a-3p, miR-34c, miR-331, and
miR-148b.
[0789] The bio-signature can comprise assessing one or more genes,
such as EFNB1, ERCC1, HER2, VEGF, and EGFR. A biomarker mutation
for colon cancer that can be assessed in an exosome can also
include one or more mutations of EGFR, KRAS, VEGFA, B-Raf, APC, or
p53. The bio-signature can also comprise one or more proteins,
ligands, or peptides that can be assessed of an exosome such as
AFRs, Rabs, ADAM10, CD44, NG2, ephrin-B1, MIF, b-catenin, Junction,
plakoglobin, glalectin-4, RACK1, tetrspanin-8, FasL, TRAIL, A33,
CEA, EGFR, dipeptidase 1, hsc-70, tetraspanins, ESCRT, TS, PTEN, or
TOPO1
[0790] An exosome can be isolated and assayed for to provide a
diagnostic, prognostic or theranostic profile, such as the stage of
the cancer, the efficacy of the cancer, or other characteristics of
the cancer. Alternatively, the exosome can be directly assayed from
a sample, such that the exosomes are not purified or concentrated
prior to assaying for a bio-signature associated with colon
cancer.
[0791] As depicted in FIG. 69, a colon cancer signature can
comprise detection of EpCam, CD63, CD81, CD9, CD66, or any
combination thereof, of an exosome. Furthermore, a colon
cancer-bio-signature for various stages of cancer can comprise
CD63, CD9, EpCam, or any combination thereof (see for example,
FIGS. 71 and 72). For example, the bio-signature can comprise CD9
and EpCam.
[0792] The colon cancer can be characterizing using one or more
processes disclosed herein with at least 60, 61, 62, 63, 64, 65,
66, 67, 68, 69, or 70% sensitivity. The colon cancer can be
characterized with at least 80, 81, 82, 83, 84, 85, 86, or 87%
sensitivity. For example, the colon cancer can be characterized
with at least 87.1, 87.2, 87.3, 87.4, 87.5, 87.6, 87.7, 87.8, 87.9,
88.0, or 89% sensitivity, such as with at least 90% sensitivity,
such as at least 91, 92, 93, 94, 95, 96, 97, 98, 99 or 100%
sensitivity.
[0793] The colon cancer of a subject can also be characterized with
at least 70, 71, 72, 73, 74, 75, 76, 77, 78, 79, 80, 81, 82, 83,
84, 85, 86, 87, 88, 89, 90, 91, 92, 93, 94, 95, 96, or 97%
specificity, such as with at least 97.1, 97.2, 97.3, 97.4, 97.5,
97.6, 97.7, 97.8, 97.8, 97.9, 98.0, 98.1, 98.2, 98.3, 98.4, 98.5,
98.6, 98.7, 98.8, 98.9, 99.0, 99.1, 99.2, 99.3, 99.4, 99.5, 99.6,
99.7, 99.8, 99.9 or 100% specificity.
[0794] The colon cancer can also be characterized with at least 70%
sensitivity and at least 80, 90, 95, 99, or 100%) specificity; at
least 80% sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity; at least 85% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; at least 86% sensitivity and at least 80,
85, 90, 95, 99, or 100% specificity; at least 87% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; at least 88%
sensitivity and at least 80, 85, 90, 95, 99, or 100% specificity;
at least 89% sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity; at least 90% sensitivity and at least 80, 85, 90, 95,
99, or 100% specificity; at least 95% sensitivity and at least 80,
85, 90, 95, 99, or 100% specificity; at least 99% sensitivity and
at least 80, 85, 90, 95, 99, or 100% specificity; or at least 100%
sensitivity and at least 80, 85, 90, 95, 99, or 100%
specificity.
[0795] Furthermore, the confidence level for determining the
specificity, sensitivity, or both, may be with at least 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99% confidence.
[0796] Ovarian Cancer
[0797] A bio-signature for characterizing ovarian cancer can
comprise an antigen associated with ovarian cancer (for example, as
shown in FIG. 1), and one or more additional biomarkers, such as
shown in FIG. 4.
[0798] In one embodiment, a bio-signature for ovarian cancer can
comprise one or more antigens associated with ovarian cancer, such
as, but not limited to, CD24, CA125, VEGF1, VEGFR2, HER2, MISIIR,
or any combination thereof. The bio-signature for ovarian cancer
can comprise one or more of the aforementioned antigens and one or
more additional biomarker, such as, but not limited to miRNA, mRNA,
DNA, or any combination thereof. The bio-signature for ovarian
cancer can comprise one or more antigens associated with ovarian
cancer, such as, but not limited to, CD24, CA125, VEGF I, VEGFR2,
HER2, MISIIR; or any combination thereof, with one or more miRNA
biomarkers, such as, but not limited to, miR-200a, miR-141,
miR-200c, miR-200b, miR-21, miR-141, miR-200a, miR-200b, miR-200c,
miR-203, miR-205, miR-214, miR-215, miR-199a, miR-140, miR-145,
miR-125b-1, or any combination thereof.
[0799] A bio-signature for ovarian cancer can comprise one or more
antigens associated with ovarian cancer, such as, but not limited
to, CD24, CA125, VEGF1, VEGFR2, HER2, MISIIR, or any combination
thereof, with one or more miRNA biomarkers (such as the
aforementioned miRNA), mRNAs (such as, but not limited to, ERCC1,
ER, TOPO1, TOP2A, AR, PTEN, HER2/neu, EGFR), mutations (including,
but not limited to, those relating to KRAS and/or B-Raf) or any
combination thereof.
[0800] An exosome can be isolated and assayed for one or more miRNA
and one or more antigens associated with ovarian cancer to provide
a diagnostic, prognostic or theranostic profile. Alternatively, the
exosome can be directly assayed from a sample, such that the
exosomes are not purified or concentrated prior to assaying for one
or more miRNA or antigens associated with ovarian cancer.
Bio-Signatures: Assessing Organ Transplant Rejection and Autoimmune
Conditions
[0801] An exosome can also be used for determining phenotypes such
as organ distress and/or organ transplant rejection. As used herein
organ transplant includes partial organ or tissue transplant. The
presence, absence or levels of one or more biomarkers present in
exosomes is assessed to monitor organ rejection or success. The
level, or amount, of exosomes in the sample can also be used to
assess organ rejection or success. The assessment can be determined
with at least 80, 81, 82, 83, 84, 85, 86, 87, 88, 89, 90, 91, 92,
93, 94, 95, 96, 97, 98, or 99% specificity, sensitivity, or both.
For example, the assessment can be determined with at least 97.5,
97.6, 97.7, 97.8, 97.8, 97.9, 98.0, 98.1, 98.2, 98.3, 98.4, 98.5,
98.6, 98.7, 98.8, 98.9, 99.0, 99.1, 998.2, 99.3, 99.4, 99.5, 99.6,
99.7, 99.8, 99.9% sensitivity, specificity, or both
[0802] The exosome can be purified or concentrated prior to
analysis. Alternatively, the level, or amount, of exosomes can be
directly assayed from a sample, without prior purification or
concentration. The exosome quantitated can be a cell-of-origin
specific exosome. For example, a cell or tissue-specific exosome
can be isolated using one or more binding agents specific for a
particular organ. The cell-of-origin specific exosome can be
assessed for one or more molecular features, such as one or more
biomarkers associated with organ distress or organ transplant
rejection. The presence, absence or levels of one or more
biomarkers present in an isolated cell-of-origin specific exosome
can be assessed to monitor organ rejection or success.
[0803] One or more exosomes can be analyzed for the assessment,
detection or diagnosis of the rejection of a tissue or organ
transplant by a subject. The tissue or organ transplant rejection
can be hyperacute, acute, or chronic rejection. The exosome can
also be analyzed for the assessment, detection or diagnosis of
graft versus host disease in a subject. The subject can be the
recipient of an autogenic, allogenic or xenogenic tissue or organ
transplant.
[0804] The exosome can also be analyzed to detect the rejection of
a tissue or organ transplant. The exosome may be produced by the
tissue or organ transplant. Such tissues or organs include, but are
not limited to, a heart, lung, pancreas, kidney, eye, cornea,
muscle, bone marrow, skin, cartilage, bone, appendages, hair, face,
tendon, stomach, intestine, vein, artery, differentiated cells,
partially differentiated cells or stem cells.
[0805] The exosome can comprise at least one biomarker which is
used to assess, diagnose or determine the probability or occurrence
of rejection of a tissue or organ transplant by a subject. A
biomarker can also be used to assess, diagnose or detect graft
versus host disease in a subject. The biomarker can be a protein, a
polysaccharide, a fatty acid or a nucleic acid (such as DNA or
RNA). The biomarker can be associated with the rejection of a
specific tissue or organ or systemic organ failure. More than one
biomarker can be analyzed, for example, one or more proteins marker
can be analyzed in combination with one or more nucleic acid
markers. The biomarker may be an intracellular or extracellular
marker.
[0806] The exosome can also be analyzed for at least one marker for
the assessment, detection or diagnosis of cell apoptosis or
necrosis associated with, or the causation of, rejection of a
tissue or organ transplant by a subject.
[0807] The presence of a biomarker can be indicative of the
rejection of a tissue or an organ by a subject, wherein the
biomarker includes, but is not limited to, CD40, CD40 ligand,
N-acetylmuramoyl-L-alanine amidase precursor, adiponectin, AMBP
protein precursor, C4b-binding protein a-chain precursor,
ceruloplasmin precursor, complement C3 precursor, complement
component C9 precursor, complement factor D precursor, alpha
1-B-glycoprotein, beta2-glycoprotein I precursor, heparin cofactor
II precursor, Immunoglobulin mu chain C region protein,
Leucine-rich alpha2-glycoprotein precursor, pigment
epithelium-derived factor precursor, plasma retinol-binding protein
precursor, translation initiation factor 3 subunit 10, ribosomal
protein L7, beta-transducin, 1-TRAF, or lysyl-tRNA synthetase.
[0808] Rejection of a kidney by a subject can also be detected by
analyzing exosomes for the presence of beta-transducin. Rejection
of transplanted tissue can also be detected by isolating a
cell-of-origin specific exosome from CD40-expressing cells and
detecting for the increase of Bcl-2 or TNFalpha.
[0809] Rejection of a liver transplant by a subject can be detected
by analyzing the exosomes for the presence of an F1 antigen marker.
The F1 antigen is, without being bound to theory, specific to liver
to and can be used to detect an increase in liver cell-of-origin
specific exosomes. This increase can be used as an early indication
of organ distress/rejection.
[0810] Bronchiolitis obliterans due to bone marrow and/or lung
transplantation or other causes, or graft atherosclerosis/graft
phlebosclerosis can also be diagnosed by the analysis of an
exosome.
[0811] An exosome can also be analyzed for the detection, diagnosis
or assessment of an autoimmune or other immunological
reaction-related phenotypes in a subject. Examples of such a
disorder include, but are not limited to, systemic lupus
erythematosus (SLE), discoid lupus, lupus nephritis, sarcoidosis,
inflammatory arthritis, including juvenile arthritis, rheumatoid
arthritis, psoriatic arthritis, Reiter's syndrome, ankylosing
spondylitis, and gouty arthritis, multiple sclerosis, hyper IgE
syndrome, polyarteritis nodosa, primary biliary cirrhosis,
inflammatory bowel disease, Crohn's disease, celiac's disease
(gluten-sensitive enteropathy), autoimmune hepatitis, pernicious
anemia, autoimmune hemolytic anemia, psoriasis, scleroderma,
myasthenia gravis, autoimmune thrombocytopenic purpura, autoimmune
thyroiditis, Grave's disease, Hasimoto's thyroiditis, immune
complex disease, chronic fatigue immune dysfunction syndrome
(CFIDS), polymyositis and dermatomyositis, cryoglobulinemia,
thrombolysis, cardiomyopathy, pemphigus vulgaris, pulmonary
interstitial fibrosis, asthma, Churg-Strauss syndrome (allergic
granulomatosis), atopic dermatitis, allergic and irritant contact
dermatitis, urtecaria, IgE-mediated allergy, atherosclerosis,
vasculitis, idiopathic inflammatory myopathies, hemolytic disease,
Alzheimer's disease, chronic inflammatory demyelinating
polyneuropathy and AIDs.
[0812] One or more biomarkers from the exosome can be used to
assess, diagnose or determine the probability of the occurrence of
an autoimmune or other immunological reaction-related disorder in a
subject. The biomarker can be a protein, a polysaccharide, a fatty
acid or a nucleic acid (such as DNA or RNA). The biomarker can be
associated with a specific autoimmune disorder, a systemic
autoimmune disorder, or other immunological reaction-related
disorder. More than one biomarker can be analyzed. For example one
or more protein markers can be analyzed in combination with one or
more nucleic acid markers. The biomarker can be an intracellular or
extracellular marker. The biomarker can also be used to detect,
diagnose or assess inflammation.
[0813] Analysis of an exosome from subjects can be used identify
subjects with inflammation associated with asthma, sarcoidosis,
emphysema, cystic fibrosis, idiopathic pulmonary fibrosis, chronic
bronchitis, allergic rhinitis and allergic diseases of the lung
such as hypersensitivity pneumonitis, eosinophilic pneumonia, as
well as pulmonary fibrosis resulting from collagen, vascular, and
autoimmune diseases such as rheumatoid arthritis.
Exosome Compositions
[0814] Also provided herein is an isolated exosome with a
particular bio-signature. The isolated exosome can comprise one or
more biomarkers or bio-signatures specific for specific cell type,
or for characterizing a phenotype, such as described above. For
example, the isolated exosome can comprise one or more biomarkers,
such as CD63, EpCam, CD81, CD9, PCSA, PSMA, B7H3, TNFR, MFG-E8,
Rab, STEAP, 5T4, or CD59. The isolated exosome can have the one or
more biomarkers on its surface of within the exosome. The isolated
exosome can also comprise one or more miRNAs, such as miR-9,
miR-629, miR-141, miR-671-3p, miR-491, miR-182, miR-125a-3p,
miR-324-5p, miR-148B, or miR-222. An isolated exosome can comprise
a biomarker such as CD66, and further comprise one or more
biomarkers selected from the group consisting of: EpCam, CD63, or
CD9. An isolated exosome can also comprise a fusion gene or
protein, such as TMRSSG2:ERG.
[0815] An isolated exosome can also comprise one or more
biomarkers, wherein the expression level of the one or more
biomarkers is higher, lower, or the same for an isolated exosome as
compared to an isolated exosome derived from a normal cell (ie. a
cell derived from a subject without a phenotype of interest). For
example, an isolated exosome can comprise one or more biomarkers
selected from the group consisting of: B7H3, PSCA, MFG-E8, Rab,
STEAP, PSMA, PCSA, 5T4, miR-9, miR-629, miR-141, miR-671-3p,
miR-491, miR-182, miR-125a-3p, miR-324-5p, miR-148b, and miR-222,
wherein the expression level of the one or more biomarkers is
higher for an isolated exosome as compared to an isolated exosome
derived from a normal cell. The isolated exosome can comprise at
least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, or 19
of the biomarkers selected from the group. The isolated exosome can
further comprising one or more biomarkers selected from the group
consisting of: EpCam, CD63, CD59, CD81, or CD9.
[0816] An isolated exosome can comprise the biomarkers PCSA, EpCam,
CD63, and CD8; the biomarkers PCSA, EpCam, B7H3 and PSMA. An
isolated exosome can comprise the biomarkers miR-9, miR-629,
miR-141, miR-671-3p, miR-491, miR-182, miR-125a-3p, miR-324-5p,
miR-148b, and miR-222.
[0817] A composition comprising an isolated exosome is also
provided herein. The composition can comprise one or more isolated
exosomes. For example, the composition can comprise a plurality of
exosomes, or one or more populations of exosomes.
[0818] The composition can be substantially enriched for exosomes.
For example, the composition can be substantially absent of
cellular debris, cells, or non-exosomal proteins, peptides, or
nucleic acids (such as biological molecules not contained within
the exosomes). The cellular debris, cells, or non-exosomal
proteins, peptides, or nucleic acids, can be present in a
biological sample along with exosomes. A composition can be
substantially absent of cellular debris, cells, or non-exosomal
proteins, peptides, or nucleic acids (such as biological molecules
not contained within the exosomes), can be obtained by any method
disclosed herein, such as through the use of one or more binding
agents or capture agents for one or more exosomes. The exosomes can
comprise at least 30, 40, 50, 60, 70, 80, 90, 95 or 99% of the
total composition, by weight or by mass. The exosomes of the
composition can be a heterogeneous or homogeneous population of
exosomes. For example, a homogeneous population of exosomes
comprises exosomes that are homogeneous as to one or more
properties or characteristics. For example, the one or more
characteristics can be selected from a group consisting of: one or
more of the same biomarkers, a substantially similar or identical
bio-signature, derived from the same cell type, exosomes of a
particular size, and a combination thereof.
[0819] Thus, in some embodiments, the composition comprises a
substantially enriched population of exosomes. The composition can
be enriched for a population of exosomes that are at least 30, 40,
50, 60, 70, 80, 90, 95 or 99% homogeneous as to one or more
properties or characteristics. For example, the one or more
characteristics can be selected from a group consisting of: one or
more of the same biomarkers, a substantially similar or identical
bio-signature, derived from the same cell type, exosomes of a
particular size, and a combination thereof. For example, the
population of exosomes can be homogeneous by all having a
particular bio-signature, having the same biomarker, having the
same biomarker combination, or derived from the same cell type. In
some embodiments, the composition comprises a substantially
homogeneous population of exosomes, such as a population with a
specific bio-signature, derived from a specific cell, or both.
[0820] The population of exosome can comprise one or more of the
same biomarkers. The biomarker can be any component present in an
exosome or on the exosome, such as any nucleic acid (e.g. RNA or
DNA), protein, peptide, polypeptide, antigen, lipid, carbohydrate,
or proteoglycan. For example, each exosome in a population can
comprise the same or identical one or more biomarkers. In some
embodiments, each exosome in the population comprises the same 1,
2, 3, 4, 5, 6, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17,
18, 19, 20, 25, 50, 75 or 100 biomarkers. The one or more
biomarkers can be selected from FIGS. 1, 3-60.
[0821] The exosome population comprising the same or identical
biomarker can refer to each exosome in the population having the
same presence or absence, expression level, mutational state, or
modification of the biomarker. For example, an enriched population
of exosome can comprise exosomes, wherein each exosome has the same
biomarker present, the same biomarker absent, the same expression
level of a biomarker, the same modification of a biomarker, or the
same mutation of a biomarker. The same expression level of a
biomarker can refer to a quantitative or qualitive measurement,
such as the exosomes in the population underexpress, overexpress,
or have the same expression level of a biomarker as compared to a
reference level. Alternatively, the same expression level of a
biomarker can be a numerical value representing the expression of a
biomarker that is similar for each exosome in a population. For
example the copy number of a miRNA, the amount of protein, or the
level of mRNA of each exosome can be quantitatively similar for
each exosome in a population, such that the numerical amount of
each exosome is .+-.1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, or 20% from
the amount in each other exosome in the population, as such
variations are appropriate.
[0822] In some embodiments, the composition comprises a
substantially enriched population of exosomes, wherein the exosomes
in the enriched population has a substantially similar or identical
bio-signature. The bio-signature can comprise one or more exosomal
characteristic such as the level or amount of exosomes, temporal
evaluation of the variation in exosomal half-life, circulating
exosomal half-life or exosomal metabolic half-life, or the activity
of an exosome. The bio-signature can also comprise the presence or
absence, expression level, mutational state, or modification of a
biomarker, such as those described herein.
[0823] The bio-signature of each exosome in the population can be
at least 30, 40, 50, 60, 70, 80, 90, 95, or 99% identical. In some
embodiments, the bio-signature of each exosome is 100% identical.
The bio-signature of each exosome in the enriched population can
have the same 1, 2, 3, 4, 5, 6, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12,
13, 14, 15, 16, 17, 18, 19, 20, 25, 50, 75 or 100 exosomal
characteristics. For example, a bio-signature of an exosome in an
enriched population can be the presence of a first biomarker, the
presence of a second biomarker, and the underexpression of a third
biomarker. Another exosome in the same population can be 100%
identical, having the same first and second biomarkers present and
underexpression of the third biomarker. Alternatively, an exosome
in the same population can have the same first and second
biomarkers, but not have underexpression of the third
biomarker.
[0824] In some embodiments, the composition comprises a
substantially enriched population of exosomes, wherein the exosomes
are derived from the same cell type. For example, the exosomes can
all be derived from cells of a specific tissue, cells from a
specific tumor of interest or a diseased tissue of interest,
circulating tumor cells, or cells of maternal or fetal origin. The
exosomes can all be derived from tumor cells. The exosomes can all
be derived from lung, pancreas, stomach, intestine, bladder,
kidney, ovary, testis, skin, colorectal, breast, prostate, brain,
esophagus, liver, placenta, or fetal cells.
[0825] The composition comprising a substantially enriched
population of exosomes can also comprise exosomes are of a
particular size. For example, the exosomes can all a diameter of
greater than about 10, 20, or 30 nm. They can all have a diameter
of about 30-1000 nm, about 30-800 nm, about 30-200 nm, or about
30-100 nm. In some embodiments, the exosomes can all have a
diameter of less than about 10,000 nm, 1000 nm, 800 nm, 500 nm, 200
nm, 100 nm or 50 nm.
[0826] The population of exosomes homogeneous for one or more
characteristics can comprises at least about 30, 40, 50, 60, 70,
80, 90, 95, or 99% of the total exosome population of the
composition. In some embodiments, a composition comprising a
substantially enriched population of exosomes comprises at least 2,
3, 4, 5, 10, 20, 25, 50, 100, 250, 500, or 1000 times the
concentration of an exosome as compared to a concentration of the
exosome in a biological sample from which the composition was
derived. In yet other embodiments, the composition can further
comprise a second enriched population of exosomes, wherein the
population of exosomes is at least 30% homogeneous as to one or
more characteristics, as described herein.
[0827] Multiplex analysis can be used to obtain a composition
substantially enriched for more than one population of exosomes,
such as at least 2, 3, 4, 5, 6, 7, 8, 9, 10 exosome populations.
Each substantially enriched exosome population can comprise at
least 5, 10, 15, 20, 25, 30, 35, 40, 45, 46, 47, 48, or 49% of the
composition, by weight or by mass. In some embodiments, the
substantially enriched exosome populations comprises at least about
30, 40, 50, 60, 70, 80, 90, 95, or 99% of the composition, by
weight or by mass.
[0828] A substantially enriched population of exosomes can be
obtained by using one or more methods, processes, or systems as
disclosed herein. For example, isolation of a population of
exosomes from a sample can be performed by using one or more
binding agents for one or more biomarkers of an exosome, such as
using two or more binding agents that target two or more biomarkers
of an exosome. One or more capture agents can be used to obtain a
substantially enriched population of exosomes. One or more
detection agents can be used to identify a substantially enriched
population of exosomes.
[0829] In one embodiment, a population of exosomes with a
particular bio-signature is obtained by using one or more binding
agents for the biomarkers of the bio-signature. The exosomes can be
isolated resulting in a composition comprising a substantially
enriched population of exosomes with the particular bio-signature.
In another embodiment, a population of exosomes with a particular
bio-signature of interest can be obtained by using one or more
binding agents for biomarkers that are not a component of the
bio-signature of interest. Thus, the binding agents can be used to
remove the exosomes that do not have the bio-signature of interest
and the resulting composition is substantially enriched for the
population of exosomes with the particular bio-signature of
interest. The resulting composition can be substantially absent of
the exosomes comprising a biomarker for the binding agent.
Detection System and Kits
[0830] Also provided is a detection system configured to determine
one or more bio-signatures for an exosome. The detection system can
be used to detect a heterogeneous population of exosomes or one or
more homogeneous population of exosomes. The detection system can
be configured to detect a plurality of exosomes, wherein at least a
subset of said plurality of exosomes comprises a different
bio-signature from another subset of said plurality of exosomes.
The detection system detect at least 2, 3, 4, 5, 6, 7, 8, 9, 10,
15, 20, 25, 30, 40, 50, 60, 70, 80, 90, or 100 different subsets of
exosomes, wherein each subset of exosomes comprises a different
bio-signature. For example, a detection system, such as using one
or more methods, processes, and compositions disclosed herein, can
be used to detect at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25,
30, 40, 50, 60, 70, 80, 90, or 100 different populations of
exosomes.
[0831] The detection system can be configured to assess at least 2,
3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90,
100, 1000, 2500, 5000, 7500, 10,000, 100,000, 150,000, 200,000,
250,000, 300,000, 350,000, 400,000, 450,000, 500,000, 750,000, or
1,000,000 different biomarkers for one or more exosomes. In some
embodiments, the one or more biomarkers are selected from FIGS. 1,
3-60, or as disclosed herein. The detection system can be
configured to assess a specific population of exosomes, such as
exosomes from a specific cell-of-origin, or to assess a plurality
of specific populations of exosomes, wherein each population of
exosomes has a specific bio-signature.
[0832] The detection system can be a low density detection system
or a high density detection system. For example, a low density
detection system can detect up to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10
different exosome populations, whereas a high density detection
system can detect at least about 15, 20, 25, 50, or 100 different
exosome populations In another embodiment, a low density detection
system can detect up to about 100, 200, 300, 400, or 500 different
biomarkers, whereas a high density detection system can detect at
least about 750, 1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000,
9,000, 10,000, 15,000, 20,000, 25,000, 50,000, or 100,000 different
biomarkers. In yet another embodiment, a low density detection
system can detect up to about 100, 200, 300, 400, or 500 different
bio-signatures or biomarker combinations, whereas a high density
detection system can detect at least about 750, 1000, 2000, 3000,
4000, 5000, 6000, 7000, 8000, 9,000, 10,000, 15,000, 20,000,
25,000, 50,000, or 100,000 bio-signatures or biomarker
combinations.
[0833] The detection system can comprise a probe that selectively
hybridizes to an exosome. The detection system can comprise a
plurality of probes to detect an exosome. In some embodiments, a
plurality of probes is used to detect the amount of exosomes in a
heterogeneous population of exosomes. In yet other embodiments, a
plurality of probes is used to detect a homogeneous population of
exosomes. A plurality of probes can be used to isolate or detect at
least two different subsets of exosomes, wherein each subset of
exosomes comprises a different bio-signature.
[0834] A detection system, such as using one or more methods,
processes, and compositions disclosed herein, can comprise a
plurality of probes configured to detect, or isolate, such as using
one or more methods, processes, and compositions disclosed herein
at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50, 60,
70, 80, 90, or 100 different subsets of exosomes, wherein each
subset of exosomes comprises a different bio-signature.
[0835] For example, a detection system can comprise a plurality of
probes configured to detect at least 2, 3, 4, 5, 6, 7, 8, 9, 10,
15, 20, 25, 30, 40, 50, 60, 70, 80, 90, or 100 different
populations of exosomes. The detection system can comprise a
plurality of probes configured to selectively hybridize to at least
2, 3, 4, 5, 6, 7, 8, 9, 10, 15, 20, 25, 30, 40, 50, 60, 70, 80, 90,
100, 1000, 2500, 5000, 7500, 10,000, 100,000, 150,000, 200,000,
250,000, 300,000, 350,000, 400,000, 450,000, 500,000, 750,000, or
1,000,000 different biomarkers for one or more exosomes. In some
embodiments, the one or more biomarkers are selected from FIGS. 1,
3-60, or as disclosed herein. The plurality of probes can be
configured to assess a specific population of exosomes, such as
exosomes from a specific cell-of-origin, or to assess a plurality
of specific populations of exosomes, wherein each population of
exosomes has a specific bio-signature.
[0836] The detection system can be a low density detection system
or a high density detection system comprising probes to detect
exosomes. For example, a low density detection system can comprise
probes to detect up to 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 different
exosome populations, whereas a high density detection system can
comprise probes to detect at least about 15, 20, 25, 50, or 100
different exosome populations In another embodiment, a low density
detection system can comprise probes to detect up to about 100,
200, 300, 400, or 500 different biomarkers, whereas a high density
detection system can comprise probes to detect at least about 750,
1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9,000, 10,000,
15,000, 20,000, 25,000, 50,000, or 100,000 different biomarkers. In
yet another embodiment, a low density detection system can comprise
probes to detect up to about 100, 200, 300, 400, or 500 different
bio-signatures or biomarker combinations, whereas a high density
detection system can comprise probes to detect at least about 750,
1000, 2000, 3000, 4000, 5000, 6000, 7000, 8000, 9,000, 10,000,
15,000, 20,000, 25,000, 50,000, or 100,000 bio-signatures or
biomarker combinations.
[0837] The probes can be specific for detecting a specific exosome
population, for example an exosome with a particular bio-signature,
and as described above. A plurality of probes for detecting
prostate specific exosomes is also provided. A plurality of probes
can comprise probes for detecting one or more of the following
biomarkers: CD9, PSCA, TNFR, CD63, MFG-E8, EpCAM, Rab, CD81, STEAP,
PCSA, 5T4, EpCAM, PSMA, CD59, CD66, CD24 and B7H3. A plurality of
probes for detecting Bcl-XL, ERCC1, Keratin 15, CD81/TAPA-1, CD9,
Epithelial,Specific Antigen (ESA), and Mast Cell Chymase can also
be provided. A plurality of probes for detecting one or more miRNAs
of an exosome can comprise probes for detecting one or more of the
following miRNAs: miR-9, miR-629, miR-141, miR-671-3p, miR-491,
miR-182, miR-125a-3p, miR-324-5p, miR-148b, and miR-222,
[0838] The probes may be attached to a solid substrate, such as an
array or bead. Alternatively, the probes are not attached. The
detection system may be an array based system, a sequencing system,
a PCR-based system, or a bead-based system, such as described
above. For example, the detection system can be a microfluidic
device as described above.
[0839] The detection system may be part of a kit. Alternatively,
the kit may comprise the one or more probe sets, or plurality of
probes, as described herein. The kit may comprise probes for
detecting an isolated exosome, a plurality of exosomes, such as
exosomes in a heterogeneous population. The kit may comprise probes
for detecting a homogeneous population of exosomes. For example,
the kit may comprise probes for detecting a population of specific
cell-of-origin exosomes, or exosomes with the same specific
bio-signature.
Portfolios
[0840] Portfolios of multiplexed markers to guide clinical
decisions and disease detection and management can be established
such that the combination of bio-signatures in the portfolio
exhibit improved sensitivity and specificity relative to individual
bio-signatures or randomly selected combinations of bio-signatures.
In the context of the instant invention, the sensitivity of the
portfolio can be reflected in the fold differences exhibited by a
bio-signature's expression in the diseased state relative to the
normal state. Specificity can be reflected in statistical
measurements of the correlation of the signaling of gene
expression, for example, with the condition of interest (e.g.
standard deviation can be a used as such a measurement). In
considering a group of bio-signature for inclusion in a portfolio,
a small standard deviation in measurements correlates with greater
specificity. Other measurements of variation such as correlation
coefficients can also be used in this capacity.
[0841] When combining biomakers or bio-signatures in this invention
In Vitro Diagnostic Multivariate Index Assays (IVDMIAs) guidelines
and regulations may apply. IVDMIAs can apply to bio-signatures as
defined as a set of 2 or more markers composed of any combination
of genes, gene alterations, mutations, amplifications, deletions,
polymorphisms or methylations, or proteins, peptides, polypeptides
or RNA molecules, miRNAs, mRNAs, snoRNAs, hnRNAs or RNA that can be
grouped so that information obtained about the set of
bio-signatures in the group provides a sound basis for making a
clinically relevant judgment such as a diagnosis, prognosis, or
treatment choice. These sets of bio-signatures make up various
portfolios of the invention. As with most diagnostic markers, it is
often desirable to use the fewest number of markers sufficient to
make a correct medical judgment. This prevents a delay in treatment
pending further analysis as well inappropriate use of time and
resources. Preferably, portfolios are established such that the
combination of bio-signatures in the portfolio exhibit improved
sensitivity and specificity relative to individual bio-signatures
or randomly selected combinations of bio-signatures. In the context
of the instant invention, the sensitivity of the portfolio can be
reflected in the fold differences exhibited by a bio-signature's
expression in the diseased state relative to the normal state.
Specificity can be reflected in statistical measurements of the
correlation of the signaling of gene expression, for example, with
the condition of interest. In considering a group of markers in a
bio-signature for inclusion in a portfolio, standard deviations,
variances, co-variances, correlation coefficients, weighted
averages, arithmetic sums, means, multiplicative values, weighted
or balanced values or any mathematical manipulation of the values
of 2 or more markers that can together be used to calculate a value
or score that taken as a whole can be shown to produce greater
sensitivity, specificity, negative predictive value, positive
predictive value or accuracy can also be used in this capacity and
are within the scope of this invention.
[0842] In another embodiment pattern recognition methods can be
used. One example involves comparing biomarker expression profiles
for various biomarkers (or bio-signature portfolios) to ascribe
diagnoses. The expression profiles of each of the biomarker
comprising the bio-signature portfolio are fixed in a medium such
as a computer readable medium.
[0843] In one example, a table can be established into which the
range of signals (e.g., intensity measurements) indicative of
disease or physiological state is input. Actual patient data can
then be compared to the values in the table to determine whether
the patient samples are normal, benign, diseased, or represent a
specific physiological state. In a more sophisticated embodiment,
patterns of the expression signals (e.g., fluorescent intensity)
are recorded digitally or graphically. In the example of RNA
expression patterns from the biomarker portfolios used in
conjunction with patient samples are then compared to the
expression patterns. Pattern comparison software can then be used
to determine whether the patient samples have a pattern indicative
of the disease, a given prognosis, a pattern that indicates
likeliness to respond to therapy, or a pattern that is indicative
of a particular physiological state. The expression profiles of the
samples are then compared to the portfolio of a control cell. If
the sample expression patterns are consistent with the expression
pattern(s) for disease, prognosis, or therapy-related response then
(in the absence of countervailing medical considerations) the
patient is diagnosed as meeting the conditions that relate to these
various circumstances. If the sample expression patterns are
consistent with the expression pattern derived from the
normal/control exosome population then the patient is diagnosed
negative for these conditions.
[0844] In another exemplary embodiment, a method for establishing
biomarker expression portfolios is through the use of optimization
algorithms such as the mean variance algorithm widely used in
establishing stock portfolios. This method is described in detail
in the U.S. Application Publication No. 20030194734, incorporated
herein by reference. Alternatively, measured DNA alterations,
changes in mRNA, protein, or metabolites to phenotypic readouts of
efficacy and toxicity may be modeled and analyzed using algorithms,
systems and methods described in U.S. Pat. Nos. 7,089,168,
7,415,359 and U.S. Application Publication Nos. 20080208784,
20040243354, or 20040088116, each of which is herein incorporated
by reference in its entirety.
[0845] An exemplary process of bio-signature portfolio selection
and characterization of an unknown is summarized as follows:
[0846] 1. Choose baseline class.
[0847] 2. Calculate mean, and standard deviation of each biomarker
for baseline class samples.
[0848] 3. Calculate (X*Standard Deviation+Mean) for each biomarker.
This is the baseline reading from which all other samples will be
compared. X is a stringency variable with higher values of X being
more stringent than lower.
[0849] 4. Calculate ratio between each Experimental sample versus
baseline reading calculated in step 3.
[0850] 5. Transform ratios such that ratios less than 1 are
negative (eg. using Log base 10). (Under expressed biomarkers now
correctly have negative values necessary for MV optimization).
[0851] 6. These transformed ratios are used as inputs in place of
the asset returns that are normally used in the software
application.
[0852] 7. The software will plot the efficient frontier and return
an optimized portfolio at any point along the efficient
frontier.
[0853] 8. Choose a desired return or variance on the efficient
frontier.
[0854] 9. Calculate the Portfolio's Value for each sample by
summing the multiples of each gene's intensity value by the weight
generated by the portfolio selection algorithm.
[0855] 10. Calculate a boundary value by adding the mean
Bio-signature Portfolio Value for Baseline groups to the multiple
of Y and the Standard Deviation of the Baseline's Bio-signature
Portfolio Values. Values greater than this boundary value shall be
classified as the Experimental Class.
[0856] 11. Optionally one can reiterate this process until best
prediction.
[0857] The process of selecting a bio-signature portfolio can also
include the application of heuristic rules. Preferably, such rules
are formulated based on biology and an understanding of the
technology used to produce clinical results. More preferably, they
are applied to output from the optimization method. For example,
the mean variance method of bio-signature portfolio selection can
be applied to microarray data for a number of biomarkers
differentially expressed in subjects with a specific disease.
Output from the method would be an optimized set of biomarkers that
could include those that are expressed in exosomes as well as in
diseased tissue. If samples used in the testing method are obtained
from exosomes and certain biomarkers differentially expressed in
instances of disease or physiological state could also be
differentially expressed in exosomes, then a heuristic rule can be
applied in which a bio-signature portfolio is selected from the
efficient frontier excluding those that are differentially
expressed in exosomes. Of course, the rule can be applied prior to
the formation of the efficient frontier by, for example, applying
the rule during data pre-selection.
[0858] Other statistical, mathematical and computational algorithms
for the analysis of linear and non-linear feature subspaces,
feature extraction and signal deconvolution in large scale datasets
to identify exosome-derived multiplex analyte profiles for
diagnosis, prognosis and therapy selection and/or characterization
of define physiological states can be done using any combination of
unsupervised analysis methods, including but not limited to:
principal component analysis (PCA) and linear and non-linear
independent component analysis (ICA); blind source separation,
nongaussinity analysis, natural gradient maximum likelihood
estimation; joint-approximate diagonalization; eigenmatrices;
Gaussian radical basis function, kernel and polynominal kernel
analysis sequential floating forward selection.
Computer Systems
[0859] An exosome can be assayed for molecular features, for
example, by determining an amount, presence or absence of one or
more biomarkers such as listed FIGS. 1, 3-60. The data generated
can be used to produce a bio-signature, which can be stored and
analyzed by a computer system, such as shown in FIG. 62. The
assaying or correlating of the bio-signature with one or more
phenotypes can also be performed by computer systems, such as by
using computer executable logic.
[0860] A computer system, such as shown in FIG. 62, can be used to
transmit data and results following analysis. Accordingly, FIG. 62
is a block diagram showing a representative example logic device
through which results from exosome analysis can be reported or
generated. FIG. 62 shows a computer system (or digital device) 800
to receive and store data generated from exosome analysis, analyze
the data to generate one or more bio-signatures, and produce a
report of the one or more bio-signatures. The computer system can
also perform comparisons and analyses of bio-signatures generated,
and transmit the results. Alternatively, the computer system can
receive raw data of exosome analysis, such as through transmission
of the data over a network, and perform the analysis.
[0861] The computer system 800 may be understood as a logical
apparatus that can read instructions from media 811 and/or network
port 805, which can optionally be connected to server 809 having
fixed media 812. The system shown in FIG. 62 includes CPU 801, disk
drives 803, optional input devices such as keyboard 815 and/or
mouse 816 and optional monitor 807. Data communication can be
achieved through the indicated communication medium to a server 809
at a local or a remote location. The communication medium can
include any means of transmitting and/or receiving data. For
example, the communication medium can be a network connection, a
wireless connection or an Internet connection. Such a connection
can provide for communication over the World Wide Web. It is
envisioned that data relating to the present invention can be
transmitted over such networks or connections for reception and/or
review by a party 822. The receiving party 822 can be but is not
limited to an individual, a health care provider or a health care
manager. In one embodiment, a computer-readable medium includes a
medium suitable for transmission of a result of an analysis of a
biological sample, such as exosome bio-signatures. The medium can
include a result regarding an exosome bio-signature of a subject,
wherein such a result is derived using the methods described
herein.
Ex vivo Harvesting of Exosomes
[0862] Exosomes for analysis and determination of a phenotype can
also be from ex vivo harvesting. Cells can be cultured and that
exosomes released from cells of interest in culture either result
spontaneously or can be stimulated to release exosomes into the
medium. (see for example, Zitvogel, et al./998. Nat. Med. 4:
594-600; Chaput, et al. 2004. J. Immunol. 172: 2137-214631:
2892-2900; Escudier, et al. 2005. J. Transl. Med. 3: 10; Morse, et
al. 2005, J. Transl. Med. 3: 9; Peche, et al. 2006. Am. J.
Transplant. 6: 1541-1550; Kim, et al. 2005. J. Immunol. 174:
6440-6448, all of which are herein incorporated by reference in
their entireties). Cell lines or tissue samples can be grown to 80%
confluence before being cultured in fresh DMEM for 72 h. Subsequent
exosome production can be stimulated (see, for example, heat shock
treatment of melanoma cells as described by Dressel, et al. 2003.
Cancer Res. 63: 8212-8220, which is herein incorporated by
reference in its entirety). The supernatant can then be harvested
and exosomes prepared as described herein.
[0863] Exosomes produced ex vivo can, in one example, be cultured
from a cell-of-origin or cell line of interest, exosomes can be
isolated from the cell culture medium and subsequently labeled with
a magnetic label, a fluorescent moiety, a radioisotope, an enzyme,
a chemiluminescent probe, a metal particle, a non-metal colloidal
particle, a polymeric dye particle, a pigment molecule, a pigment
particle, an electrochemically active species, semiconductor
nanocrystal or other nanoparticles including quantum dots or gold
particles to be reintroduced in vivo as a label for imaging
analysis. Ex vivo cultured exosomes can alternatively be used to
identify novel bio-signatures by setting up culturing conditions
for a given cell-of-origin with characteristics of interest, for
example a culture of lung cancer cells or cell line with a known
EGFR mutation that confers resistant to or susceptibility to
gefitinib, then exposing the cell culture to gefitinib, isolating
exosomes that arise from the culture and subsequently analyzing
them on a discovery array to look for novel antigens or binding
agents expressed on the outside of exosomes that could be used as a
bio-signature to capture this species of exosome. Additionally, it
would be possible to isolate any other biomarkers or bio-signatures
found within these exosomes for discovery of novel signatures
(including but not limited to nucleic acids, proteins, lipids, or
combinations thereof) that may have clinical diagnostic, prognostic
or therapy related implication.
[0864] Cells of interest can also be first isolated and cultured
from tissues of interest. For example, human hair follicles in the
growing phase, anagen, can be plucked individually from a patient's
scalp using sterile equipment and plasticware, taking care not to
damage the follicle. Each sample can be transferred to a Petri dish
containing sterile PBS for tissue culture. Isolated human anagen
hair follicles can be carefully transferred to an individual well
of a 24-well plate containing 1 ml of William's E medium. Follicles
can be maintained free-floating at 37.degree. C. in an atmosphere
of 5% CO.sub.2 and 95% air in a humidified incubator. Medium can be
changed every 3 days, taking care not to damage the follicles.
Cells can then be collected and spun down from the media. Exosomes
may then be isolated using antigens or cellular binding partners
that are specific to such cell-of-origin specific exosomes using
methods as previously described. Biomarkers and bio-signatures can
then be isolated and characterized by methods known to those
skilled in the art.
[0865] Cells of interest may also be cultured under microgravity or
zero-gravity conditions or under a free-fall environment. For
example, NASA's bioreactor technology will allow such cells to be
grown at much faster rate and in much greater quantities. Exosomes
may then be isolated using antigens or cellular binding partners
that are specific to such cell-of-origin specific exosomes using
methods as previously described.
[0866] Rotating wall vessels or RWVersus are a class of bioreactors
developed by and for NASA that are designed to grow suspension
cultures of cells in a quiescent environment that simulates
microgravity can also be used. (see for example, U.S. Pat. Nos.
5,026,650; 5,153,131; 5,153,133; 5,437,998; 5,665,594; 5,702,941;
7,351,584, 5,523,228, 5,104,802, 6,117,674, Schwarz, R P, et al.,
J. Tiss. Cult. Meth. 14:51-58, 1992; Martin et al., Trends in
biotechnology 2004; 22; 80-86, Li et al., Biochemical Engineering
Journal 2004; 18; 97-104, Ashammakhi et al., Journal Nanoscience
Nanotechnology 2006; 9-10: 2693-2711, Zhang et al., International
Journal of Medicine 2007; 4: 623-638, Cowger, N L, et al.,
Biotechnol. Bioeng 64:14-26, 1999, Spaulding, G F, et al., J. Cell.
Biochem. 51:249-251, 1993, Goodwin, T J, et al., Proc. Soc. Exp.
Biol. Med. 202:181-192, 1993; Freed, L E et al., In Vitro Cell.
Dev. Biol. 33:381-385, 1997, Clejan, S. et al, Biotechnol. Bioeng.
50:587-597, 1996). Khaoustov, V I, et al., In Vitro Cell. Dev.
Biol. 35:501-509. 1999, each of which is herein incorporated by
reference in its entirety).
[0867] Alternatively, cells of interest or cell-of-origin specific
exosomes that have been isolated may be cultured in a stationary
phase plug-flow bioreactor as generally described in U.S. Pat. No.
6,911,201, and U.S. Application Publication Nos. 20050181504,
20050180958, 20050176143 and 20050176137, each of which is herein
incorporated by reference in its entirety. Alternatively, cells of
interest or cell-origin specific exosomes may also be isolated and
cultured as generally described in U.S. Pat. No. 5,486,359.
[0868] One embodiment can include the steps of providing a tissue
specimen containing cells of interest or cell-origin specific
exosomes, adding cells or exosomes from the tissue specimen to a
medium which allows, when cultured, for the selective adherence of
only the cells of interest or cell-origin specific exosomes to a
substrate surface, culturing the specimen-medium mixture, and
removing the non-adherent matter from the substrate surface is
generally described in U.S. Pat. No. 5,486,359, which is herein
incorporated by reference in its entirety.
Exosomes as Imaging Tools
[0869] In other embodiments, exosomes can be used as imaging tools.
Labeled circulating tumor cells (CTCs) can be noninvasively
visualized in vivo as they flow through the peripheral vasculature
(He, W et al. (2007) PNAS 104(28)11760-11765). The method can
involve i.v. injection of a tumor-specific fluorescent ligand
followed by multiphoton fluorescence imaging of superficial blood
vessels to quantitate the flowing CTCs. Studies in mice with
metastatic tumors demonstrated that CTCs can be quantitated weeks
before metastatic disease is detected by other means. Similar
methods could be used and applied to circulating cell-of-origin
specific exosomes as well. The decision to administer chemotherapy
after tumor resection usually depends on an oncologist's assessment
of the presence of microscopic metastatic disease. Although
computed tomography, MRI, tissue/sentinel lymph node biopsy or
serum cancer marker analysis can each detect some level of residual
disease, the presence of circulating tumor derived exosomes can
correlate most sensitively with cancer progression and metastasis.
Noninvasive imaging of these exosomes in real time as they flow
through the peripheral vasculature could improve detection
sensitivity by enabling analysis of significantly larger blood
volumes (potentially the entire blood volume of the patient).
Exosomes isolated from bodily fluid, purified, labeled and then
reintroduced into the system can be used for identification of
early tumors not yet visible by traditional imaging methods (e.g.
early breast tumors or early ovarian tumor cells). Labeled exosomes
can also be used as a signal to identify tumors of metastatic
potential.
[0870] In one embodiment, exosomes can be labeled by
peptide/antigen targeting to label the exosomes either in vivo or
in vitro and then reintroduce in the circulatory system for the
purposes of diagnostic imaging. Suitable labels may include those
that may be detected by intravital flow cytometry, X-radiography,
NMR, PET/SPECT or MRI. For X-radiographic techniques, suitable
labels include any radioisotope that emits detectable radiation but
that is not overtly harmful to the patient, such as barium or
cesium, for example. Suitable labels for NMR or MRI generally
include those with a detectable characteristic spin, such as
deuterium. Suitable imaging systems may be used to detect the
labeled exosomes in the circulatory system.
[0871] The labeled exosomes can be administered by arterial or
venous injection, and can be formulated as a sterile, pyrogen-free,
parenterally acceptable aqueous solution. The preparation of such
parenterally acceptable solutions, having due regard to pH,
isotonicity, stability, and the like, is within the skill in the
art. A preferred formulation for intravenous injection should
contain, in addition to the labeled exosomes, an isotonic vehicle
such as Sodium Chloride Injection, Ringer's Injection, Dextrose
Injection, Dextrose and Sodium Chloride Injection, Lactated
Ringer's Injection, or other vehicle. An effective amount of
labeled exosomes can be an amount sufficient to yield an acceptable
image using equipment which is available for clinical use. An
effective amount of the labeled exosomes may be administered in
more than one injection. Effective amounts of the labeled exosomes
will vary according to factors such as the degree of susceptibility
of the individual, the age, sex, and weight of the individual,
idiosyncratic responses of the individual, the dosimetry. Effective
amounts of the labeled exosomes will also vary according to
instrument and film-related factors.
[0872] In a further embodiment, intravital flow cytometry can be
used to noninvasively count labeled exosomes in vivo as they flow
through the peripheral vasculature. The method can include i.v.
injection of a tumor-specific fluorescent ligand followed by
multiphoton fluorescence imaging of superficial blood vessels to
quantitate the flowing exosomes. Intravital flow cytometry for
detection of exosomes circumvents sampling limitations and renders
quantitation of rare events statistically significant by enabling
analysis of the majority of a patient's blood volume (.apprxeq.5
liters).
[0873] Many human carcinomas overexpress a receptor for the vitamin
folic acid (>90% of ovarian and endometrial cancers, 86% of
kidney cancers, 78% of nonsmall cell lung cancers, etc).
Alternatively, normal tissues either lack measurable folate
receptors (FR) or express FR at a site that is inaccessible to
parenterally administered drugs. Because FR-expressing cancer
masses can be selectively labeled in vivo by injection of either
radioactive or fluorescent folate conjugates that bind FR with
nanomolar affinity it is possible for single exosomes to bind
sufficient numbers of folate conjugates to allow their detection in
vivo as they pass through a patient's peripheral vasculature. To
increase signal-to-background ratios, a tumor-specific probe is
used that rapidly clear circulation if left uncaptured by exosomes.
For this purpose, folate-dye conjugates (e.g. folate-AlexaFluor
488) conjugates can be used because tumor-specific antibodies were
found to promote phagocytic clearance of the exosomes to which they
bound, thereby causing significant underestimation of exosomes
counts. To further ensure that the cells labeled with
folate-AlexaFluor 488 are indeed malignant, monoclonal anti-human
antibodies can be used (e.g. CA125 for ovarian cancer) plus an
appropriate secondary antibody conjugated to rhodamine-X.
[0874] In another embodiment, exosomes can be labeled in vivo by
intravenously introducing a labeling agent that specifically
targets the exosome for downstream imaging applications similar to
those described above.
Reimbursement Codes
[0875] In one embodiment, the use of exosomes as diagnostic,
therapy-related or prognostic markers in the identification of
disease, disease stage, progression or therapy can be assigned
specific U.S. Medicare reimbursement codes. In one embodiment, the
isolation and the use of cell-of-origin specific exosomes are used.
The reimbursement code may be a code developed under the National
Council for Prescription Drug Programs Professional Pharmacy
Services (NCPDP/PPS code). A reimbursement code can be a diagnosis
code utilized or recognized by an insurance company, for example.
The diagnostic code is assignable based upon a reimbursement
requirement by a third party. Alternatively, the diagnostic code is
assignable based upon a need to analyze the utilization of medical
resources. A set of diagnosis codes can conform to and/or be
compatible with, for example, ICD (International Classification of
Diseases) codes, 9th Edition, Clinical Modification, (ICD-9-CM),
Volumes 1, 2 and 3; ICD-10, which is maintained and distributed by
the U.S. Health and Human Services department; HCPCS (Health Care
Financing Administration Common Procedure Coding System); NDC
(National Drug Codes); CPT-4 (Current Procedural Terminology);
Fourth Edition CDPN (Code on Dental Procedures and Nomenclature);
SNOMED-RT "Systematicized Nomenclature of Medicine, Reference
Terminology" by the College of American Pathologists; UMLS (Unified
Medical Language System), by the National Library of Medicine;
LOINC Logical Observation Identifiers, Names, and Codes;
Regenstrief Institute and the Logical Observation Identifiers Names
and Codes (LOINC.RTM.) Committee; Clinical Terms also known as
"Read Codes"; DIN Drug Identification Numbers; Reimbursement
Classifications including DRGs (Diagnosis Related Groups); CDT
Current Dental Terminology; NIC (Nursing intervention codes); or
Commercial Vocabulary Services (such as HealthLanguage by
HealthLanguage Inc.), each of which is incorporated by reference in
its entirety.
[0876] In one embodiment, each of the isolation methods for
exosomes described herein can be assigned a specific reimbursement
code. For example, each of the isolation methods of cell-of-origin
specific exosomes described herein can be assigned a specific
reimbursement code. In another embodiment, the specific
bio-signature(s) obtained from the analysis of exosomes can be
assigned a specific reimbursement code. In yet another embodiment,
the specific bio-signature(s) obtained from the analysis of
cell-of-origin specific exosomes can be assigned a specific
reimbursement code. Alternatively, kits for the detection of a
particular bio-signature of exosomes in a biological sample can be
assigned to a specific reimbursement code. Alternatively, kits for
the detection of a particular bio-signature of specific
cell-of-origin exosomes in a biological sample can be assigned to a
specific reimbursement code.
[0877] While preferred embodiments of the present invention have
been shown and described herein, it will be obvious to those
skilled in the art that such embodiments are provided by way of
example only. Numerous variations, changes, and substitutions will
now occur to those skilled in the art without departing from the
invention. It should be understood that various alternatives to the
embodiments of the invention described herein may be employed in
practicing the invention. It is intended that the following claims
define the scope of the invention and that methods and structures
within the scope of these claims and their equivalents be covered
thereby.
EXAMPLES
Example 1
Purification of Exosomes from Prostate Cancer Cell Lines
[0878] Prostate cancer cell lines are cultured for 3-4 days in
culture media containing 20% FBS (fetal bovine serum) and 1% P/S/G.
The cells are then pre-spun for 10 minutes at 400.times.g at
4.degree. C. The supernatant is kept and centrifuged for 20 minutes
at 2000.times.g at 4. The supernatant containing exosomes can be
concentrated using a Millipore Centricon Plus-70 (Cat # UFC710008
Fisher).
[0879] The Centricon is pre washed with 30 mls of PBS at
1000.times.g for 3 minutes at room temperature. Next, 15-70 mls of
the pre-spun cell culture supernatant is poured into the
Concentrate Cup and is centrifuged in a Swing Bucket Adapter
(Fisher Cat #75-008-144) for 30 minutes at 1000.times.g at room
temperature.
[0880] The flow through in the Collection Cup is poured off. The
volume in the Concentrate Cup is brought back up to 60 mls with any
additional supernatant. The Concentrate Cup is centrifuged for 30
minutes at 1000.times.g at room temperature until all of the cell
supernatant is concentrated.
[0881] The Concentrate Cup is washed by adding 70 m-1s of PBS and
centrifuged for 30-60 minutes at 1000.times.g until approximately 2
mls remains. The exosomes are removed from the filter by inverting
the concentrate into the small sample cup and centrifuge for 1
minute at 4.degree. C. The volume is brought up to 25 mls with PBS.
The exosomes are now concentrated and are added to a 30% Sucrose
Cushion.
[0882] To make a cushion, 4 mls of Tris/30% Sucrose/D2O solution
(30 g protease-free sucrose, 2.4 g Tris base, 50 ml D2O, adjust pH
to 7.4 with ION NCL drops, adjust volume to 100 mls with D2O,
sterilize by passing thru a 0.22-um filter) is loaded to the bottom
of a 30 ml V bottom thin walled Ultracentrifuge tube. The diluted
25 mls of concentrated exosomes is gently added above the sucrose
cushion without disturbing the interface and is centrifuged for 75
minutes at 100,000.times.g at 4.degree. C. The .about.25 mls above
the sucrose cushion is carefully removed with a 10 ml pipet and the
.about.3.5 mls of exosome is collected with a fine tip transfer
pipet (SAMCO 233) and transferred to a fresh ultracentrifuge tube,
where 30 mls PBS is added. The tube is centrifuged for 70 minutes
at 100,000.times.g at 4.degree. C. The supernatant is poured off
carefully. The pellet is resuspended in 200 ul PBS and can be
stored at 4.degree. C. or used for assays. A BCA assay (1:2) can be
used to determine protein content and Western blotting or electron
micrography can be used to determine exosome purification.
Example 2
Purification of Exosomes from VCaP and 22Rv1
[0883] Exosomes from Vertebral-Cancer of the Prostate (VCaP) and
22Rv1, a human prostate carcinoma cell line, derived from a human
prostatic carcinoma xenograft (CWR22R) were collected by
ultracentrifugation by first diluting plasma with an equal volume
of PBS (1 ml). The diluted fluid was transferred to a 15 ml falcon
tube and centrifuged 30 minutes at 2000.times.g 4.degree. C. The
supernatant (.about.2 mls) was transferred to an ultracentrifuge
tube 5.0 ml PA thinwall tube (Sorvall #03127) and centrifuged at
12,000.times.g, 4.degree. C. for 45 minutes.
[0884] The supernatant (.about.2 mls) was transferred to a new 5.0
ml ultracentrifuge tubes and filled to maximum volume with addition
of 2.5 mls PBS and centrifuged for 90 minutes at 110,000.times.g,
4.degree. C. The supernatant was poured off without disturbing the
pellet and the pellet resuspended with 1 ml PBS. The tube was
filled to maximum volume with addition of 4.5 ml of PBS and
centrifuged at 110,000.times.g, 4.degree. C. for 70 minutes.
[0885] The supernatant was poured off without disturbing the pellet
and an additional 1 ml of PBS was added to wash the pellet. The
volume was increased to maximum volume with the addition of 4.5 mls
of PBS and centrifuged at 110,000.times.g for 70 minutes at
4.degree. C. The supernatant was removed with P-1000 pipette until
.about.100 .mu.l of PBS was in the bottom of the tube. The
.about.90 .mu.l remaining was removed with P-200 pipette and the
pellet collected with the .about.10 .mu.l of PBS remaining by
gently pipetting using a P-20 pipette into the microcentrifuge
tube. The residual pellet was washed from the bottom of a dry tube
with an additional 5 .mu.l of fresh PBS and collected into
microcentrifuge tube and suspended in phosphate buffered saline
(PBS) to a concentration of 500 .mu.g/ml.
Example 3
Plasma Collection and Exosome Purification
[0886] Blood is collected via standard veinpuncture in a 7 ml
K2-EDTA tube. The sample is spun at 400 g for 10 minutes in a
4.degree. C. centrifuge to separate plasma from blood cells
(SORVALL Legend RT+ centrifuge). The supernatant (plasma) is
transferred by careful pipetting to 15 ml Falcon centrifuge tubes.
The plasma is spun at 2,000 g for 20 minutes and the supernatant is
collected.
[0887] For storage, approximately 1 ml of the plasma (supernatant)
is aliquoted to a cryovials, placed in dry ice to freeze them and
stored in -80.degree. C. Before exosome purification, if samples
were stored at -80.degree. C., samples are thawed in a cold water
bath for 5 minutes. The samples are mixed end over end by hand to
dissipate insoluble material.
[0888] In a first prespin, the plasma is diluted with an equal
volume of PBS (example, approximately 2 ml of plasma is diluted
with 2 ml of PBS). The diluted fluid is transferred to a 15 ml
Falcon tube and centrifuged for 30 minutes at 2000.times.g at
4.degree. C.
[0889] For a second prespin, the supernatant (approximately 4 mls)
is carefully transferred to a 50 ml Falcon tube and centrifuged at
12,000.times.g at 4.degree. C. for 45 minutes in a Sorval.
[0890] In the isolation step, the supernatant (approximately 2 mls)
is carefully transferred to a 5.0 ml ultracentrifuge PA thinwall
tube (Sorvall #03127) using a P1000 pipette and filled to maximum
volume with an additional 0.5 mls of PBS. The tube is centrifuged
for 90 minutes at 110,000.times.g at 4.degree. C.
[0891] In the first wash, the supernatant is poured off without
disturbing the pellet. The pellet is resuspended or washed with 1
ml PBS and the tube is filled to maximum volume with an additional
4.5 ml of PBS. The tube is centrifuged at 110,000.times.g at
4.degree. C. for 70 minutes. A second wash is performed by
repeating the same steps.
[0892] The exosomes are collected by removing the supernatant with
P-1000 pipette until approximately 100 .mu.l of PBS is in the
bottom of the tube. Approximately 90 .mu.l 1 of the PBS is removed
and discarded with P-200 pipette. The pellet and remaining PBS is
collected by gentle pipetting using a P-20 pipette. The residual
pellet is washed from the bottom of the dry tube with an additional
5 .mu.l of fresh PBS and collected into a microcentrifuge tube.
Example 4
Analysis of Exosomes Using Antibody-Coupled Microspheres and
Directly Conjugated Antibodies
[0893] This example demonstrates the use of particles coupled to an
antibody, where the antibody captures the exosomes (see for
example, FIG. 64A). An antibody, the detector antibody, is directly
coupled to a label, and is used to detect a biomarker on the
captured exosome.
[0894] First, an antibody-coupled microsphere set is selected
(Luminex, Austin, Tex.). The microsphere set can comprise various
antibodies, and thus allows multiplexing. The microspheres are
resuspended by vortex and sonication for approximately 20 seconds.
A Working Microsphere Mixture is prepared by diluting the coupled
microsphere stocks to a final concentration of 100 microspheres of
each set/.mu.L in Startblock (Pierce (37538)). (Note: 50 .mu.L of
Working Microsphere Mixture is required for each well.) Either
PBS-1% BSA or PBS-BN(PBS, 1% BSA, 0.05% Azide, pH 7.4) may be used
as Assay Buffer.
[0895] A 1.2 .mu.m Millipore filter plate is pre-wet with 100
.mu.l/well of PBS-1% BSA (Sigma (P3688-10PAK+0.05% NaAzide
(S8032))) and aspirated by vacuum manifold. An aliquot of 50 .mu.l
of the Working Microsphere Mixture is dispensed into the
appropriate wells of the filter plate (Millipore Multiscreen HTS
(MSBVN1250)). A 50 .mu.l aliquot of standard or sample is dispensed
into to the appropriate wells. The filter plate is covered and
incubated for 60 minutes at room temperature on a plate shaker. The
plate is covered with a sealer, placed on the orbital shaker and
set to 900 for 15-30 seconds to re-suspend the beads. Following
that the speed is set to 550 for the duration of the
incubation.
[0896] The supernatant is aspirated by vacuum manifold (less than 5
inches Hg in all aspiration steps). Each well is washed twice with
100 .mu.l of PBS-1% BSA (Sigma (P3688-10PAK+0.05% NaAzide (S8032)))
and is aspirated by vacuum manifold. The microspheres are
resuspended in 50 .mu.L of PBS-1% BSA (Sigma (P3688-10PAK+0.05%
NaAzide (S8032))). The PE conjugated detection antibody is diluted
to 4 .mu.g/mL (or appropriate concentration) in PBS-1% BSA (Sigma
(P3688-10PAK+0.05% NaAzide (S8032))). (Note: 50 .mu.L of diluted
detection antibody is required for each reaction.) A 50 .mu.l
aliquot of the diluted detection antibody is added to each well.
The filter plate is covered and incubated for 60 minutes at room
temperature on a plate shaker. The filter plate is covered with a
sealer, placed on the orbital shaker and set to 900 for 15-30
seconds to re-suspend the beads. Following that the speed is set to
550 for the duration of the incubation. The supernatant is
aspirated by vacuum manifold. The wells are washed twice with 100
.mu.l of PBS-1% BSA (Sigma (P3688-10PAK+0.05% NaAzide (S8032))) and
aspirated by vacuum manifold. The microspheres are resuspended in
100 .mu.l of PBS-1'% BSA (Sigma (P3688-10PAK+0.05% NaAzide
(S8032))). The microspheres are analyzed on a Luminex analyzer
according to the system manual.
Example 5
Analysis of Exosomes Using Antibody-Coupled Microspheres and
Biotinylated Antibody
[0897] This example demonstrates the use of particles coupled to an
antibody, where the antibody captures the exosomes. An antibody,
the detector antibody, is biotinylated. A label coupled to
streptavidin is used to detect the biomarker.
[0898] First, the appropriate antibody-coupled microsphere set is
selected (Luminex, Austin, Tex.). The microspheres are resuspended
by vortex and sonication for approximately 20 seconds. A Working
Microsphere Mixture is prepared by diluting the coupled microsphere
stocks to a final concentration of 50 microspheres of each
set/.mu.L in Startblock (Pierce (37538)). (Note: 50 .mu.l of
Working Microsphere Mixture is required for each well.) Beads in
Start Block should be blocked for 30 minutes and no more than 1
hour.
[0899] A 1.2 .mu.m Millipore filter plate is pre-wet with 100
.mu.l/well of PBS-1% BSA+Azide (PBS-BN)((Sigma (P3688-10PAK+0.05%
NaAzide (S8032))) and is aspirated by vacuum manifold. A 50 .mu.l
aliquot of the Working Microsphere Mixture is dispensed into the
appropriate wells of the filter plate (Millipore Multiscreen HTS
(MSBVN1250)). A 50 .mu.l aliquot of standard or sample is dispensed
to the appropriate wells. The filter plate is covered with a seal
and is incubated for 60 minutes at room temperature on a plate
shaker. The covered filter plate is placed on the orbital shaker
and set to 900 for 15-30 seconds to re-suspend the beads. Following
that, the speed is set to 550 for the duration of the
incubation.
[0900] The supernatant is aspirated by a vacuum manifold (less than
5 inches Hg in all aspiration steps). Aspiration can be done with
the Pall vacuum manifold. The valve is place in the full off
position when the plate is placed on the manifold. To aspirate
slowly, the valve is opened to draw the fluid from the wells, which
takes approximately 3 seconds for the 100 .mu.l of sample and beads
to be fully aspirated from the well. Once all of the sample is
drained, the purge button on the manifold is pressed to release
residual vacuum pressure from the plate.
[0901] Each well is washed twice with 100 .mu.l of PBS-1% BSA+Azide
(PBS-BN)(Sigma (P3688-10PAK+0.05% NaAzide (S8032))) and is
aspirates by vacuum manifold. The microspheres are resuspended in
50 .mu.l of PBS-1% BSA+Azide (PBS-BN)((Sigma (P3688-10PAK+0.05%
NaAzide (S8032)))
[0902] The biotinylated detection antibody is diluted to 4 .mu.g/mL
in PBS-1% BSA+Azide (PBS-BN)((Sigma (P3688-10PAK+0.05% NaAzide
(S8032))). (Note: 50 .mu.l of diluted detection antibody is
required for each reaction.) A 50 .mu.l aliquot of the diluted
detection antibody is added to each well.
[0903] The filter plate is covered with a sealer and is incubated
for 60 minutes at room temperature on a plate shaker. The plate is
placed on the orbital shaker and set to 900 for 15-30 seconds to
re-suspend the beads. Following that, the speed is set to 550 for
the duration of the incubation.
[0904] The supernatant is aspirated by vacuum manifold. Aspiration
can be done with the Pall vacuum manifold. The valve is place in
the full off position when the plate is placed on the manifold. To
aspirate slowly, the valve is opened to draw the fluid from the
wells, which takes approximately 3 seconds for the 100 ul of sample
and beads to be fully aspirated from the well. Once all of the
sample is drained, the purge button on the manifold is pressed to
release residual vacuum pressure from the plate.
[0905] Each well is washed twice with 100 .mu.l of PBS-1% BSA+Azide
(PBS-BN)((Sigma (P3688-10PAK+0.05% NaAzide (S8032))) and is
aspirated by vacuum manifold. The microspheres are resuspended in
50 .mu.l of PBS-1% BSA (Sigma (P3688-10PAK+0.05% NaAzide
(S8032))).
[0906] The streptavidin-R-phycoerythrin reporter (Molecular Probes
1 mg/ml) is diluted to 4 .mu.g/mL in PBS-1% BSA+Azide (PBS-BN)(.
(Note: 50 .mu.l of diluted streptavidin-R-phycoerythrin is required
for each reaction.) A 50 .mu.l aliquot of the diluted
streptavidin-R-phycoerythrin is added to each well.
[0907] The filter plate is covered with a sealer and is incubated
for 60 minutes at room temperature on a plate shaker. The plate is
placed on the orbital shaker and set to 900 for 15-30 seconds to
re-suspend the beads. Following that, the speed is set to 550 for
the duration of the incubation.
[0908] The supernatant is aspirated by vacuum manifold. Aspiration
can be done with the Pall vacuum manifold. The valve is place in
the full off position when the plate is placed on the manifold. To
aspirate slowly, the valve is opened to draw the fluid from the
wells, which takes approximately 3 seconds for the 100 ul of sample
and beads to be fully aspirated from the well. Once all of the
sample is drained, the purge button on the manifold is pressed to
release residual vacuum pressure from the plate.
[0909] Each well is washed twice with 100 .mu.l of PBS-1% BSA+Azide
(PBS-BN)((Sigma (P3688-10PAK+0.05% NaAzide (S8032))) and is
aspirated by vacuum manifold. The microspheres are resuspended in
100 .mu.l of PBS-1% BSA+Azide (PBS-BN)((Sigma (P3688-10PAK+0.05%
NaAzide (S8032))) and analyzed on the Luminex analyzer according to
the system manual.
Example 6
Determining Bio-Signatures for Prostate Cancer Using
Multiplexing
[0910] The exosomes samples obtained using methods as described in
Example 1-3 are used in multiplexing assays as described in
Examples 4 and 5. The detection antibodies used are CD63, CD9,
CD81, B7H3 and EpCam. The capture antibodies used are CD9, PSCA,
TNFR, CD63 2X, B7H3, MFG-E8, EpCam 2.times., CD63, Rab, CD81,
SETAP, PCSA, PSMA, 5T4, Rab IgG (control) and IgG (control),
resulting in 100 combinations to be screened (FIG. 64B).
[0911] Ten prostate cancer patients and 12 normal control patients
were screened. The results are depicted in FIG. 68 and FIG. 70A.
FIG. 70B depicts the results of using PCSA capture antibodies (FIG.
70B, left graph) or EpCam capture antibodies (FIG. 70B, right
graph), and detection using one or more detector antibodies. The
sensitivity and specificity of the different combinations is
depicted in FIG. 73.
Example 7
Determining Bio-Signatures for Colon Cancer Using Multiplexing
[0912] The exosomes samples obtained using methods as described in
Example 3 is used in multiplexing assays as described in Examples 4
and 5. The detection antibodies used are CD63, CD9, CD81, B7H3 and
EpCam. The capture antibodies used are CD9, PSCA, TNFR, CD63 2X,
B7H3, MFG-E8, EpCam 2X, CD63, Rab, CD81, STEAP, PCSA, PSMA, 5T4,
Rab IgG (control) and IgG (control), resulting in 100 combinations
to be screened.
[0913] The results are depicted in FIGS. 69, 71, and 72. The
sensitivity of the different combinations is depicted in FIG.
74.
Example 9
Capture of Exosomes Using Magnetic Beads
[0914] Exosomes isolated as described in Example 2 are used.
Approximately 40 ul of the exosomes are incubated with
approximately 5 ug (.about.50 .mu.l) of EpCam antibody coated Dynal
beads (Invitrogen, Carlsbad, Calif.) and 50 .mu.l of Starting
Block. The exosomes and beads are incubated with shaking for 2
hours at 45.degree. C. in a shaking incubator. The tube containing
the Dynal beads is placed on the magnetic separator for 1 minute
and the supernatant removed. The beads are washed twice and the
supernatant removed each time. Wash beads twice, discarding the
supernatant each time.
Example 10
Detection of TMPRSS2:ERG in Exosomes
[0915] The RNA from the bead-bound exosomes of Example 9 was
isolated using the Qiagen miRneasy.TM. kit, (Cat. No. 217061),
according to the manufacturer's instructions.
[0916] The exosomes are homogenized in QIAzol.TM. Lysis Reagent
(Cat. No. 79306). After addition of chloroform, the homogenate is
separated into aqueous and organic phases by centrifugation. RNA
partitions to the upper, aqueous phase, while DNA partitions to the
interphase and proteins to the lower, organic phase or the
interphase. The upper, aqueous phase is extracted, and ethanol is
added to provide appropriate binding conditions for all RNA
molecules from 18 nucleotides (nt) upwards. The sample is then
applied to the RNeasy.TM. Mini spin column, where the total RNA
binds to the membrane and phenol and other contaminants are
efficiently washed away. High quality RNA is then eluted in
RNase-free water.
[0917] RNA from the VCAP bead captured exosomes was measured with
the Taqman TMPRSS:ERG fusion transcript assay (Kirsten D. Mertz et
al. Neoplasia. 2007 March; 9(3): 200-206.). RNA from the 22Rv1 bead
captured exosomes was measured with the Taqman SPINK1 transcript
assay (Scott A. Tomlin et al. Cancer Cell 2008 June 13(6):519-528).
The GAPDH transcript (control transcript) was also measured for
both sets of exosomal RNA.
[0918] Higher CT values indicate lower transcript expression. One
change in cycle threshold (CT) is equivalent to a 2 fold change, 3
CT difference to a 4 fold change, and so forth, which can be
calculated with the following: 2 .sup.CT1-CT2. This experiment
shows a difference in CT of the expression of the fusion transcript
TMPRSS:ERG and the equivalent captured with the IgG2 negative
control bead (FIG. 75). The same comparison of the SPINK1
transcript in 22RV1 exosomes shows a CT difference of 6.14 for a
fold change of 70.5 (FIG. 75C).
Example 11
MicroRNA Profiles in Exosomes
[0919] Exosomes were collected by ultracentrifugation from 22Rv1,
LNCaP, Vcap and normal plasma (pooled from 16 donors) as described
in Examples 1 and 2. RNA was extracted using the Exiqon miR
isolation kit (Cat. No. 300110, 300111). Equals amounts of exosomes
(30 .mu.g) were used as determined by BCA assay.
[0920] Equal volumes (5 .mu.l) were put into a
reverse-transcription reaction for microRNA. The
reverse-transcriptase reactions were diluted in 81 .mu.l of
nuclease-free water and then 9 .mu.l of this solution was added to
each individual miR assay. MiR-629 was found to only be expressed
in PCa (prostate cancer) exosomes and was virtually undetectable in
normal plasma exosomes. MiR-9 was found to be highly overexpressed
(.about.704 fold increase over normal as measured by copy number)
in all PCa cell lines, and has very low expression in normal plasma
exosomes. The top ten differentially expressed miRNAs are depicted
in FIG. 76.
Example 12
MicroRNA Profiles of Magentic EpCam-Captured Exosomes
[0921] The bead-bound exosomes of Example 9 was placed in
QIAzol.TM. Lysis Reagent (Cat. #79306). An aliquot of 125 fmol of
c. elegans miR-39 was added. The RNA from the exosomes was isolated
using the Qiagen miRneasy.TM. kit, (Cat. #217061), according to the
manufacturer's instructions, and eluted in 30 ul RNAse free
water.
[0922] 10 .mu.l of the purified RNA was placed into a
pre-amplification reaction for miR-9, miR-141 and miR-629 using a
Veriti 96-well thermocycler. A 1:5 dilution of the
pre-amplification solution was used to set up a qRT-PCR reaction
for miR9 (ABI 4373285), miR-141 (ABI 4373137) and miR-629 (ABI
4380969) as well as c. elegans miR-39 (ABI 4373455). The results
were normalized to the c. elegans results for each sample.
Example 13
MicroRNA Profiles of CD9-Captured Exosomes
[0923] The CD9 coated Dynal beads (Invitrogen, Carlsbad, Calif.)
were used instead of EpCam coated beads as in Example 12. Exosomes
from prostate cancer patients, LNCaP, or normal purified exomes
were incubated with the CD9 coated beads and the RNA isolated as
described in Example 12. The expression of miR-21 and miR-141 was
detected by qRT-PCR and the results depicted in FIGS. 77 and
78.
Example 14
Reference Values for Prostate Cancer
[0924] Fourteen stage 3 prostate cancer subjects, eleven benign
prostate hyperplasia (BPH) samples, and 15 normal samples were
tested. Exosome samples were obtained using methods as described in
Example 3 and used in multiplexing assays, such as described in
Examples 4 and 5. The samples were analyzed to determine four
criteria 1) if the sample has overexpressed exosomes, 2) if the
sample has overexpressed prostate exosomes, 3) if the sample has
overexpressed cancer exosomes, and 4) if the sample is reliable. If
the sample met all four criteria, the categorization of the sample
as positive for prostate cancer had varying sensitivities and
specificities, depending on the different bio-signatures present
for a sample as described below (Cancer-1, Cancer-2, and Cancer-3,
FIG. 79). The four criteria were as follows:
Exosome Overexpression
[0925] The mean fluorescence intensities (MFIs) for a sample in
three assays were averaged to determine a value for the sample.
Each assay used a different capture antibody. The first used a CD9
capture antibody, the second a CD81 capture antibody, and the third
a CD63 antibody. The same combination of detection antibodies was
used for each assay, antibodies for CD9, CD81, and CD63. If the
average value obtained for the three assays was greater than 3000,
the sample was categorized as having overexpressed exosomes (FIG.
79, Exosome).
[0926] Prostate Exosome Overexpression
[0927] The MFIs for a sample in two assays were averaged to
determine a value for the sample. Each assay used a different
capture antibody. The first used a PCSA capture antibody and the
second used a PSMA capture antibody. The same combination of
detection antibodies was used for each assay, antibodies for CD9,
CD81, and CD63. If the average value obtained for the two assays
was greater than 100, the sample was categorized as having prostate
exosomes overexpressed (FIG. 79, Prostate).
[0928] Cancer Exosome Overexpression
[0929] Three different cancer bio-signatures were used to determine
if cancer exosomes were overexpressed in a sample. The first,
Cancer-1, used an EpCam capture antibody and detection antibodies
for CD81, CD9, and CD63. The second, Cancer-2, used a CD9 capture
antibody with detection antibodies for EpCam and B7H3. If the MFI
value of a sample for any two of the three cancer bio-signatures
was above a reference value, the sample was categorized as having
overexpressed cancer (see FIG. 79, Cancer-1, Cancer-2,
Cancer-3).
[0930] Reliability of Sample
[0931] Two quality control measures, QC-1 and QC-2, were determined
for each sample. If the sample met one of them; the sample was
categorized as reliable.
[0932] For QC-1, the sum of all the MFIs of 7 assays was
determined. Each of the 7 assays used detection antibodies for CD59
and PSMA. The capture antibody used for each assay was CD63, CD81,
PCSA, PSMA, STEAP, B7H3, and EpCam. If the sum was greater than
4000, the sample was not reliable and not included.
[0933] For QC-2, the sum of all the MFIs of 5 assays was
determined. Each of the 5 assays used detection antibodies for CD9,
CD81 and CD63. The capture antibody used for each assay was PCSA,
PSMA, STEAP, B7H3, and EpCam. If the sum was greater than 8000, the
sample was not reliable and not included.
[0934] The sensitivity and specificity for samples with BPH and
without BPH samples after a sample met the criteria as described
herein, are shown in FIG. 79.
[0935] It will also be understood that the foregoing description is
of exemplary embodiments of the invention and that the invention is
not limited to the specific forms shown or described herein.
Various modifications may be made in the design, arrangement, and
type of elements disclosed herein, as well as the steps of
utilizing the invention without departing from the scope of the
invention as expressed in the appended claims.
* * * * *
References