U.S. patent application number 11/040267 was filed with the patent office on 2005-07-28 for genes differentially expressed in secretory versus proliferative endometrium.
This patent application is currently assigned to Affymetrix, INC.. Invention is credited to Mahadevappa, Mamatha, Warrington, Janet A..
Application Number | 20050164272 11/040267 |
Document ID | / |
Family ID | 27498005 |
Filed Date | 2005-07-28 |
United States Patent
Application |
20050164272 |
Kind Code |
A1 |
Warrington, Janet A. ; et
al. |
July 28, 2005 |
Genes differentially expressed in secretory versus proliferative
endometrium
Abstract
The present invention compares expression profiles from matched
samples to identify differential gene expression. Samples are
matched according to physiological, pharmacological and/or disease
state. Comparison of matched samples eliminates gene expression
differences that are the result of changes in variables that are
not of interest. The gene expression differences that remain can be
attributed with a high degree of confidence to the unmatched
variation. The gene expression differences thus identified can be
used for example to diagnose disease, identify physiological state,
design drugs, and monitor therapies.
Inventors: |
Warrington, Janet A.; (Los
Altos, CA) ; Mahadevappa, Mamatha; (Cupertino,
CA) |
Correspondence
Address: |
AFFYMETRIX, INC
ATTN: CHIEF IP COUNSEL, LEGAL DEPT.
3380 CENTRAL EXPRESSWAY
SANTA CLARA
CA
95051
US
|
Assignee: |
Affymetrix, INC.
Santa Clara
CA
|
Family ID: |
27498005 |
Appl. No.: |
11/040267 |
Filed: |
January 19, 2005 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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11040267 |
Jan 19, 2005 |
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09734752 |
Dec 11, 2000 |
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6884578 |
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60193719 |
Mar 31, 2000 |
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60231367 |
Sep 8, 2000 |
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60240678 |
Oct 13, 2000 |
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Current U.S.
Class: |
435/6.11 ;
424/9.1; 435/6.14 |
Current CPC
Class: |
C12Q 1/6886 20130101;
C12Q 2600/158 20130101 |
Class at
Publication: |
435/006 ;
424/009.1 |
International
Class: |
C12Q 001/68; A61K
049/00 |
Claims
1-9. (canceled)
10. A method of diagnosing endometrial adenocarcinoma in a first
endometrial sample comprising: measuring the gene expression in the
first endometrial sample of each of the following genes: MIF,
cyclin A1, MRG1, HOX1, Alpha 2 collagen type VI, Adducin, Cyclin B
and PKC zeta, to obtain a gene expression measurement for each of
said genes in the first endometrial sample; comparing the gene
expression measurement of each of said genes in the first
endometrial sample to a gene expression measurement of the same
gene in a second endometrial sample from normal endometrium; and
identifying the first endometrial sample as being endometrial
adenocarcinoma if MIF, cyclin A1, cyclin B1 and PKC zeta are
expressed at a higher level in the first endometrial sample than in
the second endometrial sample and MRG1, HOX1, Alpha 2 collagen type
VI and Adducin are expressed at a lower level in the first
endometrial sample than in the second endometrial sample.
Description
RELATED APPLICATIONS
[0001] This application is related to and claims the priority date
of U.S. provisional application entitled Genes Differentially
Expressed in Secretory vs Proliferative Endometrium, Ser. No.
60/193,719 filed on Mar. 31, 2000, U.S. provisional application
entitled Comparison of Matched Expression Profiles, Ser. No
60/231,367, filed Sep. 8, 2000, and U.S. provisional application
entitled Genes Differentially Expressed in Secretory Versus
Proliferative Endometrium, Ser. No 60/240,678, filed on Oct. 13,
2000, all of which are hereby incorporated by reference in their
entirety for all purposes
BACKGROUND
[0002] Many cellular events and processes are characterized by
altered expression levels of one or more genes. Differences in gene
expression correlate with many physiological processes such as cell
cycle progression, cell differentiation and cell death. Changes in
gene expression patterns also correlate with changes in disease or
pharmacological state. For example, the lack of sufficient
expression of functional tumor suppressor genes and/or the over
expression of oncogene/protooncogenes could lead to tumorgenesis
(Marshall, Cell, 64 313-326 (1991), Weinberg, Science, 254
1138-1146 (1991), incorporated herein by reference for all
purposes). Thus, changes in the expression levels of particular
genes (e g oncogenes or tumor suppressors) serve as signposts for
different physiological, pharmacological and disease states.
[0003] Gene expression profiles produce a snapshot that reflects
the biological status of the sample, but in many circumstances
biological status will reflect more than one characteristic of the
sample. For example, when comparing tumor samples from two
patients, there will be changes that correlate with differences
between the states of the tumors as well as changes that correlate
with the different physiological states of the two patients. One
aspect of the current invention is directed at identifying genes
that are differentially expressed between two biological states as
being further correlated with disease, physiological or
pharmacological state.
SUMMARY OF THE INVENTION
[0004] The present invention is a method to analyze samples that
differ from one another in multiple variables in such a way as to
account for the variables and to focus on elements that are under
investigation, such as disease state for example. Comparison of
matched samples eliminates gene expression differences that are the
result of changes in variables that are not of interest. The gene
expression differences that remain can be attributed with a high
degree of confidence to the unmatched variation. The gene
expression differences thus identified can be used, for example, to
diagnose disease, identify physiological state, design drugs, and
monitor therapies.
DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS
[0005] This application relies on, and cites the disclosure of
other patent applications and literature references. These
documents are hereby incorporated by reference in their entireties
for all purposes. The practice of the present invention may employ,
unless otherwise indicated, conventional techniques of organic
chemistry, polymer technology, molecular biology (including
recombinant techniques), cell biology, biochemistry, and
immunology, which are within the skill of the art. Such
conventional techniques include polymer array synthesis,
hybridization, ligation, detection of hybridization using a label.
Specific illustrations of suitable techniques can be had by
reference to the example hereinbelow. However, other equivalent
conventional procedures can, of course, also be used. Such
conventional techniques can be found in standard laboratory manuals
such as Genome Analysis A Laboratory Manual Series (Vols I-IV),
Using Antibodies. A Laboratory Manual, Cells. A Laboratory Manual,
PCR Primer A Laboratory Manual, and Molecular Cloning A Laboratory
Manual (all from Cold Spring Harbor Laboratory Press), all of which
are herein incorporated in their entirety by reference.
[0006] This section presents a detailed description of the
preferred invention and its application. This description is by way
of several exemplary illustrations, in increasing detail and
specificity, and of the general methods of this invention. These
examples are non-limiting, and related variants that will be
apparent to one of skill in the art are intended to be encompassed
by the appended claims. Following these examples are descriptions
of embodiments of the data gathering steps that accompany the
general methods.
[0007] Description of Concepts
[0008] Nucleic acids according to the present invention may include
any polymer or oligomer of pyrimidine and purine bases, preferably
cytosine, thymine, and uracil, and adenine and guanine,
respectively. See Albert L Lehninger, PRINCIPLES OF BIOCHEMISTRY,
at 793-800 (Worth Pub 1982). Indeed, the present invention
contemplates any deoxynbonucleotide, ribonucleotide or peptide
nucleic acid component, and any chemical variants thereof, such as
methylated, hydroxymethylated or glucosylated forms of these bases,
and the like. The polymers or oligomers may be heterogeneous or
homogeneous in composition, and may be isolated from
naturally-occurring sources or may be artificially or synthetically
produced. In addition, the nucleic acids may be DNA or RNA, or a
mixture thereof, and may exist permanently or transitionally in
single-stranded or double-stranded form, including homoduplex,
heteroduplex, and hybrid states. Oligonucleotide and polynucleotide
are included in this definition and relate to two or more nucleic
acids in a polynucleotide.
[0009] Pepetide. A polymer in which the monomers are alpha amino
acids and which are joined together through amide bonds,
alternatively referred to as a polypeptide. In the context of this
specification it should be appreciated that the amino acids may be,
for example, the L-optical isomer or the D-optical isomer. Peptides
are often two or more amino acid monomers long, and often 4 or more
amino acids long, often 5 or more amino acids long, often 10 or
more amino acids long, often 15 or more amino acids long, and often
20 or more amino acid monomers long, for example. Standard
abbreviations for amino acids are used (e g, P for proline). These
abbreviations are included in Stryer, Biochemistry, Third Ed, 1988,
which is incorporated herein by reference for all purposes.
[0010] Array. An array comprises a solid support with peptide or
nucleic acid probes attached to said support. Arrays typically
comprise a plurality of different nucleic acid or peptide probes
that are coupled to a surface of a substrate in different, known
locations. These arrays, also described as "microarrays" or
colloquially "chips" have been generally described in the art, for
example, U.S. Pat. Nos. 5,143,854, 5,445,934, 5,744,305, 5,677,195,
6,040,193, 5,424,186 and Fodor et al, Science, 251 767-777 (1991).
Each of which is incorporated by reference in its entirety for all
purposes. These arrays may generally be produced using mechanical
synthesis methods or light directed synthesis methods which
incorporate a combination of photolithographic methods and solid
phase synthesis methods. Techniques for the synthesis of these
arrays using mechanical synthesis methods are described in, e g,
U.S. Pat. No 5,384,261, incorporated herein by reference in its
entirety for all purposes. Although a planar array surface is
preferred, the array may be fabricated on a surface of virtually
any shape or even a multiplicity of surfaces. Arrays may be
peptides or nucleic acids on beads, gels, polymeric surfaces,
fibers such as fiber optics, glass or any other appropriate
substrate, see U.S. Pat. Nos. 5,770,358, 5,789,162, 5,708,153,
6,040,193 and 5,800,992, which are hereby incorporated in their
entirety for all purposes. Arrays may be packaged in such a manner
as to allow for diagnostics or other manipulation of an all
inclusive device, see for example, U.S. Pat. Nos. 5,856,174 and
5,922,591 incorporated in their entirety by reference for all
purposes. See also U.S. patent application Ser. No 09/545,207,
filed Apr. 7, 2000 for additional information concerning arrays,
their manufacture, and their characteristics. It is hereby
incorporated by reference in its entirety for all purposes.
[0011] Physiological state or physiological status. According to
the present invention, a physiological state refers to any normal
biological state of a cell or organism. The parameters that are
considered in determining physiological state include but are not
limited to age, gender, ethnic origin, and reproductive state,
which includes, but is not limited to menstrual state, post-partum,
pregnancy, lactation, and nulliparity. For the purposes of this
invention the physiological state may be determined by a single
indicator. For example, the age of a patient may be the only
indicator of physiological state used to categorize a reference
sample. Preferably several indicators of physiological state will
be used to categorize a reference sample. Methods to determine the
physiological state of a sample include but are not limited to
measuring the abundance and/or activity of cellular constituents
(expression profile, genotyping), morphological phenotype, or
interview of the subject.
[0012] Physiological state can refer to, but is not limited to, the
physiological state of an organism, an organ, a tissue, a
collection of cells or an individual cell. In a preferred
embodiment, the physiological state refers to the physiological
state of a whole organism. In another embodiment physiological
state refers to the physiological state of a tissue, for example
the physiological state of the uterine lining.
[0013] Disease state or disease status. In addition to a
physiological state, a sample may or may not be affected with a
disease state. According to the present invention, a disease state
refers to any abnormal biological state of a cell. This includes
but is not limited to an interruption, cessation or disorder of
body functions, systems or organs. In general, a disease state will
be detrimental to a biological system With respect to the present
invention, any biological state, such as a premalignancy state,
that is associated with a disease or disorder is considered to be a
disease state. A pathological state is the equivalent of a disease
state.
[0014] Disease states can be further categorized into different
levels of disease state. As used in the present invention, the
level of a disease or disease state is an arbitrary measure
reflecting the progression of a disease or disease state.
Generally, a disease or disease state will progress through a
plurality of levels or stages, wherein the affects of the disease
become increasingly severe. The level of a disease state may be
impacted by the physiological state of the sample.
[0015] Therapy or therapeutic regimen. In order to alleviate or
alter a disease state, a therapy or therapeutic regimen is often
undertaken. A therapy or therapeutic regimen, as used herein,
refers to a course of treatment intended to reduce or eliminate the
affects or symptoms of a disease. A therapeutic regimen will
typically comprise, but is not limited to, a prescribed dosage of
one or more drugs or surgery. Therapies, ideally, will be
beneficial and reduce the disease state but in many instances the
effect of a therapy will have non-desirable effects as well. The
effect of therapy will also be impacted by the physiological state
of the sample.
[0016] Pharmacological state or pharmacological status. Treatment
with drugs may affect the pharmacological state of a sample. The
pharmacological state of a sample relates to changes in the
biological status following drug treatment. Some of the changes
following drug treatment or surgery may be relevant to the disease
state. Some may be unrelated-side effects of the therapy. Some will
be specific to physiological state. Indicators of pharmacological
state include, but are not limited to, duration of therapy, types
and doses of drugs prescribed, degree of compliance with a given
course of therapy, and/or unprescribed drugs ingested.
[0017] Biological state or biological status. According to the
present invention, the biological state of a sample refers to the
state of a collection of cellular constituents or any other
observable phenotype, which is sufficient to characterize the
sample for an intended purpose. The biological state reflects the
physiological state of a sample, any disease state that affects the
sample and the pharmacological state if applicable. Some methods to
determine the biological state of a sample include but are not
limited to measuring the abundance and/or activity of cellular
constituents, characterizing according to morphological phenotype
or a combination of the above methods.
[0018] The biological status of a sample can be measured or
observed by interrogating the abundances and/or activities of a
collection of cellular constituents. In various embodiments, this
invention includes making such measurements and/or observations on
different collections of cellular constituents.
[0019] Expression profile. One measurement of cellular constituents
that is particularly useful in the present invention is the
expression profile. As used herein, an "expression profile"
comprises measurement of the relative abundance of a plurality of
cellular constituents. Such measurements may include, RNA or
protein abundances or activity levels. The expression profile can
be a measurement for example of the transcriptional state or the
translational state. See U.S. Pat. Nos 6,040,138, 5,800,992,
6,020,135, 6,033,860 and U.S. Ser. No. 09/341,302 which are hereby
incorporated by reference in their entireties.
[0020] Transcriptional state. The transcriptional state of a sample
includes the identities and relative abundances of the RNA species,
especially mRNAs present in the sample. Preferably, a substantial
fraction of all constituent RNA species in the sample are measured,
but at least, a sufficient fraction is measured to characterize the
state of the sample. The transcriptional state is the currently
preferred aspect of the biological state measured in this
invention. It can be conveniently determined by measuring
transcript abundances by any of several existing gene expression
technologies.
[0021] Translational state. Translational state includes the
identities and relative abundances of the constituent protein
species in the sample. As is known to those of skill in the art,
the transcriptional state and translational state are related.
[0022] The gene expression monitoring system, in a preferred
embodiment, may comprise a nucleic acid probe array (such as those
described above), membrane blot (such as used in hybridization
analysis such as Northern, Southern, dot, and the like), or
microwells, sample tubes, gels, beads or fibers (or any solid
support comprising bound nucleic acids). See U.S. Pat. Nos
5,770,722, 5,874,219, 5,744,305, 5,677,195 and 5,445,934, which are
expressly incorporated herein by reference. See also Examples,
infra. The gene expression monitoring system may also comprise
nucleic acid probes in solution.
[0023] The gene expression monitoring system according to the
present invention may be used to facilitate a comparative analysis
of expression in different cells or tissues, different
subpopulations of the same cells or tissues, different
physiological states of the same cells or tissue, different
developmental stages of the same cells or tissue, or different cell
populations of the same tissue.
[0024] Differentially expressed. The term differentially expressed
as used herein means that the measurement of a cellular constituent
varies in two or more samples. The cellular constituent can be
either upregulated in the experimental relative to the reference or
downregulated in the experimental relative to the reference.
Differential gene expression can also be used to distinguish
between cell types or nucleic acids. See U.S. Pat. No
5,800,992.
[0025] General
[0026] The comparison of gene expression profiles from an
experimental sample and a reference sample to identify genes that
are differentially expressed between two or more different
biological states in the same cell type has become a powerful
diagnostic and prognostic tool. Genes identified through this
method can be used as markers for the presence or level of a
disease, as prognostic devices to monitor efficacy of treatment
regimens and as targets for drug design.
[0027] The availability of comprehensive methods to analyze gene
expression patterns for a large number of genes simultaneously has
led to a flood of reports describing the expression profiles
associated with an increasingly comprehensive set of biological
states. The yeast, Saccharomyces cerevisiae, has been the subject
of a majority of these reports because of the availability of the
entire genomic sequence, the relatively small size of the yeast
genome and the relative ease with which different experimental
conditions can be tested.
[0028] The yeast system has been used to assay changes in gene
expression associated with a variety of different physiological,
developmental, disease and pharmacological conditions. These
include nch versus minimal media, (see, Wodicka et al, Nat
Biotechnol 15 1359-1367 (1997)), progression through the mitotic
cell cycle (see, Cho et al, Mol Cell 2 65-73 (1998)), response to
mutation (see Holstege et al, Cell 95 717-728 (1998)[AFFY],
cellular response to DNA damage (see, Jelinsky and Sampson, Proc
Natl Acad Sci USA 96 1486-1491 (1999)) and pseudohyphal formation
under conditions of nitrogen starvation (see, Madhani et al, Proc
Natl Acad Sci USA 96 12530-12535 (1999)) all of which are
incorporated herein by reference for all purposes.
[0029] In each of these reports the approach has been to compare
expression profiles from an experimental sample and a reference
sample under a given set of conditions following a change in
experimental conditions. Ideally a single variable is changed
between the reference and experimental samples, allowing any
observed changes to be attributed to the single changed variable.
When an experimental sample is compared to a reference sample under
less controlled circumstances the differential expression that is
observed can result from either the changed experimental condition
or from another difference between the two samples.
[0030] It is relatively simple to know and control many variables,
such as genotype and environmental conditions such as temperature,
aeration, nutrient availability, and stress conditions, when
studying a model organism such as yeast in a laboratory
environment. However, this approach decreases in utility as the
subject increases in complexity and it becomes increasingly
difficult to identify and control all variables. In a particularly
preferred embodiment the subject of the present invention is human
and one skilled in the art will recognize that it is difficult to
Identify and/or control variables when the subject is human.
[0031] Differential gene expression analysis experiments have been
done in higher eukaryotes but they are typically restricted to
those experiments in which variation between reference and
experimental samples can be minimized. Differential gene expression
experiments have been done in mice to identify variation resulting
from aging and from reduced caloric intake. See, Lee et al, Science
285 1390-1393 (1999) which is incorporated herein by reference for
all purposes. In order to limit variation not attributable to the
experimental conditions, all mice used in the experiments were
males of the same strain maintained under identical housing and
feeding conditions.
[0032] Gene expression studies have also been done in humans to
identify differences in gene expression in diseased samples. In
studies of humans researchers have taken several approaches to
minimize variability between experimental and reference samples.
Growing cells in culture is one method that researchers have taken
to model biological responses of human cells. For example, the
changes in expression profiles in cultured human fibroblasts in
response to human cytomegalovirus infection, have been
characterized using DNA array technology. See, Zhu et al, Proc Natl
Acad Sci USA 95 14470-14475 (1998) which is incorporated herein by
reference for all purposes. Because of the differences between in
vitro cell culture and samples derived in vivo, this type of in
vitro examination of gene expression is recognized by those of
skill in the art to represent a highly useful but potentially
distorted and incomplete picture of a normal response.
[0033] When expression profile comparisons are done using primary
patient material rather than cell culture, extra steps can
sometimes be taken to minimize variation resulting from unknown or
uncontrolled differences between the experimental and reference
samples. Typically reference and experimental samples are matched
by isolating both from the same tissue type and often from the same
patient in a single procedure. For example, genes that were
differentially expressed in colon tumors were identified by
comparing expression data from colon tumors and normal colon. See,
Zhang et al., Science 276.1268-1272 which is incorporated herein by
reference for all purposes. However, both of these approaches have
limitations. If a patient has a disease that effects the entire
organism or an entire organ it will not be possible to generate a
normal sample from this individual. Even if an apparently normal
sample can be obtained from the same individual it is possible that
the sample will be affected by the disease. When a normal sample is
from an individual distinct from the patient there will be
differences that are attributed to differences in the
physiological, pharmacological or disease states of the two
individuals.
[0034] Another approach has been to compare expression profiles
from a collection of samples to identify differences in gene
expression between two states that consistently correlated with one
state or the other in order to identify genes that could be used to
predict the state of an unknown sample as being one of the two
states. See Golub et al, Science 286 531-537 (1999) which is
incorporated herein by reference for all purposes. One limitation
to this approach is that only genes that consistently correlate
with one state or another are useful. For example, genes that are
differentially expressed only in a subset of samples would not be
useful. This subset may represent samples that share another aspect
of biological state such as a common physiological state.
[0035] A preferred aspect of the present invention describes a
novel approach to compare expression profiles and to derive useful
information about genes that are differentially expressed in
response to a change in a specific variable even when it is not
practical or possible to control changes in other variables. The
current invention facilitates separation of differential gene
expression data into physiological, disease and/or pharmacological
components.
[0036] Changes in a biological system, whether the result of a
disease state or normal physiological variation, will affect many
constituents of a sample. In particular, as a result of regulatory,
homeostatic, and/or compensatory networks and systems present in
biological systems, even the direct disruption of only a single
constituent can have complicated and often unpredictable effects on
other constituents.
[0037] Alteration of the activity or level of a single,
hypothetical protein, such as protein P is considered herein as an
example. Although the activity of only protein P is directly
disrupted, additional cellular constituents that are inhibited or
stimulated by protein P, or which are elevated or diminished to
compensate for the loss of protein P activity will also be
affected. Still other cellular constituents will be affected by
changes in the levels or activity of the second tier constituents,
and so on.
[0038] As a further example consider a sample in which the
alteration of the activity of two hypothetical proteins, P1 and P2,
has been altered, the alteration of P1 resulting from a disease
state and the alteration of P2 resulting from a change in
physiological state. As in the first example, each alteration will
affect a second tier of constituents that will, in turn, affect the
levels or activity of a third tier of constituents, and so on.
Measurements of the biological state of the sample will detect
changes in effected constituents but will not distinguish those
that result from the P1 alteration from those that result from the
P2 alteration. One aspect of the current invention distinguishes
between changes in the expression profile that correlate with the
change in P1, resulting from the disease state, and changes that
correlate with the change in P2, resulting from the change in
physiological state.
[0039] Measurement of the transcriptional state of a cell is
preferred in this invention because it is relatively easy to
measure, it is typically more sensitive than other methods such as
morphological characterization and can typically be applied more
consistantly than morphological characterization.
[0040] Some disease states can be difficult to identify based on
morphological differences, especially at early levels of the
disease state. A genetic mutation may result in a dramatic change
in the expression levels of a group of genes but biological systems
can compensate for changes by altering the expression of other
genes. As a result of these internal compensation responses, many
perturbations may have minimal effects on observable phenotypes of
the system but profound effects to the composition of cellular
constituents.
[0041] It will be appreciated by one skilled in the art that
samples can be derived from a variety of sources including, but not
limited to, single cells, a collection of cells, tissue, cell
culture, urine, blood, or other bodily fluids The tissue or cell
source may include a tissue biopsy sample, a cell sorted
population, cell culture, or a single cell. In a preferred
embodiment, the tissue source may include brain, liver, heart,
kidney, lung, spleen, retina, bone, lymph node, endocrine gland,
reproductive organ, blood, nerve, vascular tissue, and olfactory
epithelium. In one embodiment, eukaryotic tissue is preferred, and
in another, mammalian tissue is preferred, and in yet another,
human tissue is preferred.
[0042] In yet another preferred embodiment, the tissue or cell
source may be embryonic or tumongenic. Tumongenic tissue according
to the present invention may include tissue associated with
malignant and pre-neoplastic conditions, not limited to the
following acute lymphocytic leukemia, acute myelocytic leukemia,
myeloblastic leukemia, promyelocytic leukemia, myelomonocytic
leukemia, monocytic leukemia, erythroleukemia, chronic myelocytic
(granulocytic) leukemia, chronic lymphocytic leukemia, polycythemia
vera, lymphoma, Hodgkin's disease, non-Hodgkin's disease, multiple
myeloma, Waldenstrom's macroglobulinemia, heavy chain disease,
solid tumors, endometrial cancer, ovarian cancer, leiomyoma,
fibrosarcoma, myxosarcoma, liposarcoma, chondrosarcoma, osteogenic
sarcoma, chordoma, angiosarcoma, endothehosarcoma,
lymphanglosarcoma, lymphangioendotheliosarcoma, synovioma,
mesothelioma, Ewing's tumor, leiomyosarcoma, rhabdomyosarcoma,
colon carcinoma, pancreatic cancer, breast cancer, ovarian cancer,
prostate cancer, squamous cell carcinoma, basal cell carcinoma,
adenocarcinoma, sweat gland carcinoma, sebaceous gland carcinoma,
papillary carcinoma, papillary adenocarcinomas, cystadenocarcinoma
medullary carcinoma, bronchogenic carcinoma, renal cell carcinoma,
hepatoma, bile duct carcinoma, chonocarcinoma, seminoma, embryonal
carcinoma, Wilms' tumor, cervical cancer, testicular tumor, lung
carcinoma, small cell lung carcinoma, bladder carcinoma, epithelial
carcinoma, glioma, astrocytoma, medulloblastoma, cramopharyngioma,
ependymoma, pinealoma, hemangioblastoma, acoustic neuroma,
oligodendroglioma, menangioma, melanoma, neuroblastoma, and
retinoblastoma. See Fishman, et al, Medicine, 2d Ed (J B Lippincott
Co., Philadelphia, Pa. 1985) hereby incorporated by reference in
its entirety for all purposes.
OVERVIEW OF THE METHODS OF THIS INVENTION
[0043] It is well understood by those of skill in the art that
variation in the global pattern of gene expression underlies much
of the phenotypic diversity among cells. Phenotypic diversity
includes both normal variation associated with a change in
physiological state and abnormal variation associated with a
pharmacological or disease state. One aspect of the current
invention differentiates between abnormal variation associated with
disease and/or pharmacological state and normal variation
associated with physiological state.
[0044] A preferred embodiment of the current invention matches an
experimental sample to one or more reference samples that match the
experimental sample in at least one parameter that is a determinant
of physiological status, pharmacological and/or disease status and
compares the expression profiles of the experimental and reference
samples. In a particularly preferred embodiment, the current
invention is used to identify genes that are differentially
expressed between matched samples. The embodiments of the present
invention are also applicable to diagnosing the disease state of a
sample. The embodiments of the present invention are also
applicable to characterizing and monitoring disease states. This
includes identifying and monitoring the level of a disease state as
well as monitoring the effect of therapies on a disease state. The
embodiments of the present invention are also applicable to
identifying and monitoring drug responses that are specific to a
given physiological state. Thus, the present invention is also
useful for designing drug therapies that are tailored to the
physiological state of a subject. The present invention in one
aspect can also be used to identify the physiological or
pharmacological state of a sample.
[0045] Genes have been identified whose expression is varied
greatly (preferably more than 4, 10, 15, or 20 fold) between
different physiological states. Differences in physiological states
between an experimental and reference sample make it difficult to
distinguish between genes that are differentially expressed because
of the change in physiological state and genes that are
differentially expressed because of another difference between the
samples. For example, when comparing an experimental sample to a
reference sample to identify genes that are differentially
expressed in a disease state, it is preferable to match the
physiological state of the experimental and reference samples so
that any changes in gene expression that are observed can be
attributed to the disease state. Similarly, a difference in disease
or pharmacological state can obscure differences in physiological
state. In many embodiments the current invention matches the
physiological, pharmacological and/or disease states of reference
and experimental samples before comparing expression profiles.
[0046] Determining the physiological, pharmacological and/or
disease state of a sample
[0047] In one aspect the invention requires the gathering of
information about the physiological, pharmacological and/or disease
state of a sample. If, for example, the goal is to diagnose disease
in an experimental sample from a human patient one aspect of the
invention is to discover information about the physiological and
pharmacological state of the sample. Another aspect of the
invention is to match the experimental sample to reference samples
of similar physiological and pharmacological state. This requires
knowledge of the physiological and pharmacological state of the
reference sample. In this example, another aspect of the invention
that the reference samples are also of known disease status to
allow diagnosis of the disease state of the experimental sample.
Information about physiological state can be gathered in a variety
of ways. If the subject is human, the sex can be obtained for
example through an interview, a visual inspection or through
karyotyping.
[0048] Information about genotypic state can be derived by sequence
analysis. There are a variety of methods, such as array based
analysis, standard sequencing techniques, and other commercially
available methods.
[0049] Information about disease state can be also be obtained
through a variety of mechanisms such as identification of symptoms
or morphological examination of effected tissue. Determinants of
disease state include phenotypic symptoms, level of disease,
progress of therapy. It is possible to have more than one disease
contributing to the disease state of the sample.
[0050] Information about pharmacological state can similarly be
obtained through a variety of mechanisms. In some circumstances a
subject can be interviewed. Under other circumstances it may be
necessary to inspect the medical history of the subject or to assay
for evidence of drug use through chemical analysis of blood, urine,
skin, saliva or hair.
[0051] There may be variation in the expression profiles obtained
from samples that apparently share a common physiological state. In
some embodiments of the invention the best expression profile to
use as a reference sample is an average from a plurality of
expression profiles of common physiological state. A phenotypic
disease state may alter physiological state expression profile
(women with a history of sexual abuse have dramatically altered
levels of certain hormones--this would be a disease state that
might go clinically undetected).
[0052] Matching Reference Sample(s) to Experimental Sample(s)
[0053] According to one aspect of the current invention, samples
can be matched by disease state, by physiological state, or by
pharmacological state, or any combination of these states. The
objective is to minimize differences between the experimental and
reference samples. In a particularly preferred embodiment variation
between the experimental and reference sample is limited to a
single aspect of a disease, physiological or pharmacological state
that is being interrogated. In another embodiment the invention
removes variation due to one or more indicators of physiological
status, pharmacological status or disease status.
[0054] In another aspect the invention removes variation due to one
or more indicators of physiological status and one or more
indicators of pharmacological status. In another aspect the
invention removes variation due to one or more indicators of
physiological status and one or more indicators of disease status.
In another aspect the invention removes variation due to one or
more indicators of disease status and one or more indicators of
pharmacological status.
[0055] In one aspect of the invention the reference sample(s) is
selected to match the experimental sample in at least one parameter
that is a determinant of physiological state. In this aspect of the
invention it is preferable that the reference sample(s) matches the
experimental sample in many parameters that are determinants of
physiological state. The reference sample and the experimental
sample could be from subjects that are similar in age, gender,
reproductive status or ethnic on gin, any combination of these
aspects or other aspects that are determinants of physiological
state.
[0056] In one aspect of the invention the reference sample is
selected to match the experimental sample in at least one aspect of
a disease state In this aspect of the invention it is preferable
that the reference sample(s) matches the experimental sample in
many parameters that are determinants of disease state.
[0057] In another aspect of the invention the reference sample is
selected to match the experimental sample in at least one aspect of
a pharmacological state. In this aspect of the invention it is
preferable that the reference sample(s) matches the experimental
sample in many parameters that are determinants of pharmacological
state.
[0058] Identifying Differentially Expressed Genes From Matched
Samples.
[0059] In one embodiment of the invention matched experimental and
reference samples are compared to identify differences. Comparisons
that can be made include, but are not limited to diseased to normal
from matching physiological state, diseased to diseased from
different physiological states, normal to normal from different
physiological states, diseased to diseased from the same
physiological state, and normal to normal from the same
physiological state. A sample of unknown physiological state can be
compared to a plurality of samples of known physiological state to
identify the physiological state of the sample.
[0060] In many embodiments of the current invention, expression
profiles will be compared. In a particularly preferred embodiment
expression profiles are compared to identify genes that are
differentially expressed between the samples. This embodiment of
the invention is useful, for example, for identifying genes that
are differentially expressed in a diseased and normal sample or in
different levels of disease. Genes that are differentially
expressed can be used as diagnostic or prognostic markers or
drug/therapy targets or indicators of physiological or
pharmacological status. They can be used individually or in sets
of, for example, 2, 5, 10, 20, 30, 100, 150, 200, 250, 500, or
1,000 or more. The identified genes can be used to design probes
for microarrays.
[0061] Diagnosing Disease States
[0062] In a particularly preferred embodiment the current invention
can be used to diagnose disease. Reference samples are selected to
match the experimental sample in physiological and/or
pharmacological state and to represent a plurality of different
known disease states. The expression profile from the experimental
sample is then compared to a plurality of expression profiles from
reference samples to identify one or more reference samples that
match the expression profile of the experimental sample. The
experimental sample is diagnosed with the disease of the matching
reference sample(s).
[0063] In one aspect of the invention the disease states
represented are selected from a subset of diseases that match one
or more symptoms in the experimental sample. For example, if the
experimental sample is from a 30year-old female patient with
difficulty becoming pregnant, samples from 30year-old females
diagnosed with specific forms of infertility can be chosen as
reference samples.
[0064] Monitoring Disease States
[0065] Following the diagnosis of a particular disease in a patient
or subject it is often useful to obtain information about the level
of the disease state. If diagnosis is followed by therapy it is
also often useful to obtain information about the level of the
disease state during and after therapy.
[0066] In one aspect the invention is used to identify or
characterize the stage of a tumor. Tumorogenic experimental samples
are compared to reference samples that are matched to the
experimental sample in one or more indicators of physiological or
pharmacological status. Reference samples with well characterized
tumors are selected. Comparison can be of morphological features or
of other biological readouts including expression profiles. The
present method stages tumors by comparison to reference samples of
matching physiological and/or pharmacological state, thus
eliminating gene expression differences that result from
differences in physiological and/or pharmacological state that may
not be relevant to the disease state.
[0067] In one embodiment the present invention can be used for
monitoring the disease state of a subject undergoing one or more
therapies. This requires the comparison of a sample before
treatment with samples following treatment. There may be changes to
the physiological state of the patient that occur over the course
of the therapy that are unrelated to the therapy. When comparing a
sample before treatment to a sample after treatment it will be
preferable to identify changes between the samples that result from
a change in physiological state. In one aspect the current
invention identifies changes that are the result of physiological
change rather than therapeutic intervention.
[0068] Identifying and Monitoring Drug Responses that are Specific
to Physiological State.
[0069] The current invention can be used to correlate differences
in drug efficacy with differences in physiological state. Some drug
therapies are highly effective in one patient but ineffective or
deleterious in another patient. Differences in drug efficacy may
correlate with differences in genotypic state, disease state or
physiological state.
[0070] The current invention can be used to identify changes in
gene expression following drug treatment that are specific to a
physiological state. This could facilitate the discovery/design of
therapies that are specific for the physiological state of the
patient.
[0071] Drug therapies will have different effects depending on the
physiological status of subject. Some drug therapies have different
side effects in different physiological states. Some drug therapies
have different efficacies in men and women, in particular many are
less effective in women than in men. In a preferred embodiment the
current invention is used to identify drug effects that are
specific to women. In another preferred embodiment the method is
used to identify drug effects that are specific to men.
[0072] The invention can also be used to identify therapeutic
regimens that are optimized for the physiological state of the
patient. Therapeutic treatments ideally impart maximal disease
reduction with minimal adverse side effects, but many therapeutic
treatments do have undesirable side effects. These side effects may
be specific to the physiological state of the sample. The current
invention could be used as a tool to design therapeutic regimens
that are specific for the physiological state of the subject.
[0073] Identifying the Physiological State of an Experimental
Sample
[0074] A sample for which relatively little information is known
about the subject from which the sample was supplied could be
compared to a plurality of expression profiles of known
physiological status in order to determine the physiological status
of the subject.
[0075] For example a blood or semen sample isolated from a crime
scene could be used to obtain information about the physiological
status of the criminal, such as age and ethnic origin.
[0076] Specific Applications
[0077] Those skilled in the art will recognize that in a preferred
embodiment, the expression profiles from the reference samples will
be input to a database. A relational database is preferred and can
be used, but one of skill in the art will recognize that other
databases could be used. A relational database is a set of tables
containing data fitted into predefined categories. Each table, or
relation, contains one or more data categories in columns. Each row
contains a unique instance of data for the categories defined by
the columns. For example, a typical database for the invention
would include a table that describes a sample with columns for age,
gender, reproductive status, expression profile and so forth.
Another table would describe a disease symptoms, level, sample
identification, expression profile and so forth. See U.S. Ser. No
09/354,935, which is hereby incorporated by reference in its
entirety for all purposes.
[0078] In one embodiment the invention matches the experimental
sample to a database of reference samples. The database is
assembled with a plurality of different samples to be used as
reference samples. An individual reference sample in one embodiment
will be obtained from a patient during a visit to a medical
professional. The sample could be for example a tissue, blood,
urine, feces or saliva sample. Information about the physiological,
disease and/or pharmacological status of the sample will also be
obtained through any method available. This may include, but is not
limited to, expression profile analysis, clinical analysis, medical
history and/or patient interview. For example, the patient could be
interviewed to determine age, sex, ethnic origin, symptoms or past
diagnosis of disease, and the identity of any therapies the patient
is currently undergoing. A plurality of these reference samples
will be taken. A single individual may contribute a single
reference sample or more than one sample over time. One skilled in
the art will recognize that confidence levels in predictions based
on comparison to a database increase as the number of reference
samples in the database increases. One skilled in the art will also
recognize that some of the indicators of status will be determined
by less precise means, for example information obtained from a
patient interview is limited by the subjective interpretation of
the patient. Additionally, a patient may lie about age or lack
sufficient information to provide accurate information about ethnic
or other information. Descriptions of the seventy of disease
symptoms is a particularly subjective and unreliable indicator of
disease status.
[0079] The database is organized into groups of reference samples.
Each reference sample contains information about physiological,
pharmacological and/or disease status. In one aspect the database
is a relational database with data organized in three data tables,
one where the samples are grouped primarily by physiological
status, one where the samples are grouped primarily by disease
status and one where the samples are grouped primarily by
pharmacological status. Within each table the samples can be
further grouped according to the two remaining categories. For
example the physiological status table could be further categorized
according to disease and pharmacological status.
[0080] As will be appreciated by one of skill in the art, the
present invention may be embodied as a method, data processing
system or program products. Examples of computer programs and
databases are shown in U.S. Ser. Nos 09/354,935, 08/828,952,
09/341,302, 09/397,494, 60/220,587, and 60/220,645, which are
hereby incorporated by reference in their entireties for all
purposes.
[0081] Accordingly, the present invention may take the form of data
analysis systems, methods, analysis software and etc. Software
written according to the present invention is to be stored in some
form of computer readable medium, such as memory, hard-drive, DVD
ROM or CD ROM, or transmitted over a network, and executed by a
processor. The present invention also provides a computer system
for analyzing physiological states, levels of disease states and/or
therapeutic efficacy. The computer system comprises a processor,
and memory coupled to said processor which encodes one or more
programs. The programs encoded in memory cause the processor to
perform the steps of the above methods wherein the expression
profiles and information about physiological, pharmacological and
disease states are received by the computer system as input
[0082] U.S. Pat. No 5,733,729 illustrates an example of a computer
system that may be used to execute the software of an embodiment of
the invention. This patent shows a computer system that includes a
display, screen, cabinet, keyboard, and mouse. The mouse may have
one or more buttons for interacting with a graphic user interface.
The cabinet preferably houses a CD-ROM or DVD-ROM drive, system
memory and a hard drive which may be utilized to store and retrieve
software programs incorporating computer code that implements the
invention, data for use with the invention and the like. Although a
CD is shown as an exemplary computer readable medium, other
computer readable storage media including floppy disk, tape, flash
memory, system memory, and hard drive may be utilized Additionally,
a data signal embodied in a carrier wave (e g, in a network
including the internet) may be the computer readable storage
medium.
[0083] The patent also shows a system block diagram of a computer
system used to execute the software of an embodiment of the
invention. The computer system includes monitor, and keyboard, and
mouse. The computer system further includes subsystems such as a
central processor, system memory, fixed storage (e g, hard drive),
removable storage (e g, CD-ROM), display adapter, sound card,
speakers, and network interface. Other computer systems suitable
for use with the invention may include additional or fewer
subsystems. For example, another computer system may include more
than one processor or a cache memory. Computer systems suitable for
use with the invention may also be embedded in a measurement
instrument. The embedded systems may control the operation of, for
example, a GeneChip.RTM. Probe array scanner as well as executing
computer codes of the invention.
[0084] Computer methods can be used to measure the variables and to
match samples to eliminate gene expression differences that are a
result of differences that are not of interest. For example, a
plurality of values can be input into computer code for one or more
of a physiological, pharmacological or disease states. The computer
code can thereafter measure the differences or similarities between
the values to eliminate changes not attributable to a value of
interest. Examples of computer programs and databases that can be
used for this purpose are shown U.S. Ser. Nos 09/354,935,
08/828,952, 09/341,302, 09/397,494, 60/220,587, and 60/220,645,
which are hereby incorporated by reference in their entireties.
[0085] In one aspect of the invention, microarrays will be used to
measure expression profiles. Microarrays are particularly well
suited because of the reproducibility between different experiments
DNA microarrays provide one method for the simultaneous measurement
of the expression levels of large numbers of genes. Each array
consists of a reproducible pattern of thousands of different DNAs
attached to a solid support. Labeled RNA or DNA is hybridized to
complementary probes on the array and then deteted by laser
scanning Hybridization intensities for each probe on the array are
determined and converted to a quantitative read-out of relative
gene expression levels. The data can be further analyzed to
identify expression patterns and variation that correlates with the
biological state of the sample (See U.S. Pat. Nos 6,040,138,
5,800,992 and 6,020,135, 6,033,860 and U.S. Ser. No. 09/341,302
which are incorporated herein by reference).
[0086] High-density oligonucleotide arrays are particularly useful
for monitoring the gene expression pattern of a sample. In one
approach, total mRNA isolated from the sample is converted to
labeled cRNA and then hybridized to an array such as a
GeneChip.RTM. oligonucleotide array. Each sample is hybridized to a
separate array. Relative transcript levels are calculated by
reference to appropriate controls present on the array and in the
sample. See Mahadevappa, M & Warrington, J. A. Nat. Biotechnol
17, 1134-1136 (1999) which is hereby incorporated by reference in
its entirety for all purposes.
[0087] Characterization of Biological Status in Females
[0088] The current invention is particularly useful when applied to
analysis of experimental samples from female subjects. Women differ
from men in the physiological indicator of gender, which
contributes to an as yet uncharacterized level of differential gene
expression. In addition, there is a tremendous amount of normal
variation between female subjects and between different samples
from the same female subject. In particular, the female
reproductive system and the menstrual cycle add an additional level
of physiological variation to the analysis of samples derived from
female subjects. As part of a monthly cycle the lining of the
female uterus, the endometrium, undergoes a cycle of controlled
tissue remodeling unparalleled in other organs. Thus cycle is
presumably driven by changes in gene expression.
[0089] Physiological variation between women and men complicates
the design of effective therapies for women and the monitoring of
therapeutic treatments in women. It is currently well accepted that
gender differences result in extensive disparity in the ways males
and females respond to therapeutic treatments for a variety of
non-gender specific diseases including heart disease and stroke.
The reasons for these differences, however, are not well
understood, but the menstrual cycle is likely to be at least
partially responsible. Much of the research into novel drugs and
therapeutic treatments is done using male test subjects. Therefore,
there is a great need in the art for methods of incorporating
information about the physiological state of a patient into the
diagnosis and management of diseases.
[0090] Gender differences in the efficacy of drug therapy have been
appreciated for many years, but little has been done to investigate
these differences. It is believed that hormonal fluctuations within
the menstrual cycle may be a primary cause of gender specific drug
response. A systematic investigation of the physiological variation
throughout the menstrual cycle, both under normal physiological
conditions and in response to drug treatment, would be
beneficial.
[0091] In one embodiment, the current invention correlates
information about variation in gene expression with variation in
gender. Male and female samples that are matched in other
indicators of physiological state are compared to identify genes
that are differentially expressed. For example a healthy
30-year-old male of similar, i.e., European, descent could be
compared to a healthy 30-year-old female of European descent to
identify genes that are differentially expressed between the two
physiological conditions. In a further embodiment the current
invention could also be used to monitor changes in pharmacological
status resulting from drug treatments, taking normal physiological
variation into account. For example, the subjects in the first
example could be compared again following therapeutic treatment.
The genes that were identified in the first example would be
compared or subtracted from the genes identified in the second
example to identify genes that are differentially expressed as a
result of the therapy
[0092] In another aspect, the current invention diagnoses diseases
of the female reproductive system. Many disorders of the female
reproductive system have relatively poor methods of diagnosis and
prognosis and many are typically diagnosed based simply on patient
perception, which tends to be unreliable. For example,
pre-menstrual syndrome effects large numbers of women, but is
typically diagnosed only when other explanations for the observed
symptoms are eliminated. More reliable methods of diagnosis such as
the use of gene expression profiles for diagnosis and prognosis
have been complicated by the changes in gene expression that
accompany the normal physiological variation of the system.
[0093] Menopause is a woman's final menstrual period, but currently
the actual event can be determined only in retrospect, after she
has not had a period for 12 continuous months. Menopause can occur
naturally any time between the mid-30s through the late 50s, but
can also be brought on prematurely by events such as gynecological
surgery, cancer therapy and certain illnesses and diseases. The
current invention can be used to determine a molecular profile
consistent with a diagnosis of menopause that would allow earlier
diagnosis.
[0094] In one embodiment the current invention diagnosis diseases
of the female reproductive organs. An expression profile from an
experimental sample is compared to expression profiles from
reference samples that match the experimental sample in
physiological state. The reference samples represent a plurality of
different disease states that effect the uterus and the
experimental sample is identified as being of the disease state of
the reference sample that is the closest match. The samples can be
derived from, for example, endometrial tissue, myometrial tissue,
and/or uterine tissue.
[0095] In one aspect, a database of reference samples could be
comprised of expression profiles from endometrial samples and data
points identifying the physiological, pharmacological and/or
disease state of the samples. These reference samples would be from
many different individuals representing many different
physiological, pharmacological and/or disease states The reference
samples can be derived from for example normal tissue at different
stages of development and differentiation, tissues affected with a
variety of pathological conditions, including but not limited to,
premenstrual syndrome, PMDD, stress urinary incontinence,
polycystic ovarian disease, endometriosis, endometrial cancer,
infertility, hormone imbalance, and tissue subjected to a variety
of perturbations including but not limited to hormone replacement
therapy, or chemical contraception. In one preferred embodiment,
reference samples will be taken from individuals during routine
doctor visits. In one embodiment the reference samples would
represent different physiological states of the menstrual cycle
including but not limited to the secretory and proliferative stages
of the endometrium.
[0096] Providing a Nucleic Acid Sample
[0097] One of skill in the art will appreciate that it is desirable
to have nucleic samples containing target nucleic acid sequences
that reflect the transcripts of interest. Therefore, suitable
nucleic acid samples may contain transcripts of interest. Suitable
nucleic acid samples, however, may contain nucleic acids derived
from the transcripts of interest. As used herein, a nucleic acid
derived from a transcript refers to a nucleic acid for whose
synthesis the mRNA transcript or a subsequence thereof has
ultimately served as a template. Thus, a cDNA reverse transcribed
from a transcript, an RNA transcribed from that cDNA, a DNA
amplified from the cDNA, an RNA transcribed from the amplified DNA,
etc., are all derived from the transcript and detection of such
derived products is indicative of the presence and/or abundance of
the original transcript in a sample. Thus, suitable samples
include, but are not limited to, transcripts of the gene or genes,
cDNA reverse transcribed from the transcript, cRNA transcribed from
the cDNA, DNA amplified from the genes, RNA transcribed from
amplified DNA, and the like.
[0098] Transcripts, as used herein, may include, but not limited to
pre-mRNA nascent transcript(s), transcript processing
intermediates, mature mRNA(s) and degradation products. It is not
necessary to monitor all types of transcripts to practice this
invention. For example, one may choose to practice the invention to
measure the mature mRNA levels only.
[0099] In one embodiment, such sample is a homogenate of cells or
tissues or other biological samples. Preferably, such sample is a
total RNA preparation of a biological sample. More preferably in
some embodiments, such a nucleic acid sample is the total mRNA
isolated from a biological sample. Those of skill in the art will
appreciate that the total mRNA prepared with most methods includes
not only the mature mRNA, but also the RNA processing intermediates
and nascent pre-mRNA transcripts. For example, total mRNA purified
with poly (T) column contains RNA molecules with poly (A) tails.
Those poly A+RNA molecules could be mature mRNA, RNA processing
intermediates, nascent transcripts or degradation
intermediates.
[0100] Biological samples may be of any biological tissue or fluid
or cells. Frequently the sample will be a "clinical sample" which
is a sample derived from a patient. Clinical samples provide rich
sources of information regarding the various states of genetic
network or gene expression. Some embodiments of the invention are
employed to detect mutations and to identify the function of
mutations. Such embodiments have extensive applications in clinical
diagnostics and clinical studies. Typical clinical samples include,
but are not limited to, sputum, blood, blood cells (e g, white
cells), tissue or fine needle biopsy samples, urine, pentoneal
fluid, and pleural fluid, or cells therefrom. Biological samples
may also include sections of tissues such as frozen sections taken
for histological purposes.
[0101] Another typical source of biological samples are cell
cultures where gene expression states can be manipulated to explore
the relationship among genes. In one aspect of the invention,
methods are provided to generate biological samples reflecting a
wide variety of states of the genetic network.
[0102] One of skill in the art would appreciate that it is
desirable to inhibit or destroy RNase present in homogenates before
homogenates can be used for hybridization. Methods of inhibiting or
destroying nucleases are well known in the art. In some preferred
embodiments, cells or tissues are homogenized in the presence of
chaotropic agents to inhibit nuclease. In some other embodiments,
RNases are inhibited or destroyed by heat treatment followed by
proteinase treatment.
[0103] Methods of isolating total mRNA are also well known to those
of skill in the art. For example, methods of isolation and
purification of nucleic acids are described in detail in Chapter 3
of Laboratory Techniques in Biochemistry and Molecular Biology
Hybridization With Nucleic Acid Probes, Part I Theory and Nucleic
Acid Preparation, P Tijssen, ed Elsevier, N.Y. (1993) and Chapter 3
of Laboratory Techniques in Biochemistry and Molecular Biology
Hybridization With Nucleic Acid Probes, Part I Theory and Nucleic
Acid Preparation, P. Tijssen, ed Elsevier, N.Y. (1993))
[0104] In a preferred embodiment, the total RNA is isolated from a
given sample using, for example, an acid
guanidinium-phenol-chloroform extraction method and polyA.sup.+
mRNA is isolated by oligo dT column chromatography or by using
(dT)n magnetic beads (see, e g, Sambrook et al, Molecular Cloning A
Laboratory Manual (2nd ed), Vols 1-3, Cold Spring Harbor
Laboratory, (1989), or Current Protocols in Molecular Biology, F
Ausubel et al, ed Greene Publishing and Wiley-Interscience, New
York (1987)) See also PCT/US99/25200 for complexity management and
other sample preparation techniques, which is hereby incorporated
by reference in its entirety.
[0105] Frequently, it is desirable to amplify the nucleic acid
sample prior to hybridization. One of skill in the art will
appreciate that whatever amplification method is used, if a
quantitative result is desired, care must be taken to use a method
that maintains or controls for the relative frequencies of the
amplified nucleic acids to achieve quantitative amplification.
[0106] Methods of "quantitative" amplification are well known to
those of skill in the art. For example, quantitative PCR involves
simultaneously co-amplifying a known quantity of a control sequence
using the same primers. This provides an internal standard that may
be used to calibrate the PCR reaction. The high density array may
then include probes specific to the internal standard for
quantification of the amplified nucleic acid.
[0107] Other suitable amplification methods include, but are not
limited to polymerase chain reaction (PCR) (Innis, et al , PCR
Protocols A guide to Methods and Application Academic Press, Inc.
San Diego, (1990)), ligase chain reaction (LCR) (see Wu and
Wallace, Genomics, 4 560 (1989), Landegren, et al, Science, 241
1077 (1988) and Barringer, et al, Gene, 89 117 (1990),
transcription amplification (Kwoh, et al, Proc Natl Acad Sci USA,
86 1173 (1989)), and self-sustained sequence replication (Guatelli,
et al, Proc Nat Acad Sci USA, 87 1874 (1990)).
[0108] Cell lysates or tissue homogenates often contain a number of
inhibitors of polymerase activity. Therefore, RT-PCR typically
incorporates preliminary steps to isolate total RNA or mRNA for
subsequent use as an amplification template. One tube mRNA capture
methods may be used to prepare poly(A)+ RNA samples suitable for
immediate RT-PCR in the same tube (Boehringer Mannheim). The
captured mRNA can be directly subjected to RT-PCR by adding a
reverse transcription mix and, subsequently, a PCR mix. In a
particularly preferred embodiment, the sample mRNA is reverse
transcribed with a reverse transcriptase and a primer consisting of
oligo dT and a sequence encoding the phage T7 promoter to provide
single stranded DNA template. The second DNA strand is polymerized
using a DNA polymerase. After synthesis of double-stranded cDNA, T7
RNA polymerase is added and RNA is transcribed from the cDNA
template. Successive rounds of transcription from each single cDNA
template result in amplified RNA. Methods of in vitro
polymerization are well known to those of skill in the art (see, e
g, Sambrook, supra).
[0109] It will be appreciated by one of skill in the art that the
direct transcription method described above provides an antisense
(aRNA) pool. Where antisense RNA is used as the target nucleic
acid, the oligonucleotide probes provided in the array are chosen
to be complementary to subsequences of the antisense nucleic acids.
Conversely, where the target nucleic acid pool is a pool of sense
nucleic acids, the oligonucleotide probes are selected to be
complementary to subsequences of the sense nucleic acids. Finally,
where the nucleic acid pool is double stranded, the probes may be
of either sense as the target nucleic acids include both sense and
antisense strands.
[0110] The protocols cited above include methods of generating
pools of either sense or antisense nucleic acids. Indeed, one
approach can be used to generate either sense or antisense nucleic
acids as desired. For example, the cDNA can be directionally cloned
into a vector (e g, Stratagene's p Bluescript II KS (+) phagemid)
such that it is flanked by the T3 and T7 promoters. In vitro
transcription with the T3 polymerase will produce RNA of one sense
(the sense depending on the orientation of the insert), while in
vitro transcription with the T7 polymerase will produce RNA having
the opposite sense. Other suitable cloning systems include phage
lambda vectors designed for Cre-loxP plasmid subcloning (see e g,
Palazzolo et al, Gene, 88-25-36 (1990)).
[0111] Other analysis methods that can be used in the present
invention include electrochemical denaturation of double stranded
nucleic acids, U.S. Pat. No. 6,045,996 and 6,033,850, the use of
multiple arrays (arrays of arrays), U.S. Pat. No 5,874,219, the use
of scanners to read the arrays, U.S. Pat. Nos. 5,631,734,
5,744,305, 5,981,956 and 6,025,601, methods for mixing fluids, U.S.
Pat. No 6,050,719, integrated device for reactions, U.S. Pat. No
6,043,080, integrated nucleic acid diagnostic device, U.S. Pat. No.
5,922,591, and nucleic acid affinity columns, U.S. Pat. No
6,013,440. All of the above patents are hereby incorporated by
reference in their entireties.
[0112] Throughout this disclosure, various aspects of this
invention are presented in a range format. It should be understood
that the description in range format is merely for convenience and
brevity and should not be construed as an inflexible limitation on
the scope of the invention. Accordingly, the description of a range
should be considered to have specifically disclosed all the
possible subranges as well as individual numerical values within
that range. For example, description of a range such as from 1 to 6
should be considered to have specifically disclosed subranges such
as from 1 to 3, from 1 to 4, from 1 to 5, from 2 to 4, from 2 to 6,
from 3 to 6 etc, as well as individual numbers within that range,
for example, 1, 2, 3, 4, 5, and 6. This applies regardless of the
breadth of the range.
[0113] All publications and patent applications cited above are
incorporated by reference in their entirety for all purposes to the
same extent as if each individual publication or patent application
were specifically and individually indicated to be so incorporated
by reference. Although the present invention has been described in
some detail by way of illustration and example for purposes of
clarity and understanding, it will be apparent that certain changes
and modifications may be practiced within the scope of the appended
claims.
[0114] The above disclosure generally describes the present
invention A more complete understanding can be obtained by
reference to the following specific examples which are provided
herein for purposes of illustration only, and are not intended to
limit the scope of the invention.
EXAMPLES
[0115] The following examples are offered to illustrate, but not to
limit the present invention.
Example 1
[0116] Detection of genes differentially expressed in the secretory
and proliferative stage endometrium. This is the first report of
differential expression between two different physiological states
in human subjects. The data obtained from this experiment
demonstrates that there are differences in gene expression between
different physiological states in humans. These differences are
large enough to be detected by arrays and the number of genes
changed is substantial but manageable, making the information
useful for diagnostic and prognostic applications.
[0117] Experiments were designed to identify genes that were
differentially expressed in the physiologically distinct secretory
and proliferative stages of endometrial tissue. Gene expression
levels were quantitatively measured in tissue samples using high
density oligonucleotide arrays containing probes representing
approximately 6800 full-length human genes (commercially available
from Affymetrix, Santa Clara). Probe arrays (DNA chips) of this
type have been shown to behave quantitatively with high specificity
and sensitivity (Lockhart, D J et al, 1996, Nat Biotech 14
1657-1680). See also, U.S. Pat. No. 6,040,138 The probe sequences
were based on information from public sequence databases, such a
GenBank Samples derived from secretory and proliferative stage
endometrium were hybridized to the probe arrays and the relative
concentration of more than 6800 human genes were measured
simultaneously. The RNAs were classified by relative abundance and
differentially expressed genes were identified by direct
comparison. Using this method one can produce, in a relatively
short period of time, a quantitative representation of gene
expression for a plurality of different physiological states for a
plurality of different cell or tissue types.
1TABLE 1 Genes downregulated in proliferative vs secretory
endometrium Avg Diff Probe Set Change Fold Change Entrez Definition
HG721- -13342 -56 6 Placental Protein 14, Endometrial Alpha 2
HT4828 Globulin, Alt Splice 3 HG721- -12704 -45 5 Placental Protein
14, Endometrial Alpha 2 HT4827 Globulin, Alt Splice 2 D00632 -8069
-27 7 Human plasma (extracellular) mRNA for glutathione peroxidase,
complete cds X64177 -11610 -39 3 H sapiens mRNA for metallothionein
X04470 -6159 -16 8 Human mRNA for antileukoprotease (ALP) from
cervix uterus M83667 -5851 -14 9 Human NF-IL6-beta protein mRNA,
complete cds M13690 -5998 -13 8 Human plasma protease (C1)
inhibitor mRNA, complete cds Y10032 -3126 -13 4 H sapiens mRNA for
putative serine/threonine protein kinase X65965 -1760 -11 1 H
sapiens SOD-2 gene for manganese superoxide dismutase M34455 -3551
-8 6 Human interferon-gamma-inducible indoleamine 2,3-dioxygenase
(IDO) mRNA, complete cds U10117 -1315 -10 8 Human
endothelial-monocyte activating polypeptide II mRNA, complete cds
D15050 -668 -5 Human mRNA for transcription factor AREB6, complete
cds K02765_at -8578 -8 1 Human complement component C3 mRNA, alpha
and beta subunits, complete cds M59815 -6015 -7 3 Human complement
component C4A gene J02611 -10627 -8 8 Human apolipoprotein D mRNA,
complete cds M60974 -977 -5 2 Human growth arrest and DNA-damage-
inducible protein (gadd45) mRNA, complete cds U28368 -1357 -6 7
Human Id-related helix-loop-helix protein Id4 mRNA, complete cds
M85276 -10891 -14 3 Homo sapiens NKG5 gene, complete cds HG2981-
-722 -7 1 Epican, Alt Splice 1 1 HT3127 X92744 -3311 -10 6 H
sapiens mRNA for hBD-1 protein X97324 -1020 -7 4 H sapiens mRNA for
adipophilin /gb = X97324 /ntype = RNA M55153 -2002 -6 5 Human
transglutaminase (TGase) mRNA, complete cds M61916 -1907 -5 8 Human
laminin B1 chain mRNA, complete cds M55543 -370 *-4 3 Human
guanylate binding protein isoform II (GBP-2) mRNA, complete cds
M97796 -3808 -5 4 Human helix-loop-helix protein (Id-2) mRNA,
complete cds M13929 -1042 -5 6 Human c-myc-P64 mRNA, initiating
from promoter P0, (HLmyc2 5) partial cds L00058 -886 -5 5 Human
(GH) germline c-myc proto- oncogene, 5' flank U02556 -3709 -9 2
Human RP3 mRNA, complete cds J04080 -8872 -6 2 Human complement
component C1r mRNA, complete cds U08989 -984 -6 4 Human glutamate
transporter mRNA, complete cds X16396 -615 -5 9 Human mRNA for
NAD-dependent methylene tetrahydrofolate dehydrogenase
cyclohydrolase (EC 1 5 1 15) M26062 -1378 -11 6 Human interleukin 2
receptor beta chain (p70-75) mRNA, complete cds U63455 -1401 -6 3
Human sulfonylurea receptor (SUR1) gene X69699 -4265 -5 4 H sapiens
Pax8 mRNA M24069 -1090 -6 1 Human DNA-binding protein A (dbpA)
gene, 3' end M27492 -2004 -4 6 Human interleukin 1 receptor mRNA,
complete cds M14058 -4723 -5 4 Human complement C1r mRNA, complete
cds S37730 -6004 -6 9 insulin-like growth factor binding protein- 2
[human, placenta, Genomic, 4575 nt 4 segments] U46499 -1951 -4 5
Human microsomal glutathione transferase (GST12) gene, 5' sequence
M21574 -2474 -6 Human platelet-derived growth factor receptor alpha
(PDGFRA) mRNA, complete cds U65093 -1037 -6 9 Human msg1-related
gene 1 (mrg1) mRNA, complete cds X76717 -5904 -8 5 H sapiens MT-11
mRNA U33147 -976 -7 5 Human mammaglobin mRNA, complete cds U09284
-1158 -4 5 Human PINCH protein mRNA, complete cds M94856 -1105 -4 9
Human fatty acid binding protein homologue (PA-FABP) mRNA, complete
cds X65614 -5954 -28 9 H sapiens mRNA for calcium-binding protein
S100P Z68228 -2909 -5 H sapiens mRNA for plakoglobin D87953 -2386
-4 4 Human mRNA for RTP, complete cds K02574 -1199 -4 Human purine
nucleoside phosphorylase (PNP) mRNA, complete cds X05908 -744 -4 4
Human mRNA for lipocortin U21936 -1382 *-13 4 Human peptide
transporter (HPEPT1) mRNA, complete cds J04102 -689 *-7 2 Human
erythroblastosis virus oncogene homolog 2 (ets-2) mRNA, complete
cds M62486 -1190 *-11 7 Human C4b-binding protein gene Z19002 -1444
*-14 0 H sapiens of PLZF gene encoding kruppel-like zinc finger
protein X57348 -1411 *-13 7 H sapiens mRNA (clone 9112) M15958
-1554 *-15 0 Human gastrin gene, complete cds M13955 -363 *-4 3
Human mesothelial keratin K7 (type II) mRNA, 3' end U51010 -1007
*-10 1 Human nicotinamide N-methyltransferase gene, exon 1 and 5'
flanking region /gb = U51010 /ntype = DNA /annot = exon M92357
-1377 -11 6 Homo sapiens B94 protein mRNA, complete cds M38591
-1176 *-11 6 Homo sapiens cellular ligand of annexin II (p11) mRNA,
complete cds U20758 -1314 *-12 8 Human osteopontin gene, complete
cds M13699 -2125 *-20 1 Human ceruloplasmin (ferroxidase) mRNA,
complete cds J05068 -1459 *-14 1 human transcobalamin I mRNA,
complete cds L32137 -1246 *-12 2 Human germline oligomeric matrix
protein (COMP) mRNA, complete cds U08021 -2064 *-19 6 Human
nicotinamide N-methyltransferase (NNMT) mRNA, complete cds U07919
-3912 *-36 2 Human aldehyde dehydrogenase 6 mRNA, complete cds
M84526 -3742 *-34 7 Human adipsin/complement factor D mRNA,
complete cds X96719 -388 *-4 5 H sapiens mRNA for AICL (activation-
induced C-type lectin) L09235 -895 *-9 0 Human vacuolar ATPase
(isoform VA68) mRNA, complete cds U14528 -499 *-5 5 Human sulfate
transporter (DTD) mRNA, complete cds HG4321- -336 *-4 0
Ahnak-Related Sequence HT4591 X95240 -591 *-6 3 H sapiens mRNA for
cysteine-rich secretory protein-3 X58079 -388 *-4 5 Human mRNA for
S100 alpha protein U42031 -696 *-7 3 Human 54 kDa progesterone
receptor- associated immunophilin FKBP54 mRNA, partial cds M31516
-841 *-8 6 Human decay-accelerating factor mRNA, complete cds
X92814 -669 *-7 0 H sapiens mRNA for rat HREV107-like protein
X87342 -581 *-6 2 H sapiens mRNA for human giant larvae homolog
U60873 -388 *-4 5 Human clone 137308 mRNA, partial cds U00115 -622
*-6 6 Human zinc-finger protein (bcl-6) mRNA, complete cds L11005
-422 *-4 8 Human aldehyde oxidase (hAOX) mRNA, complete cds Z26653
-1126 *-11 1 H sapiens mRNA for laminin M chain (merosin) D31762
-739 *-7 6 Human mRNA for KIAA0057 gene, complete cds U25997 -728
*-7 5 Human stanniocalcin precursor (STC) mRNA, complete cds U17760
-700 *-7 3 Human laminin S B3 chain (LAMB3) gene U26173 -615 *-6 5
Human bZIP protein NF-IL3A (IL3BP1) mRNA, complete cds M57730 -827
*-8 4 Human B61 mRNA, complete cds M22430 -1069 *-10 6 Human RASF-A
PLA2 mRNA, complete cds V00594 -15429 *-139 7 Human mRNA for
metallothionein from cadmium-treated cells *expression level in
proliferative was close to 0 Indistinguishable from background
[0118]
2TABLE 2 Genes upregulated in proliferative vs secretory Avg Diff
Fold Accession number Change Change Entrez Definition M34516 4759
*43 8 Human omega light chain protein 14 1 (Ig lambda chain
related) gene M63438 8960 *81 6 Human Ig rearranged gamma chain
mRNA, V-J-C region and complete cds L22524 717 *7 4 Human
matrilysin gene X57766 6160 7 Human stromelysin-3 mRNA M16364 1877
*17.9 Human creatine kinase-B mRNA, complete cds M68516 910 6 7 PCI
gene (plasminogen activator inhibitor 3) extracted from Human
protein C inhibitor gene, complete cds J04970 998 *10 0 Human
carboxypeptidase M, 3' end U83411 1586 *15 3 Homo sapiens carboxy-
peptidase Z precursor, mRNA, complete cds U79299 1359 6 Human
neuronal olfacto- medin-related ER localized protein mRNA, partial
cds L38517 1527 *14 7 Homo sapiens indian hedgehog protein (IHH)
mRNA, 5' end M96789 914 *9 2 Homo sapiens connexin 37 (GJA4) mRNA,
complete cds AFFX- 6662 16 2 HUMRGE/M10098.sub.-- M_at AFFX- 3192
13 7 HUMRGE/M10098.sub.-- 5_at *expression level in secretory was
close to 0 Indistinguishable from background
Example 2
[0119] Detection of gene expression changes in endometrial cancer
(adenocarcinoma and clear cell carcinoma). The goals of the
experiment were an improved understanding of etiology,
identification of candidate genes, improved diagnostics, and
improved therapeutics. Tissues used in the study were 4 matched
adenocarcinomas, surgically obtained with matching normal tissue.
All patients were of Northern European descent. Total RNA was
isolated from surgical samples and hybridized to Affymetrix HuGene
FL arrays as in Example 1.
3TABLE 3 Tissue sample origin Patient number Age in years Normal
sample Tumor sample 87 57 Endometrium Grade III 106 65 Benign tumor
Grade III 119 75 Endometrium Grade III 122 75 Endometrium Grade
III
[0120]
4TABLE 4 Genes expresses in normal v endometrial tumor normal tumor
Transcripts detected 989 835 Unique transcripts 318 164 Shared
detected 671 671 Shared absent 2736 2736
[0121]
5TABLE 5 Genes differentially expressed in endometrial tumors
Present in Normals/ Absent in Tumors Absent in Normals/Present in
Tumors KIAA0367 KIAA0119 Platelet activating factor acetylhydrolase
1B gamma- subunit UDP-galactose transporter related isozyme High
mobility group protein (HMG-1) Lamin B
[0122]
6TABLE 6 Genes differentially expressed by at least 4 fold in
endometrial tumors Cyclin-selective ubiquitin Alpha topoisomerase
truncated-form carrier Connexin Carcinoma-associated antigen PKC
zeta, thymidine kinase +2 p78 Keratin 7 Thyroid receptor interactor
(TRIP7) NGAL Nucleolar protein p40 Gastrointestinal
tumor-associated antigen Sm protein F Cyclin A1 Ezrin Placental
bikunin Cycstatin B SIX1 Placental protein 15 Chaperonin 10
Retinoic acid inducible factor Diazepam binding inhibitor Splicing
factor SRp30c Histone H2B 1 MLN62 Nm23 BST-2 Thymosin beta-10
Ribosomal protein L3 Nuclear localization sequence receptor PAX8
hSRP1alpha Stromelysin 3 Transformation-sensitive protein Tumor
rejection antigen gp96 Mitochondrial matrix protein P1 Inositol
polyphosphate 5-phosphatase, HSP 90 beta-glucuronidase DM kinase,
Flt4 tyrosine kinase, ERK1, Oncoprotein 18 protein serine/threonine
kinase, Protein Kinase Ht31, creatine kinase-B KIAA0015, 172, 136,
092, 073, 382, 263, PDGF receptor, steroid 084, 239, Unknown - 2
hormone receptor Ner-I Glycine-rich RNA binding protein Splicing
factor, SF1-Bo isoform Homeotic Protein Pl2 Serum response factor
(SRF), ERF-2, guanine nucleotide regulatory factor (LFP40), PSE-
binding factor PTF delta subunit Non-muscle alpha-actinin Collagen
VI alpha-2 Cisplatin resistance associated alpha MTG8a protein
(hCRA alpha) Serum constituent protein (MSE55) MADER CDC42
GTPase-activating protein ARP-1 Guanine nucleotide-binding
regulatory HOX 5 1 protein (G-y-alpha)) Ubiquitin-activating enzyme
E1 related p126 (ST5) protein HNF-3/fork-head homolog-3 HFH-3
Archain PKD1 Bcl-6 Cyclin 1 SATB1 HCG V
Example 3
[0123] Matched normal tissue and adenocarcinoma or clear cell
carcinomas ranging from Grade I to III were collected from more
than 10 patients. Total RNA was used as starting material for the
preparation of fluorescently labeled nucleic acid targets from all
of the samples. The labeled targets were hybridized to high-density
DNA microarrays containing probes representing .about.6800
full-length human genes (Affymetrix, Inc., Santa Clara, Calif.).
Sample preparation and hybridization was carried out in a manner
similar to the examples and description above. Differential gene
expression patterns in both of the subtypes of endometrial cancer
were identified.
7TABLE 7 Differential expression in endometrial cancers Clear cell
Normal Adenocarcinoma carcinoma MIF - + Cyclin A1 - + MRG1 + - HOX1
+ - Alpha 2 collagen + +/- type VI Adducin + +/- +/- Cyclin B +/- +
PKC zeta +/- + Calponin + - Caldesmon + - Keratin K17 - + ESE-1b -
+ HMG1 - + LAMB3 +/- + Laminin SB3 +/- + Osteopontin +/- + decorin
+ +/- ([-], no expression observed, [+], expression observed,
[+/-], expression observed but lower than corresponding matched
sample)
Example 4
[0124] GeneCluster. The application of self-organizing maps, a type
of mathematical cluster analysis that is particularly well suited
for recognizing and classifying features in complex,
multidimensional data. The method has been implemented in a
publicly available computer package, GENECLUSTER, that performs the
analytical calculations and provides easy data visualization
GENECLUSTER was used to organize the genes into biologically
relevant clusters. SOMs have a number of features that make them
particularly well suited to clustering and analysis of gene
expression patterns. They are ideally suited to exploratory data
analysis, allowing one to impose partial structure on the clusters
(in contrast to the rigid structure of hierarchical clustering, the
strong prior hypotheses used in Bayesian clustering, and the
nonstructure of k-means clustering) and facilitating easy
visualization and interpretation. SOMs have good computational
properties and are easy to implement, reasonably fast, and scalable
to large data sets. SOMs have been well studied and empirically
tested on a wide variety of problems.
[0125] The microarray data, though voluminous, can be analyzed by
pattern recognition (clustering) software to aid in deriving lists
of genes that distinguish and characterize disease versus normal
biopsies, thus shedding light on molecular genetic profiles and
ultimately the mechanism of the disease under study. Techniques
used for clustering include self-organizing maps (SOM), Bayesian,
hierarchical, and k-means SOM was selected for our analysis because
of advantages in initial exploration of the data allowing the
operator to impose partial structure on the clusters 9. Other
advantages of SOM include good computational properties,
computational speed and easy implementation.
[0126] GeneCluster Analysis was conducted on endometrial cancer
samples. It reveals that expression patterns delineating normal
from tumor tissues. Hierarchical clustering using GenExplore
distingushed majority of the normal and tumor tissues.
CONCLUSION
[0127] From the foregoing it can be seen that the advantage of the
present invention is that samples that differ from one another in
multiple variables can be analyzed in such a way as to account for
the variables and to focus on elements that are under
investigation, such as disease state for example. Comparison of
matched samples eliminates gene expression differences that are the
result of changes in variables that are not of interest. The gene
expression differences that remain can be attributed with a high
degree of confidence to the unmatched variation. The gene
expression differences thus identified can be used for example to
diagnose disease, identify physiological state, design drugs, and
monitor therapies.
[0128] All publications and patent applications cited above are
incorporated by reference in their entirety for all purposes to the
same extent as if each individual publication or patent application
were specifically and individually indicated to be so incorporated
by reference. Although the present invention has been described in
some detail by way of illustration and example for purposes of
clarity and understanding, it will be apparent that certain changes
and modifications may be practiced within the scope of the appended
claims.
* * * * *