U.S. patent application number 17/683656 was filed with the patent office on 2022-06-16 for methods for predicting anti-cancer response.
This patent application is currently assigned to Children's Medical Center Corporation. The applicant listed for this patent is The Brigham and Women's Hospital, Inc., Children's Medical Center Corporation, Dana-Farber Cancer Institute, Inc., The Technical University of Denmark. Invention is credited to Nicolai Juul BIRKBAK, Aron EKLUND, Andrea RICHARDSON, Daniel SILVER, Zoltan SZALLASI, Zhigang WANG.
Application Number | 20220186311 17/683656 |
Document ID | / |
Family ID | |
Filed Date | 2022-06-16 |
United States Patent
Application |
20220186311 |
Kind Code |
A1 |
SZALLASI; Zoltan ; et
al. |
June 16, 2022 |
METHODS FOR PREDICTING ANTI-CANCER RESPONSE
Abstract
The present invention is based, in part, on the identification
of novel methods for defining predictive biomarkers of response to
anti-cancer drugs.
Inventors: |
SZALLASI; Zoltan; (Boston,
MA) ; BIRKBAK; Nicolai Juul; (Kobenhaven O, DK)
; EKLUND; Aron; (Kobenhaven O, DK) ; SILVER;
Daniel; (Wayland, MA) ; WANG; Zhigang;
(Chestnut Hill, MA) ; RICHARDSON; Andrea;
(Chestnut Hill, MA) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Children's Medical Center Corporation
The Technical University of Denmark
Dana-Farber Cancer Institute, Inc.
The Brigham and Women's Hospital, Inc. |
Boston
Lingby
Boston
Boston |
MA
MA
MA |
US
DK
US
US |
|
|
Assignee: |
Children's Medical Center
Corporation
Boston
MA
The Technical University of Denmark
Lingby
MA
Dana-Farber Cancer Institute, Inc.
Boston
MA
The Brigham and Women's Hospital, Inc.
Boston
|
Appl. No.: |
17/683656 |
Filed: |
March 1, 2022 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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16235247 |
Dec 28, 2018 |
11299782 |
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17683656 |
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14466208 |
Aug 22, 2014 |
10190160 |
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16235247 |
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PCT/US13/27295 |
Feb 22, 2013 |
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14466208 |
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61602460 |
Feb 23, 2012 |
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61604810 |
Feb 29, 2012 |
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International
Class: |
C12Q 1/6874 20060101
C12Q001/6874; C12Q 1/6886 20060101 C12Q001/6886 |
Goverment Interests
GOVERNMENT SUPPORT
[0002] This invention was made with government support under grant
number CA089393097193 awarded by National Institutes of Health. The
Government has certain rights in the invention.
Claims
1. An assay for selecting therapy for a subject having cancer, the
assay comprising subjecting a biological sample comprising a cancer
cell or nucleic acid from a cancer cell taken from the subject to
telomeric allelic imbalance (tAI) analysis; detecting the number of
telomeric allelic imbalance (NtAI) in the cancer cell or nucleic
acid from the cancer cell, and selecting a platinum-comprising
therapy for the subject when the NtAI is detected to be above a
reference value based on the recognition that platinum-comprising
therapy is effective in patients who have NtAI above the reference
value; and selecting a non-platinum-comprising cancer therapy for
the subject when the NtAI is detected to be below a reference value
based on the recognition that platinum-comprising cancer therapy is
not effective in patients who have the NtAI below a reference
value.
2. The assay of claim 1 further comprising the step of treating the
subject with the selected therapy.
3. The assay of claim 1, wherein the cancer is breast cancer or
ovarian cancer.
4. The assay of claim 1, wherein the reference value is 22.
5. The assay of claim 1, wherein the reference value is 24.
6. The assay of claim 1, wherein the reference value is 27.
7. The assay of claim 1, wherein the cancer cell does not have
mutations in the BRCA1 and/or BRCA2 gene.
8. The assay of claim 1 further comprising a step of assaying for
BRCA1 mRNA expression or methylation status of the BRCA1 promoter,
detecting the amount of BRCA1 mRNA expression or the amount of
methylation of the BRCA1 promoter, wherein the platinum comprising
therapy is selected when decreased expression of BRCA1 or increased
methylation of BRCA1 promoter is detected.
9. A method for selecting platinum-comprising therapy for a subject
having cancer comprising subjecting a biological sample taken from
the subject to allelic imbalance (AI) analysis; detecting the
number of AI; and selecting platinum-comprising cancer therapy for
the subject when the number of AIs is above a reference value based
on the recognition that platinum-comprising cancer therapy is
effective in patients who have the number of AIs is above a
reference value.
10. The method of claim 9 further comprising the step of treating
the subject with platinum-comprising cancer therapy when
platinum-comprising cancer therapy is selected.
11. The method of claim 9, wherein the cancer is selected from
breast cancer and ovarian cancer.
12. The method of claim 11, wherein the breast cancer does not have
a BRCA1 mutations.
13. The method of claim 9, wherein the allelic imbalance is within
about 25 kB of a copy number variation (CNV).
14. The method of claim 13, wherein the CNV is pericentromeric or
subtelomeric CNV.
15. The method of claim 9, wherein the allelic imbalance is
telomeric allelic imbalance.
16. A method comprising: detecting, in a cancer cell or genomic DNA
derived therefrom, allelic imbalance in a representative number of
pairs of human chromosomes of the cancer cell; and determining the
number of allelic imbalance.
17. The method of claim 16, said representative number of pairs of
human chromosomes is representative of the entire genome.
18. The method of claim 16, further comprising correlating an
increased number of allelic imbalance regions to an increased
likelihood of deficiency in HDR.
19. The method of claim 16, further comprising correlating an
increased number of allelic imbalance regions to an increased
likelihood of said cancer cell to respond to platinum comprising
cancer therapy.
20. The method of claim 16, further comprising correlating a
non-increased number of allelic imbalance regions to a decreased
likelihood of said cancer cell to respond to platinum comprising
cancer therapy.
21. The method of claim 19 or 20, wherein the platinum comprising
cancer therapy comprises cisplatin, carboplatin, oxalaplatin, or
picoplatin.
22. A method comprising: a) detecting, in a cancer cell or genomic
DNA derived therefrom, LOH regions in a representative number of
pairs of human chromosomes of the cancer cell; and b) determining
the number and size of said LOH regions.
23. The method of claim 22, said representative number of pairs of
human chromosomes is representative of the entire genome.
24. The method of claim 22, further comprising correlating an
increased number of LOH regions of a particular size to an
increased likelihood of deficiency in HDR.
25. The method of claim 24, wherein said particular size is longer
than about 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 75, or 100
megabases and less than the length of the entire chromosome that
contains the LOH region.
26. The method of either of claim 24 or 25, wherein 6, 7, 8, 9, 10,
11, 12 or 13 or more LOH regions of said particular size are
correlated to an increased likelihood of deficiency in HDR.
27. A method of determining prognosis in a patient comprising: a)
determining whether the patient comprises cancer cells having an
LOH signature, wherein the presence of more than a reference number
of LOH regions in at least one pair of human chromosomes of a
cancer cell of the cancer patient that are longer than a first
length but shorter than the length of the whole chromosome
containing the LOH region indicates that the cancer cells have the
LOH signature, wherein the at least one pair of human chromosomes
is not a human X/Y sex chromosome pair, wherein the first length is
about 1.5 or more megabases, an b) (1) determining, based at least
in part on the presence of the LOH signature, that the patient has
a relatively good prognosis, or b)(2) determining, based at least
in part on the absence of the LOH signature, that the patient has a
relatively poor prognosis
28. A composition comprising a therapeutic agent selected from the
group consisting of DNA damaging agent, anthracycline,
topoisomerase I inhibitor, and PARP inhibitor for use in treating a
cancer selected from the group consisting of breast cancer, ovarian
cancer, liver cancer, esophageal cancer, lung cancer, head and neck
cancer, prostate cancer, colon cancer, rectal cancer, colorectal
cancer, and pancreatic cancer in a patient with more than a
reference number of LOH regions in at least one pair of human
chromosomes of a cancer cell of the patient that are longer than a
first length but shorter than the length of the whole chromosome
containing the LOH region, wherein the at least one pair of human
chromosomes is not a human X/Y sex chromosome pair, wherein the
first length is about 1.5 or more megabases.
29. The composition of claim 28, wherein said LOH regions are
determined in at least two, five, ten or 21 pairs of human
chromosomes.
30. The composition of claim 28, wherein the total number of said
LOH regions is 9, 15, 20 or more.
31. The composition of claim 28, wherein said first length is about
6, 12, or 15 or more megabases.
32. The composition of claim 28, wherein said reference number is
6, 7, 8, 9, 10, 11, 12 or 13 or greater.
33. A method of treating cancer in a patient, comprising: a)
determining in a sample from said patient the number of LOH regions
in at least one pair of human chromosomes of a cancer cell of the
cancer patient that are longer than a first length but shorter than
the length of the whole chromosome containing the LOH region
indicates that the cancer cells have the LOH signature, wherein the
at least one pair of human chromosomes is not a human X/Y sex
chromosome pair, wherein the first length is about 1.5 or more
megabases; b) providing a test value derived from the number of
said LOH regions; c) comparing said test value to one or more
reference values derived from the number of said LOH regions in a
reference population (e.g., mean, median, terciles, quartiles,
quintiles, etc.); and d) administering to said patient an
anti-cancer drug, or recommending or prescribing or initiating a
treatment regimen comprising chemotherapy and/or a synthetic
lethality agent based at least in part on said comparing step
revealing that the test value is greater (e.g., at least 2-, 3-,
4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater; at least 1, 2, 3, 4, 5,
6, 7, 8, 9, or 10 standard deviations greater) than at least one
said reference value; or e) recommending or prescribing or
initiating a treatment regimen not comprising chemotherapy and/or a
synthetic lethality agent based at least in part on said comparing
step revealing that the test value is not greater (e.g., not more
than 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater; not more
than 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standard deviations greater)
than at least one said reference value.
34. The method of claim 33, wherein said LOH regions are determined
in at least two, five, ten or 21 pairs of human chromosomes.
35. The method of claim 33, wherein the total number of said LOH
regions is 9, 15, 20 or more.
36. The method of claim 33, wherein said first length is about 6,
12, or 15 or more megabases.
37. The method of claim 33, wherein said reference number is 6, 7,
8, 9, 10, 11, 12 or 13 or greater.
38. The method of claim 33, wherein said chemotherapy is selected
from the group consisting of a DNA damaging agent, an
anthracycline, and a topoisomerase I inhibitor and/or wherein said
synthetic lethality agent is a PARP inhibitor drug.
39. The method of claim 33, wherein said DNA damaging agent is
cisplatin, carboplatin, oxalaplatin, or picoplatin, said
anthracycline is epirubincin or doxorubicin, said topoisomerase I
inhibitor is campothecin, topotecan, or irinotecan, and/or said
PARP inhibitor is iniparib, olaparib or velapirib.
40. A composition comprising a therapeutic agent selected from the
group consisting of platinum comprising cancer therapy and
anthracycline for use in treating a cancer selected from the group
consisting of breast cancer, ovarian cancer, liver cancer,
esophageal cancer, lung cancer, head and neck cancer, prostate
cancer, colon cancer, rectal cancer, colorectal cancer, and
pancreatic cancer in a patient with increased allelic
imbalance.
41. The composition of claim 40, wherein the allelic imbalance is
telomeric allelic imbalance.
42. The composition of claim 40, wherein the allelic imbalance is
within about 25 kB of a copy number variation (CNV).
43. The composition of claim 40, wherein the patient is further
determined not to carry a BRCA1 and/or BRCA2 mutation.
44. The composition of claim 40 or 43, wherein the patient is
further determined to have decreased BRCA1 mRNA amount in the
cancer cell and/or is further determined to have increased
methylation of the BRCA1 promoter region.
45. A method for predicting the outcome of anti-cancer treatment of
a subject with a cell hyperproliferative disorder, comprising
determining a global chromosomal aberration score (GCAS),
comprising obtaining a biological sample from the subject and
determining whether a plurality of chromosomal regions displaying a
chromosomal aberration exists within a plurality of chromosomal
loci, wherein said chromosomal aberrations are selected from the
group consisting of allelic imbalance (NAI), loss of heterozygosity
(NLOH), copy number aberrations (NCNA), copy number gain (NCNG),
copy number decrease (NCND) and combinations thereof, relative to a
control, and wherein the presence of a plurality of chromosomal
regions displaying said chromosomal aberrations predicts the
outcome of anti-cancer treatment of the subject.
46. The method of claim 45, wherein the anti-cancer treatment is
chemotherapy treatment.
47. The method of claim 46, wherein the chemotherapy treatment
comprises platinum-based chemotherapeutic agents.
48. The method of claim 47, wherein the platinum-based
chemotherapeutic agents are selected from the group consisting of
cisplatin, carboplatin, oxaliplatin, nedaplatin, and
iproplatin.
49. The method of claim 45, wherein the subject is a human.
50. The method of claim 45, wherein the cell hyperproliferative
disorder is selected from the group consisting of breast cancer,
ovarian cancer, transitional cell bladder cancer, bronchogenic lung
cancer, thyroid cancer, pancreatic cancer, prostate cancer, uterine
cancer, testicular cancer, gastric cancer, soft tissue and
osteogenic sarcomas, neuroblastoma, Wilms' tumor, malignant
lymphoma (Hodgkin's and non-Hodgkin's), acute myeloblastic
leukemia, acute lymphoblastic leukemia, Kaposi's sarcoma, Ewing's
tumor, refractory multiple myeloma, and squamous cell carcinomas of
the head, neck, cervix, colon cancer, melanoma, and vagina.
51. The method of claim 45, wherein the biological sample is
selected from the group consisting of cells, cell lines,
histological slides, frozen core biopsies, paraffin embedded
tissues, formalin fixed tissues, biopsies, whole blood, nipple
aspirate, serum, plasma, buccal scrape, saliva, cerebrospinal
fluid, urine, stool, and bone marrow.
52. The method of claim 45, wherein the biological sample is
enriched for the presence of hyperproliferative cells to at least
75% of the total population of cells.
53. The method of claim 52, wherein the enrichment is performed
according to at least one technique selected from the group
consisting of needle microdissection, laser microdissection,
fluorescence activated cell sorting, and immunological cell
sorting.
54. The method of claim 52 or 53, wherein an automated machine
performs the at least one technique to thereby transform the
biological sample into a purified form enriched for the presence of
hyperproliferative cells.
55. The method of claim 45, wherein the biological sample is
obtained before the subject has received adjuvant chemotherapy.
56. The method of claim 45, wherein the biological sample is
obtained after the subject has received adjuvant chemotherapy.
57. The method of claim 45, wherein the control is determined from
a non-cell hyperproliferative cell sample from the patient or
member of the same species to which the patient belongs.
58. The method of claim 45, wherein the control is determined from
the average frequency of genomic locus appearance of chromosomal
regions of the same ethnic group within the species to which the
patient belongs.
59. The method of claim 57 or 58, wherein the control is from
non-cancerous tissue that is the same tissue type as said cancerous
tissue of the subject.
60. The method of claim 57 or 58, wherein the control is from
non-cancerous tissue that is not the same tissue type as said
cancerous tissue of the subject.
61. The method of claim 45, wherein NAI is determined using major
copy proportion (MCP).
62. The method of claim 61, wherein NAI for a given genomic region
is counted when MCP is greater than 0.70.
63. The method of claim 45, wherein the plurality of chromosomal
loci are randomly distributed throughout the genome at least every
100 Kb of DNA.
64. The method of claim 45, wherein the plurality of chromosomal
loci comprise at least one chromosomal locus on each of the 23
human chromosome pairs.
65. The method of claim 45, wherein the plurality of chromosomal
loci comprise at least one chromosomal locus on each arm of each of
the 23 human chromosome pairs.
66. The method of claim 65, wherein the plurality of chromosomal
loci comprise at least one chromosomal locus on at least one
telomere of each of the 23 human chromosome pairs.
67. The method of claim 66, wherein the plurality of chromosomal
loci comprise at least one chromosomal locus on each telomere of
each of the 23 human chromosome pairs.
68. The method of claim 45 or 67, wherein the chromosomal
aberrations have a minimum segment size of at least 1 Mb.
69. The method of claim 68, wherein the chromosomal aberrations
have a minimum segment size of at least 12 Mb.
70. The method of claim 45, wherein the plurality of chromosomal
aberrations comprises at least 5 chromosomal aberrations.
71. The method of claim 70, wherein the plurality of chromosomal
aberrations comprises at least 13 chromosomal aberrations.
72. The method of claim 45, wherein the chromosomal loci are
selected from the group consisting of single nucleotide
polymorphisms (SNPs), restriction fragment length polymorphisms
(RFLPs), and simple tandem repeats (STRs).
73. The method of claim 45, wherein the chromosomal loci are
analyzed using at least one technique selected from the group
consisting of molecular inversion probe (MIP), single nucleotide
polymorphism (SNP) array, in situ hybridization, Southern blotting,
transcriptional arrays, array comparative genomic hybridization
(aCGH), and next-generation sequencing.
74. The method of claim 45, wherein outcome of treatment is
measured by at least one criteria selected from the group
consisting of survival until mortality, pathological complete
response, semi-quantitative measures of pathologic response,
clinical complete remission, clinical partial remission, clinical
stable disease, recurrence-free survival, metastasis free survival,
disease free survival, circulating tumor cell decrease, circulating
marker response, and RECIST criteria.
75. The method of claim 45, further comprising determining a
suitable treatment regimen for the subject.
76. The method of claim 75, wherein said suitable treatment regimen
comprises at least one platinum-based chemotherapeutic agent when a
plurality of genomic chromosomal aberrations is determined or does
not comprise at least one platinum-based chemotherapeutic agent
when no plurality of genomic chromosomal aberrations is determined.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] This application is continuation application of U.S. patent
application Ser. No. 16/235,247 filed Dec. 28, 2018, which is a
continuation application of U.S. patent application Ser. No.
14/466,208 filed Aug. 22, 2014, now U.S. Pat. No. 10,190,160, which
is a continuation application of International Application No.
PCT/US13/27295 filed Feb. 22, 2013, which claims benefit under 35
U.S.C. 119(e) of U.S. provisional applications No. 61/602,460 filed
Feb. 23, 2012, and 61/604,810 filed Feb. 29, 2012, the contents of
which are incorporated herein by reference in their entirety.
BACKGROUND OF THE INVENTION
[0003] Medical oncologists have benefited greatly from relatively
recent efforts to dissect and understand the genetic elements
underlying mammalian cancer. The identification of specific genetic
predispositions, such as mutations in BRCA-1, BRCA2, and HER2, has
provided key insights into the mechanisms underlying tumorigenesis
and has proven useful for the design of new generations of targeted
approaches for clinical intervention. With the determination of the
human genome sequence and improvements in sequencing and
bioinformatics technologies, systematic analyses of genetic
alterations in human cancers have become possible.
[0004] However, clinical interventions based upon this information
have been severely hampered by the fact that often only a
percentage of patients will respond favorably to a particular
anti-cancer treatment. Medical oncologists currently cannot
generally predict which patients will or will not respond to a
proposed chemotherapeutic treatment.
[0005] Accordingly, there is a great need in the art to identify
patient responsiveness to particular anti-cancer therapies.
SUMMARY OF THE INVENTION
[0006] The present invention is based, at least in part, on the
discovery that certain patterns of DNA aberrations described herein
are predictive of anti-cancer response of the cells harboring such
DNA aberrations to anti-cancer therapies.
[0007] Accordingly, in one aspect, the present invention features a
method for predicting the outcome of anti-cancer treatment of a
subject with a cell hyperproliferative disorder, comprising
determining a global chromosomal aberration score (GCAS),
comprising obtaining a biological sample from the subject and
determining whether a plurality of chromosomal regions displaying a
chromosomal aberration exists within a plurality of chromosomal
loci, wherein said chromosomal aberrations are selected from the
group consisting of allelic imbalance (AI), loss of heterozygosity
(LOH), copy number aberrations (CNA), copy number gain (CNG), copy
number decrease (CND) and combinations thereof, relative to a
control, and wherein the presence of a plurality of chromosomal
regions displaying said chromosomal aberrations predicts the
outcome of anti-cancer treatment of the subject. The subject can be
a mammal, such as a human.
[0008] For example, mutations in BRCA1 or BRCA2 cause defects in
DNA repair that predict sensitivity to platinum salts in breast and
ovarian cancer; however, some patients without BRCA mutations also
benefit from these agents. This study shows that defects in DNA
repair that cause platinum sensitivity can be inferred from the
number of allelic imbalance (AI) or the number of telomeric allelic
imbalance (NtAI), a measure of genomic aberration in tumors. NtAI
may identify cancer patients without BRCA mutations who are likely
to benefit from platinum-based therapy.
[0009] In one aspect, the anti-cancer treatment is chemotherapy
treatment. In another embodiment, the anti-cancer treatment
comprises platinum-based chemotherapeutic agents (e.g., cisplatin,
carboplatin, oxaliplatin, nedaplatin, and iproplatin).
[0010] In another aspect, the cell hyperproliferative disorder is
selected from the group consisting of breast cancer, ovarian
cancer, transitional cell bladder cancer, bronchogenic lung cancer,
thyroid cancer, pancreatic cancer, prostate cancer, uterine cancer,
testicular cancer, gastric cancer, soft tissue and osteogenic
sarcomas, neuroblastoma, Wilms' tumor, malignant lymphoma
(Hodgkin's and non-Hodgkin's), acute myeloblastic leukemia, acute
lymphoblastic leukemia, Kaposi's sarcoma, Ewing's tumor, refractory
multiple myeloma, and squamous cell carcinomas of the head, neck,
cervix, and vagina.
[0011] In still another aspect, the biological sample is selected
from the group consisting of cells, cell lines, histological
slides, frozen core biopsies, paraffin embedded tissues, formalin
fixed tissues, biopsies, whole blood, nipple aspirate, serum,
plasma, buccal scrape, saliva, cerebrospinal fluid, urine, stool,
and bone marrow. In one embodiment, the biological sample is
enriched for the presence of hyperproliferative cells to at least
75% of the total population of cells. In another embodiment, the
enrichment is performed according to at least one technique
selected from the group consisting of needle microdissection, laser
microdissection, fluorescence activated cell sorting, and
immunological cell sorting. In still another embodiment, an
automated machine performs the at least one technique to thereby
transform the biological sample into a purified form enriched for
the presence of hyperproliferative cells. IN yet another
embodiment, the biological sample is obtained before the subject
has received adjuvant chemotherapy. Alternatively, the biological
sample is obtained after the subject has received adjuvant
chemotherapy.
[0012] In yet another aspect, the control is determined from a
non-cell hyperproliferative cell sample from the patient or member
of the same species to which the patient belongs. In one
embodiment, the control is determined from the average frequency of
genomic locus appearance of chromosomal regions of the same ethnic
group within the species to which the patient belongs. In another
embodiment, the control is from non-cancerous tissue that is the
same tissue type as said cancerous tissue of the subject. In still
another embodiment, the control is from non-cancerous tissue that
is not the same tissue type as said cancerous tissue of the
subject.
[0013] In another aspect, AI is determined using major copy
proportion (MCP). In one embodiment, AI for a given genomic region
is counted when MCP is greater than 0.70.
[0014] In still another aspect, the plurality of chromosomal loci
are randomly distributed throughout the genome at least every 100
Kb of DNA. In one embodiment, the plurality of chromosomal loci
comprise at least one chromosomal locus on each of the 23 human
chromosome pairs. In another embodiment, the plurality of
chromosomal loci comprise at least one chromosomal locus on each
arm of each of the 23 human chromosome pairs. In still another
embodiment, the plurality of chromosomal loci comprise at least one
chromosomal locus on at least one telomere of each of the 23 human
chromosome pairs. In yet another embodiment, the plurality of
chromosomal loci comprise at least one chromosomal locus on each
telomere of each of the 23 human chromosome pairs.
[0015] In yet another aspect, the chromosomal aberrations have a
minimum segment size of at least 1 Mb. In one embodiment, the
chromosomal aberrations have a minimum segment size of at least 12
Mb.
[0016] In another aspect, the plurality of chromosomal aberrations
comprises at least 5 chromosomal aberrations. In one embodiment,
the plurality of chromosomal aberrations comprises at least 13
chromosomal aberrations.
[0017] In still another aspect, the chromosomal loci are selected
from the group consisting of single nucleotide polymorphisms
(SNPs), restriction fragment length polymorphisms (RFLPs), and
simple tandem repeats (STRs).
[0018] In yet another aspect, the chromosomal loci are analyzed
using at least one technique selected from the group consisting of
molecular inversion probe (MIP), single nucleotide polymorphism
(SNP) array, in situ hybridization, Southern blotting, array
comparative genomic hybridization (aCGH), and next-generation
sequencing.
[0019] In another aspect, the outcome of treatment is measured by
at least one criteria selected from the group consisting of
survival until mortality, pathological complete response,
semi-quantitative measures of pathologic response, clinical
complete remission, clinical partial remission, clinical stable
disease, recurrence-free survival, metastasis free survival,
disease free survival, circulating tumor cell decrease, circulating
marker response, and RECIST criteria.
[0020] In still another aspect, the method further comprises
determining a suitable treatment regimen for the subject. In one
embodiment, the suitable treatment regimen comprises at least one
platinum-based chemotherapeutic agent when a plurality of genomic
chromosomal aberrations is determined or does not comprise at least
one platinum-based chemotherapeutic agent when no plurality of
genomic chromosomal aberrations is determined.
[0021] The invention also provides an assay, such as an assay or a
method for selecting therapy for a subject having cancer, the assay
comprising: subjecting a biological sample comprising a cancer cell
or nucleic acid from a cancer cell taken from the subject to
telomeric allelic imbalance (tAI) analysis; detecting the number of
telomeric allelic imbalance (NtAI) in the cancer cell or nucleic
acid from the cancer cell, and selecting a platinum-comprising
therapy for the subject when the NtAI is detected to be above a
reference value based on the recognition that platinum-comprising
therapy is effective in patients who have NtAI above the reference
value; and selecting a non-platinum-comprising cancer therapy for
the subject when the NtAI is detected to be below a reference value
based on the recognition that platinum-comprising cancer therapy is
not effective in patients who have the NtAI below a reference
value, and optionally administering to the subject, such as a human
subject, the selected therapy.
[0022] An assay or a method for selecting platinum-comprising
therapy for a subject having cancer comprising: subjecting a
biological sample taken from the subject to allelic imbalance (AI)
analysis; detecting the number of AI; and selecting
platinum-comprising cancer therapy for the subject when the number
of AIs is above a reference value based on the recognition that
platinum-comprising cancer therapy is effective in patients who
have the number of AIs is above a reference value, and optionally
administering the platinum-comprising cancer therapy if it is
selected.
[0023] The assays may optionally comprise the steps of obtaining a
sample comprising cancer cells or cancer cell-derived DNA from the
subject, subjecting the sample to manipulations, such as
purification, DNA amplification, contacting the sample with a
probe, labeling and other such steps that are needed in analysis of
the NtAI or NAI. Moreover, the assaying and analysis may be
performed by a non-human machine executing an algorithm and
determining automatically whether the sample comprises the
conditions to select a platinum-comprising cancer therapy or
non-platinum comprising cancer therapy to the subject based on the
analysis of NAI or NtAI.
[0024] The cancer may be any cancer. In some aspects of all the
embodiments of the invention, the cancer is selected from breast
and ovarian cancers. In some aspects of all the embodiments of the
invention, the subject is negative for the well-known BRCA1 and/or
BRCA2 mutations. In some aspects of all the embodiments, the
subject has decrease or increase in BRCA1 and/or BRCA2 mRNA, which
may be optionally determined together with the assay or before or
after performing the assay, and which may further assist in
determining whether the cancer will be responsive or resistant to
treatment with platinum-comprising cancer therapy.
[0025] We also provide a method for predicting the outcome of
anti-cancer treatment of a subject with a cell hyperproliferative
disorder, comprising determining a global chromosomal aberration
score (GCAS), comprising obtaining a biological sample from the
subject and determining whether a plurality of chromosomal regions
displaying a chromosomal aberration exists within a plurality of
chromosomal loci, wherein said chromosomal aberrations are selected
from the group consisting of allelic imbalance (NAI), loss of
heterozygosity (NLOH), copy number aberrations (NCNA), copy number
gain (NCNG), copy number decrease (NCND) and combinations thereof,
relative to a control, and wherein the presence of a plurality of
chromosomal regions displaying said chromosomal aberrations
predicts the outcome of anti-cancer treatment of the subject.
[0026] We also provide a method for predicting the outcome of
anti-cancer treatment of a subject with a cell hyperproliferative
disorder, comprising determining a global chromosomal aberration
score (GCAS), comprising obtaining a biological sample from the
subject and determining whether a plurality of chromosomal regions
displaying a chromosomal aberration exists within a plurality of
chromosomal loci, wherein said chromosomal aberrations are selected
from the group consisting of allelic imbalance (NAI), loss of
heterozygosity (NLOH), copy number aberrations (NCNA), copy number
gain (NCNG), copy number decrease (NCND) and combinations thereof,
relative to a control, and wherein the presence of a plurality of
chromosomal regions displaying said chromosomal aberrations
predicts the outcome of anti-cancer treatment of the subject.
[0027] We further provide a method of determining prognosis in a
patient comprising: (a) determining whether the patient comprises
cancer cells having an LOH signature, wherein the presence of more
than a reference number of LOH regions in at least one pair of
human chromosomes of a cancer cell of the cancer patient that are
longer than a first length but shorter than the length of the whole
chromosome containing the LOH region indicates that the cancer
cells have the LOH signature, wherein the at least one pair of
human chromosomes is not a human X/Y sex chromosome pair, wherein
the first length is about 1.5 or more megabases, and (b) (1)
determining, based at least in part on the presence of the LOH
signature, that the patient has a relatively good prognosis, or
(b)(2) determining, based at least in part on the absence of the
LOH signature, that the patient has a relatively poor prognosis
[0028] We provide a composition comprising a therapeutic agent
selected from the group consisting of DNA damaging agent,
anthracycline, topoisomerase I inhibitor, and PARP inhibitor for
use in treating a cancer selected from the group consisting of
breast cancer, ovarian cancer, liver cancer, esophageal cancer,
lung cancer, head and neck cancer, prostate cancer, colon cancer,
rectal cancer, colorectal cancer, and pancreatic cancer in a
patient with more than a reference number of LOH regions in at
least one pair of human chromosomes of a cancer cell of the patient
that are longer than a first length but shorter than the length of
the whole chromosome containing the LOH region, wherein the at
least one pair of human chromosomes is not a human X/Y sex
chromosome pair, wherein the first length is about 1.5 or more
megabases.
[0029] We further provide a method of treating cancer in a patient,
comprising: (a) determining in a sample from said patient the
number of LOH regions in at least one pair of human chromosomes of
a cancer cell of the cancer patient that are longer than a first
length but shorter than the length of the whole chromosome
containing the LOH region indicates that the cancer cells have the
LOH signature, wherein the at least one pair of human chromosomes
is not a human X/Y sex chromosome pair, wherein the first length is
about 1.5 or more megabases; (b) providing a test value derived
from the number of said LOH regions; (c) comparing said test value
to one or more reference values derived from the number of said LOH
regions in a reference population (e.g., mean, median, terciles,
quartiles, quintiles, etc.); and(d) administering to said patient
an anti-cancer drug, or recommending or prescribing or initiating a
treatment regimen comprising chemotherapy and/or a synthetic
lethality agent based at least in part on said comparing step
revealing that the test value is greater (e.g., at least 2-, 3-,
4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater; at least 1, 2, 3, 4, 5,
6, 7, 8, 9, or 10 standard deviations greater) than at least one
said reference value; or (e) recommending or prescribing or
initiating a treatment regimen not comprising chemotherapy and/or a
synthetic lethality agent based at least in part on said comparing
step revealing that the test value is not greater (e.g., not more
than 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater; not more
than 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standard deviations greater)
than at least one said reference value.
[0030] The method of claim 33, wherein said DNA damaging agent is
cisplatin, carboplatin, oxalaplatin, or picoplatin, said
anthracycline is epirubincin or doxorubicin, said topoisomerase I
inhibitor is campothecin, topotecan, or irinotecan, and/or said
PARP inhibitor is iniparib, olaparib or velapirib.
[0031] We provide a composition comprising a therapeutic agent
selected from the group consisting of platinum comprising cancer
therapy and anthracycline for use in treating a cancer selected
from the group consisting of breast cancer, ovarian cancer, liver
cancer, esophageal cancer, lung cancer, head and neck cancer,
prostate cancer, colon cancer, rectal cancer, colorectal cancer,
and pancreatic cancer in a patient with increased allelic
imbalance.
[0032] We provide a method for predicting the outcome of
anti-cancer treatment of a subject with a cell hyperproliferative
disorder, comprising determining a global chromosomal aberration
score (GCAS), comprising obtaining a biological sample from the
subject and determining whether a plurality of chromosomal regions
displaying a chromosomal aberration exists within a plurality of
chromosomal loci, wherein said chromosomal aberrations are selected
from the group consisting of allelic imbalance (NAI), loss of
heterozygosity (NLOH), copy number aberrations (NCNA), copy number
gain (NCNG), copy number decrease (NCND) and combinations thereof,
relative to a control, and wherein the presence of a plurality of
chromosomal regions displaying said chromosomal aberrations
predicts the outcome of anti-cancer treatment of the subject. In
some aspects of all the embodiments of the invention, the
anti-cancer treatment is chemotherapy treatment, which may also be
platinum-based chemotherapeutic agents, for example, cisplatin,
carboplatin, oxaliplatin, nedaplatin, and iproplatin.
[0033] In some aspects of all the embodiments of the invention, the
cell hyperproliferative disorder can be selected from the group
consisting of breast cancer, ovarian cancer, transitional cell
bladder cancer, bronchogenic lung cancer, thyroid cancer,
pancreatic cancer, prostate cancer, uterine cancer, testicular
cancer, gastric cancer, soft tissue and osteogenic sarcomas,
neuroblastoma, Wilms' tumor, malignant lymphoma (Hodgkin's and
non-Hodgkin's), acute myeloblastic leukemia, acute lymphoblastic
leukemia, Kaposi's sarcoma, Ewing's tumor, refractory multiple
myeloma, and squamous cell carcinomas of the head, neck, cervix,
colon cancer, melanoma, and vagina.
[0034] The biological sample can be selected from the group
consisting of cells, cell lines, histological slides, frozen core
biopsies, paraffin embedded tissues, formalin fixed tissues,
biopsies, whole blood, nipple aspirate, serum, plasma, buccal
scrape, saliva, cerebrospinal fluid, urine, stool, and bone marrow,
wherein the sample comprises cancer cells.
[0035] In some aspect of all the embodiments of the invention,
including the assays and methods, the cancer cells in the sample
may be enriched using, for example, needle microdissection, laser
microdissection, fluorescence activated cell sorting, and
immunological cell sorting.
[0036] In some aspects of all the embodiments of the invention an
automated machine performs the at least one technique to thereby
transform the biological sample into a purified form enriched for
the presence of hyperproliferative cells.
[0037] In some aspects of all the embodiments of the invention, the
sample or biological sample is obtained before the subject has
received adjuvant chemotherapy, or after the subject has received
adjuvant chemotherapy.
[0038] In some aspects of all the embodiments of the invention, the
control is determined from the average frequency of genomic locus
appearance of chromosomal regions of the same ethnic group within
the species to which the patient belongs. The control may also be
from non-cancerous tissue that is the same tissue type as said
cancerous tissue of the subject, or from non-cancerous tissue that
is not the same tissue type as said cancerous tissue of the
subject.
BRIEF DESCRIPTION OF THE DRAWINGS
[0039] FIGS. 1A-1C show the correlation between allelic imbalance
(AI) regions and cisplatin sensitivity in vitro. FIG. 1A shows a
dose response curves of six TNBC cell lines as determined by a
proliferation assay after 48 hours of cisplatin exposure. Curves
for cells with lower IC50 values (greater sensitivity) are shown in
blue; the cell line with highest IC50 (greatest resistance) is
shown in red; cell lines with intermediate sensitivity are shown in
grey. FIG. 1B shows the effect of the AI segment size threshold on
the correlation between the number of telomeric AI regions and the
cisplatin sensitivity in the six cell lines. Each point represent
an R2 value based on linear regression between the count of CNA
regions of a minimum size indicated at X-axis, and cisplatin
IC.sub.50 in a panel of 6 TNBC cell lines (BT20, BT-549, HCC1187,
HCC38, MDA-MB-231, MDA-MB-468). The optimum minimum segment size
threshold is indicated by the dotted line. FIG. 1C shows a
comparison between the number of telomeric AI regions (NtAI,12) and
cisplatin sensitivity at the selected optimum threshold of 12 Mb.
The cell lines are indicated as follows: 1, BT-20; 2, BT-549; 3,
HCC1187; 4, HCC38; 5, MDA-MB-231; 6, MDA-MB-468.
[0040] FIG. 2 shows that major copy proportion (MCP) analysis
identifies allelic imbalance in tumor biopsy samples with different
degrees of tumor cell purity. FIG. 2 shows the formula for
calculation of MCP, as well as normal bi-allelic chromosomes and
three different ways in which allelic imbalance of a chromosomal
region may occur and the corresponding MCP calculation. We also
prepared diagrams depicting the display of loss of heterozygosity
(LOH), AI determined by MCP, and absolute copy number analysis in
two tumor samples with different degrees of normal cell
contamination: T7 with >95% tumor cell content and T5 with
approximately 80% tumor content. The chromosomes are indicated
along the left side. The first columns for each tumor show the
cells for LOH (blue) and retention of heterozygosity (yellow) at
each chromosome position. The second columns show the MCP levels
(between 0.5 and 1.0) at each chromosomal position. The MCP cut off
of 0.7 is indicated by red lines. AI is called for regions with MCP
greater than 0.7. The third and forth columns display the absolute
DNA copy number at each position with white indicating diploid,
shades of red indicating copy gain and shades of blue indicating
copy loss. The copy number levels are shown in the far right
panels. The tumor sample with greater purity (T7) shows agreement
between LOH and MCP-determined AI calls. In the tumor sample with
only 80% tumor cells, the LOH signal is lost, but AI can still be
estimated by MCP with a 0.70 threshold.
[0041] FIGS. 3A-3D show the association between cisplatin
sensitivity and number of genomic abnormalities in a panel of TNBC
cell lines. FIG. 3A shows cisplatin IC50 versus number of telomeric
AI regions at least 1 Mb long with AI defined by MCP>0.7. FIG.
3B shows cisplatin IC50 versus count of regions with copy number
aberration, including gains and losses, at least 1 Mb long. FIG. 3C
shows cisplatin IC50 versus count of regions with copy number gain,
at least 1 Mb long. FIG. 3D shows cisplatin IC50 versus count of
regions with copy number loss, at least 1 Mb long. The cell lines
are indicated on each figure and are the same as in FIG. 1.
[0042] FIGS. 4A-4B show the association between cisplatin
sensitivity and count of either telomeric or interstitial AI
regions in a panel of TNBC cell lines. FIG. 4A shows cisplatin IC50
versus number of telomeric AI regions at least 1 Mb long with AI
defined by MCP>0.7. FIG. 4B shows cisplatin IC50 versus number
of interstitial AI regions at least 1 Mb long with AI defined by
MCP>0.7. The cell lines are indicated on each figure and are the
same as in FIG. 1.
[0043] FIGS. 5A-5F show the association between enumerated copy
number aberrations (CNA) and sensitivity to cisplatin in vitro.
FIGS. 5A-5C show the determination of the minimum segment size that
demonstrates the best correlation to cisplatin sensitivity for
number of copy number aberrations (NCNA; FIG. 5A), number of
regions with copy number gain (NCNA, gain; FIG. 5B), and number of
regions with copy number loss (NCNA, loss; FIG. 5C). Each point
represent an R2 value based on linear regression between the count
of CNA regions of a minimum size indicated at X-axis, and cisplatin
IC50 in a panel of 6 TNBC cell lines (BT20, BT-549, HCC1187, HCC38,
MDA-MB-231, MDA-MB-468). The optimal minimum size of CNA regions is
indicated by the dotted line. FIG. 5D-5F show plots of the
cisplatin IC50 values (.mu.M, X-axis) vs. the number of CNA regions
with optimum minimum segment sizes (Y-axis) as follows: NCNA at
least 9 Mb long (FIG. 5D), NCNA, gain at least 9 Mb long (FIG. 5E),
and NCNA, loss at least 5 Mb long, in 6 TNBC cell lines (FIG. 5F),
as indicated.
[0044] FIGS. 6A-6C show AI regions and cisplatin response in breast
cancer. Pathologic response to cisplatin was assessed by the
Miller-Payne (MP) score, which can range from 0 (progression) to 5
(pathologic complete response, pCR). FIG. 6A shows representations
of individual tumor genomes arranged in order of increasing MP
score. Regions of telomeric AI (dark blue) and interstitial AI
(light blue) are indicated, with thin white lines demarcating
individual chromosomes. FIG. 6B shows association between the MP
score and the NtAI,12. FIG. 6C shows a receiver operating
characteristics (ROC) curve evaluating the performance of NtAI,12
to predict pCR to cisplatin therapy (pCR, n=4; no pCR, n=20).
[0045] FIG. 7 shows whole chromosome allelic imbalance (isodisomy)
and cisplatin sensitivity in breast cancers. Regions of whole
chromosome AI are indicated in red for each chromosomal location.
Each row defined by thin white lines represents a different
chromosome and chromosome numbers are indicated along the left
side. Each column represents an individual tumor sample. The
Miller-Payne (MP) pathologic response score for each tumor is
indicated along the bottom. Cases are arranged in order of
increasing pathologic response to cisplatin (0=progression,
5=pathologic complete response (pCR)).
[0046] FIGS. 8A-8B show AI regions and time to relapse in serous
ovarian cancer treated with platinum based therapy. FIG. 8A shows a
rank of individuals according to increasing NtAI,12. Those who
relapsed within one year are indicated by closed circles and those
without relapse within one year are indicated by open circles. A
cutoff value of NtAI,12=13, based on the TNBC ROC analysis for
prediction of pathologic complete response (pCR) to cisplatin, is
indicated by the dotted line. FIG. 8B shows Kaplan-Meier survival
curves for time to relapse in individuals classified as high
NtAI,12 (13 or greater NtAI,12 regions, blue) or low NtAI,12 (fewer
than 13 NtAI,12 regions, red).
[0047] FIG. 9 shows a model relating DNA repair to accumulation of
AI and response to platinum agents. Various genetic lesions can
result in defects in common pathways of DNA repair, leading first
to abnormal repair of spontaneous DNA breaks, then to illegitimate
chromosome recombination and aberrant quadriradial chromosome
formation, and finally to high levels of telomeric allelic
imbalance. In parallel, the defective DNA repair pathway can also
result in the inability of the tumor cell to repair drug-induced
DNA damage, leading to tumor sensitivity to drugs such as platinum
salts. Thus, the level of telomeric AI in a tumor serves as an
indicator of defective DNA repair and predicts sensitivity to
treatment with genotoxic agents.
[0048] FIGS. 10A-10C show chromosomal aberrations and cisplatin
sensitivity in vitro. The relationship between AI regions and
cisplatin sensitivity was analyzed in 10 breast cancer cell lines:
1: CAMA-1, 2: HCC1954, 3: MDA-MB-231, 4: MDA-MB-361, 5: HCC1187, 6:
BT-549, 7: HCC1143, 8: MDA-MB-468, 9: BT-20, 10: T47D. FIG. 10A
shows IC.sub.50 values for each of the 10 cell lines. A
proliferation assay was used to assess viability after 48 hours of
cisplatin exposure and IC.sub.50 was determined from the dose
response curves. FIG. 10B shows comparison between number of
regions with telomeric allelic imbalance (NtAI) and cisplatin
sensitivity. Breast cancer subtype is indicated as follows: TN,
red; HER2+, green, ER+ HER2-, blue. FIG. 10C shows comparison
between (NtAI) and cisplatin sensitivity as determined by GI50 in
breast cancer cell lines from Heiser et al. (18). Reported
transcriptional subtype is indicated as follows: basal, red;
claudin-low, pink; ERBB2Amp, green; luminal, blue.
[0049] FIGS. 11A-11D show an NtAI and cisplatin response in breast
cancer. In two clinical trials, TNBC patients were given
preoperative cisplatin (Cisplatin-1, FIG. 11A-11B) or cisplatin and
bevacizumab (Cisplatin-2, FIG. 11C-11D). Cisplatin sensitive tumors
are indicated in red, cisplatin insensitive tumors are indicated in
black. Tumors with germline mutations in BRCA1/2 are indicated with
triangles. FIG. 11A and FIG. 11C show box plots showing NtAI
distribution in cisplatin resistant and sensitive tumors. FIG. 11B
and FIG. 11D show Receiver operating characteristic curves showing
the ability of NtAI to predict for sensitivity to cisplatin.
[0050] FIG. 12 shows NtAI and cisplatin response in serous ovarian
cancer. Box plots showing NtAI distribution in platinum sensitive
and resistant tumors in cancers without BRCA1 or BRCA2 mutations
(wtBRCA) and for cancers with germline or somatic mutation in BRCA1
(mBRCA1) or in BRCA2 (mBRCA2). Red indicate sensitive samples,
triangles indicate samples with germline or somatic mutations in
BRCA1 or BRCA2. Significant differences between resistant wtBRCA
and sensitive groups are indicated. In addition, significant
differences were found between sensitive wtBRCA and sensitive
mBRCA2 (P=0.047), and sensitive wtBRCA and sensitive mBRCA1
(P=0.014).
[0051] FIGS. 13A-13B show enrichment of common CNVs in tAI
chromosomal breakpoints from TNBC. Association of tAI breakpoints
with common CNV loci based on computational simulations that
compared the expected number of breakpoints containing CNVs with
the observed number in total cases in Cisplatin-1 (FIG. 13A) and
Cisplatin-2 (FIG. 13B).
[0052] FIGS. 14A-14C show Association between BRCA1 expression,
NtAI and BRCA1 promoter methylation. Red indicates tumors sensitive
to cisplatin. Tumors with a germline mutation in BRCA1 or BRCA2 are
excluded in FIG. 14A. and 14B., but included in 14C., represented
as triangles. FIG. 14A shows BRCA1 expression measured by qPCR is
significantly lower in sensitive tumors in the Cisplatin-2 cohort.
FIG. 14B shows BRCA1 expression is lower in samples that show
methylation of the BRCA1 promoter region in the combined
Cisplatin-1 and Cisplatin-2 cohorts. FIG. 14C shows BRCA1
expression measured by qPCR shows a negative correlation with NtAI
in the combined Cisplatin-1 and Cisplatin-2 cohorts.
[0053] FIGS. 15A-15D show a model relating DNA repair to
accumulation of telomeric AI and response to platinum agents. FIG.
15A shows in DNA repair-competent cells, DNA breaks are repaired
using error-free homologous recombination employing the identical
sister chromatid as a template, resulting in no AI. FIG. 15B and
FIG. 15C show compromised DNA repair favors the use of error-prone
repair pathways, resulting in chromosome rearrangements and
aberrant radial chromosome formation. After mitotic division,
daughter cells will have imbalance in the parental contribution of
telomeric segments of chromosomes (telomeric AI). FIG. 15B shows
non-homologous end joining is one error-prone mechanism that joins
a broken chromatid of one chromosome (dark blue) to the chromatid
of another, usually non-homologous, chromosome (white). Mitotic
segregation results in cells with telomeric AI due to mono-allelic
change in DNA copy number of the affected telomeric region. FIG.
15C shows mitotic recombination may result in rearrangements
between homologous chromosomes (dark blue and light blue). Mitotic
segregation results in cells with AI due to copy neutral LOH.
Break-induced replication would be expected to result in a similar
outcome. FIG. 15D shows the same compromise in DNA repair that
causes telomeric AI may also result in the inability of the tumor
cell to repair drug-induced DNA damage, leading to tumor
sensitivity to drugs such as platinum salts.
[0054] FIG. 16 shows an example definition of allelic imbalance.
The diagram shows normal bi-allelic chromosomes and three different
ways in which allelic imbalance of a chromosomal region may
occur.
[0055] FIGS. 17A-17C show association between cisplatin sensitivity
and measures of genomic abnormalities in a panel of breast cancer
cell lines. Cisplatin IC.sub.50 versus: FIG. 17A, total number of
AI regions; FIG. 17B, total number of copy number gain regions; and
FIG. 17C, total number of copy number loss regions. Numbers
represents the same cell lines as in FIG. 1.
[0056] FIGS. 18A-18E show association between cisplatin sensitivity
and telomeric/interstitial gains and losses. Cisplatin IC.sub.50
versus: FIG. 18A, the number of telomeric copy number gain regions;
FIG. 18B, the number of telomeric copy number loss regions; FIG.
18C, the number of interstitial copy number gain regions; FIG. 18D,
the number of interstitial copy number loss regions; and FIG. 18E,
NtAI score. Numbers represents the same cell lines as in FIG. 10
(1).
[0057] FIG. 19 shows receiver operating characteristic curve
showing the ability of NtAI to predict for sensitivity to
platinum-based therapy in wtBRCA serous ovarian cancer.
[0058] FIG. 20 shows distribution of dsDNA breaks resulting in
telomeric allelic imbalance and association with common CNVs
according to cisplatin response. Squares indicate inferred
chromosomal location of dsDNA breaks resulting in tAI, pooled from
both trials. Stacked squares represent multiple tumors with dsDNA
breaks at the same position.
[0059] FIGS. 21A-21B show BRCA1 expression and NtAI versus response
to cisplatin in Cisplatin-1 and Cisplatin-2 combined. FIG. 21A
shows identification of the optimum cut-off for NtAI (black) and
BRCA1 mRNA (blue) to predict cisplatin response separately. Filled
circles represent optimum cut-points. FIG. 21B shows how the
combination of BRCA1 expression and NtAI may improve prediction of
cisplatin response. Red indicates samples sensitive to cisplatin.
Lines represents the optimum cut-off for prediction of response
based on NtAI and BRCA1 mRNA, as determined in FIG. 21A. "Sens"
represents the number of sensitive per total cases shown in each
quadrant defined by the NtAI and BRCA1 mRNA cut-offs. The table
shows the prediction accuracy based on the defined cut-offs for
NtAI alone, BRCA1 mRNA alone, and the two measurements combined.
ACC: accuracy. PPV: positive predictive value. NPV: negative
predictive value. SENS: sensitivity. SPEC: specificity. P: p-value
based on Fishers exact test. This table is based only on the
samples shown in FIG. 21B.
[0060] FIGS. 22A-22C show BRCA1 expression by gene expression micro
array in TCGA cohorts. FIG. 22A. BRCA1 mRNA expression versus NtAI
in the TCGA ER-/HER2- breast cancers (n=78). FIG. 22B shows BRCA1
mRNA expression versus NtAI in the TCGA wtBRCA serous ovarian
cancers (n=165). FIG. 22C shows BRCA1 mRNA expression versus
treatment response in the TCGA wtBRCA serous ovarian cancers.
[0061] FIG. 23 shows an exemplary process by which a computing
system can determine a chromosomal aberration score
[0062] FIG. 24 is a diagram of an example of a computer device 1400
and a mobile computer device 1450, which may be used with the
techniques described herein.
DETAILED DESCRIPTION OF THE INVENTION
[0063] The present invention relates to methods for predicting
response of a cancer in a subject to anti-cancer therapies based
upon a determination and analysis of a chromosomal aberration
score, such as the number of allelic imbalance or the number of
telomeric allelic imbalance in the chromosomes of the human
genome.
[0064] According to one aspect of the invention, Global Chromosomal
Aberration Score (GCAS) is a measurement predictive of
responsiveness to anti-cancer therapies of a cancer in a subject.
This utility of GCAS is based upon the novel finding that the
summation of individual chromosomal aberrations can predict
responsiveness of a cancer in a subject to anti-cancer agents
independently of identifying specific chromosomal aberrations.
Informative loci of interest (e.g., single nucleotide polymorphisms
(SNPs), restriction fragment length polymorphisms (RFLPs), simple
tandem repeats (STRs), etc.), are used to determine GCAS as they
are useful for detecting and/or distinguishing chromosomal
aberrations. As used herein, "chromosomal aberration" means allelic
imbalance (AI), loss of heterozygosity (LOH), copy number
aberrations (CNA), copy number gain (CNG), copy number decrease
(CND) and combinations thereof. GCAS is a type of chromosomal
aberration score, of which other types include telomeric aberration
score, telomeric allelic imbalance score, etc. Thus, unless
explicitly stated otherwise or unless the context clearly indicates
otherwise, references to GCAS may apply in some embodiments equally
to other chromosomal aberration scores (e.g., telomeric aberration
score, telomeric allelic imbalance score, etc.).
[0065] GCAS is determined by determining a plurality or the total
number of chromosome regions displaying allelic imbalance (NAI),
loss of heterozygosity (LOH), copy number aberrations (NCNA), copy
number gain (NCNG), and/or copy number decrease (NCND), as
described further herein and according to methods well-known in the
art. A GCAS of at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14,
15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31,
32, 33, 34, 35, 36, 37, 38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48,
49, 50, 51, 52, 53, 54, 55, 56, 57, 58, 59, or 60 or more is
predictive of response to anti-cancer therapy of the cancer cell
from which the assayed nucleic acid was derived.
[0066] In one embodiment, the analysis is based upon nucleic acids
obtained from a subject and/or control sample. Such samples can
include "body fluids," which refer to fluids that are excreted or
secreted from the body as well as fluids that are normally not
(e.g. amniotic fluid, aqueous humor, bile, blood and blood plasma,
cerebrospinal fluid, cerumen and earwax, cowper's fluid or
pre-ejaculatory fluid, chyle, chyme, stool, female ejaculate,
interstitial fluid, intracellular fluid, lymph, menses, breast
milk, mucus, pleural fluid, pus, saliva, sebum, semen, serum,
sweat, synovial fluid, tears, urine, vaginal lubrication, vitreous
humor, vomit). In a preferred embodiment, the subject and/or
control sample is selected from the group consisting of cells, cell
lines, histological slides, paraffin embedded tissues, biopsies,
whole blood, nipple aspirate, serum, plasma, buccal scrape, saliva,
cerebrospinal fluid, urine, stool, and bone marrow.
[0067] In one embodiment, SNPs are used in determining GCAS, for
predicting responsiveness of a cancer to an anti-cancer therapy.
There are six possible SNP types, either transitions (A< >T
or G< >C) or transversions (A< >G, A< >C, G<
>T or C< >T). SNPs are advantageous in that large numbers
can be identified.
[0068] In some embodiments, the SNPs or other genomic loci can be
scored to detect copy number abnormalities. In such cases, such
genomic loci do not need to be informative in terms of genotype
since copy number is determined by hybridization intensities and
doesn't depend on the genotype. Also, copy number abnormalities can
be detected using methods that do not use SNPs, such as, for
example, array CGH using BAC, cDNA and/or oligonucleotide arrays;
microsatellite markers; STRs, RFLPS; etc.
[0069] For example, methods for evaluating copy number of nucleic
acid in a sample include, but are not limited to,
hybridization-based assays. One method for evaluating the copy
number of encoding nucleic acid in a sample involves a Southern
Blot. In a Southern Blot, the genomic DNA (typically fragmented and
separated on an electrophoretic gel) is hybridized to a probe
specific for the target region. Comparison of the intensity of the
hybridization signal from the probe for the target region with
control probe signal from analysis of normal genomic DNA (e.g., a
non-amplified portion of the same or related cell, tissue, organ,
etc.) provides an estimate of the relative copy number of the
target nucleic acid. Alternatively, a Northern blot may be utilized
for evaluating the copy number of encoding nucleic acid in a
sample. In a Northern blot, mRNA is hybridized to a probe specific
for the target region. Comparison of the intensity of the
hybridization signal from the probe for the target region with
control probe signal from analysis of normal mRNA (e.g., a
non-amplified portion of the same or related cell, tissue, organ,
etc.) provides an estimate of the relative copy number of the
target nucleic acid. Similar methods for determining copy number
can be performed using transcriptional arrays, which are well-known
in the art.
[0070] An alternative means for determining the copy number is in
situ hybridization (e.g., Angerer (1987) Meth. Enzymol 152: 649).
Generally, in situ hybridization comprises the following steps: (1)
fixation of tissue or biological structure to be analyzed; (2)
prehybridization treatment of the biological structure to increase
accessibility of target DNA, and to reduce nonspecific binding; (3)
hybridization of the mixture of nucleic acids to the nucleic acid
in the biological structure or tissue; (4) post-hybridization
washes to remove nucleic acid fragments not bound in the
hybridization and (5) detection of the hybridized nucleic acid
fragments. The reagent used in each of these steps and the
conditions for use vary depending on the particular
application.
[0071] Preferred hybridization-based assays include, but are not
limited to, traditional "direct probe" methods such as Southern
blots or in situ hybridization (e.g., FISH and FISH plus SKY), and
"comparative probe" methods such as comparative genomic
hybridization (CGH), e.g., cDNA-based or oligonucleotide-based CGH.
The methods can be used in a wide variety of formats including, but
not limited to, substrate (e.g. membrane or glass) bound methods or
array-based approaches.
[0072] In a typical in situ hybridization assay, cells are fixed to
a solid support, typically a glass slide. If a nucleic acid is to
be probed, the cells are typically denatured with heat or alkali.
The cells are then contacted with a hybridization solution at a
moderate temperature to permit annealing of labeled probes specific
to the nucleic acid sequence encoding the protein. The targets
(e.g., cells) are then typically washed at a predetermined
stringency or at an increasing stringency until an appropriate
signal to noise ratio is obtained.
[0073] The probes are typically labeled, e.g., with radioisotopes
or fluorescent reporters. Preferred probes are sufficiently long so
as to specifically hybridize with the target nucleic acid(s) under
stringent conditions. The preferred size range is from about 200
bases to about 1000 bases.
[0074] In some applications it is necessary to block the
hybridization capacity of repetitive sequences. Thus, in some
embodiments, tRNA, human genomic DNA, or Cot-I DNA is used to block
non-specific hybridization.
[0075] In CGH methods, a first collection of nucleic acids (e.g.,
from a sample, e.g., a possible tumor) is labeled with a first
label, while a second collection of nucleic acids (e.g., a control,
e.g., from a healthy cell/tissue) is labeled with a second label.
The ratio of hybridization of the nucleic acids is determined by
the ratio of the two (first and second) labels binding to each
fiber in the array. Where there are chromosomal deletions or
multiplications, differences in the ratio of the signals from the
two labels will be detected and the ratio will provide a measure of
the copy number. Array-based CGH may also be performed with
single-color labeling (as opposed to labeling the control and the
possible tumor sample with two different dyes and mixing them prior
to hybridization, which will yield a ratio due to competitive
hybridization of probes on the arrays). In single color CGH, the
control is labeled and hybridized to one array and absolute signals
are read, and the possible tumor sample is labeled and hybridized
to a second array (with identical content) and absolute signals are
read. Copy number difference is calculated based on absolute
signals from the two arrays. Hybridization protocols suitable for
use with the methods of the invention are described, e.g., in
Albertson (1984) EMBO J. 3: 1227-1234; Pinkel (1988) Proc. Natl.
Acad. Sci. USA 85: 9138-9142; EPO Pub. No. 430,402; Methods in
Molecular Biology, Vol. 33: In situ Hybridization Protocols, Choo,
ed., Humana Press, Totowa, N.J. (1994), etc. In one embodiment, the
hybridization protocol of Pinkel, et al. (1998) Nature Genetics 20:
207-211, or of Kallioniemi (1992) Proc. Natl Acad Sci USA
89:5321-5325 (1992) is used.
[0076] The methods of the invention are particularly well suited to
array-based hybridization formats. Array-based CGH is described in
U.S. Pat. No. 6,455,258, the contents of which are incorporated
herein by reference. In still another embodiment,
amplification-based assays can be used to measure copy number. In
such amplification-based assays, the nucleic acid sequences act as
a template in an amplification reaction (e.g., Polymerase Chain
Reaction (PCR). In a quantitative amplification, the amount of
amplification product will be proportional to the amount of
template in the original sample. Comparison to appropriate
controls, e.g. healthy tissue, provides a measure of the copy
number.
[0077] 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. Detailed protocols for
quantitative PCR are provided in Innis, et al. (1990) PCR
Protocols, A Guide to Methods and Applications, Academic Press,
Inc. N.Y.). Measurement of DNA copy number at microsatellite loci
using quantitative PCR analysis is described in Ginzonger, et al.
(2000) Cancer Research 60:5405-5409. The known nucleic acid
sequence for the genes is sufficient to enable one of skill in the
art to routinely select primers to amplify any portion of the gene.
Fluorogenic quantitative PCR may also be used in the methods of the
invention. In fluorogenic quantitative PCR, quantitation is based
on amount of fluorescence signals, e.g., TaqMan and sybr green.
[0078] Other suitable amplification methods include, but are not
limited to, ligase chain reaction (LCR) (see Wu and Wallace (1989)
Genomics 4: 560, Landegren, et al. (1988) Science 241:1077, and
Barringer et al. (1990) Gene 89: 117), transcription amplification
(Kwoh, et al. (1989) Proc. Natl. Acad. Sci. USA 86: 1173),
self-sustained sequence replication (Guatelli, et al. (1990) Proc.
Nat. Acad. Sci. USA 87: 1874), dot PCR, and linker adapter PCR,
etc.
[0079] In still other embodiments of the methods provided herein,
sequencing of individual nucleic molecules (or their amplification
products) is performed, as an alternative to hybridization-based
assays, using nucleic acid sequencing techniques. In one
embodiment, a high throughput parallel sequencing technique that
isolates single nucleic acid molecules of a population of nucleic
acid molecules prior to sequencing may be used. Such strategies may
use so-called "next generation sequencing systems" including,
without limitation, sequencing machines and/or strategies well
known in the art, such as those developed by Illumina/Solexa (the
Genome Analyzer; Bennett et al. (2005) Pharmacogenomics, 6:373-20
382), by Applied Biosystems, Inc. (the SOLiD Sequencer;
solid.appliedbiosystems.com), by Roche (e.g., the 454 GS FLX
sequencer; Margulies et al. (2005) Nature, 437:376-380; U.S. Pat.
Nos. 6,274,320; 6,258,568; 6,210,891), by HELISCOPE.TM. system from
Helicos Biosciences (see, e.g., U.S. Patent App. Pub. No.
2007/0070349), and by others. Other sequencing strategies such as
stochastic sequencing (e.g., as developed by Oxford Nanopore) may
also be used, e.g., as described in International Application No.
PCT/GB2009/001690 (pub. no. WO/2010/004273). All of the copy number
determining strategies described herein can similarly be applied to
any of other nucleic acid-based analysis described herein, such as
for informative loci and the like described further below.
[0080] In other embodiments, SNPs can be scored for heterozygosity
or absence of heterozygosity. Techniques like major copy proportion
analysis utilize the allelic-imbalance and copy number information
to extend the analyses that can be performed with copy number of
LOH events alone since they can involve copy number deletion,
neutral, or gain events. In other embodiments, to determine the
GCAS of a cancer in a subject, heterozygous SNPs located throughout
the genome are identified using nucleic acid samples derived from
non-cancerous tissue of the subject or a population of subjects of
a single species, and the number is determined of those
heterozygous SNPs identified that maintain heterozygosity (or
alternatively do not exhibit heterozygosity, i.e., have lost
heterozygosity) in a nucleic acid sample of, or derived from,
genomic DNA of cancerous tissue of the subject. A nucleic acid
sample "derived from" genomic DNA includes but is not limited to
pre-messenger RNA (containing introns), amplification products of
genomic DNA or pre-messenger RNA, fragments of genomic DNA
optionally with adapter oligonucleotides ligated thereto or present
in cloning or other vectors, etc. (introns and noncoding regions
should not be selectively removed).
[0081] All of the SNPs known to exhibit heterozygosity in the
species to which the subject with cancer belongs need not be
included in the number of heterozygous SNPs used or analyzed. In
some embodiments, at least 45, 50, 75, 100, 125, 150, 175, 200,
225, 250, 275, 300, 350, 400, 450, 500, 550, 600, 650, 700, 750,
800, 850, 900, 950, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000,
7,000, 8,000, 9,000, 10,000, 11,000, 12,000, 13,000, 14,000,
15,000, 16,000, 17,000, 18,000, 19,000, 20,000, 21,000, 22,000,
23,000, 24,000, 25,000, 26,000, 27,000, 28,000, 29,000, 30,000,
31,000, 32,000, 33,000,34,000, 35,000, 36,000, 37,000, 38,000,
39,000, 40,000, 41,000, 42,000, 43,000, 44,000, 45,000, 50,000,
60,000, 70,000, 80,000, 90,000, 100,000, 150,000, 200,000, 250,000,
300,000, 350,000, 400,000, 450,000, 500,000, 550,000, 600,000,
650,000, 700,000, 750,000, 800,000, 850,000, 900,000, 950,000,
1,000,000 SNPs or more, or any range in between, or other
informative loci of interest (e.g., RFLPs, STRs, etc.) are used.
Preferably, such SNPs are in the human genome. In one embodiment,
the plurality of heterozygous SNPs are randomly distributed
throughout the genome at least every 1, 5, 10, 50, 100, 250, 500,
1,000, 1,500, 2,000, 2,500, 3,000, 5,000, 10,000 kb or more, or any
range in between. By "randomly distributed," as used above, is
meant that the SNPs of the plurality are not selected by bias
toward any specific chromosomal locus or loci; however, other
biases (e.g., the avoidance of repetitive DNA sequences) can be
used in the selection of the SNPs. In other embodiments, the
plurality of heterozygous SNPs are not randomly distributed
throughout the genome (i.e., distributed within at least 250, 500,
1,000, 1,500, 2,000, 2,500, 3,000, 5,000, 10,000, 11,000, 12,000,
13,000, 14,000, 15,000, 16,000, 17,000, 18,000, 19,000, 20,000,
21,000, 22,000, 23,000, 24,000, or 25,000 kb=25 Mb). Such regions
can further be biased, in some embodiments, to specific chromosomal
regions such as telomeres (sometimes herein called "telomeric
regions" or "telomeric segments") defined as regions extending
toward the telomere but not crossing the centromere. In one
embodiment, the telomeric allelic imbalance segment size is at
least 1 Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, 10 Mb,
11 Mb, 12 Mb, 13 Mb, 14 Mb, 15 Mb, 16 Mb, 17 Mb, 18 Mb, 19 Mb, 20
Mb, 21 Mb, 22 Mb, 23 Mb, 24 Mb, 25 Mb, or more, or any range in
between, such as between 5 and 25 Mb. In another embodiment, the
telomeric allelic imbalance segment size is 12 Mb. By contrast,
interstitial regions do not involve the telomere. Interstitial
regions are defined herein as regions of allelic imbalance that
start downstream of the telomere meaning that there is at least
some part of the chromosome with no allelic imbalance between the
telomere and the region of allelic imbalance. In one embodiment,
the plurality of heterozygous SNPs is not found in regions of
genomic DNA that are repetitive. In another embodiment, the
plurality of heterozygous SNPs comprises SNPs located in the genome
on different chromosomal loci, wherein the different chromosomal
loci comprise loci on each of the chromosomes of the species, or on
each arm of each chromosome of the species (e.g., telomeric region
thereof).
[0082] With many modern high-throughput techniques (including those
discussed herein), it is possible to determine genotype, copy
number, copy proportion, etc. for tens, hundreds, thousands,
millions or even billions of genomic loci (e.g., all known
heterozygous SNPs in a particular species, whole genome sequencing,
etc.). Once a global assay has been performed (e.g., assaying all
or substantially all known heterozygous SNPs), one may then
informatically analyze one or more subsets of loci (i.e., panels of
test loci or, as sometimes used herein, pluralities of test loci).
Thus, in some embodiments, after assaying for allelic imbalance in
hundreds of loci or more in a sample (or after receiving the data
from such an assay), one may analyze (e.g., informatically) a panel
or plurality of test loci according to the present invention (e.g.,
entirely or primarily telomeric SNPs) by combining the data
relating to the individual test loci to obtain a test value
indicative of the overall level, nature, etc. of allelic imbalance
in the desired group of test loci.
[0083] Thus, in one aspect the invention provides a method of
deriving a chromosomal aberration score (e.g., GCAS, telomeric
aberration score, telomeric allelic imbalance score, etc.)
comprising: determining whether a sample has a chromosomal
aberration (e.g., of allelic imbalance, loss of heterozygosity,
copy number aberrations, copy number gain, copy number decrease) at
a plurality of assay (e.g., genomic) loci; analyzing a plurality of
test loci within said plurality of assay loci for chromosomal
aberrations; combining the data from (2) to derive a score
reflecting the overall extent of chromosomal aberration in said
plurality of test loci, thereby deriving a chromosomal aberration
score.
[0084] In some embodiments determining whether a sample has a
chromosomal aberration at the plurality of assay loci comprises
assaying a tissue sample (e.g., physically processing a tangible
patient specimen to derive data therefrom) and analyzing the data
(e.g., SNP genotype data) derived from such assay. In some
embodiments, determining whether a sample has a chromosomal
aberration at the plurality of assay loci comprises analyzing data
derived from an assay on a tissue sample.
[0085] In some embodiments the assay loci represent all loci
analyzed in the relevant assay (e.g., all heterozygous SNPs
represented on the particular SNP array, all nucleotides in a
sequencing assay). In some embodiments the assay loci represent
particular loci analyzed in the relevant assay (e.g., certain
nucleotides, such as SNPs, in a sequencing assay). In some
embodiments all assay loci are test loci. In some embodiments the
test loci represent at least some percentage (e.g., 5%, 10%, 15%,
20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or 100%) of the assay
loci. In some embodiments at least some percentage (e.g., 5%, 10%,
15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or 100%) of the
assay loci are telomeric loci. In some embodiments at least some
percentage (e.g., 5%, 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%,
90%, 95% or 100%) of the test loci are telomeric loci. Thus, in
some embodiments the invention provides a method of deriving a
chromosomal aberration score (e.g., GCAS, telomeric aberration
score, telomeric allelic imbalance score, etc.)
comprising:determining whether a sample has a chromosomal
aberration (e.g., of allelic imbalance, loss of heterozygosity,
copy number aberrations, copy number gain, copy number decrease) at
a plurality of assay (e.g., genomic) loci; analyzing a plurality of
test loci within said plurality of assay loci for chromosomal
aberrations, wherein at least 5% (or 10%, or 15%, or 20%, or 30%,
or 40%, or 50%, or 60%, or 70%, or 80%, or 90%, or 95%, or 100%) of
the test loci are telomeric loci; combining the data from (2) to
derive a score reflecting the overall extent of chromosomal
aberration in said plurality of test loci, thereby deriving a
chromosomal aberration score.
[0086] In some embodiments each test locus is assigned a particular
weight in calculating the chromosomal aberration score. In some
embodiments test loci are assigned a weight by each being given a
particular coefficient in a formula (final or intermediate) used to
calculate the chromosomal aberration score. In some embodiments
telomeric test loci (all or at least 5%, 10%, 15%, 20%, 30%, 40%,
50%, 60%, 70%, 80%, 90%, 95% of telomeric test loci) are weighted
such that they contribute at least some percentage (5%, 10%, 15%,
20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%, 95% or 100%) to the
chromosomal aberration score. Thus, in some embodiments the
invention provides a method of deriving a chromosomal aberration
score (e.g., GCAS, telomeric aberration score, telomeric allelic
imbalance score, etc.) comprising:determining whether a sample has
a chromosomal aberration (e.g., of allelic imbalance, loss of
heterozygosity, copy number aberrations, copy number gain, copy
number decrease) at a plurality of assay (e.g., genomic) loci;
analyzing a plurality of test loci within said plurality of assay
loci for chromosomal aberrations; combining the data from (2) to
derive a score reflecting the overall extent of chromosomal
aberration in said plurality of test loci, wherein each test locus
is assigned a weighting coefficient that determines its
contribution to the chromosomal aberration score and wherein
telomeric loci are weighted such that they contribute at least 5%
(or 10%, or 15%, or 20%, or 30%, or 40%, or 50%, or 60%, or 70%, or
80%, or 90%, or 95%, or 100%) to the chromosomal aberration score,
thereby deriving a chromosomal aberration score.
[0087] "Telomeric locus" as used herein means a locus within a
telomere or within some defined distance along the chromosome from
the telomere. In some embodiments a telomeric locus is within 1 Kb,
2 Kb, 3 Kb, 4 Kb, 5 Kb, 6 Kb, 7 Kb, 8 Kb, 9 Kb, 10 Kb, 15 Kb, 20
Kb, 25 Kb, 30 Kb, 35 Kb, 40 Kb, 45 Kb, 50 Kb, 100 Kb, 200 Kb, 300
Kb, 400 Kb, 500 Kb, 750 Kb, 1 Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7
Mb, 8 Mb, 9 Mb, 10 Mb, 15 Mb, 20 Mb, 25 Mb, 30 Mb, 35 Mb, 40 Mb, 45
Mb, 50 Mb, 60 Mb, 70 Mb, 80 Mb, 90 Mb, or 100 Mb or less of the
telomere. In some embodiments, the distance between the telomeric
locus and the telomere is less than 1%, 2%, 3%, 4%, 5%, 10%, 15%,
20%, 30%, 40%, 50%, 60%, 70%, 80%, or 90% of the length of the
entire chromosome arm.
[0088] Thus, in some embodiments a telomeric region or telomeric
segment is a chromosomal region encompassing at least some number
of telomeric loci (e.g., at least 1, 2, 3, 4, 5, 10, 15, 20, 25,
50, 75, 100, 150, 200, 250, 300, 400, 500, 750, 1,000, 1,500,
2,000, 2,500, 3,000, 4,000, 5,000, 7,500, or 10,000 or more
telomeric loci). In some embodiments a telomeric region or
telomeric segment is a chromosomal region encompassing at least 1,
2, 3, 4, 5, 10, 15, 20, 25, 50, 75, 100, 150, 200, 250, 300, 400,
500, 750, 1,000, 1,500, 2,000, 2,500, 3,000, 4,000, 5,000, 7,500,
or 10,000 or more telomeric loci, wherein such telomeric loci are
within 50 Kb, 100 Kb, 200 Kb, 300 Kb, 400 Kb, 500 Kb, 750 Kb, 1 Mb,
2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, or 10 Mb of the
telomere (or any such combination of number of telomeric loci and
distance of such loci from the telomere). In some embodiments
telomeric regions do not cross the centromere.
[0089] DNA repair competency is one determinant of sensitivity to
certain chemotherapy drugs, such as cisplatin. Cancer cells with
intact DNA repair can avoid the accumulation of genome damage
during growth and also can repair platinum-induced DNA damage. We
sought genomic signatures indicative of defective DNA repair in
cell lines and tumors, and correlated these signatures to platinum
sensitivity. The number of sub-chromosomal regions with allelic
imbalance extending to the telomere (NtAI) predicted cisplatin
sensitivity in-vitro, and pathologic response to preoperative
cisplatin treatment in patients with triple-negative breast cancer
(TNBC). In serous ovarian cancer treated with platinum-based
chemotherapy, higher NtAI forecast better initial response. We
found an inverse relationship between BRCA1 expression and number
of regions of tAI (NtAI) in sporadic TNBC and serous ovarian
cancers without BRCA1 or BRCA2 mutation. Thus, accumulation of tAI
is a marker of cisplatin sensitivity and suggests impaired DNA
repair, and NtAI can be useful for predicting response to
treatments targeting defective DNA repair.
[0090] Mutations in BRCA1 or BRCA2 cause defects in DNA repair that
predict sensitivity to platinum salts in breast and ovarian cancer;
however, some patients without BRCA mutations also benefit from
these agents. This study shows that defects in DNA repair that
cause platinum sensitivity can be inferred from the number of
allelic imbalance (NAI), for example, the number of telomeric
imbalance (NtAI), a measure of genomic aberration in tumors. We
have demonstrated that NAI and/or NtAI can identify cancer patients
without BRCA mutations who are likely to benefit from
platinum-based therapy, such as cancer patients with triple
negative breast cancer or triple negative ovarian cancer.
[0091] Cell lines carrying BRCA1 or BRCA2 mutations are more
sensitive to killing by the platinum salts cisplatin and
carboplatin than wild-type cells (Samouelian, et al.
Chemosensitivity and radiosensitivity profiles of four new human
epithelial ovarian cancer cell lines exhibiting genetic alterations
in BRCA2, TGFbeta-RII, KRAS2, TP53 and/or CDNK2A. Cancer Chemother
Pharmacol 2004; 54: 497-504, Tassone, et al. BRCA1 expression
modulates chemosensitivity of BRCA1-defective HCC1937 human breast
cancer cells. Br J Cancer 2003; 88: 1285-1291). Breast and ovarian
cancers in patients carrying BRCA1 or BRCA2 mutations are likewise
sensitive to platinum-based chemotherapy (Byrski, T., et al.
Response to neoadjuvant therapy with cisplatin in BRCA1-positive
breast cancer patients. Breast Cancer Res Treat 2009; 115: 359-363,
Cass, I., et al. Improved survival in women with BRCA-associated
ovarian carcinoma. Cancer 2003; 97: 2187-2195). The majority of
breast cancers arising in women with a germline BRCA1 mutation lack
expression of estrogen and progesterone receptors or amplification
of the HER2-neu gene ("triple-negative"). BRCA1-related breast
cancers share a number of phenotypic characteristics with sporadic
triple-negative breast cancer (TNBC) (Turner, N. C., et al. BRCA1
dysfunction in sporadic basal-like breast cancer. Oncogene 2007;
26: 2126-2132; Sorlie, T., et al. Repeated observation of breast
tumor subtypes in independent gene expression data sets. Proc Natl
Acad Sci USA 2003; 100: 8418-8423; Lakhani, S. R., et al.
Prediction of BRCA1 status in patients with breast cancer using
estrogen receptor and basal phenotype. Clin Cancer Res 2005; 11:
5175-5180). Both tumor types share a common pattern of genomic
abnormalities and have high global levels of chromosomal
aberrations including allelic imbalance (AI), the unequal
contribution of maternal and paternal DNA sequences with or without
changes in overall DNA copy number (Wang, Z. C., et al. Loss of
heterozygosity and its correlation with expression profiles in
subclasses of invasive breast cancers. Cancer Research 2004; 64:
64-71; Richardson, A. L., et al. X chromosomal abnormalities in
basal-like human breast cancer. Cancer Cell 2006; 9: 121-132; Van
Loo, P., et al. Allele-specific copy number analysis of tumors.
Proc Natl Acad Sci USA 2010; 107: 16910-16915). Since they have in
common genomic aberrations suggesting a shared lesion in genomic
integrity control, it is reasonable to posit sporadic TNBC that has
accumulated high levels of AI might share the sensitivity to
platinum-based chemotherapy that characterizes BRCA1-associated
cancer.
[0092] We performed a clinical trial, Cisplatin-1, in which 28
patients with operable TNBC were treated preoperatively with
cisplatin monotherapy. Preoperative treatment in Cisplatin-1
resulted in greater than 90% tumor reduction in 10 of 28 (36%)
patients, including pathologic complete response (pCR) in 6 women,
2 of whom had BRCA1-associated cancers (Silver, D. P., et al.
Efficacy of neoadjuvant Cisplatin in triple-negative breast cancer.
J Clin Oncol 2010; 28: 1145-1153). A second trial, Cisplatin-2,
accrued 51 patients with TNBC who received the same preoperative
cisplatin regimen as Cisplatin-1, but in combination with the
angiogenesis inhibitor bevacizumab (Ryan, P. D., et al. Neoadjuvant
cisplatin and bevacizumab in triple negative breast cancer (TNBC):
Safety and Efficacy. J Clin Oncol 2009; 27: 551). Response rate in
Cisplatin-2 were similar to Cisplatin-1. In the second trial, a
greater than 90% tumor reduction was observed in 17 of 44 women
(39%) completing treatment. In Cisplatin-2, 8 patients carried a
germline BRCA1 or BRCA2 mutation, of which 4 patients achieved a
pCR or near pCR to the cisplatin-bevacizumab regimen. In both
trials, all patients had research sequencing to determine their
germline BRCA1 and BRCA2 status. Thus in some aspects of all the
embodiments of the invention, the BRCA1 and BRCA2 status can be
determined either simultaneously with or before the allelic
imbalance or telomeric allelic imbalance analysis. In some aspects,
only patients without BRCA1 or BRCA2 mutations are subjected to the
NAI (number of allelic imbalance) or NtAI (number of telomeric
allelic imbalance) assays or analyses. Cisplatin was used as an
example of platinum comprising cancer therapies.
[0093] We compared the number of various chromosomal abnormalities
including AI present in tumor biopsies obtained before therapy to
pathologically determined tumor response to cisplatin, alone or in
combination with bevacizumab, assessed by examination of the
post-treatment surgical specimen.
[0094] Without wishing to be bound by theory, chromosomal
abnormalities such as regions of allelic imbalance, other than
those resulting from whole chromosome gain or loss, can result from
improper repair of DNA double-strand breaks during tumor
development. If so, then a genome-wide count of abnormal
chromosomal regions in tumors can indicate the degree of DNA repair
incompetence, independent of knowledge of any specific causative
DNA repair defect. We hypothesized that the number of chromosomal
regions of AI in tumors would predict sensitivity to drugs that
induce DNA crosslinks such as cisplatin.
[0095] We sought associations between various measures of
sub-chromosomal abnormalities and sensitivity to cisplatin in
breast cancer cell lines and found the most accurate predictor to
be AI extending to the telomeric end of the chromosome (NtAI).
Finally, we tested if NtAI was associated with treatment response
in patient tumor samples in the Cisplatin-1 and Cisplatin-2 TNBC
trials and in The Cancer Genome Atlas (TCGA) public data set of
serous ovarian cancer, a cancer routinely treated with
platinum-based therapy. In an effort to understand more about the
processes leading to telomeric allelic imbalances, we mapped the
location of their breakpoints and observed a striking association
of these breakpoints with regions of the genome that are difficult
to replicate, common copy number variants (CNVs). Further, a subset
of high NtAI tumors display low BRCA1 mRNA levels. These
observations begin to suggest models of how tAI may occur.
[0096] We showed that Cisplatin sensitivity correlates with burden,
i.e. increase in the number of telomeric allelic imbalance compared
to normal cells in, for example, breast cancer cell lines. We
obtained single nucleotide polymorphism (SNP) genotype array data
from the Wellcome Trust Sanger Institute for a set of established
BRCA1 wild-type breast cancer cell lines for which we had
determined cisplatin sensitivity (Li, Y., et al. Amplification of
LAPTM4B and YWHAZ contributes to chemotherapy resistance and
recurrence of breast cancer. Nat Med 2010; 16: 214-218) (FIG. 10A).
Allele copy number was determined from the SNP array data and AI
detected using ASCAT analysis (10) (FIG. 16), although any other
allelic imbalance analysis can be used as well. We tested for
association between the IC.sub.50 values for cisplatin and each of
three summary measures of chromosomal alteration: the number of
chromosome regions with AI (NAI, FIG. 17A), the number of regions
with copy number gains (NGain, FIG. 17B), and the number of regions
with copy number loss (NLoss, FIG. 17C). None of these measures
were correlated with cisplatin sensitivity in the cell lines.
[0097] Known defects in DNA double strand break repair, including
loss of BRCA1, cause the spontaneous formation of triradial and
quadriradial chromosome structures, which are cytologic indications
of aberrant chromosome recombination (Silver, D. P., et al. Further
evidence for BRCA1 communication with the inactive X chromosome.
Cell 2007; 128: 991-1002; Luo, G., et al. Cancer predisposition
caused by elevated mitotic recombination in Bloom mice. Nat Genet
2000; 26: 424-429; Xu, X., et al., Centrosome amplification and a
defective G2-M cell cycle checkpoint induce genetic instability in
BRCA1 exon 11 isoform-deficient cells. Mol Cell 1999; 3: 389-395).
The resolution of these chromosome rearrangements at mitosis can
result in large regions of AI and/or copy number changes extending
from the crossover to the telomere (Luo, G., et al. Cancer
predisposition caused by elevated mitotic recombination in Bloom
mice. Nat Genet 2000; 26: 424-429; Vrieling, H. Mitotic maneuvers
in the light. Nat Genet 2001; 28: 101-102). More generally, several
error-prone repair processes potentially employed by cells with
defective DNA repair cause chromosome cross-over or copy choice
events that result in allelic loss or copy number change extending
from the site of DNA damage to the telomere.
[0098] We looked for an association between cisplatin sensitivity
and the number of contiguous regions of AI, copy gain, or copy loss
that either extended to a telomere and did not cross the centromere
(telomeric regions) or did not extend to a telomere (interstitial
regions) (FIG. 16, FIG. 10B, and FIG. 18). The number of regions of
telomeric AI (NtAI) was the only summary genomic measure that was
significantly associated with cisplatin sensitivity in the breast
cancer cell lines (r=0.76 P=0.011, FIG. 10B); the correlation
between NtAI and cisplatin sensitivity was stronger when the
analysis was restricted to the triple negative breast cancer lines
(FIG. 1B, red circles; r=0.82 P=0.0499). A similar relationship was
observed between NtAI and cisplatin sensitivity as measured by GI50
in a recently published study of breast cancer cell lines (r=0.57
P=0.0018, FIG. 10C) (18). Of all the drugs tested in this study,
NtAI was most highly correlated to cisplatin sensitivity.
[0099] We showed that tumors sensitive to cisplatin-based
chemotherapy have higher levels of telomeric allelic imbalance. We
investigated whether the association between NtAI in clinical tumor
samples and cisplatin sensitivity was present in the Cisplatin-1
trial. Sensitivity was measured by pathologic response determined
after pre-operative treatment (Silver, D. P., et al. Efficacy of
neoadjuvant Cisplatin in triple-negative breast cancer. J Clin
Oncol 2010; 28: 1145-1153). Molecular inversion probe SNP genotype
data from pretreatment tumor samples (n=27) were evaluated by ASCAT
analysis to determine NtAI. We compared tumors with a reduction of
at least 90% in the content of malignant cells (cisplatin
sensitive) to tumors with limited or no response to cisplatin
(cisplatin resistant, defined by tumor reduction of less than
90%).
[0100] We showed that cisplatin sensitive tumors had significantly
higher NtAI (median 24 versus 17.5, P=0.047, FIG. 11A). We tested
the ability of NtAI to predict cisplatin response by calculating
the area under the receiver operating characteristic (ROC) curve
(AUC). ROC analysis showed that higher NtAI was associated with
cisplatin sensitivity (AUC=0.74, CI 0.50-0.90, FIG. 11B).
[0101] In the Cisplatin-2 trial, cisplatin sensitive tumors (n=9)
had significantly higher NtAI than resistant tumors (n=17, median
27 versus 20, P=0.019, FIG. 11C). NtAI was also associated with
response to cisplatin and bevacizumab by ROC analysis (AUC=0.79, CI
0.55-0.93, FIG. 11D). The association between NtAI and cisplatin
sensitivity remained significant when cases with BRCA1 or BRCA2
mutation were excluded and only BRCA normal cases were analyzed
(P=0.030 and P=0.023 in Cisplatin-1 and Cisplatin-2, respectively).
Therefore, in two separate pre-operative trials in breast cancer,
in which treatment sensitivity was assessed by a quantitative
measure of pathologic response, NtAI reliably forecast the response
to cisplatin-based treatment.
[0102] To test if the NtAI metric indicates platinum sensitivity in
cancers other than breast, we determined the association between
NtAI and initial treatment response in The Cancer Genome Atlas
(TCGA) cohort of serous ovarian cancer patients that had received
adjuvant platinum and taxane chemotherapy (Bell, D., et al.,
Integrated genomic analyses of ovarian carcinoma. Nature 2011; 474:
609-615). Again, among the ovarian cancers without mutation in
BRCA1 or BRCA2 (wtBRCA), the platinum sensitive tumors had
significantly higher NtAI than platinum-resistant cancers (median
22 versus 20, P=0.036, FIG. 12), and were predictive of treatment
response by ROC analysis (AUC=0.63, CI 0.50-0.76, FIG. 19). The
ovarian cancers with somatic or germline mutation in BRCA1 or BRCA2
that were sensitive to platinum therapy had even higher NtAI
(median=26, P=0.0017 and median 23.5, P=0.037 versus resistant
wtBRCA, respectively, FIG. 12). All of the BRCA2 mutated cancers
were platinum sensitive; however, 5 BRCA1 mutated tumors were
resistant to platinum therapy yet appeared to have relatively high
levels of NtAI. Thus high NtAI is characteristic of serous ovarian
cancer with known mutation in either BRCA1 or BRCA2; high NtAI is
also found in a subset of sporadic cancers without BRCA mutations
where it is predictive of platinum sensitivity.
[0103] Accordingly, we provide a method for selecting therapy for a
human cancer patient, the method comprising assaying a sample
comprising tumor cells taken from the human cancer patient for the
number of allelic imbalance, for example telomeric allelic
imbalance, and selecting, and optionally administering a
platinum-comprising cancer therapy to the human cancer patient if
the number of allelic imbalance is increased compared to a
reference value. The reference value for the number of allelic
imbalance, such as telomeric allelic imbalance can be, for example,
at least 20, at least 21, at least 22, at least 23, at least 23.5,
at least 24, at least 25, at least 26, at least 27, at least 28 at
least 29, or at least 30. The reference value can be determined for
each tumor, for example from the number of allelic imbalance
collected from similar cancers that are platinum-resistant. So, for
example, in a lung cancer, samples from lung cancer cells from
platinum-resistant cancers can provide a median number of allelic
imbalance for the cancer to be used as a reference value for
non-responding samples.
[0104] We further showed that locations of NtAI-associated
chromosomal breaks are not random. To understand the processes
leading to tAI better, we mapped the location of the chromosome
breakpoints defining the boundary of the tAI regions. We observed
many breakpoints were located in very close proximity to each other
(FIG. 20), suggesting a non-random distribution of DNA breaks
causing telomeric allelic imbalance.
[0105] Without wishing to be bound by a theory, recurrent
chromosomal translocation breakpoints can be associated with
regions of repeated DNA sequence that can cause stalled replication
forks, an increased frequency of DNA breaks, and subsequent
rearrangement by non-allelic homologous recombination or other
similar mechanisms (Kolomietz, E., et al., The role of Alu repeat
clusters as mediators of recurrent chromosomal aberrations in
tumors. Genes Chromosomes Cancer 2002; 35: 97-112; Hastings, P. J.,
Ira, G., and Lupski, J. R. A microhomology-mediated break-induced
replication model for the origin of human copy number variation.
PLoS Genet 2009; 5: e1000327).
[0106] Copy number variants (CNVs) are highly homologous DNA
sequences for which germline copy number varies between healthy
individuals (Iafrate, A. J., et al. Detection of large-scale
variation in the human genome. Nat Genet 2004; 36: 949-951; Sebat,
J., et al., Large-scale copy number polymorphism in the human
genome. Science 2004; 305: 525-528). CNVs have been proposed to
facilitate the generation of chromosomal alterations, similar to
fragile sites (Hastings, P. J., Ira, G., and Lupski, J. R. A
microhomology-mediated break-induced replication model for the
origin of human copy number variation. PLoS Genet 2009; 5:
e1000327; Stankiewicz, P., et al. Genome architecture catalyzes
nonrecurrent chromosomal rearrangements. Am J Hum Genet 2003; 72:
1101-1116; Hastings, P. J., et al., Mechanisms of change in gene
copy number. Nat Rev Genet 2009; 10: 551-564). We compared the
number of observed breaks within 25 kB of a CNV to the frequency
expected by chance alone, based on permuted data. In the
Cisplatin-1 cohort, of 517 NtAI breakpoints, 255 (49%) were
associated with overlapping CNVs. Similarly, in the cisplatin-2
cohort, out of 599 NtAI breakpoints, 340 (57%) were associated with
CNVs. In both trials, the observed number of NtAI breaks associated
with CNVs was significantly higher than expected by chance (FIG.
13A-13B). Thus many of the breakpoints leading to telomeric AI in
TNBC occur near CNVs suggesting stalled replication forks,
replication stress, or other CNV-associated mechanisms may be
involved in the genesis of telomeric AI.
[0107] Accordingly, in some aspects of all the embodiments of the
invention, we provide a method or an assay for determining whether
a patient is responsive to platinum-comprising therapy by assaying
the number of allelic imbalance, such as telomeric allelic
imbalance, wherein the AI is associated with copy number variations
(CNVs). If increase of CNV associates NAI, such as NtAI is
detected, then determining that the patient is responsive to
platinum-comprising cancer therapy and optionally administering the
platinum-comprising therapy to the cancer patient. If no increase
in CNV associated NAI, such as NtAI is detected, then determining
that the cancer patient is not responsive to platinum comprising
cancer therapy and optionally administering to the cancer patient a
non-platinum comprising cancer therapy.
[0108] We demonstrated that low BRCA1 mRNA is associated with high
NtAI and sensitivity to cisplatin.
[0109] According, in some aspects of all the embodiments of the
invention, we provide an assay or a method for determining
responsiveness of a cancer patient to a platinum-comprising cancer
therapy, the assay or method comprising, assaying in a cancer-cell
comprising sample taken from the cancer patient the number of
allelic imbalance and/or the BRCA1 mRNA amount, and if the number
of allelic imbalance is increased and/or the BRCA1 mRNA amount is
decreased, then selecting, and optionally administering to the
cancer patient platinum-comprising cancer therapy. If, on the other
hand no increase in the number of allelic imbalance and/or no
decrease in BRCA1 mRNA amount is detected, then selecting, and
optionally administering to said cancer patient a non-platinum
comprising cancer therapy.
[0110] In our Cisplatin-1 trial, we found an association between
low BRCA1 transcript levels and better response to cisplatin. In
the Cisplatin-2 trial, BRCA1 transcript levels measured, for
example, by qPCR are also associated with cisplatin response
(P=0.015, FIG. 14A). In a combined analysis of data from both
trials, lower BRCA1 transcript levels are associated with
methylation of the BRCA1 promoter (P=0.027, FIG. 14B), though BRCA1
promoter methylation itself is not significantly associated with
cisplatin response (P=0.25, Fishers exact test). BRCA1 mRNA levels
are inversely associated with NtAI in the two cisplatin trials
(r=-0.50, P=0.0053, FIG. 14C). This finding suggests that
dysfunction of a BRCA1-dependent process or other abnormality
causing low BRCA1 mRNA may be responsible for the high level of
telomeric allelic imbalance and also cisplatin sensitivity in many
of these TNBCs.
[0111] In some aspects of all the embodiments of the invention, the
assays and methods comprise assaying the methylation status of
BRCA1, wherein increase in methylation of BRCA1 promoter region is
associated with a responsiveness to platinum-comprising cancer
therapy and no increase in methylation of BRCA1 promoter region is
associated with resistance to platinum-comprising cancer therapy.
If increased methylation of BRCA1 promoter region is detected, then
selecting, and optionally administering, a platinum-comprising
therapy for the cancer patient, and if no increase in methylation
of BRCA1 promoter region is detected, then selecting, and
optionally administering a non-platinum comprising therapy for the
cancer patient. In some aspects of this embodiment, the cancer is
breast cancer.
[0112] ROC analysis of the combined TNBC trials suggests that BRCA1
expression level or NtAI may give a similar predictive accuracy for
cisplatin sensitivity (FIG. 21A). When high NtAI and low BRCA1
expression are combined in a predictive model, the positive
predictive value and specificity of prediction improved
considerably but the sensitivity was decreased relative to NtAI
alone (FIG. 21B), suggesting that low BRCA1 expression does not
account for all cisplatin sensitive tumors.
[0113] In the TNBC trials, we noted a few cisplatin sensitive
tumors with high levels of NtAI but high BRCA1 mRNA, suggesting
that alternative mechanisms may drive the generation of tAI in some
tumors. Analysis of TCGA data of ER-/HER2- breast cancer and wtBRCA
serous ovarian cancer demonstrate an inverse correlation between
NtAI and BRCA1 expression. Yet in both cohorts there was a
considerable subset of tumors with high NtAI and high BRCA1
expression (FIGS. 22A, 22B). Unlike NtAI, BRCA1 expression was not
apparently different between sensitive and resistant wtBRCA serous
ovarian cancers (FIG. 22C). These findings suggest a model whereby
high NtAI may represent a readout of DNA repair deficiency
resulting from either low BRCA1 expression or from other known or
unknown mechanisms (FIG. 15).
[0114] In some aspects of all the embodiments of the invention, the
NtAI or NAI analysis is performed alone without separately
detecting or determining the status of BRCA1 and/or BRCA2, such as
whether the tumor cell carries a BRCA1 and/or BRCA2 mutation or
whether the BRCA1 or BRCA2 expression is decreased or not, or
whether the BRCA1 and/or BRCA2 promoter methylation is increased or
not. In some aspects of all the embodiments of the invention, the
NtAI or NAI analysis is performed in combination with detecting or
determining the status of BRCA1 and/or BRCA2.
[0115] Several embodiments of the invention described herein
involve a step of correlating an LOH signature or the number of AI
or tAI according to the present invention (e.g., the total number
of LOH/AI/tAI regions in at least one pair of human chromosomes of
said cancer cell that are longer than a first length but shorter
than the length of the whole chromosome containing the LOH/AI/tAI
region, wherein said at least one pair of human chromosomes is not
a human X/Y sex chromosome pair, wherein said first length is about
1.5 or more megabases) to a particular clinical feature (e.g., an
increased likelihood of a deficiency in the BRCA1 or BRCA2 gene; an
increased likelihood of HDR deficiency; an increased likelihood of
response to a treatment regimen comprising a DNA damaging agent, an
anthracycline, a topoisomerase I inhibitor, radiation, and/or a
PARP inhibitor; etc.) if the number is greater than some reference
(or optionally to another feature if the number is less than some
reference). Throughout this document, wherever such an embodiment
is described, another embodiment of the invention may involve, in
addition to or instead of a correlating step, one or both of the
following steps: (a) concluding that the patient has the clinical
feature based at least in part on the presence or absence of the
LOH signature or increase or not of the number of AI or tAI; or (b)
communicating that the patient has the clinical feature based at
least in part on the presence or absence of the LOH signature or
increase of NAI or NtAI.
[0116] By way of illustration, but not limitation, one embodiment
described in this document is a method of predicting a cancer
patient's response to a cancer treatment regimen comprising a DNA
damaging agent, an anthracycline, a topoisomerase I inhibitor,
radiation, and/or a PARP inhibitor, said method comprising: (1)
determining, in a cancer cell from said cancer patient, the number
of LOH/AI/tAI regions in at least one pair of human chromosomes of
a cancer cell of said cancer patient that are longer than a first
length but shorter than the length of the whole chromosome
containing the LOH/AI/tAI region, wherein said at least one pair of
human chromosomes is not a human X/Y sex chromosome pair, wherein
said first length is about 1.5 or more megabases; and (2)
correlating said total number that is greater than a reference
number with an increased likelihood that said cancer patient will
respond to said cancer treatment regimen. According to the
preceding paragraph, this description of this embodiment is
understood to include a description of two related embodiments,
i.e., a method of predicting a cancer patient's response to a
cancer treatment regimen comprising a DNA damaging agent, an
anthracycline, a topoisomerase I inhibitor, radiation, and/or a
PARP inhibitor, said method comprising: (1) determining, in a
cancer cell from said cancer patient, the number of LOH/AI/tAI
regions in at least one pair of human chromosomes of a cancer cell
of said cancer patient that are longer than a first length but
shorter than the length of the whole chromosome containing the
LOH/AI/tAI region, wherein said at least one pair of human
chromosomes is not a human X/Y sex chromosome pair, wherein said
first length is about 1.5 or more megabases; and (2)(a) concluding
that said patient has an increased likelihood that said cancer
patient will respond to said cancer treatment regimen based at
least in part on a total number that is greater than a reference
number; or (2)(b) communicating that said patient has an increased
likelihood that said cancer patient will respond to said cancer
treatment regimen based at least in part on a total number that is
greater than a reference number.
[0117] In each embodiment described in this document involving
correlating a particular assay or analysis output (e.g., total
number of LOH/AI/tAI regions greater than a reference number, etc.)
to some likelihood (e.g., increased, not increased, decreased,
etc.) of some clinical feature (e.g., response to a particular
treatment, cancer-specific death, etc.), or additionally or
alternatively concluding or communicating such clinical feature
based at least in part on such particular assay or analysis output,
such correlating, concluding or communicating may comprise
assigning a risk or likelihood of the clinical feature occurring
based at least in part on the particular assay or analysis output.
In some embodiments, such risk is a percentage probability of the
event or outcome occurring. In some embodiments, the patient is
assigned to a risk group (e.g., low risk, intermediate risk, high
risk, etc.). In some embodiments "low risk" is any percentage
probability below 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or
50%. In some embodiments "intermediate risk" is any percentage
probability above 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or
50% and below 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%,
65%, 70%, or 75%. In some embodiments "high risk" is any percentage
probability above 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%,
75%, 80%, 85%, 90%, 95%, or 99%.
[0118] As used herein, "communicating" a particular piece of
information means to make such information known to another person
or transfer such information to a thing (e.g., a computer). In some
methods of the invention, a patient's prognosis or likelihood of
response to a particular treatment is communicated. In some
embodiments, the information used to arrive at such a prognosis or
response prediction (e.g., LOH signature or NTAI or NtAI according
to the present invention, etc.) is communicated. This communication
may be auditory (e.g., verbal), visual (e.g., written), electronic
(e.g., data transferred from one computer system to another), etc.
In some embodiments, communicating a cancer classification (e.g.,
prognosis, likelihood of response, appropriate treatment, etc.)
comprises generating a report that communicates the cancer
classification. In some embodiments the report is a paper report,
an auditory report, or an electronic record. In some embodiments
the report is displayed and/or stored on a computing device (e.g.,
handheld device, desktop computer, smart device, website, etc.). In
some embodiments the cancer classification is communicated to a
physician (e.g., a report communicating the classification is
provided to the physician). In some embodiments the cancer
classification is communicated to a patient (e.g., a report
communicating the classification is provided to the patient).
Communicating a cancer classification can also be accomplished by
transferring information (e.g., data) embodying the classification
to a server computer and allowing an intermediary or end-user to
access such information (e.g., by viewing the information as
displayed from the server, by downloading the information in the
form of one or more files transferred from the server to the
intermediary or end-user's device, etc.).
[0119] Wherever an embodiment of the invention comprises concluding
some fact (e.g., a patient's prognosis or a patient's likelihood of
response to a particular treatment regimen), this may include in
some embodiments a computer program concluding such fact, typically
after performing an algorithm that applies information on
LOH/AI/tAI regions according to the present invention.
[0120] In each embodiment described herein involving a number of
LOH regions (e.g., LOH Indicator Regions) or a total combined
length of such LOH regions, the present invention encompasses a
related embodiment involving a test value or score (e.g., HRD
score, LOH score, NAI, NtAI etc.) derived from, incorporating,
and/or, at least to some degree, reflecting such number or length.
In other words, the bare LOH/AI/tAI region numbers or lengths need
not be used in the various methods, systems, etc. of the invention;
a test value or score derived from such numbers or lengths may be
used. For example, one embodiment of the invention provides a
method of treating cancer in a patient, comprising: (1) determining
in a sample from said patient the number of LOH/AI/tAI regions in
at least one pair of human chromosomes of a cancer cell of the
cancer patient that are longer than a first length but shorter than
the length of the whole chromosome containing the LOH/AI/tAI region
indicates that the cancer cells have the LOH signature or the
number of AI or tAI, wherein the at least one pair of human
chromosomes is not a human X/Y sex chromosome pair, wherein the
first length is about 1.5 or more megabases; (2) providing a test
value derived from the number of said LOH/AI/tAI regions; (3)
comparing said test value to one or more reference values derived
from the number of said LOH/AI/tAI regions in a reference
population (e.g., mean, median, terciles, quartiles, quintiles,
etc.); and (4)(a) administering to said patient an anti-cancer
drug, or recommending or prescribing or initiating a treatment
regimen comprising chemotherapy and/or a synthetic lethality agent
based at least in part on said comparing step revealing that the
test value is greater (e.g., at least 2-, 3-, 4-, 5-, 6-, 7-, 8-,
9-, or 10-fold greater; at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10
standard deviations greater) than at least one said reference
value; or (4)(b) recommending or prescribing or initiating a
treatment regimen not comprising chemotherapy and/or a synthetic
lethality agent based at least in part on said comparing step
revealing that the test value is not greater (e.g., not more than
2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater; not more than
1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standard deviations greater) than
at least one said reference value. The invention encompasses,
mutatis mutandis, corresponding embodiments where the test value or
score is used to determine the patient's prognosis, the patient's
likelihood of response to a particular treatment regimen, the
patient's or patient's sample's likelihood of having a BRCA1,
BRCA2, RAD51C or HDR deficiency, etc.
[0121] In one aspect, the invention provides a kit comprising, in a
container, reagents suitable for determining allelic imbalance in
at least 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, 75, 100, 150, 200, 250,
300, 400, 500, 750, 1,000, 1,500, 2,000, 2,500, 3,000, 4,000,
5,000, 7,500, or 10,000 or more telomeric loci (e.g., loci within
50 Kb, 100 Kb, 200 Kb, 300 Kb, 400 Kb, 500 Kb, 750 Kb, 1 Mb, 2 Mb,
3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, or 10 Mb of the
telomere). In some embodiments the kit comprises reagents for
determining allelic imbalance in no more than 10,000, 7,500, 5,000,
4,000, 3,000, 2,000, 1,000, 750, 500, 400, 300, 200, 150, 100, 90,
80, 70, 60, or 50 total loci. In some embodiments telomeric loci
comprise at least 10%, 15%, 20%, 30%, 40%, 50%, 60%, 70%, 80%, 90%,
95%, 99%, or 100% of the loci for which the kit contains reagents
for determining allelic imbalance.
[0122] As discussed above, allelic imbalance is a type of
chromosomal aberration. As used herein, "allelic imbalance" means a
change in the number and/or type of alleles of a chromosome in a
somatic tissue as compared to germline. In some embodiments allelic
imbalance is loss of heterozygosity ("LOH"). This can be copy
number neutral, such as when one of the heterozygous parental
alleles is lost and the other allele is duplicated as a
"replacement." LOH can also occur in a non-copy number neutral way,
where one parental allele is simply lost. In some embodiments
allelic imbalance is duplication of one allele over another
(somatic AA/B from AA/B germline) or greater duplication of one
allele as compared to another (e.g., somatic AAAA/BB from A/B
germline). In some embodiments a region has allelic imbalance if
loci in that region show MCP (as discussed in greater detail in
Section IV.H. below) of is greater than 0.51, 0.52, 0.53, 0.54,
0.55, 0.56, 0.57, 0.58, 0.59, 0.60, 0.61, 0.62, 0.63, 0.64, 0.65,
0.66, 0.67, 0.68, 0.69, 0.70, 0.71, 0.72, 0.73, 0.74, 0.75, 0.76,
0.77, 0.78, 0.79, 0.80. 0.81, 0.82, 0.83, 0.84, 0.85, 0.86, 0.87,
0.88, 0.89, 0.90, 0.91, 0.92, 0.92, 0.93, 0.94, 0.95, 0.96, 0.97,
0.98, or 0.99 (including MCP of 1).
[0123] Thus, a predefined number of chromosomes may be analyzed to
determine the total number of Indicator LOH Regions, preferably the
total number of LOH regions of a length of greater than 9
megabases, 10 megabases, 12 megabases, 14 megabases, more
preferably greater than 15 megabases. Alternatively or in addition,
the sizes of all identified Indicator LOH Regions may be summed up
to obtain a total length of Indicator LOH Regions.
[0124] For classification of positive LOH signature status, the
reference number discussed above for the total number of Indicator
LOH Regions may be 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18,
19, 20 or greater, preferably 5, preferably 8, more preferably 9 or
10, most preferably 10. The reference number for the total (e.g.,
combined) length of Indicator LOH Regions may be about 75, 90, 105,
120, 130, 135, 150, 175, 200, 225, 250, 275, 300, 325 350, 375,
400, 425, 450, 475, 500 megabases or greater, preferably about 75
megabases or greater, preferably about 90 or 105 megabases or
greater, more preferably about 120 or 130 megabases or greater, and
more preferably about 135 megabases or greater, and most preferably
about 150 megabases or greater.
[0125] In some specific embodiments, the total number of LOH
regions of a length of greater than about 14 or 15 megabases is
determined and compared to a reference number of about 5, 6, 7, 8,
9, 10, 11, 12, 13, 14, 15, 16, 18, 19, or 20. Alternatively or in
addition, the total length of LOH regions of a length of greater
than about 14 or 15 megabases is determined and compared to a
reference number of about 75, 90, 105, 120, 130, 135, 150, 175,
200, 225, 250, 275, 300, 325 350, 375, 400, 425, 450, 475, or 500
megabases.
[0126] In some embodiments, the number of LOH regions (or the
combined length, or a test value or score derived from either) in a
patient sample is considered "greater" than a reference if it is at
least 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or 10-fold greater than the
reference while in some embodiments, it is considered "greater" if
it is at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standard deviations
greater than the reference. Conversely, in some embodiments the
number of LOH regions (or the combined length, or a test value or
score derived from either) in a patient sample is considered "not
greater" than a reference if it is not more than 2-, 3-, 4-, 5-,
6-, 7-, 8-, 9-, or 10-fold greater than the reference while in some
embodiments, it is considered "not greater" if it is not more than
1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standard deviations greater than
the reference.
[0127] In some embodiments the reference number (or length, value
or score) is derived from a relevant reference population. Such
reference populations may include patients (a) with the same cancer
as the patient being tested, (b) with the same cancer sub-type, (c)
with cancer having similar genetic or other clinical or molecular
features, (d) who responded to a particular treatment, (e) who did
not respond to a particular treatment, (f) who are apparently
healthy (e.g., do not have any cancer or at least do not have the
tested patient's cancer), etc. The reference number (or length,
value or score) may be (a) representative of the number (or length,
value or score) found in the reference population as a whole, (b)
an average (mean, median, etc.) of the number (or length, value or
score) found in the reference population as a whole or a particular
sub-population, (c) representative of the number (or length, value
or score) (e.g., an average such as mean or median) found in
terciles, quartiles, quintiles, etc. of the reference population as
ranked by (i) their respective number (or length, value or score)
or (ii) the clinical feature they were found to have (e.g.,
strength of response, prognosis (including time to cancer-specific
death), etc.).
[0128] As described herein, patients having cancer cells identified
as having a positive LOH signature status or increase in the NAI or
NtAI can be classified, based at least in part on a positive LOH
signature status or increase in the NAI or NtAI, as being likely to
respond to a particular cancer treatment regimen. For example,
patients having cancer cells with a genome containing an LOH
signature or increase in the NAI or NtAI can be classified, based
at least in part on a positive LOH signature status or increase in
the NAI or NtAI, as being likely to respond to a cancer treatment
regimen that includes the use of a DNA damaging agent, a synthetic
lethality agent (e.g., a PARP inhibitor), radiation, or a
combination thereof. Preferably the patients are treatment naive
patients.
[0129] Examples of DNA damaging agents include, without limitation,
platinum-based chemotherapy drugs (e.g., cisplatin, carboplatin,
oxaliplatin, and picoplatin), anthracyclines (e.g., epirubicin and
doxorubicin), topoisomerase I inhibitors (e.g., campothecin,
topotecan, and irinotecan), DNA crosslinkers such as mitomycin C,
and triazene compounds (e.g., dacarbazine and temozolomide).
Synthetic lethality therapeutic approaches typically involve
administering an agent that inhibits at least one critical
component of a biological pathway that is especially important to a
particular tumor cell's survival. For example, when a tumor cell
has a deficient homologous repair pathway (e.g., as determined
according to the present invention), inhibitors of poly ADP ribose
polymerase (or platinum drugs, double strand break repair
inhibitors, etc.) can be especially potent against such tumors
because two pathways critical to survival become obstructed (one
biologically, e.g., by BRCA1 mutation, and the other synthetically,
e.g., by administration of a pathway drug). Synthetic lethality
approaches to cancer therapy are described in, e.g., O'Brien et
al., Converting cancer mutations into therapeutic opportunities,
EMBO MOL. MED. (2009) 1:297-299.
[0130] Examples of synthetic lethality agents include, without
limitation, PARP inhibitors or double strand break repair
inhibitors in homologous repair-deficient tumor cells, PARP
inhibitors in PTEN-deficient tumor cells, methotrexate in
MSH2-deficient tumor cells, etc. Examples of PARP inhibitors
include, without limitation, olaparib, iniparib, and veliparib.
Examples of double strand break repair inhibitors include, without
limitation, KU55933 (ATM inhibitor) and NU7441 (DNA-PKcs
inhibitor). Examples of information that can be used in addition to
a positive LOH signature status to base a classification of being
likely to respond to a particular cancer treatment regimen include,
without limitation, previous treatment results, germline or somatic
DNA mutations, gene or protein expression profiling (e.g.,
ER/PR/HER2 status, PSA levels), tumor histology (e.g.,
adenocarcinoma, squamous cell carcinoma, papillary serous
carcinoma, mucinous carcinoma, invasive ductal carcinoma, ductal
carcinoma in situ (non-invasive), etc.), disease stage, tumor or
cancer grade (e.g., well, moderately, or poorly differentiated
(e.g., Gleason, modified Bloom Richardson), etc.), number of
previous courses of treatment, etc.
[0131] In addition to predicting likely treatment response or
selecting desirable treatment regimens, an LOH signature or
increase in the NAI or NtAI can be used to determine a patient's
prognosis. We have shown that patients whose tumors have an LOH
signature or increase in the NAI or NtAI show significantly better
survival than patients whose tumors do not have such an LOH
signature or increase in the NAI or NtAI. Thus, in one aspect, this
document features a method for determining a patient's prognosis
based at least in part of detecting the presence or absence of an
LOH signature or increase in the NAI or NtAI in a sample from the
patient. The method comprises, or consists essentially of, (a)
determining whether the patient comprises cancer cells having an
LOH signature or increase in the NAI or NtAI as described herein
(e.g., wherein the presence of more than a reference number of LOH
regions in at least one pair of human chromosomes of a cancer cell
of the cancer patient that are longer than a first length but
shorter than the length of the whole chromosome containing the LOH
region or AI or tAI region indicates that the cancer cells have the
LOH signature or increase in the NAI or NtAI, wherein the at least
one pair of human chromosomes is not a human X/Y sex chromosome
pair, wherein the first length is about 1.5 or more megabases), and
(b)(1) determining, based at least in part on the presence of the
LOH signature or or increase in the NAI or NtAI, that the patient
has a relatively good prognosis, or (b)(2) determining, based at
least in part on the absence of the LOH signature or increase in
the NAI or NtAI, that the patient has a relatively poor
prognosis.
[0132] Prognosis may include the patient's likelihood of survival
(e.g., progression-free survival, overall survival), wherein a
relatively good prognosis would include an increased likelihood of
survival as compared to some reference population (e.g., average
patient with this patient's cancer type/subtype, average patient
not having an LOH signature or increase in the NAI or NtAI, etc.).
Conversely, a relatively poor prognosis in terms of survival would
include a decreased likelihood of survival as compared to some
reference population (e.g., average patient with this patient's
cancer type/subtype, average patient having an LOH signature or
increase in the NAI or NtAI, etc.).
[0133] "Telomeric allelic imbalance" means allelic imbalance in a
telomeric region or segment. "Allelic imbalance" in a region or a
"region of allelic imbalance" means allelic imbalance in at least
some number of loci defining (in whole or in part) such region.
These are generally to be distinguished from isolated loci of
allelic imbalance. Thus, in some embodiments regions of allelic
imbalance are defined as at least 2, 3, 4, 5, 10, 15, 20, 25, 50,
75, 100, 150, 200, 250, 300, 400, 500, or more consecutive probes
showing allelic imbalance.
[0134] The number or proportion of telomeric regions having allelic
imbalance can be used to derive a telomeric allelic imbalance score
(sometimes referred to herein as NtAI), which is analogous to the
chromosomal aberration score described above (including the GCAS)
and particularly below, though focused on telomeric regions. Thus,
in some embodiments the invention provides a method of deriving a
telomeric allelic imbalance score comprising:determining whether a
sample has a chromosomal aberration (e.g., of allelic imbalance,
loss of heterozygosity, copy number aberrations, copy number gain,
copy number decrease) at a plurality of assay (e.g., genomic) loci;
analyzing a plurality of test loci within said plurality of assay
loci for chromosomal aberrations; combining the data from (2) to
derive a score reflecting the overall extent of chromosomal
aberration in said plurality of test loci, thereby deriving a
chromosomal aberration score.
[0135] In some embodiments, the data are combined in (3) in such a
way that each test locus is assigned a weighting coefficient that
determines its contribution to the chromosomal aberration score and
telomeric loci are weighted such that they contribute at least 5%
(or 10%, or 15%, or 20%, or 30%, or 40%, or 50%, or 60%, or 70%, or
80%, or 90%, or 95%, or 100%) to the chromosomal aberration score.
In some embodiments, at least 5% (or 10%, or 15%, or 20%, or 30%,
or 40%, or 50%, or 60%, or 70%, or 80%, or 90%, or 95%, or 100%) of
the test loci in (2) are telomeric loci.
[0136] In some embodiments the telomeric allelic imbalance score
will count all telomeric regions showing allelic imbalance. In some
embodiments this will include regions of allelic imbalance that
encompass an entire chromosome. In some embodiments the telomeric
allelic imbalance score will count all telomeric regions of at
least some minimum size (e.g., 1 Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb,
7 Mb, 8 Mb, 9 Mb, 10 Mb, 11 Mb, 12 Mb, 13 Mb, 14 Mb, 15 Mb, 16 Mb,
17 Mb, 18 Mb, 19 Mb, 20 Mb, 21 Mb, 22 Mb, 23 Mb, 24 Mb, 25 Mb, or
more, or any range in between, such as between 5 and 25 Mb) showing
allelic imbalance.
[0137] In some embodiments, at least 1, 2, 3, 4, 5, 10, 15, 20, 25,
50, 75, or 100 or more telomeric regions with allelic imbalance
(e.g., a high telomeric allelic imbalance score (e.g., a score of
at least 1, 2, 3, 4, 5, 10, 15, 20, 22, 23, 23.5, 24, 25, 26, 27,
50, 75, or 100 or more)) indicates an increased likelihood of
response to therapy comprising a particular modality (e.g.,
platinum compounds, cytotoxic antibiotics, antimetabolities,
anti-mitotic agents, alkylating agents, arsenic compounds, DNA
topoisomerase inhibitors, taxanes, nucleoside analogues, plant
alkaloids, and toxins; cisplatin, treosulfan, and trofosfamide;
plant alkaloids: vinblastine, paclitaxel, docetaxol; DNA
topoisomerase inhibitors: teniposide, crisnatol, and mitomycin;
anti-folates: methotrexate, mycophenolic acid, and hydroxyurea;
pyrimidine analogs: 5-fluorouracil, doxifluridine, and cytosine
arabinoside; purine analogs: mercaptopurine and thioguanine; DNA
antimetabolites: 2'-deoxy-5-fluorouridine, aphidicolin glycinate,
and pyrazoloimidazole; and antimitotic agents: halichondrin,
colchicine, and rhizoxin; and synthetic derivatives thereof).
[0138] Thus, in some embodiments the invention provides a method of
predicting whether a patient will respond to a particular treatment
comprising:determining whether a sample has a chromosomal
aberration (e.g., of allelic imbalance, loss of heterozygosity,
copy number aberrations, copy number gain, copy number decrease) at
a plurality of assay (e.g., genomic) loci; analyzing a plurality of
test loci within said plurality of assay loci for chromosomal
aberrations; combining the data from (2) to derive a chromosomal
aberration score reflecting the overall extent of chromosomal
aberration in said plurality of test loci; correlating a high
chromosomal aberration score to increased likelihood of response to
a particular treatment.
[0139] In some embodiments, the data are combined in (3) in such a
way that each test locus is assigned a weighting coefficient that
determines its contribution to the chromosomal aberration score and
telomeric loci are weighted such that they contribute at least 5%
(or 10%, or 15%, or 20%, or 30%, or 40%, or 50%, or 60%, or 70%, or
80%, or 90%, or 95%, or 100%) to the chromosomal aberration score.
In some embodiments, at least 5% (or 10%, or 15%, or 20%, or 30%,
or 40%, or 50%, or 60%, or 70%, or 80%, or 90%, or 95%, or 100%) of
the test loci in (2) are telomeric loci. In some embodiments the
telomeric allelic imbalance score will count all telomeric regions
showing allelic imbalance. In some embodiments this will include
regions of allelic imbalance that encompass an entire chromosome.
In some embodiments the telomeric allelic imbalance score will
count all telomeric regions of at least some minimum size (e.g., 1
Mb, 2 Mb, 3 Mb, 4 Mb, 5 Mb, 6 Mb, 7 Mb, 8 Mb, 9 Mb, 10 Mb, 11 Mb,
12 Mb, 13 Mb, 14 Mb, 15 Mb, 16 Mb, 17 Mb, 18 Mb, 19 Mb, 20 Mb, 21
Mb, 22 Mb, 23 Mb, 24 Mb, 25 Mb, or more, or any range in between,
such as between 5 and 25 Mb) showing allelic imbalance. In some
embodiments, a telomeric allelic imbalance score is high if at
least 1, 2, 3, 4, 5, 10, 15, 20, 25, 50, 75, or 100 or more
telomeric regions have allelic imbalance.
[0140] Heterozygous SNPs can be used in the methods of the
invention to determine the phenotype of a cancer are informative,
meaning heterozygosity is observed in the nucleic acid sample from
non-cancerous tissue and/or cells of a subject. According to the
methods of the invention, these informative SNPs are examined in
the nucleic acid sample from a cancerous tissue and/or cells of a
subject to determine GCAS. In a further embodiment, the nucleic
acid samples used to determine the number of heterozygous SNPs in
the plurality of SNPs, that exhibit heterozygosity in genomic DNA
of non-cancerous tissue of the species to which the cancer patient
belongs, are taken from at least 1, 2, 5, 10, 20, 30, 40, 50, 100,
or 250 different organisms of that species. A skilled artisan will
understand that appropriate controls can be determined based upon
the average frequency of SNP alleles that exist within the same
ethnic group of the species to which the patient belongs. In
certain embodiments, the informative SNPs used in the methods of
the invention to determine and/or predict the phenotype of a cancer
comprise at least one SNP on each chromosome of a subject (e.g., a
telomeric region of each chromosome). In a related embodiment, the
informative SNPs used in the methods of the invention to determine
and/or predict the phenotype of a cancer comprise at least one SNP
on each arm of each chromosome of a subject (e.g., a telomeric
region of each arm of each chromosome).
[0141] In certain embodiments, the invention provides methods for
determining the phenotype of a cancer wherein the phenotype is
response to therapy. The therapy may be any anti-cancer therapy
including, but not limited to, chemotherapy, radiation therapy,
immunotherapy, small molecule inhibitors, shRNA, hormonal, and
combinations thereof. Where GCAS represents copy deletions, copy
gains, whole chromosome losses, whole chromosome gains and/or loss
of heterozygosity, subjects whose cancerous tissue exhibit a GCAS
below a threshold value are predicted to have a poorer response to
therapy (e.g., radiation or chemotherapy) than those with high GCAS
(above the threshold value). Where GCAS represents lack of copy or
chromosome number changes and/or retention of heterozygosity,
subjects whose cancerous tissue exhibits a GCAS above a threshold
value are predicted to have a poorer response to therapy (e.g.,
radiation or chemotherapy) than those with low GCAS (below the
threshold value).
[0142] By way of explanation, but without being bound by theory, it
is believed that where the GCAS value represents loss of
heterozygosity or allelic imbalance, it identifies cells harboring
improperly repaired chromosomal DNA double-strand breaks and the
genome-wide count of these chromosomal rearrangements in a specific
tumor indicates the degree of DNA repair incompetence, independent
of the specific causative DNA repair defect. In such subjects, the
total number of chromosomal rearrangements in a tumor indicates the
inability to repair DNA damage induced by anti-cancer therapies,
and consequently predicts sensitivity to such anti-cancer
therapies. Also by way of explanation and without being bound by
theory, it is believed that GCAS representing copy gains may
indicate genetic defects other than or in addition to DNA repair
defects and that GCAS representing whole chromosome loss or gain
may indicate mitotic checkpoint defects or chromosome segregation
defects, and the like. Such aberrations in faithful DNA repair,
segregation, check point control, etc. has been determined to be
predictive of the cells harboring such aberrations to treatment
with anti-cancer therapies (e.g., chemotherapeutics) in
subjects.
[0143] The response to anti-cancer therapies relates to any
response of the tumour to chemotherapy, preferably to a change in
tumour mass and/or volume after initiation of neoadjuvant or
adjuvant chemotherapy. Tumor response may be assessed in a
neoadjuvant or adjuvant situation where the size of a tumour after
systemic intervention can be compared to the initial size and
dimensions as measured by CT, PET, mammogram, ultrasound or
palpation and the cellularity of a tumor can be estimated
histologically and compared to the cellularity of a tumor biopsy
taken before initiation of treatment. Response may also be assessed
by caliper measurement or pathological examination of the tumour
after biopsy or surgical resection. Response may be recorded in a
quantitative fashion like percentage change in tumour volume or
cellularity or using a semi-quantitative scoring system such as
residual cancer burden (Symmans et al., J. Clin. Oncol. (2007)
25:4414-5 4422) or Miller-Payne score (Ogston et al., Breast
(Edinburgh, Scotland) (2003) 12:320-327) in a qualitative fashion
like "pathological complete response" (pCR), "clinical complete
remission" (cCR), "clinical partial remission" (cPR), "clinical
stable disease" (cSD), "clinical progressive disease" (cPD) or
other qualitative criteria. Assessment of tumor response may be
performed early after the onset of neoadjuvant or adjuvant therapy,
e.g., after a few hours, days, weeks or preferably after a few
months. A typical endpoint for response assessment is upon
termination of neoadjuvant chemotherapy or upon surgical removal of
residual tumor cells and/or the tumor bed.
[0144] Additional criteria for evaluating the response to
anti-cancer therapies are related to "survival," which includes all
of the following: survival until mortality, also known as overall
survival (wherein said mortality may be either irrespective of
cause or tumor related); "recurrence-free survival" (wherein the
term recurrence shall include both localized and distant
recurrence); metastasis free survival; disease free survival
(wherein the term disease shall include cancer and diseases
associated therewith). The length of said survival may be
calculated by reference to a defined start point (e.g. time of
diagnosis or start of treatment) and end point (e.g. death,
recurrence or metastasis). In addition, criteria for efficacy of
treatment can be expanded to include response to chemotherapy,
probability of survival, probability of metastasis within a given
time period, and probability of tumor recurrence.
[0145] For example, in order to determine appropriate threshold
values, a particular anti-cancer therapeutic regimen can be
administered to a population of subjects and the outcome can be
correlated to GCAS's that were determined prior to administration
of any anti-cancer therapy. The outcome measurement may be
pathologic response to therapy given in the neo-adjuvant setting.
Alternatively, outcome measures, such as overall survival and
disease-free survival can be monitored over a period of time for
subjects following anti-30 cancer therapy for whom GCAS values are
known. In certain embodiments, the same doses of anti-cancer agents
are administered to each subject. In related embodiments, the doses
administered are standard doses known in the art for anti-cancer
agents. The period of time for which subjects are monitored can
vary. For example, subjects may be monitored for at least 2, 4, 6,
8, 10, 12, 14, 16, 18, 20, 25, 30, 35, 40, 45, 50, 55, or 60
months. GCAS threshold values that correlate to outcome of an
anti-cancer therapy can be determined using methods such as those
described in the Example section.
[0146] In some embodiments, the test value representing the
chromosomal aberration score is compared to one or more reference
values (or index values), and optionally correlated to an increased
(or not) likelihood of response to a particular treatment. For
example, the index value may represent the average chromosomal
aberration score for a set of individuals from a diverse cancer
population or a subset of the population. For example, one may
determine the average chromosomal aberration score in a random
sampling of patients with cancer (or a particular cancer). This
average chromosomal aberration score may be termed the "threshold
index value," with patients having a chromosomal aberration score
higher than this value expected to have a higher likelihood of
response than those having a chromosomal aberration score lower
than this value. In some embodiments the test value is correlated
to an increased likelihood of response to a particular treatment if
the test value exceeds the reference value by at least some amount
(e.g., at least 0.5, 0.75, 0.85, 0.90, 0.95, 1, 2, 3, 4, 5, 6, 7,
8, 9, or 10 or more fold or standard deviations)
[0147] Alternatively the index value may represent the average
chromosomal aberration score in a plurality of training patients
with similar outcomes whose clinical and follow-up data are
available and sufficient to define and categorize the patients by
outcome, e.g., response to a particular treatment. See, e.g.,
Examples, infra. For example, a "response index value" can be
generated from a plurality of training cancer patients
characterized as having "response" to the particular treatment. A
"no (or poor) response index value" can be generated from a
plurality of training cancer patients defined as having "no (or
poor) response" to the particular treatment. Thus, a response
prognosis index value may represent the average chromosomal
aberration score in patients having "response," whereas a no (or
poor) response index value represents the average chromosomal
aberration score in patients having no or poor response. Thus, when
the determined chromosomal aberration score is closer to the
response index value than to the no response index value, then it
can be concluded that the patient is more likely to respond. On the
other hand, if the determined 1 chromosomal aberration score is
closer to the no response index value than to the response index
value, then it can be concluded that the patient does not have an
increased likelihood of response.
[0148] Prognosis may include the patient's likelihood of survival
(e.g., progression-free survival, overall survival), wherein a
relatively good prognosis would include an increased likelihood of
survival as compared to some reference population (e.g., average
patient with this patient's cancer type/subtype, average patient
not having an LOH signature, patient not having increased number of
AI or tAI etc.). Conversely, a relatively poor prognosis in terms
of survival would include a decreased likelihood of survival as
compared to some reference population (e.g., average patient with
this patient's cancer type/subtype, average patient having an LOH
signature, patient not having increased number of AI or tAI
etc.).
[0149] Anti-Cancer Therapeutic Agents
[0150] The efficacy of anti-cancer therapies which damage DNA, as
well as agents that take advantage of DNA repair defects but do not
damage DNA themselves, such as poly ADP ribose polymerase (PARP)
inhibitors, as well as chemotherapy or radiation therapy, is
predicted according to the GCAS level of a cancer in a subject
according to the methods described herein. In one embodiment, the
efficacy of chemotherapies is predicted. Chemotherapy includes the
administration of a chemotherapeutic agent. Such a chemotherapeutic
agent may be, but is not limited to, those selected from among the
following groups of compounds: platinum compounds, cytotoxic
antibiotics, antimetabolities, anti-mitotic agents, alkylating
agents, arsenic compounds, DNA topoisomerase inhibitors, taxanes,
nucleoside analogues, plant alkaloids, and toxins; and synthetic
derivatives thereof. Exemplary compounds include, but are not
limited to, alkylating agents: cisplatin, treosulfan, and
trofosfamide; plant alkaloids: vinblastine, paclitaxel, docetaxol;
DNA topoisomerase inhibitors: teniposide, crisnatol, and mitomycin;
anti-folates: methotrexate, mycophenolic acid, and hydroxyurea;
pyrimidine analogs: 5-fluorouracil, doxifluridine, and cytosine
arabinoside; purine analogs: mercaptopurine and thioguanine; DNA
antimetabolites: 2'-deoxy-5-fluorouridine, aphidicolin glycinate,
and pyrazoloimidazole; and antimitotic agents: halichondrin,
colchicine, and rhizoxin. Compositions comprising one or more
chemotherapeutic agents (e.g., FLAG, CHOP) may also be used. FLAG
comprises fludarabine, cytosine arabinoside (Ara-C) and G-CSF. CHOP
comprises cyclophosphamide, vincristine, doxorubicin, and
prednisone. In another embodiments, PARP (e.g., PARP-1 and/or
PARP-2) inhibitors are used and such inhibitors are well known in
the art (e.g., Olaparib, ABT-888, BSI-201, BGP-15 (N-Gene Research
Laboratories, Inc.); INO-1001 (Inotek Pharmaceuticals Inc.); PJ34
(Soriano et al., 2001; Pacher et al., 2002b); 3-aminobenzamide
(Trevigen); 4-amino-1,8-naphthalimide; (Trevigen);
6(5H)-phenanthridinone (Trevigen); benzamide (U.S. Pat. Re.
36,397); and NU1025 (Bowman et al.). The foregoing examples of
chemotherapeutic agents are illustrative, and are not intended to
be limiting.
[0151] In a preferred embodiment, the chemotherapeutic agents are
platinum compounds or platinum-comprising cancer therapies, such as
cisplatin, carboplatin, oxaliplatin, nedaplatin, and iproplatin.
Other antineoplastic platinum coordination compounds are well known
in the art, can be modified according to well-known methods in the
art, and include the compounds disclosed in U.S. Pat. Nos.
4,996,337, 4,946,954, 5,091,521, 5,434,256, 5,527,905, and
5,633,243, all of which are incorporated herein by reference. In
another embodiment, GCAS predicts efficacy of radiation therapy.
The radiation used in radiation therapy can be ionizing radiation.
Radiation therapy can also be gamma rays, X-rays, or proton beams.
Examples of radiation therapy include, but are not limited to,
external-beam radiation therapy, interstitial implantation of
radioisotopes (I-125, palladium, iridium), radioisotopes such as
strontium-89, thoracic radiation therapy, intraperitoneal P-32
radiation therapy, and/or total abdominal and pelvic radiation
therapy. For a general overview of radiation therapy, see Hellman,
Chapter 16: Principles of Cancer Management: Radiation Therapy, 6th
edition, 2001, DeVita et al., eds., J. B. Lippencott Company,
Philadelphia. The radiation therapy can be administered as external
beam radiation or teletherapy wherein the radiation is directed
from a remote source. The radiation treatment can also be
administered as internal therapy or brachytherapy wherein a
radioactive source is placed inside the body close to cancer cells
or a tumor mass. Also encompassed is the use of photodynamic
therapy comprising the administration of photosensitizers, such as
hematoporphyrin and its derivatives, Vertoporfin (BPD-MA),
phthalocyanine, photosensitizer Pc4, demethoxy-hypocrellin A; and
2BA-2-DMHA.
[0152] Anti-cancer therapies which damage DNA to a lesser extent
than chemotherapy or radiation therapy may have efficacy in
subjects determined to have relatively lower or higher GCAS
determinations using the methods of the invention for determining
the phenotype of a cancer. Examples of such therapies include
immunotherapy, hormone therapy, and gene therapy. Such therapies
include, but are not limited to, the use of antisense
polynucleotides, ribozymes, RNA interference molecules, triple
helix polynucleotides and the like, where the nucleotide sequence
of such compounds are related to the nucleotide sequences of DNA
and/or RNA of genes that are linked to the initiation, progression,
and/or pathology of a tumor or cancer. For example, oncogenes,
growth factor genes, growth factor receptor genes, cell cycle
genes, DNA repair genes, and others, may be used in such
therapies.
[0153] Immunotherapy may comprise, for example, use of cancer
vaccines and/or sensitized antigen presenting cells. The
immunotherapy can involve passive immunity for short-term
protection of a host, achieved by the administration of pre-formed
antibody directed against a cancer antigen or disease antigen
(e.g., administration of a monoclonal antibody, optionally linked
to a chemotherapeutic agent or toxin, to a tumor antigen).
Immunotherapy can also focus on using the cytotoxic
lymphocyte-recognized epitopes of cancer cell lines.
[0154] Hormonal therapeutic treatments can comprise, for example,
hormonal agonists, hormonal antagonists (e.g., flutamide,
bicalutamide, tamoxifen, raloxifene, leuprolide acetate (LUPRON),
LH-RH antagonists), inhibitors of hormone biosynthesis and
processing, and steroids (e.g., dexamethasone, retinoids, deltoids,
betamethasone, cortisol, cortisone, prednisone,
dehydrotestosterone, glucocorticoids, mineralocorticoids, estrogen,
testosterone, progestins), vitamin A derivatives (e.g., all-trans
retinoic acid (ATRA)); vitamin D3 analogs; antigestagens (e.g.,
mifepristone, onapristone), or antiandrogens (e.g., cyproterone
acetate).
[0155] In one embodiment, anti-cancer therapy used for cancers
whose phenotype is determined by the methods of the invention can
comprise one or more types of therapies described herein including,
but not limited to, chemotherapeutic agents, immunotherapeutics,
anti-angiogenic agents, cytokines, hormones, antibodies,
polynucleotides, radiation and photodynamic therapeutic agents. For
example, combination therapies can comprise one or more
chemotherapeutic agents and radiation, one or more chemotherapeutic
agents and immunotherapy, or one or more chemotherapeutic agents,
radiation and chemotherapy.
[0156] The duration and/or dose of treatment with anti-cancer
therapies may vary according to the particular anti-cancer agent or
combination thereof. An appropriate treatment time for a particular
cancer therapeutic agent will be appreciated by the skilled
artisan. The invention contemplates the continued assessment of
optimal treatment schedules for each cancer therapeutic agent,
where the phenotype of the cancer of the subject as determined by
the methods of the invention is a factor in determining optimal
treatment doses and schedules.
[0157] Cancers for which Phenotype Can Be Determined
[0158] The methods of the invention can be used to determine the
phenotype of many different cancers. Specific examples of types of
cancers for which the phenotype can be determined by the methods
encompassed by the invention include, but are not limited to, human
sarcomas and carcinomas, e.g., fibrosarcoma, myxosarcoma,
liposarcoma, chondrosarcoma, osteogenic sarcoma, chordoma,
angiosarcoma, endotheliosarcoma, lymphangiosarcoma,
lymphangioendotheliosarcoma, synovioma, mesothelioma, Ewing's
tumor, leiomyosarcoma, rhabdomyosarcoma, colon carcinoma,
colorectal cancer, 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, liver cancer,
choriocarcinoma, seminoma, embryonal carcinoma, Wilms' tumor,
cervical cancer, bone cancer, brain tumor, testicular cancer, lung
carcinoma, small cell lung carcinoma, bladder carcinoma, epithelial
carcinoma, glioma, astrocytoma, medulloblastoma, craniopharyngioma,
ependymoma, pinealoma, hemangioblastoma, acoustic neuroma,
oligodendroglioma, meningioma, melanoma, neuroblastoma,
retinoblastoma; leukemias, e.g., acute lymphocytic leukemia and
acute myelocytic leukemia (myeloblastic, promyelocytic,
myelomonocytic, monocytic and erythroleukemia); chronic leukemia
(chronic myelocytic (granulocytic) leukemia and chronic lymphocytic
leukemia); and polycythemia vera, lymphoma (Hodgkin's disease and
non-Hodgkin's disease), multiple myeloma, Waldenstrom's
macroglobulinemia, and heavy chain disease.
[0159] In some embodiments, the cancer cells are primary or
metastatic cancer cells of ovarian cancer, breast cancer, lung
cancer or esophageal cancer.
[0160] In some embodiments, the cancer whose phenotype is
determined by the method of the invention is an epithelial cancer
such as, but not limited to, bladder cancer, breast cancer,
cervical cancer, colon cancer, gynecologic cancers, renal cancer,
laryngeal cancer, lung cancer, oral cancer, head and neck cancer,
ovarian cancer, pancreatic cancer, prostate cancer, or skin cancer.
In other embodiments, the cancer is breast cancer, prostate cancer,
lung cancer, or colon cancer. In still other embodiments, the
epithelial cancer is non-small-cell lung cancer, nonpapillary renal
cell carcinoma, cervical carcinoma, ovarian carcinoma (e.g., serous
ovarian carcinoma), or breast carcinoma. The epithelial cancers may
be characterized in various other ways including, but not limited
to, serous, endometrioid, mucinous, clear cell, brenner, or
undifferentiated.
[0161] Subjects
[0162] In one embodiment, the subject for whom predicted efficacy
of an anti-cancer therapy is determined, is a mammal (e.g., mouse,
rat, primate, non-human mammal, domestic animal such as dog, cat,
cow, horse), and is preferably a human. In another embodiment of
the methods of the invention, the subject has not undergone
chemotherapy or radiation therapy. In alternative embodiments, the
subject has undergone chemotherapy or radiation therapy (e.g., such
as with cisplatin, carboplatin, and/or taxane). In related
embodiments, the subject has not been exposed to levels of
radiation or chemotoxic agents above those encountered generally or
on average by the subjects of a species. In certain embodiments,
the subject has had surgery to remove cancerous or precancerous
tissue. In other embodiments, the cancerous tissue has not been
removed, e.g., the cancerous tissue may be located in an inoperable
region of the body, such as in a tissue that is essential for life,
or in a region where a surgical procedure would cause considerable
risk of harm to the patient.
[0163] In some embodiments, the patients are treatment naive
patients.
[0164] According to one aspect of the invention, GCAS can be used
to determine the phenotype, i.e. responsivenes to therapy of a
cancer in a subject, where the subject has previously undergone
chemotherapy, radiation therapy, or has been exposed to radiation,
or a chemotoxic agent. Such therapy or exposure could potentially
damage DNA and alter the numbers of informative heterozygous SNPs
in a subject. The altered number of informative heterozygous SNPs
would in turn alter the GCAS of a subject. Because the
non-cancerous DNA samples would exhibit greater or fewer
heterozygous SNPs, the range of GCASs would be altered for a
population of subjects. In certain embodiments, DNA damage from
therapy or exposure in a subject or population of subjects occurs
about 1 month, 2 months, 3 months, 4 months, 5 months, 6 months, 7
months, 8 months, 9 months, 10 months, 11 months, 1 year, 1.5
years, 2 years or more before determination of GCAS. To determine
GCAS threshold values for subjects that exhibit DNA damage from
therapy or exposure, a population of subjects is monitored who have
had chemotherapy or radiation therapy, preferably via identical or
similar treatment regimens, including dose and frequency, for said
subjects.
[0165] Nucleic Acid Sample Preparation
[0166] Nucleic Acid Isolation
[0167] Nucleic acid samples derived from cancerous and
non-cancerous cells of a subject that can be used in the methods of
the invention to determine the phenotype of a cancer can be
prepared by means well known in the art. For example, surgical
procedures or needle biopsy aspiration can be used to collect
cancerous samples from a subject. In some embodiments, it is
important to enrich and/or purify the cancerous tissue and/or cell
samples from the non-cancerous tissue and/or cell samples. In other
embodiments, the cancerous tissue and/or cell samples can then be
microdissected to reduce amount of normal tissue contamination
prior to extraction of genomic nucleic acid or pre-RNA for use in
the methods of the invention. In still another embodiment, the
cancerous tissue and/or cell samples are enriched for cancer cells
by at least 50%, 55%, 60%, 65%, 70%, 75%, 76%, 77%, 78%, 79%, 80%,
81%, 82%, 83%, 84%, 85%, 86%, 87%, 88%, 89%, 90%, 91%, 92%, 93%,
94%, 95%, 96%, 97%, 98%, 99%, or more or any range in between, in
cancer cell content. Such enrichment can be accomplished according
to methods well-15 known in the art, such as needle
microdissection, laser microdissection, fluorescence activated cell
sorting, and immunological cell sorting. In one embodiment, an
automated machine performs the hyperproliferative cell enrichment
to thereby transform the biological sample into a purified form
enriched for the presence of hyperproliferative cells.
[0168] Collecting nucleic acid samples from non-cancerous cells of
a subject can also be accomplished with surgery or aspiration. In
surgical procedures where cancerous tissue is removed, surgeons
often remove non-cancerous tissue and/or cell samples of the same
tissue type of the cancer patient for comparison. Nucleic acid
samples can be isolated from such non-cancerous tissue of the
subject for use in the methods of the invention. In certain
embodiments of the methods of the invention, nucleic acid samples
from non-cancerous tissues are not derived from the same tissue
type as the cancerous tissue and/or cells sampled, and/or are not
derived from the cancer patient. The nucleic acid samples from
non-cancerous tissues may be derived from any non-cancerous and/or
disease-free tissue and/or cells. Such non-cancerous samples can be
collected by surgical or non-surgical procedures. In certain
embodiments, non-cancerous nucleic acid samples are derived from
tumor-free tissues. For example, non-cancerous samples may be
collected from lymph nodes, peripheral blood lymphocytes, and/or
mononuclear blood cells, or any subpopulation thereof. In a
preferred embodiment, the non-cancerous tissue is not pre-cancerous
tissue, e.g., it does not exhibit any indicia of a pre-neoplastic
condition such as hyperplasia, metaplasia, or dysplasia.
[0169] In one embodiment, the nucleic acid samples used to compute
GCAS (e.g., the number of heterozygous SNPs in the plurality of
total SNPs that exhibit heterozygosity in genomic DNA of
non-cancerous tissue of the species to which the cancer patient
belongs) are taken from at least 1, 2, 5, 10, 20, 30, 40, 50, 100,
or 200 different organisms of that species. According to certain
aspects of the invention, nucleic acid "derived from" genomic DNA,
as used in the methods of the invention, e.g., in hybridization
experiments to determine heterozygosity of SNPs, can be fragments
of genomic nucleic acid generated by restriction enzyme digestion
and/or ligation to other nucleic acid, and/or amplification
products of genomic nucleic acids, or pre-messenger RNA (pre-mRNA),
amplification products of pre-mRNA, or genomic DNA fragments grown
up in cloning vectors generated, e.g., by "shotgun" cloning
methods. In certain embodiments, genomic nucleic acid samples are
digested with restriction enzymes.
[0170] Amplification of Nucleic Acids
[0171] Though the nucleic acid sample need not comprise amplified
nucleic acid, in some embodiments, the isolated nucleic acids can
be processed in manners requiring and/or taking advantage of
amplification. The genomic DNA samples of a subject optionally can
be fragmented using restriction endonucleases and/or amplified
prior to determining GCAS. In one embodiment, the DNA fragments are
amplified using polymerase chain reaction (PCR). Methods for
practicing PCR are well known to those of skill in the art. One
advantage of PCR is that small quantities of DNA can be used. For
example, genomic DNA from a subject may be about 150 ng, 175, ng,
200 ng, 225 ng, 250 ng, 275 ng, or 300 ng of DNA.
[0172] In certain embodiments of the methods of the invention, the
nucleic acid from a subject is amplified using a single primer
pair. For example, genomic DNA samples can be digested with
restriction endonucleases to generate fragments of genomic DNA that
are then ligated to an adaptor DNA sequence which the primer pair
recognizes. In other embodiments of the methods of the invention,
the nucleic acid of a subject is amplified using sets of primer
pairs specific to loci of interest (e.g., RFLPs, STRs, SNPs, etc.)
located throughout the genome. Such sets of primer pairs each
recognize genomic DNA sequences flanking particular loci of
interest (e.g., SNPs, RFLPs, STRs, etc.). A DNA sample suitable for
hybridization can be obtained, e.g., by polymerase chain reaction
(PCR) amplification of genomic DNA, fragments of genomic DNA,
fragments of genomic DNA ligated to adaptor sequences or cloned
sequences. Computer programs that are well known in the art can be
used in the design of primers with the desired specificity and
optimal amplification properties, such as Oligo version 5.0
(National Biosciences). PCR methods are well known in the art, and
are described, for example, in Innis et al., eds., 1990, PCR
Protocols: A Guide to Methods And Applications, Academic Press
Inc., San Diego, Calif. It will be apparent to one skilled in the
art that controlled robotic systems are useful for isolating and
amplifying nucleic acids and can be used.
[0173] In other embodiments, where genomic DNA of a subject is
fragmented using restriction endonucleases and amplified prior to
determining GCAS, the amplification can comprise cloning regions of
genomic DNA of the subject. In such methods, amplification of the
DNA regions is achieved through the cloning process. For example,
expression vectors can be engineered to express large quantities of
particular fragments of genomic DNA of the subject (Sambrook, J. et
al., eds., 1989, Molecular Cloning: A Laboratory Manual, 2nd Ed.,
Cold Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., at
pp. 9.47-9.51).
[0174] In yet other embodiments, where the DNA of a subject is
fragmented using restriction endonucleases and amplified prior to
determining GCAS, the amplification comprises expressing a nucleic
acid encoding a gene, or a gene and flanking genomic regions of
nucleic acids, from the subject. RNA (pre-messenger RNA) that
comprises the entire transcript including introns is then isolated
and used in the methods of the invention to determine GCAS and the
phenotype of a cancer. In certain embodiments, no amplification is
required. In such embodiments, the genomic DNA, or pre-RNA, of a
subject may be fragmented using restriction endonucleases or other
methods. The resulting fragments may be hybridized to SNP probes.
Typically, greater quantities of DNA are needed to be isolated in
comparison to the quantity of DNA or pre-mRNA needed where
fragments are amplified. For example, where the nucleic acid of a
subject is not amplified, a DNA sample of a subject for use in
hybridization may be about 400 ng, 500 ng, 600 ng, 700 ng, 800 ng,
900 ng, or 1000 ng of DNA or greater. Alternatively, in other
embodiments, methods are used that require very small amounts of
nucleic acids for analysis, such as less than 400 ng, 300 ng, 200
ng, 100 ng, 90 ng, 85 ng, 80 ng, 75 ng, 70 ng, 65 ng, 60 ng, 55 ng,
50 ng, or less, such as is used for molecular inversion probe (MIP)
assays. These techniques are particularly useful for analyzing
clinical samples, such as paraffin embedded formalin-fixed material
or small core needle biopsies, characterized as being readily
available but generally having reduced DNA quality (e.g., small,
fragmented DNA) and/or not providing large amounts of nucleic
acids.
[0175] Hybridization
[0176] The nucleic acid samples derived from a subject used in the
methods of the invention can be hybridized to arrays comprising
probes (e.g., oligonucleotide probes) in order to identify
informative loci of interest (e.g., SNPs, RFLPs, STRs, etc.).
Hybridization can also be used to determine whether the informative
loci of interest (e.g., SNPs, RFLPs, STRs, etc.) identified exhibit
chromosomal aberrations (e.g., allelic imbalance, loss of
heterozygosity, total copy number change, copy number gain, and
copy number loss) in nucleic acid samples from cancerous tissues
and/or cells of the subject. In preferred embodiments, the probes
used in the methods of the invention comprise an array of probes
that can be tiled on a DNA chip (e.g., SNP oligonucleotide probes).
In some embodiments, heterozygosity of a SNP locus is determined by
a method that does not comprise detecting a change in size of
restriction enzyme-digested nucleic acid fragments. In other
embodiments, SNPs are analyzed to identify allelic imbalance.
Hybridization and wash conditions used in the methods of the
invention are chosen so that the nucleic acid samples to be
analyzed by the invention specifically bind or specifically
hybridize to the complementary oligonucleotide sequences of the
array, preferably to a specific array site, wherein its
complementary DNA is located. In some embodiments, the
complementary DNA can be completely matched or mismatched to some
degree as used, for example, in Affymetrix oligonucleotide arrays
such as those used to analyze SNPs in MIP assays. The
single-stranded synthetic oligodeoxyribonucleic acid DNA probes of
an array may need to be denatured prior to contact with the nucleic
acid samples from a subject, e.g., to remove hairpins or dimers
which form due to self-complementary sequences.
[0177] Optimal hybridization conditions will depend on the length
of the probes and type of nucleic acid samples from a subject.
General parameters for specific (i.e., stringent) hybridization
conditions for nucleic acids are described in Sambrook, J. et al.,
eds., 1989, Molecular Cloning: A Laboratory Manual, 2nd Ed., Cold
Spring Harbor Laboratory Press, Cold Spring Harbor, N.Y., at pp.
9.47-9.51 and 11.55-11.61; Ausubel et al., eds., 1989, Current
Protocols in Molecules Biology, Vol. 1, Green Publishing
Associates, Inc., John Wiley & Sons, Inc., New York, at pp.
2.10.1-2.10.16. Exemplary useful hybridization conditions are
provided in, e.g., Tijessen, 1993, Hybridization With Nucleic Acid
Probes, Elsevier Science Publishers B. V. and Kricka, 1992,
Nonisotopic DNA Probe Techniques, Academic Press, San Diego,
Calif.
[0178] Oligonucleotide Nucleic Acid Arrays
[0179] In some embodiments of the methods of the present invention,
DNA arrays can be used to determine whether nucleic acid samples
exhibit chromosomal aberrations (e.g., allelic imbalance, loss of
heterozygosity, total copy number change, copy number gain, and
copy number loss) by measuring the level of hybridization of the
nucleic acid sequence to oligonucleotide probes that comprise
complementary sequences. Hybridization can be used to determine the
presence or absence of heterozygosity. Various formats of DNA
arrays that employ oligonucleotide "probes," (i.e., nucleic acid
molecules having defined sequences) are well known to those of
skill in the art. Typically, a set of nucleic acid probes, each of
which has a defined sequence, is immobilized on a solid support in
such a manner that each different probe is immobilized to a
predetermined region. In certain embodiments, the set of probes
forms an array of positionally-addressable binding (e.g.,
hybridization) sites on a support. Each of such binding sites
comprises a plurality of oligonucleotide molecules of a probe bound
to the predetermined region on the support. More specifically, each
probe of the array is preferably located at a known, predetermined
position on the solid support such that the identity (i.e., the
sequence) of each probe can be determined from its position on the
array (i.e., on the support or surface). Microarrays can be made in
a number of ways, of which several are described herein. However
produced, microarrays share certain characteristics, they are
reproducible, allowing multiple copies of a given array to be
produced and easily compared with each other.
[0180] Numerous variations on nucleic acid arrays useful in the
invention are known in the art. These include Affymetrix 500K
GeneChip array; Affymetrix OncoScan.TM. FFPE Express 2.0 Services
(Formerly MIP CN Services), and the like.
[0181] Preferably, the microarrays are made from materials that are
stable under binding (e.g., nucleic acid hybridization) conditions.
The microarrays are preferably small, e.g., between about 1 cm2 and
25 cm2, preferably about 1 to 3 cm2. However, both larger and
smaller arrays are also contemplated and may be preferable, e.g.,
for simultaneously evaluating a very large number of different
probes. Oligonucleotide probes can be synthesized directly on a
support to form the array. The probes can be attached to a solid
support or surface, which may be made, e.g., from glass, plastic
(e.g., polypropylene, nylon), polyacrylamide, nitrocellulose, gel,
or other porous or nonporous material. The set of immobilized
probes or the array of immobilized probes is contacted with a
sample containing labeled nucleic acid species so that nucleic
acids having sequences complementary to an immobilized probe
hybridize or bind to the probe. After separation of, e.g., by
washing off, any unbound material, the bound, labeled sequences are
detected and measured. The measurement is typically conducted with
computer assistance. Using DNA array assays, complex mixtures of
labeled nucleic acids, e.g., nucleic acid fragments derived a
restriction digestion of genomic DNA from non-cancerous tissue, can
be analyzed. DNA array technologies have made it possible to
determine heterozygosity of a large number of informative loci of
interest (e.g., SNPs, RFLPs, STRs, etc.) throughout the genome.
[0182] In certain embodiments, high-density oligonucleotide arrays
are used in the methods of the invention. These arrays containing
thousands of oligonucleotides complementary to defined sequences,
at defined locations on a surface can be synthesized in situ on the
surface by, for example, photolithographic techniques (see, e.g.,
Fodor et al., 1991, Science 251:767-773; Pease et al., 1994, Proc.
Natl. Acad. Sci. U.S.A. 91:5022-5026; Lockhart et al., 1996, Nature
Biotechnology 14:1675; U.S. Pat. Nos. 5,578,832; 5,556,752;
5,510,270; 5,445,934; 5,744,305; and 6,040,138). Methods for
generating arrays using inkjet technology for in situ
oligonucleotide synthesis are also known in the art (see, e.g.,
Blanchard, International Patent Publication WO 98/41531, published
Sep. 24, 1998; Blanchard et al., 1996, Biosensors And
Bioelectronics 11:687-690; Blanchard, 1998, in Synthetic DNA Arrays
in Genetic Engineering, Vol. 20, J. K. Setlow, Ed., Plenum Press,
New York at pages 111-123). Another method for attaching the
nucleic acids to a surface is by printing on glass plates, as is
described generally by Schena et al. (1995, Science 270:467-470).
Other methods for making microarrays, e.g., by masking (Maskos and
Southern, 1992, Nucl. Acids. Res. 20:1679-1684), may also be used.
When these methods are used, oligonucleotides (e.g., 15 to 60-mers)
of known sequence are synthesized directly on a surface such as a
derivatized glass slide. The array produced can be redundant, with
several oligonucleotide molecules corresponding to each informative
locus of interest (e.g., SNPs, RFLPs, STRs, etc.).
[0183] One exemplary means for generating the oligonucleotide
probes of the DNA array is by synthesis of synthetic
polynucleotides or oligonucleotides, e.g., using N-phosphonate or
phosphoramidite chemistries (Froehler et al., 1986, Nucleic Acid
Res. 14:5399-5407; McBride et al., 1983, Tetrahedron Lett.
24:246-248). Synthetic sequences are typically between about 15 and
about 600 bases in length, more typically between about 20 and
about 100 bases, most preferably between about 40 and about 70
bases in length. In some embodiments, synthetic nucleic acids
include non-natural bases, such as, but by no means limited to,
inosine. As noted above, nucleic acid analogues may be used as
binding sites for hybridization. An example of a suitable nucleic
acid analogue is peptide nucleic acid (see, e.g., Egholm et al.,
1993, Nature 363:566-568; U.S. Pat. No. 5,539,083). In alternative
embodiments, the hybridization sites (i.e., the probes) are made
from plasmid or phage clones of regions of genomic DNA
corresponding to SNPs or the complement thereof. The size of the
oligonucleotide probes used in the methods of the invention can be
at least 10, 20, 25, 30, 35, 40, 45, or 50 nucleotides in length.
It is well known in the art that although hybridization is
selective for complementary sequences, other sequences which are
not perfectly complementary may also hybridize to a given probe at
some level. Thus, multiple oligonucleotide probes with slight
variations can be used, to optimize hybridization of samples. To
further optimize hybridization, hybridization stringency condition,
e.g., the hybridization temperature and the salt concentrations,
may be altered by methods that are well known in the art.
[0184] In some embodiments, the high-density oligonucleotide arrays
used in the methods of the invention comprise oligonucleotides
corresponding to informative loci of interest (e.g., SNPs, RFLPs,
STRs, etc.). The oligonucleotide probes may comprise DNA or DNA
"mimics" (e.g., derivatives and analogues) corresponding to a
portion of each informative locus of interest (e.g., SNPs, RFLPs,
STRs, etc.) in a subject's genome. The oligonucleotide probes can
be modified at the base moiety, at the sugar moiety, or at the
phosphate backbone. Exemplary DNA mimics include, e.g.,
phosphorothioates. For each SNP locus, a plurality of different
oligonucleotides may be used that are complementary to the
sequences of sample nucleic acids. For example, for a single
informative locus of interest (e.g., SNPs, RFLPs, STRs, etc.) about
2, 3, 4, 5, 6, 7, 8,9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20,
21, 22, 23, 24, 25, 26, 27, 28, 29, 30, 31, 32, 33, 34, 35, 36, 37,
38, 39, 40, 41, 42, 43, 44, 45, 46, 47, 48, 49, 50, or more
different oligonucleotides can be used. Each of the
oligonucleotides for a particular informative locus of interest may
have a slight variation in perfect matches, mismatches, and
flanking sequence around the SNP. In certain embodiments, the
probes are generated such that the probes for a particular
informative locus of interest comprise overlapping and/or
successive overlapping sequences which span or are tiled across a
genomic region containing the target site, where all the probes
contain the target site. By way of example, overlapping probe
sequences can be tiled at steps of a predetermined base intervals,
e. g. at steps of 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 bases intervals.
In certain embodiments, the assays can be performed using arrays
suitable for use with molecular inversion probe protocols such as
described by Wang et al. (2007) Genome Biol. 8, R246. For
oligonucleotide probes targeted at nucleic acid species of closely
resembled (i.e., homologous) sequences, "cross-hybridization" among
similar probes can significantly contaminate and confuse the
results of hybridization measurements. Cross-hybridization is a
particularly significant concern in the detection of SNPs since the
sequence to be detected (i.e., the particular SNP) must be
distinguished from other sequences that differ by only a single
nucleotide. Cross-hybridization can be minimized by regulating
either the hybridization stringency condition and/or during
post-hybridization washings. Highly stringent conditions allow
detection of allelic variants of a nucleotide sequence, e.g., about
1 mismatch per 10-30 nucleotides. There is no single hybridization
or washing condition which is optimal for all different nucleic
acid sequences. For particular arrays of informative loci of
interest, these conditions can be identical to those suggested by
the manufacturer or can be adjusted by one of skill in the art. In
preferred embodiments, the probes used in the methods of the
invention are immobilized (i.e., tiled) on a glass slide called a
chip. For example, a DNA microarray can comprises a chip on which
oligonucleotides (purified single-stranded DNA sequences in
solution) have been robotically printed in an (approximately)
rectangular array with each spot on the array corresponds to a
single DNA sample which encodes an oligonucleotide. In summary the
process comprises, flooding the DNA microarray chip with a labeled
sample under conditions suitable for hybridization to occur between
the slide sequences and the labeled sample, then the array is
washed and dried, and the array is scanned with a laser microscope
to detect hybridization. In certain embodiments there are at least
250, 500, 1,000, 2,000, 3,000, 4,000, 5,000, 6,000, 7,000, 8,000,
9,000, 10,000, 11,000, 12,000, 13,000, 14,000, 15,000, 16,000,
17,000, 18,000, 19,000, 20,000, 21,000, 22,000, 23,000, 24,000,
25,000, 26,000, 27,000, 28,000, 29,000, 30,000, 31,000, 32,000,
33,000, 34,000, 35,000, 36,000, 37,000, 38,000, 39,000, 40,000,
41,000, 42,000, 43,000, 44,000, 45,000, 50,000, 60,000, 70,000,
80,000, 90,000, 100,000 or more or any range in between, of
informative loci of interest for which probes appear on the array
(with match/mismatch probes for a single locus of interest or
probes tiled across a single locus of interest counting as one
locus of interest). The maximum number of informative loci of
interest being probed per array is determined by the size of the
genome and genetic diversity of the subjects species. DNA chips are
well known in the art and can be purchased in pre-5 fabricated form
with sequences specific to particular species. In some embodiments,
the Genome-Wide Human SNP Array 6.0.TM. and/or the 50K XbaI arrays
(Affymetrix, Santa Clara, Calif.) are used in the methods of the
invention. In other embodiments, SNPs and/or DNA copy number can be
detected and quantitated using sequencing methods, such as
"next-generation sequencing methods" as described further
above.
[0185] Signal Detection
[0186] In some embodiments, nucleic acid samples derived from a
subject are hybridized to the binding sites of an array described
herein. In certain embodiments, nucleic acid samples derived from
each of the two sample types of a subject (i.e., cancerous and
non-cancerous) are hybridized to separate, though identical,
arrays. In certain embodiments, nucleic acid samples derived from
one of the two sample types of a subject (i.e., cancerous and
non-cancerous) is hybridized to such an array, then following
signal detection the chip is washed to remove the first labeled
sample and reused to hybridize the remaining sample. In other
embodiments, the array is not reused more than once. In certain
embodiments, the nucleic acid samples derived from each of the two
sample types of a subject (i.e., cancerous and non-cancerous) are
differently labeled so that they can be distinguished. When the two
samples are mixed and hybridized to the same array, the relative
intensity of signal from each sample is determined for each site on
the array, and any relative difference in abundance of an allele of
informative loci of interest detected. Signals can be recorded and,
in some embodiments, analyzed by computer. In one embodiment, the
scanned image is despeckled using a graphics program (e.g., Hijaak
Graphics Suite) and then analyzed using an image gridding program
that creates a spreadsheet of the average hybridization at each
wavelength at each site. If necessary, an experimentally determined
correction for "cross talk" (or overlap) between the channels for
the two fluors may be made. For any particular hybridization site
on the array, a ratio of the emission of the two fluorophores can
be calculated, which may help in eliminating cross hybridization
signals to more accurately determining whether a particular SNP
locus is heterozygous or homozygous.
[0187] Labeling
[0188] In some embodiments, the nucleic acids samples, fragments
thereof, or fragments thereof ligated to adaptor regions used in
the methods of the invention are detectably labeled. For example,
the detectable label can be a fluorescent label, e.g., by
incorporation of nucleotide analogues. Other labels suitable for
use in the present invention include, but are not limited to,
biotin, iminobiotin, antigens, cofactors, dinitrophenol, lipoic
acid, olefinic compounds, detectable polypeptides, electron rich
molecules, enzymes capable of generating a detectable signal by
action upon a substrate, and radioactive isotopes.
[0189] Radioactive isotopes include that can be used in conjunction
with the methods of the invention, but are not limited to, 32P and
14C. Fluorescent molecules suitable for the present invention
include, but are not limited to, fluorescein and its derivatives,
rhodamine and its derivatives, texas red, 5'carboxy-fluorescein
("FAM"), 2',7'-dimethoxy-4',5'-dichloro-6-carboxy-fluorescein
("JOE"), N,N,N',N'-tetramethyl-6-carboxy-rhodamine ("TAMRA"),
6-carboxy-X-rhodamine ("ROX"), HEX, TET, IRD40, and IRD41.
[0190] Fluorescent molecules which are suitable for use according
to the invention further include: cyamine dyes, including but not
limited to Cy2, Cy3, Cy3.5, CY5, Cy5.5, Cy7 and FLUORX; BODIPY dyes
including but not limited to BODIPY-FL, BODIPY-TR, BODIPY-TMR,
BODIPY-630/650, and BODIPY-650/670; and ALEXA dyes, including but
not limited to ALEXA-488, ALEXA-532, ALEXA-546, ALEXA-568, and
ALEXA-594; as well as other fluorescent dyes which will be known to
those who are skilled in the art. Electron rich indicator molecules
suitable for the present invention include, but are not limited to,
ferritin, hemocyanin, and colloidal gold.
[0191] Two-color fluorescence labeling and detection schemes may
also be used (Shena et al., 1995, Science 270:467-470). Use of two
or more labels can be useful in detecting variations due to minor
differences in experimental conditions (e.g., hybridization
conditions). In some embodiments of the invention, at least 5, 10,
20, or 100 dyes of different colors can be used for labeling. Such
labeling would also permit analysis of multiple samples
simultaneously which is encompassed by the invention.
[0192] The labeled nucleic acid samples, fragments thereof, or
fragments thereof ligated to adaptor regions that can be used in
the methods of the invention are contacted to a plurality of
oligonucleotide probes under conditions that allow sample nucleic
acids having sequences complementary to the probes to hybridize
thereto. Depending on the type of label used, the hybridization
signals can be detected using methods well known to those of skill
in the art including, but not limited to, X-Ray film, phosphor
imager, or CCD camera. When fluorescently labeled probes are used,
the fluorescence emissions at each site of a transcript array can
be, preferably, detected by scanning confocal laser microscopy. In
one embodiment, a separate scan, using the appropriate excitation
line, is carried out for each of the two fluorophores used.
Alternatively, a laser can be used that allows simultaneous
specimen illumination at wavelengths specific to the two
fluorophores and emissions from the two fluorophores can be
analyzed simultaneously (see Shalon et al. (1996) Genome Res. 6,
639-645). In a preferred embodiment, the arrays are scanned with a
laser fluorescence scanner with a computer controlled X-Y stage and
a microscope objective. Sequential excitation of the two
fluorophores is achieved with a multi-line, mixed gas laser, and
the emitted light is split by wavelength and detected with two
photomultiplier tubes. Such fluorescence laser scanning devices are
described, e.g., in Schena et al. (1996) Genome Res. 6, 639-645.
Alternatively, a fiber-optic bundle can be used such as that
described by Ferguson et al. (1996) Nat. Biotech. 14, 1681-1684.
The resulting signals can then be analyzed to determine the
presence or absence of heterozygosity or homozygosity for
informative loci of interest (e.g., SNPs, RFLPs, STRs, etc.) using
computer software.
[0193] Algorithms for Analyzing Informative Loci of Interest
[0194] Once the hybridization signal has been detected the
resulting data can be analyzed using algorithms. In certain
embodiments, the algorithm for determining heterozygosity at
informative loci of interest (e.g., SNPs, RFLPs, STRs, etc.) is
based on well known methods for calling allelic imbalance (AI),
loss of heterozygosity (LOH), copy number aberrations (CNA), copy
number gain (CNG), and copy number decrease (CND). For example, AI
can be determined using major copy proportion (MCP) wherein AI for
a given SNP is called, when the MCP value is greater than 0.60,
0.61, 0.62, 0.63, 0.64, 0.65, 0.66, 0.67, 0.68, 0.69, 0.70, 0.71,
0.72, 0.73, 0.74, 0.75, 0.76, 0.77, 0.78, 0.79, 0.80. 0.81, 0.82,
0.83, 0.84, 0.85, 0.86, 0.87, 0.88, 0.89, 0.90, 0.91, 0.92, 0.92,
0.93, 0.94, 0.95, 0.96, 0.97, 0.98, or 0.99. Once calling is
determined, enumeration methods can further be applied. For
example, GCAS can be determined, for example, by: 1) the count of
the total number of SNPs affected by AI or copy gain or LOH, 2) the
count of the number of regions affected by AI (e.g., NAI as
described further in the Examples; a single region is defined as a
string of neighboring SNPs all showing AI bounded on at least one
side by SNPs showing no AI/retention of heterozygosity. The region
size is defined by the length of the chromosome represented by the
string of SNPs with AI); 3) the count of the number of chromosomes
with whole chromosome loss, or 4) the count of the number of
chromosomal regions with CNA, CNG, CND, etc. Additional
representative illustrations of such well known algorithms are
provided in the Examples section below.
[0195] Computer Implementation Systems and Methods
[0196] In certain embodiments, the methods of the invention
implement a computer program to calculate a chromosomal aberration
score (e.g., GCAS, telomeric aberration score, telomeric allelic
imbalance score, etc.). For example, a computer program can be used
to perform the algorithms described herein. A computer system can
also store and manipulate data generated by the methods of the
present invention which comprises a plurality of hybridization
signal changes/profiles during approach to equilibrium in different
hybridization measurements and which can be used by a computer
system in implementing the methods of this invention. In certain
embodiments, a computer system receives probe hybridization data;
(ii) stores probe hybridization data; and (iii) compares probe
hybridization data to determine the state of informative loci of
interest in said nucleic acid sample from cancerous or
pre-cancerous tissue. The GCAS is then calculated. In some
embodiments, a computer system (i) compares the determined GCAS to
a threshold value; and (ii) outputs an indication of whether said
GCAS is above or below a threshold value, or a phenotype based on
said indication. In certain embodiments, such computer systems are
also considered part of the present invention.
[0197] Numerous types of computer systems can be used to implement
the analytic methods of this invention according to knowledge
possessed by a skilled artisan in the bioinformatics and/or
computer arts.
[0198] Several software components can be loaded into memory during
operation of such a computer system. The software components can
comprise both software components that are standard in the art and
components that are special to the present invention (e.g., dCHIP
software described in Lin et al. (2004) Bioinformatics 20,
1233-1240; CRLMM software described in Silver et al. (2007) Cell
128, 991-1002; Aroma Affymetrix software described in Richardson et
al. (2006) Cancer Cell 9, 121-132. The methods of the invention can
also be programmed or modeled in mathematical software packages
that allow symbolic entry of equations and high-level specification
of processing, including specific algorithms to be used, thereby
freeing a user of the need to procedurally program individual
equations and algorithms. Such packages include, e.g., Matlab from
Mathworks (Natick, Mass.), Mathematica from Wolfram Research
(Champaign, Ill.) or S-Plus from MathSoft (Seattle, Wash.). In
certain embodiments, the computer comprises a database for storage
of hybridization signal profiles. Such stored profiles can be
accessed and used to calculate GCAS. For example, of the
hybridization signal profile of a sample derived from the
non-cancerous tissue of a subject and/or profiles generated from
population-based distributions of informative loci of interest in
relevant populations of the same species were stored, it could then
be compared to the hybridization signal profile of a sample derived
from the cancerous tissue of the subject.
[0199] In addition to the exemplary program structures and computer
systems described herein, other, alternative program structures and
computer systems will be readily apparent to the skilled artisan.
Such alternative systems, which do not depart from the above
described computer system and programs structures either in spirit
or in scope, are therefore intended to be comprehended within the
accompanying claims.
[0200] Once a laboratory technician or laboratory professional or
group of laboratory technicians or laboratory professionals
determines whether a sample has a chromosomal aberration at a
plurality of assay loci as described above (e.g., step (1) in many
of the methods above), the same or a different laboratory
technician or laboratory professional (or group) can analyze a
plurality of test loci to determine whether they have a chromosomal
aberration (e.g., step (2) in many of the methods above). Next, the
same or a different laboratory technician or laboratory
professional (or group) can combine the chromosomal aberration data
from the test loci to derive a chromosomal aberration score (e.g.,
step (3) in many of the methods above). Optionally, the same or a
different laboratory technician or laboratory professional (or
group) can correlate a high chromosomal aberration score to an
increased likelihood of response to a particular therapy (e.g.,
those mentioned above). For example, one or more laboratory
technicians or laboratory professionals can identify a patient
having cancer cells that were detected to have a high chromosomal
aberration score by associating that high chromosomal aberration
score or the result (or results or a summary of results) of the
performed diagnostic analysis with the corresponding patient's
name, medical record, symbolic/numerical identifier, or a
combination thereof. Such identification can be based solely on
detecting the presence of a high chromosomal aberration score or
can be based at least in part on detecting the presence of a high
chromosomal aberration score. For example, a laboratory technician
or laboratory professional can identify a patient having cancer
cells that were detected to have a high chromosomal aberration
score as having cancer cells with an increased likelihood of
response to a particular therapy based on a combination of a high
chromosomal aberration score and the results of other genetic and
biochemical tests performed at the testing laboratory.
[0201] FIG. 23 shows an exemplary process by which a computing
system can determine a chromosomal aberration score. The process
begins at box 300, where data regarding the genotype (e.g.,
relative or absolute copy number, homozygous, heterozygous) of a
plurality of loci along a chromosome is collected by the computing
system. As described herein, any appropriate assay such as a SNP
array-based assay or sequencing-based assay can be used to assess
loci along a chromosome for genotype. In some cases, a system
including a signal detector and a computer can be used to collect
data (e.g., fluorescent signals or sequencing results) regarding
the genotype of the plurality of loci. At box 310, data regarding
the genotype of a plurality of loci as well as the location or
spatial relationship of each locus is assessed by the computing
system to determine, e.g., the length of any chromosomal aberration
(e.g., allelic imbalance) regions present along a chromosome or the
number of telomeric aberration (e.g., allelic imbalance) regions.
At box 320, data regarding the number of chromosomal aberration
regions detected and optionally the length or the location of each
detected chromosomal aberration region is assessed by the computing
system to determine the number of chromosomal aberration regions
that are telomeric regions. At box 330, the computing system
formats an output providing an indication of the presence or
absence of a high chromosomal aberration score. Once formatted, the
computing system can present the output to a user (e.g., a
laboratory technician, clinician, or medical professional). As
described herein, the presence or absence of a high chromosomal
aberration score can be used to provide an indication about
possible cancer treatment regimens.
[0202] FIG. 24 is a diagram of an example of a computer device 1400
and a mobile computer device 1450, which may be used with the
techniques described herein. Computing device 1400 is intended to
represent various forms of digital computers, such as laptops,
desktops, workstations, personal digital assistants, servers, blade
servers, mainframes, and other appropriate computers. Computing
device 1450 is intended to represent various forms of mobile
devices, such as personal digital assistants, cellular telephones,
smart phones, and other similar computing devices. The components
shown here, their connections and relationships, and their
functions, are meant to be exemplary only, and are not meant to
limit implementations of the inventions described and/or claimed in
this document.
[0203] Computing device 1400 includes a processor 1402, memory
1404, a storage device 1406, a high-speed interface 1408 connecting
to memory 1404 and high-speed expansion ports 1410, and a low speed
interface 1415 connecting to low speed bus 1414 and storage device
1406. Each of the components 1402, 1404, 1406, 1408, 1410, and
1415, are interconnected using various busses, and may be mounted
on a common motherboard or in other manners as appropriate. The
processor 1402 can process instructions for execution within the
computing device 1400, including instructions stored in the memory
1404 or on the storage device 1406 to display graphical information
for a GUI on an external input/output device, such as display 1416
coupled to high speed interface 1408. In other implementations,
multiple processors and/or multiple buses may be used, as
appropriate, along with multiple memories and types of memory.
Also, multiple computing devices 1400 may be connected, with each
device providing portions of the necessary operations (e.g., as a
server bank, a group of blade servers, or a multi-processor
system).
[0204] The memory 1404 stores information within the computing
device 1400. In one implementation, the memory 1404 is a volatile
memory unit or units. In another implementation, the memory 1404 is
a non-volatile memory unit or units. The memory 1404 may also be
another form of computer-readable medium, such as a magnetic or
optical disk.
[0205] The storage device 1406 is capable of providing mass storage
for the computing device 1400. In one implementation, the storage
device 1406 may be or contain a computer-readable medium, such as a
floppy disk device, a hard disk device, an optical disk device, or
a tape device, a flash memory or other similar solid state memory
device, or an array of devices, including devices in a storage area
network or other configurations. A computer program product can be
tangibly embodied in an information carrier. The computer program
product may also contain instructions that, when executed, perform
one or more methods, such as those described herein. The
information carrier is a computer- or machine-readable medium, such
as the memory 1404, the storage device 1406, memory on processor
1402, or a propagated signal.
[0206] The high speed controller 1408 manages bandwidth-intensive
operations for the computing device 1400, while the low speed
controller 1415 manages lower bandwidth-intensive operations. Such
allocation of functions is exemplary only. In one implementation,
the high-speed controller 1408 is coupled to memory 1404, display
1416 (e.g., through a graphics processor or accelerator), and to
high-speed expansion ports 1410, which may accept various expansion
cards (not shown). In the implementation, low-speed controller 1415
is coupled to storage device 1406 and low-speed expansion port
1414. The low-speed expansion port, which may include various
communication ports (e.g., USB, Bluetooth, Ethernet, or wireless
Ethernet) may be coupled to one or more input/output devices, such
as a keyboard, a pointing device, a scanner, an optical reader, a
fluorescent signal detector, or a networking device such as a
switch or router, e.g., through a network adapter.
[0207] The computing device 1400 may be implemented in a number of
different forms, as shown in the figure. For example, it may be
implemented as a standard server 1420, or multiple times in a group
of such servers. It may also be implemented as part of a rack
server system 1424. In addition, it may be implemented in a
personal computer such as a laptop computer 1422. Alternatively,
components from computing device 1400 may be combined with other
components in a mobile device (not shown), such as device 1450.
Each of such devices may contain one or more of computing device
1400, 1450, and an entire system may be made up of multiple
computing devices 1400, 1450 communicating with each other.
[0208] Computing device 1450 includes a processor 1452, memory
1464, an input/output device such as a display 1454, a
communication interface 1466, and a transceiver 1468, among other
components (e.g., a scanner, an optical reader, a fluorescent
signal detector). The device 1450 may also be provided with a
storage device, such as a microdrive or other device, to provide
additional storage. Each of the components 1450, 1452, 1464, 1454,
1466, and 1468, are interconnected using various buses, and several
of the components may be mounted on a common motherboard or in
other manners as appropriate.
[0209] The processor 1452 can execute instructions within the
computing device 1450, including instructions stored in the memory
1464. The processor may be implemented as a chipset of chips that
include separate and multiple analog and digital processors. The
processor may provide, for example, for coordination of the other
components of the device 1450, such as control of user interfaces,
applications run by device 1450, and wireless communication by
device 1450.
[0210] Processor 1452 may communicate with a user through control
interface 1458 and display interface 1456 coupled to a display
1454. The display 1454 may be, for example, a TFT LCD
(Thin-Film-Transistor Liquid Crystal Display) or an OLED (Organic
Light Emitting Diode) display, or other appropriate display
technology. The display interface 1456 may comprise appropriate
circuitry for driving the display 1454 to present graphical and
other information to a user. The control interface 1458 may receive
commands from a user and convert them for submission to the
processor 1452. In addition, an external interface 1462 may be
provide in communication with processor 1452, so as to enable near
area communication of device 1450 with other devices. External
interface 1462 may provide, for example, for wired communication in
some implementations, or for wireless communication in other
implementations, and multiple interfaces may also be used.
[0211] The memory 1464 stores information within the computing
device 1450. The memory 1464 can be implemented as one or more of a
computer-readable medium or media, a volatile memory unit or units,
or a non-volatile memory unit or units. Expansion memory 1474 may
also be provided and connected to device 1450 through expansion
interface 1472, which may include, for example, a SIMM (Single In
Line Memory Module) card interface. Such expansion memory 1474 may
provide extra storage space for device 1450, or may also store
applications or other information for device 1450. For example,
expansion memory 1474 may include instructions to carry out or
supplement the processes described herein, and may include secure
information also. Thus, for example, expansion memory 1474 may be
provide as a security module for device 1450, and may be programmed
with instructions that permit secure use of device 1450. In
addition, secure applications may be provided via the SIMM cards,
along with additional information, such as placing identifying
information on the SIMM card in a non-hackable manner.
[0212] The memory may include, for example, flash memory and/or
NVRAM memory, as discussed below. In one implementation, a computer
program product is tangibly embodied in an information carrier. The
computer program product contains instructions that, when executed,
perform one or more methods, such as those described herein. The
information carrier is a computer- or machine-readable medium, such
as the memory 1464, expansion memory 1474, memory on processor
1452, or a propagated signal that may be received, for example,
over transceiver 1468 or external interface 1462.
[0213] Device 1450 may communicate wirelessly through communication
interface 1466, which may include digital signal processing
circuitry where necessary. Communication interface 1466 may provide
for communications under various modes or protocols, such as GSM
voice calls, SMS, EMS, or MMS messaging, CDMA, TDMA, PDC, WCDMA,
CDMA2000, or GPRS, among others. Such communication may occur, for
example, through radio-frequency transceiver 1468. In addition,
short-range communication may occur, such as using a Bluetooth,
WiFi, or other such transceiver (not shown). In addition, GPS
(Global Positioning System) receiver module 1470 may provide
additional navigation- and location-related wireless data to device
1450, which may be used as appropriate by applications running on
device 1450.
[0214] Device 1450 may also communicate audibly using audio codec
1460, which may receive spoken information from a user and convert
it to usable digital information. Audio codec 1460 may likewise
generate audible sound for a user, such as through a speaker, e.g.,
in a handset of device 1450. Such sound may include sound from
voice telephone calls, may include recorded sound (e.g., voice
messages, music files, etc.) and may also include sound generated
by applications operating on device 1450.
[0215] The computing device 1450 may be implemented in a number of
different forms, as shown in the figure. For example, it may be
implemented as a cellular telephone 1480. It may also be
implemented as part of a smartphone 1482, personal digital
assistant, or other similar mobile device.
[0216] Various implementations of the systems and techniques
described herein can be realized in digital electronic circuitry,
integrated circuitry, specially designed ASICs (application
specific integrated circuits), computer hardware, firmware,
software, and/or combinations thereof. These various
implementations can include implementation in one or more computer
programs that are executable and/or interpretable on a programmable
system including at least one programmable processor, which may be
special or general purpose, coupled to receive data and
instructions from, and to transmit data and instructions to, a
storage system, at least one input device, and at least one output
device.
[0217] These computer programs (also known as programs, software,
software applications or code) include machine instructions for a
programmable processor, and can be implemented in a high-level
procedural and/or object-oriented programming language, and/or in
assembly/machine language. As used herein, the terms
"machine-readable medium" and "computer-readable medium" refer to
any computer program product, apparatus and/or device (e.g.,
magnetic discs, optical disks, memory, and Programmable Logic
Devices (PLDs)) used to provide machine instructions and/or data to
a programmable processor, including a machine-readable medium that
receives machine instructions as a machine-readable signal. The
term "machine-readable signal" refers to any signal used to provide
machine instructions and/or data to a programmable processor.
[0218] To provide for interaction with a user, the systems and
techniques described herein can be implemented on a computer having
a display device (e.g., a CRT (cathode ray tube) or LCD (liquid
crystal display) monitor) for displaying information to the user
and a keyboard and a pointing device (e.g., a mouse or a trackball)
by which the user can provide input to the computer. Other kinds of
devices can be used to provide for interaction with a user as well;
for example, feedback provided to the user can be any form of
sensory feedback (e.g., visual feedback, auditory feedback, or
tactile feedback); and input from the user can be received in any
form, including acoustic, speech, or tactile input.
[0219] The systems and techniques described herein can be
implemented in a computing system that includes a back end
component (e.g., as a data server), or that includes a middleware
component (e.g., an application server), or that includes a front
end component (e.g., a client computer having a graphical user
interface or a Web browser through which a user can interact with
an implementation of the systems and techniques described herein),
or any combination of such back end, middleware, or front end
components. The components of the system can be interconnected by
any form or medium of digital data communication (e.g., a
communication network). Examples of communication networks include
a local area network ("LAN"), a wide area network ("WAN"), and the
Internet.
[0220] The computing system can include clients and servers. A
client and server are generally remote from each other and
typically interact through a communication network. The
relationship of client and server arises by virtue of computer
programs running on the respective computers and having a
client-server relationship to each other.
[0221] The results of any analyses according to the invention will
often be communicated to physicians, genetic counselors and/or
patients (or other interested parties such as researchers) in a
transmittable form that can be communicated or transmitted to any
of the above parties. Such a form can vary and can be tangible or
intangible. The results can be embodied in descriptive statements,
diagrams, photographs, charts, images or any other visual forms.
For example, graphs or diagrams showing genotype or LOH (or HRD
status) information can be used in explaining the results. The
statements and visual forms can be recorded on a tangible medium
such as papers, computer readable media such as floppy disks,
compact disks, flash memory, etc., or in an intangible medium,
e.g., an electronic medium in the form of email or website on
internet or intranet. In addition, results can also be recorded in
a sound form and transmitted through any suitable medium, e.g.,
analog or digital cable lines, fiber optic cables, etc., via
telephone, facsimile, wireless mobile phone, internet phone and the
like.
[0222] Thus, the information and data on a test result can be
produced anywhere in the world and transmitted to a different
location. As an illustrative example, when an assay is conducted
outside the United States, the information and data on a test
result may be generated, cast in a transmittable form as described
above, and then imported into the United States. Accordingly, the
present invention also encompasses a method for producing a
transmittable form of information on an LOH signature for at least
one patient sample. The method comprises the steps of (1)
determining an LOH signature according to methods of the present
invention; and (2) embodying the result of the determining step in
a transmittable form. The transmittable form is a product of such a
method.
[0223] In some cases, a computing system provided herein can be
configured to include one or more sample analyzers. A sample
analyzer can be configured to produce a plurality of signals about
genomic DNA of at least one pair of human chromosomes of a cancer
cell. For example, a sample analyzer can produce signals that are
capable of being interpreted in a manner that identifies the
homozygous or heterozygous nature of loci along a chromosome. In
some cases, a sample analyzer can be configured to carry out one or
more steps of a SNP array-based assay or sequencing-based assay and
can be configured to produce and/or capture signals from such
assays. In some cases, a computing system provided herein can be
configured to include a computing device. In such cases, the
computing device can be configured to receive signals from a sample
analyzer. The computing device can include computer-executable
instructions or a computer program (e.g., software) containing
computer-executable instructions for carrying out one or more of
the methods or steps described herein. In some cases, such
computer-executable instructions can instruct a computing device to
analyze signals from a sample analyzer, from another computing
device, from a SNP array-based assay, or from a sequencing-based
assay. The analysis of such signals can be carried out to determine
genotypes, chromosomal aberration at certain loci, regions of
chromosomal aberration, the number of chromosomal aberration
regions, to determine the location of chromosomal aberration
regions (e.g., telomeric), to determine the number of chromosomal
aberration regions having a particular location (e.g., telomeric),
to determine whether or not a sample is positive for a high
chromosomal aberration score, to determine a likelihood that a
cancer patient will respond to a particular cancer treatment
regimen (e.g., a regimen as described above), or to determine a
combination of these items.
[0224] In some cases, a computing system provided herein can
include computer-executable instructions or a computer program
(e.g., software) containing computer-executable instructions for
formatting an output providing an indication about the number of
chromosomal aberration regions, the location of chromosomal
aberration regions (e.g., telomeric), the number of LOH regions
having a particular location (e.g., telomeric), whether or not a
sample is positive for a high chromosomal aberration score, a
likelihood that a cancer patient will respond to a particular
cancer treatment regimen (e.g., a regimen as described above), or a
combination of these items. In some cases, a computing system
provided herein can include computer-executable instructions or a
computer program (e.g., software) containing computer-executable
instructions for determining a desired cancer treatment regimen for
a particular patient based at least in part on the presence or
absence of a high chromosomal aberration score.
[0225] In some cases, a computing system provided herein can
include a pre-processing device configured to process a sample
(e.g., cancer cells) such that a SNP array-based assay or
sequencing-based assay can be performed. Examples of pre-processing
devices include, without limitation, devices configured to enrich
cell populations for cancer cells as opposed to non-cancer cells,
devices configured to lyse cells and/or extract genomic nucleic
acid, and devices configured to enrich a sample for particular
genomic DNA fragments.
[0226] In general, one aspect of this invention features a method
for assessing LOH in a cancer cell or genomic DNA thereof. In some
embodiments, the method comprises, or consists essentially of, (a)
detecting, in a cancer cell or genomic DNA derived therefrom, LOH
regions in at least one pair of human chromosomes of the cancer
cell (e.g., any pair of human chromosomes other than a human X/Y
sex chromosome pair); and (b) determining the number and size
(e.g., length) of said LOH regions. In some embodiments, LOH
regions are analyzed in a number of chromosome pairs that are
representative of the entire genome (e.g., enough chromosomes are
analyzed such that the number and size of LOH regions are expected
to be representative of the number and size of LOH regions across
the genome). In some embodiments, the method further comprises
determining the total number of LOH regions that are longer than
about 1.5, 5, 12, 13, 14, 15, 16, 17 or more (preferably 14, 15, 16
or more, more preferably 15 or more) megabases but shorter than the
entire length of the respective chromosome which the LOH region is
located within (Indicator LOH Regions). Alternatively or
additionally, the total combined length of such Indicator LOH
Regions is determined. In some specific embodiments, if that total
number of Indicator LOH Regions or total combined length of
Indicator LOH Regions is equal to or greater than a predetermined
reference number, then said cancer cell or genomic DNA or a patient
having said cancer cell or genomic DNA is identified as having an
HDR-deficiency LOH signature.
[0227] Other embodiments of the present invention are described in
the following Examples. The present invention is further
illustrated by the following examples which should not be construed
as further limiting.
[0228] The following paragraphs define the invention in more
detail
[0229] 1. An assay for selecting therapy for a subject having
cancer, the assay comprising
[0230] subjecting a biological sample comprising a cancer cell or
nucleic acid from a cancer cell taken from the subject to telomeric
allelic imbalance (tAI) analysis;
[0231] detecting the number of telomeric allelic imbalance (NtAI)
in the cancer cell or nucleic acid from the cancer cell, and
[0232] selecting a platinum-comprising therapy for the subject when
the NtAI is detected to be above a reference value based on the
recognition that platinum-comprising therapy is effective in
patients who have NtAI above the reference value; and selecting a
non-platinum-comprising cancer therapy for the subject when the
NtAI is detected to be below a reference value based on the
recognition that platinum-comprising cancer therapy is not
effective in patients who have the NtAI below a reference
value.
[0233] 2. The assay of paragraph 1 further comprising the step of
treating the subject with the selected therapy.
[0234] 3. The assay of any of the preceding paragraphs, wherein the
cancer is breast cancer or ovarian cancer.
[0235] 4. The assay of any of the preceding paragraphs, wherein the
reference value is 22.
[0236] 5. The assay of any of the preceding paragraphs, wherein the
reference value is 24.
[0237] 6. The assay of any of the preceding paragraphs, wherein the
reference value is 27.
[0238] 7. The assay of any of the preceding paragraphs, wherein the
cancer cell does not have mutations in the BRCA1 and/or BRCA2
gene.
[0239] 8. The assay of any of the preceding paragraphs further
comprising a step of assaying for BRCA1 mRNA expression or
methylation status of the BRCA1 promoter, detecting the amount of
BRCA 1 mRNA expression or the amount of methylation of the BRCA1
promoter, wherein the platinum comprising therapy is selected when
decreased expression of BRCA1 or increased methylation of BRCA1
promoter is detected.
[0240] 9. A method for selecting platinum-comprising therapy for a
subject having cancer comprising
[0241] subjecting a biological sample taken from the subject to
allelic imbalance (AI) analysis;
[0242] detecting the number of AI; and
[0243] selecting platinum-comprising cancer therapy for the subject
when the number of AIs is above a reference value based on the
recognition that platinum-comprising cancer therapy is effective in
patients who have the number of AIs is above a reference value.
[0244] 10. The method of any of the preceding paragraphs further
comprising the step of treating the subject with
platinum-comprising cancer therapy when platinum-comprising cancer
therapy is selected.
[0245] 11. The method of any of the preceding paragraphs, wherein
the cancer is selected from breast cancer and ovarian cancer.
[0246] 12. The method of any of the preceding paragraphs, wherein
the breast cancer does not have a BRCA1 mutations.
[0247] 13. The method of any of the preceding paragraphs, wherein
the allelic imbalance is within about 25 kB of a copy number
variation (CNV).
[0248] 14. The method of any of the preceding paragraphs, wherein
the CNV is pericentromeric or subtelomeric CNV.
[0249] 15. The method of any of the preceding paragraphs, wherein
the allelic imbalance is telomeric allelic imbalance.
[0250] 16. A method comprising:
[0251] detecting, in a cancer cell or genomic DNA derived
therefrom, allelic imbalance in a representative number of pairs of
human chromosomes of the cancer cell; and
[0252] determining the number of allelic imbalance.
[0253] 17. The method of Paragraph 16, said representative number
of pairs of human chromosomes is representative of the entire
genome.
[0254] 18. The method of Paragraph 16-17, further comprising
correlating an increased number of allelic imbalance regions to an
increased likelihood of deficiency in HDR.
[0255] 19. The method of paragraph 16-18, further comprising
correlating an increased number of allelic imbalance regions to an
increased likelihood of said cancer cell to respond to platinum
comprising cancer therapy.
[0256] 20. The method of paragraph 16-19, further comprising
correlating a non-increased number of allelic imbalance regions to
a decreased likelihood of said cancer cell to respond to platinum
comprising cancer therapy.
[0257] 21. The method of paragraph 16-21, wherein the platinum
comprising cancer therapy comprises cisplatin, carboplatin,
oxalaplatin, or picoplatin.
[0258] 22. A method comprising:
[0259] a) detecting, in a cancer cell or genomic DNA derived
therefrom, LOH regions in a representative number of pairs of human
chromosomes of the cancer cell; and
[0260] b) determining the number and size of said LOH regions.
[0261] 23. The method of Paragraph 22, said representative number
of pairs of human chromosomes is representative of the entire
genome.
[0262] 24. The method of Paragraph 22-23, further comprising
correlating an increased number of LOH regions of a particular size
to an increased likelihood of deficiency in HDR.
[0263] 25. The method of Paragraph 22-24, wherein said particular
size is longer than about 1.5, 2, 2.5, 3, 4, 5, 6, 7, 8, 9, 10, 11,
12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 75, or
100 megabases and less than the length of the entire chromosome
that contains the LOH region.
[0264] 26. The method of any of the paragraphs 22-25, wherein 6, 7,
8, 9, 10, 11, 12 or 13 or more LOH regions of said particular size
are correlated to an increased likelihood of deficiency in HDR.
[0265] 27. A method of determining prognosis in a patient
comprising:
[0266] a) determining whether the patient comprises cancer cells
having an LOH signature, wherein the presence of more than a
reference number of LOH regions in at least one pair of human
chromosomes of a cancer cell of the cancer patient that are longer
than a first length but shorter than the length of the whole
chromosome containing the LOH region indicates that the cancer
cells have the LOH signature, wherein the at least one pair of
human chromosomes is not a human X/Y sex chromosome pair, wherein
the first length is about 1.5 or more megabases, an
[0267] b) (1) determining, based at least in part on the presence
of the LOH signature, that the patient has a relatively good
prognosis, or b)(2) determining, based at least in part on the
absence of the LOH signature, that the patient has a relatively
poor prognosis
[0268] 28. A composition comprising a therapeutic agent selected
from the group consisting of DNA damaging agent, anthracycline,
topoisomerase I inhibitor, and PARP inhibitor for use in treating a
cancer selected from the group consisting of breast cancer, ovarian
cancer, liver cancer, esophageal cancer, lung cancer, head and neck
cancer, prostate cancer, colon cancer, rectal cancer, colorectal
cancer, and pancreatic cancer in a patient with more than a
reference number of LOH regions in at least one pair of human
chromosomes of a cancer cell of the patient that are longer than a
first length but shorter than the length of the whole chromosome
containing the LOH region, wherein the at least one pair of human
chromosomes is not a human X/Y sex chromosome pair, wherein the
first length is about 1.5 or more megabases.
[0269] 29. The composition of any of the preceding Paragraphs,
wherein said LOH regions are determined in at least two, five, ten
or 21 pairs of human chromosomes.
[0270] 30. The composition of any of the preceding paragraphs,
wherein the total number of said LOH regions is 9, 15, 20 or
more.
[0271] 31. The composition of any of the preceding paragraphs,
wherein said first length is about 6, 12, or 15 or more
megabases.
[0272] 32. The composition of any of the preceding paragraphs,
wherein said reference number is 6, 7, 8, 9, 10, 11, 12 or 13 or
greater.
[0273] 33. A method of treating cancer in a patient,
comprising:
[0274] a) determining in a sample from said patient the number of
LOH regions in at least one pair of human chromosomes of a cancer
cell of the cancer patient that are longer than a first length but
shorter than the length of the whole chromosome containing the LOH
region indicates that the cancer cells have the LOH signature,
wherein the at least one pair of human chromosomes is not a human
X/Y sex chromosome pair, wherein the first length is about 1.5 or
more megabases;
[0275] b) providing a test value derived from the number of said
LOH regions;
[0276] c) comparing said test value to one or more reference values
derived from the number of said LOH regions in a reference
population (e.g., mean, median, terciles, quartiles, quintiles,
etc.); and
[0277] d) administering to said patient an anti-cancer drug, or
recommending or prescribing or initiating a treatment regimen
comprising chemotherapy and/or a synthetic lethality agent based at
least in part on said comparing step revealing that the test value
is greater (e.g., at least 2-, 3-, 4-, 5-, 6-, 7-, 8-, 9-, or
10-fold greater; at least 1, 2, 3, 4, 5, 6, 7, 8, 9, or 10 standard
deviations greater) than at least one said reference value; or
[0278] e) recommending or prescribing or initiating a treatment
regimen not comprising chemotherapy and/or a synthetic lethality
agent based at least in part on said comparing step revealing that
the test value is not greater (e.g., not more than 2-, 3-, 4-, 5-,
6-, 7-, 8-, 9-, or 10-fold greater; not more than 1, 2, 3, 4, 5, 6,
7, 8, 9, or 10 standard deviations greater) than at least one said
reference value.
[0279] 34. The method of Paragraph 33, wherein said LOH regions are
determined in at least two, five, ten or 21 pairs of human
chromosomes.
[0280] 35. The method of Paragraph 33-34, wherein the total number
of said LOH regions is 9, 15, 20 or more.
[0281] 36. The method of Paragraph 33-35, wherein said first length
is about 6, 12, or 15 or more megabases.
[0282] 37. The method of Paragraph 33-36, wherein said reference
number is 6, 7, 8, 9, 10, 11, 12 or 13 or greater.
[0283] 38. The method of Paragraph 33-37, wherein said chemotherapy
is selected from the group consisting of a DNA damaging agent, an
anthracycline, and a topoisomerase I inhibitor and/or wherein said
synthetic lethality agent is a PARP inhibitor drug.
[0284] 39. The method of Paragraph 33-38, wherein said DNA damaging
agent is cisplatin, carboplatin, oxalaplatin, or picoplatin, said
anthracycline is epirubincin or doxorubicin, said topoisomerase I
inhibitor is campothecin, topotecan, or irinotecan, and/or said
PARP inhibitor is iniparib, olaparib or velapirib.
[0285] 40. A composition comprising a therapeutic agent selected
from the group consisting of platinum comprising cancer therapy and
anthracycline for use in treating a cancer selected from the group
consisting of breast cancer, ovarian cancer, liver cancer,
esophageal cancer, lung cancer, head and neck cancer, prostate
cancer, colon cancer, rectal cancer, colorectal cancer, and
pancreatic cancer in a patient with increased allelic
imbalance.
[0286] 41. The composition of paragraph 40, wherein the allelic
imbalance is telomeric allelic imbalance.
[0287] 42. The composition of paragraph 40-41, wherein the allelic
imbalance is within about 25 kB of a copy number variation
(CNV).
[0288] 43. The composition of paragraph 40-42, wherein the patient
is further determined not to carry a BRCA1 and/or BRCA2
mutation.
[0289] 44. The composition of paragraph 40-43, wherein the patient
is further determined to have decreased BRCA1 mRNA amount in the
cancer cell and/or is further determined to have increased
methylation of the BRCA1 promoter region.
[0290] 45. A method for predicting the outcome of anti-cancer
treatment of a subject with a cell hyperproliferative disorder,
comprising determining a global chromosomal aberration score
(GCAS), comprising obtaining a biological sample from the subject
and determining whether a plurality of chromosomal regions
displaying a chromosomal aberration exists within a plurality of
chromosomal loci, wherein said chromosomal aberrations are selected
from the group consisting of allelic imbalance (NAI), loss of
heterozygosity (NLOH), copy number aberrations (NCNA), copy number
gain (NCNG), copy number decrease (NCND) and combinations thereof,
relative to a control, and wherein the presence of a plurality of
chromosomal regions displaying said chromosomal aberrations
predicts the outcome of anti-cancer treatment of the subject.
[0291] 46. The method of paragraph 45, wherein the anti-cancer
treatment is chemotherapy treatment.
[0292] 47. The method of paragraph 45-46, wherein the chemotherapy
treatment comprises platinum-based chemotherapeutic agents.
[0293] 48. The method of paragraph 45-47, wherein the
platinum-based chemotherapeutic agents are selected from the group
consisting of cisplatin, carboplatin, oxaliplatin, nedaplatin, and
iproplatin.
[0294] 49. The method of paragraph 45-48, wherein the subject is a
human.
[0295] 50. The method of paragraph 45-49, wherein the cell
hyperproliferative disorder is selected from the group consisting
of breast cancer, ovarian cancer, transitional cell bladder cancer,
bronchogenic lung cancer, thyroid cancer, pancreatic cancer,
prostate cancer, uterine cancer, testicular cancer, gastric cancer,
soft tissue and osteogenic sarcomas, neuroblastoma, Wilms' tumor,
malignant lymphoma (Hodgkin's and non-Hodgkin's), acute
myeloblastic leukemia, acute lymphoblastic leukemia, Kaposi's
sarcoma, Ewing's tumor, refractory multiple myeloma, and squamous
cell carcinomas of the head, neck, cervix, colon cancer, melanoma,
and vagina.
[0296] 51. The method of paragraph 45-50, wherein the biological
sample is selected from the group consisting of cells, cell lines,
histological slides, frozen core biopsies, paraffin embedded
tissues, formalin fixed tissues, biopsies, whole blood, nipple
aspirate, serum, plasma, buccal scrape, saliva, cerebrospinal
fluid, urine, stool, and bone marrow.
[0297] 52. The method of paragraph 45-51, wherein the biological
sample is enriched for the presence of hyperproliferative cells to
at least 75% of the total population of cells.
[0298] 53. The method of paragraph 45-52, wherein the enrichment is
performed according to at least one technique selected from the
group consisting of needle microdissection, laser microdissection,
fluorescence activated cell sorting, and immunological cell
sorting.
[0299] 54. The method of paragraph 45-53, wherein an automated
machine performs the at least one technique to thereby transform
the biological sample into a purified form enriched for the
presence of hyperproliferative cells.
[0300] 55. The method of paragraph 45-54, wherein the biological
sample is obtained before the subject has received adjuvant
chemotherapy.
[0301] 56. The method of paragraph 45-55, wherein the biological
sample is obtained after the subject has received adjuvant
chemotherapy.
[0302] 57. The method of paragraph 45-56, wherein the control is
determined from a non-cell hyperproliferative cell sample from the
patient or member of the same species to which the patient
belongs.
[0303] 58. The method of paragraph 45-58, wherein the control is
determined from the average frequency of genomic locus appearance
of chromosomal regions of the same ethnic group within the species
to which the patient belongs.
[0304] 59. The method of paragraph 45-58, wherein the control is
from non-cancerous tissue that is the same tissue type as said
cancerous tissue of the subject.
[0305] 60. The method of paragraph 45-59, wherein the control is
from non-cancerous tissue that is not the same tissue type as said
cancerous tissue of the subject.
[0306] 61. The method of paragraph 45-60, wherein NAI is determined
using major copy proportion (MCP).
[0307] 62. The method of paragraph 45-61, wherein NAI for a given
genomic region is counted when MCP is greater than 0.70.
[0308] 63. The method of paragraph 45-62, wherein the plurality of
chromosomal loci are randomly distributed throughout the genome at
least every 100 Kb of DNA.
[0309] 64. The method of paragraph 45-63, wherein the plurality of
chromosomal loci comprise at least one chromosomal locus on each of
the 23 human chromosome pairs.
[0310] 65. The method of paragraph 45-64, wherein the plurality of
chromosomal loci comprise at least one chromosomal locus on each
arm of each of the 23 human chromosome pairs.
[0311] 66. The method of paragraph 45-65, wherein the plurality of
chromosomal loci comprise at least one chromosomal locus on at
least one telomere of each of the 23 human chromosome pairs.
[0312] 67. The method of paragraph 45-66, wherein the plurality of
chromosomal loci comprise at least one chromosomal locus on each
telomere of each of the 23 human chromosome pairs.
[0313] 68. The method of paragraph 45-67, wherein the chromosomal
aberrations have a minimum segment size of at least 1 Mb.
[0314] 69. The method of paragraph 45-68, wherein the chromosomal
aberrations have a minimum segment size of at least 12 Mb.
[0315] 70. The method of paragraph 45-69, wherein the plurality of
chromosomal aberrations comprises at least 5 chromosomal
aberrations.
[0316] 71. The method of paragraph 45-70, wherein the plurality of
chromosomal aberrations comprises at least 13 chromosomal
aberrations.
[0317] 72. The method of paragraph 45-71, wherein the chromosomal
loci are selected from the group consisting of single nucleotide
polymorphisms (SNPs), restriction fragment length polymorphisms
(RFLPs), and simple tandem repeats (STRs).
[0318] 73. The method of paragraph 45-72, wherein the chromosomal
loci are analyzed using at least one technique selected from the
group consisting of molecular inversion probe (MIP), single
nucleotide polymorphism (SNP) array, in situ hybridization,
Southern blotting, transcriptional arrays, array comparative
genomic hybridization (aCGH), and next-generation sequencing.
[0319] 74. The method of paragraph 45-73, wherein outcome of
treatment is measured by at least one criteria selected from the
group consisting of survival until mortality, pathological complete
response, semi-quantitative measures of pathologic response,
clinical complete remission, clinical partial remission, clinical
stable disease, recurrence-free survival, metastasis free survival,
disease free survival, circulating tumor cell decrease, circulating
marker response, and RECIST criteria.
[0320] 75. The method of paragraph 45-74, further comprising
determining a suitable treatment regimen for the subject.
[0321] 76. The method of paragraph 45-75, wherein said suitable
treatment regimen comprises at least one platinum-based
chemotherapeutic agent when a plurality of genomic chromosomal
aberrations is determined or does not comprise at least one
platinum-based chemotherapeutic agent when no plurality of genomic
chromosomal aberrations is determined.
EXAMPLES
Example 1
Materials and Methods for Example 2
[0322] Pathologic response after neoadjuvant cisplatin therapy in
the TNBC cohort was measured using the semi-quantitative
Miller-Payne scale as described (Silver et al. (2010) J. Clin.
Oncol. 28, 1145-1153; Ogston et al. (2003) Breast 12, 320-327). MIP
genotyping was performed as described (Wang et al. (2007) Genome
Biol. 8, R246). Allele signal intensity and genotypes from MIP
genotyping or public SNP array analyses were processed by the CRLMM
algorithm (Lin et al. (2008) Genome Biol. 9, R63) as implemented in
the R package "oligo". DNA copy number was determined using the R
package "AromaAffymetrix" (Bengtsson et al. (2008) Bioinformatics
24, 759-767). Processed genotype data was exported to dChip
(available on the world wide web at
http://biosun1.harvard.edu/complab/dchip/) for major copy
proportion (MCP) determination, defined as ratio of major copy
number to major+minor copy number (Li et al. (2008) Bioinformatics
9, 204). An estimate of level of normal DNA contamination was made
from the genomic MCP curve as described (Li et al. (2008)
Bioinformatics 9, 204). Breast or ovarian cases estimated to have
75% or more tumor content were included in analyses. Allelic
imbalance (AI) for specific purposes of some Examples described
herein was defined as MCP>0.7 and regions of AI defined as more
than 10 consecutive probes with AI. Telomeric AI for specific
purposes of some Examples described herein was defined as AI
regions that extend to telomere and do not cross the centromere.
Association between NtAI,12 and response to cisplatin in TNBC
subjects was estimated by area under curve (AUC) of receiver
operator characteristic (ROC) curve; p value is from two-sided
Wilcoxon's rank test. Association between telomeric AI and time to
recurrence of ovarian cancer after platinum therapy was estimated
by Kaplan Meier analysis using a cutoff of 13 to define high
NtAI,12 group; p value is based on log-rank test. A complete
listing of materials and methods is as follows:
[0323] Cell Lines and Drug Sensitivity Assays
[0324] Tripe-negative breast cancer cell lines BT20, BT549,
HCC1187, HCC38, MDA-MB231 and MDA-MB468 were maintained at
37.degree. C. with 5% CO2 in RPMI 1640 medium and/or MEM medium
supplemented with 10% FBS or other supplements as recommended by
ATCC for each cell line. To test drug sensitivity, cells were
exposed to a series of concentrations of cisplatin for 48 hours.
Viable cell number was quantified using CellTiter 96 Aqueous One
Solution Cell Proliferation Assay according to the manufacturer's
instructions (Promega). The results are presented as the percentage
of viable cells in drug-treated wells vs. media-treated control
wells and plotted as a drug-does dependent cell survival curves
(FIG. 1A). Drug sensitivity was quantified as the does of drug
causing a 50% reduction of growth (IC50). This data was originally
generated for a separate study in which it was reported as "data
not shown" in Li et al. (2010) Nat. Med. 16, 214-218.
[0325] Breast Cancer Cohort
[0326] A total of 28 mainly sporadic TNBC patients were treated
with cisplatin monotherapy in the neo-adjuvant setting (Silver et
al. (2010) J. Clin. Oncol. 28, 1145-1153). Cisplatin response was
measured using the semiquantitative Miller-Payne score by
pathological assessment of surgical samples after therapy (Ogston
et al. (2003) Breast 12, 320-327). Pathologic complete response is
equivalent to Miller-Payne score and is defined as no residual
invasive carcinoma in breast or lymph nodes.
[0327] Preparation of Breast Cancer Samples
[0328] A frozen core biopsy of the tumor was obtained before
treatment started. Tumor tissue was available in the frozen core
biopsy for 24 of 28 cases and in formalin fixed paraffin embedded
diagnostic core biopsy samples from an additional 3 cases. Tumor
cells were enriched by needle microdissection to remove stroma from
hematoxylin and eosin (H & E) stained tissue sections. The
remaining tissue on slides was examined by microscopy for
estimation of enrichment. DNA was extracted from enriched tumor
cells by proteinase K and RNase A digestions, phenol/chloroform
extraction followed by ethanol precipitation. Adequate DNA for MIP
genotyping analysis (minimum 80 ng) was obtained from all 27 cases
for which tumor tissue was available. Paired normal DNA from each
patient was obtained from peripheral blood lymphocytes.
[0329] Molecular Inversion Probe (MIP) Genotyping Analysis
[0330] DNA from breast tumor biopsy samples were sent to
Affymetrix, Inc. (Santa Clara, Calif.) for MIP targeted genotyping
analysis which generated allele signal intensity and genotypes for
42,000 individual single nucleotide polymorphisms (SNP). The
complete MIP genotype data set is available on the NCBI GEO
database.
[0331] Public Datasets
[0332] Affymetrix SNP 6.0 genomic profiles of six triple negative
breast cancer cell lines, BT20, BT549, HCC1187, HCC38, MDA-MB231
and MDA-MB468, were acquired from the Welcome Trust Sanger
Institute (information available on the world wide web at
http://www.sanger.ac.uk/).
[0333] SNP data representing 118 ovarian carcinoma tumors arrayed
on the Affymetrix 50K XbaI platform were acquired from the gene
expression omnibus (GEO, GSE13813; Etemadmoghadam et al. (2009)
Clin. Cancer Res. 15, 1417-1427). Of these, 38 tumors were of the
serous subtype, had residual tumor after surgical debulking of less
than 1 cm, and had received either adjuvant cisplatin or
carboplatin treatment. Most patients (35 of 38) had also received
taxane treatment.
[0334] Genotype and Copy Number Analysis
[0335] Allele signal intensity and genotypes from MIP genotyping or
SNP array analyses were processed by the CRLMM algorithm (Lin et
al. (2008) Genome Biol. 9, R63) as implemented in the R package
"oligo". DNA copy number was determined using the R package
"AromaAffymetrix" (Bengtsson et al. (2008) Bioinformatics 24,
759-767). Processed genotype data was exported to dChip (available
on the world wide web at http://biosun1.harvard.edu/complab/dchip/)
for major copy proportion (MCP) determination.
[0336] MCP is defined as the ratio of the major allele copy number
to the major+minor allele copy number (Li et al. (2008)
Bioinformatics 9, 204). The degree of normal cell contamination was
estimated by the degree of shift in the MCP curve of the majority
of regions showing allelic imbalance across genome, excluding all
regions of copy number gain (The shift observed in the genomic MCP
curves in paired normal and tumor cell line mixture experiments was
used as reference to estimate normal contamination as described
(Waddell et al. (2009) Breast Cancer Res. Treat. (December 4;
e-published)). Accordingly, 21 of the 27 breast tumor samples and
33 of 38 of the ovarian cancer cases were estimated to have 25% or
less of normal DNA contamination (.quadrature.75% tumor content)
and were deemed acceptable for subsequent analysis.
[0337] Allelic imbalance (AI) was defined for purposes of some
Examples described herein as MCP>0.70, which allows detection of
the majority of loss of heterozygosity (LOH) events and of
high-copy monoallelic amplifications in samples with 25% or less
contamination or heterogeneity, but also excludes low-level copy
gains (4-copy gains or less). Regions of AI were defined for
purposes of some Examples described herein as more than 10
consecutive probes showing AI. In the TNBC dataset, the AI regions
defined by these criteria included all callable LOH regions as
determined from conventional genotype comparison. The total copy
numbers (combining both alleles) were segmented by the circular
binary segmentation algorithm. Eighty five percent of AI regions
had total copy number near diploid or below, 9% of the AI regions
showed total copy gain of 3, and 6% with total copy gain
.quadrature.4. Thus, the identified AI regions predominantly
represent LOH or uniparental chromosomal deletion.
[0338] Association Between Number of Genomic Aberrations and
Platinum Sensitivity In Vitro
[0339] The numbers of regions of AI or regions with copy number
aberration were compared to cell line-specific IC50 values after
applying a 1 Mb minimum size filter to remove very small regions
that could be caused by noise in the SNP 6.0 data (FIG. 3). For
comparison of telomeric and interstitial AI regions, telomeric AI
was defined for purposes of the Examples described herein as AI
that extends to the telomere but does not cross the centromere.
Conversely, interstitial AI was defined for purposes of the
Examples described herein as AI regions that do not involve the
telomere. To investigate if there was an optimum minimum size of
telomeric AI or copy number alteration segments that showed a
superior correlation to the cisplatin IC50, linear regression was
used to compare the IC50 values with the total number of segments
larger than a certain threshold, which was increased by 1 Mb
intervals between 0 and 100 Mb (FIG. 5).
[0340] Association Between Number of Telomeric Al Regions and
Platinum Sensitivity in Tumors
[0341] Total number of regions of telomeric AI was determined for
each TNBC case with at least 75% tumor content. The optimal minimum
telomeric AI segment size threshold of 12 Mb found in the cell
lines were applied, and NtA1,12 were counted for each subject. ROC
(Receiver Operating Characteristic) curve analysis was performed to
evaluate the capability of the total number of telomeric AI
segments to predict pCR (Miller-Payne score 5) to cisplatin
treatment.
[0342] The association of NtAI,12 with pCR to cisplatin was
estimated by the area under the curve (AUC); the corresponding
p-value is from two-sided Wilcoxon's rank test. Based on the ROC
analysis, a NtAI.12 of 13 resulted in 100% sensitivity for
prediction of pCR in the TNBC cisplatin treated cohort.
[0343] The association between NtAI,12 and time to recurrence after
platinum-based therapy in the ovarian cancer cohort was estimated
by Kaplan-Meier analysis with the "high NtAI,12" group defined as
at least 13 regions of NtAI,12. P value is based on a log-rank
test.
Example 2
Total Number of Chromosomal Rearrangements is Predictive of
Chemotherapeutic Drug Sensitivity
[0344] Without being bound by theory, it is believed that
intrachromosomal loss of heterozycosity (LOH) or allelic imbalance
(AI) results from improper repair of chromosomal DNA double-strand
breaks and that the genome-wide count of these chromosomal
rearrangements in a specific tumor may indicate the degree of DNA
repair incompetence, independent of the specific causative DNA
repair defect. Therefore, the total number of chromosomal
rearrangements in a tumor reflects the inability to repair DNA
damage induced by drugs like cisplatin, and consequently predicts
sensitivity to these agents. Cisplatin sensitivity of six TNBC cell
lines for which SNP array data was available from Wellcome Trust
Sanger Institute, UK, was thus determined (FIG. 1A). AI was
determined by major copy proportion (MCP) analysis, a method less
sensitive to normal contamination in heterogeneous tumor samples
(Li et al. (2008) Bioinformatics 9, 204).
[0345] The MCP is the number of major copy alleles at a locus
divided by the sum of the number of major plus minor copy alleles
(FIG. 2). Gains or reductions in total DNA copy number at each
chromosomal region were inferred using dChip software (Lin et al.
(2004) Bioinformatics 20, 1233-1240).
[0346] The DNA repair lesion(s) rendering cells sensitive to
cisplatin may preferentially induce chromosomal alterations of a
specific type or with a specific size range. In the six cell lines,
the association between cisplatin sensitivity and each of four
measures of chromosomal alterations was tested. The four measures
were (1) the number of chromosome regions with AI (NAI), (2) the
number of copy number aberrations (NCNA), (3) the number of regions
with copy number gain, and (4) the number of regions with copy
number decrease (FIG. 3). Of these four measures, the NAI was most
strongly correlated with cisplatin sensitivity (R2=0.5).
[0347] Known defects in DNA double strand break repair, including
loss of BRCA1 or mutations in the Bloom helicase, cause the
spontaneous formation of triradial and quadriradial chromosome
structures, which are cytologic indications of aberrant
recombination (Silver et al. (2007) Cell 128, 991-1002; Luo et al.
(2000) Nat. Genet. 26, 424-429; Xu et al. (1999) Mol. Cell 3,
389-395). The resolution of these chromosome rearrangements at
mitosis can result in loss of distal (telomeric) chromosome
fragments and large regions of AI (Luo et al. (2000) Nat. Genet.
26, 424-429; Vrieling (2001) Nat. Genet. 28, 101-102). Thus,
telomeric and interstitial (non-telomeric) AI regions were compared
and it was found that the correlation between cisplatin sensitivity
and AI was stronger when limited to AI regions involving telomeres,
whereas only weak association was seen between cisplatin
sensitivity and the number of interstitial AI regions (FIG. 4).
[0348] Next, it was determined if the correlations could be
improved between cisplatin sensitivity and measures of genomic
aberrations by testing a range of minimum segment sizes, in TNBC
cell lines (FIG. 1B and FIGS. 5A-5C). Significant correlation with
cisplatin sensitivity was seen using minimum telomeric AI segment
size cutoffs between 5 and 25 Mb with the highest level of
correlation seen for total number of segments with telomeric AI
(NtAI) of at least 12 MB (R2=0.8; P=0.016; FIG. 1C). Testing for
optimum minimum segment size did not appreciably improve the
correlation between cisplatin sensitivity and measures of copy
number aberrations, which remained not significant (FIGS.
5D-5F).
[0349] Whether the same association between NtAI and cisplatin
sensitivity was present in clinical tumor samples using the optimum
segment size cutoff of 12 MB (NtAI,12) was also investigated.
NtAI,12 was compared to chemotherapy response in subjects with TNBC
treated with preoperative cisplatin monotherapy (Silver et al.
(2010) J. Clin. Oncol. 28, 1145-1153). Cryostat tissue sections of
pre-treatment core biopsies were enriched for tumor cells by needle
microdissection, and DNA was extracted for genotyping. Genotypes of
42,000 SNPs were determined with the Molecular Inversion Probe
(MIP) targeted genotyping system (Affymetrix, Inc.) (Wang et al.
(2007) Genome Biol. 8, R246). The degree of normal cell
contamination was estimated from the MIP genotype data as described
(Li et al. (2008) Bioinformatics 9, 204). No association was
observed between the degree of normal contamination and response to
cisplatin (R2=0.004, P=0.75).
[0350] MIP genotype data from 21 cases with at least 75% tumor cell
content were evaluated by MCP analysis to define the regions of
telomeric, interstitial, or whole chromosome AI across the genome
(FIG. 6A and FIG. 7). A correlation between the NtAI,12 and the
response rate was observed, as quantified by the Miller-Payne score
(R2=0.5; P=0.00032; FIG. 6B; Ogston et al. (2003) Breast 12,
320-327), with higher numbers of tAI regions associated with
greater sensitivity to cisplatin. Receiver operating characteristic
(ROC) curve analysis revealed that NtAI,12 was significantly
associated with pathologic complete response to cisplatin
(Miller-Payne 5) by the area under the curve (AUC=0.85; P=0.017;
FIG. 6C). There was no apparent association between number of
interstitial AI segments (FIG. 6A) or level of whole chromosome AI
(FIG. 7) and response to cisplatin.
[0351] Serous ovarian carcinoma is often treated with
platinum-based therapies. A publicly available SNP array data set
of ovarian carcinomas treated with cisplatin or carboplatin plus a
taxane (Etemadmoghadam et al. (2009) Clin. Cancer Res. 15,
1417-1427) was investigated and 33 cases of the serous subtype
treated after optimal surgical debulking (residual tumor <1 cm)
and reasonable tumor purity (>75%, estimated from SNP data) were
identified. NtAI,12 was determined by MCP analysis. In these
platinum-treated ovarian cancer cases, an association was found
between higher levels of telomeric AI in tumors and absence of
relapse within a year (FIG. 8A). The ROC analysis in the TNBC
cohort was used to define a cutoff value of NtAI,12 of at least 13
events, which gave the greatest sensitivity for the classification
of pCR to platinum therapy in the TNBC cohort. This cutoff was used
to classify the ovarian cancer cohort into high and low NtAI,12
groups and longer disease-free survival, a surrogate indicator of
higher sensitivity to platinum, was found in the high NtAI,12 group
(FIG. 8B).
[0352] Thus, chromosomal instability, manifested by high levels of
telomeric AI, characterize subsets of TNBC and ovarian cancer, and
further, higher levels of these changes predict specific
therapeutic vulnerabilities. Although sporadic TNBC appear similar
to BRCA1-associated breast cancer in the patterns of chromosomal
alterations and various other immuno-phenotypes and histological
features, the precise molecular defect(s) in maintenance of
chromosomal stability in these tumors is unknown. The results of
the examples described herein indicate that the burden of
chromosome rearrangements resulting from improperly repaired DNA
strand breaks are indicators of DNA repair defects that sensitize
cells to certain chemotherapies (FIG. 9). As such, levels of
allelic imbalance provide an accurate biomarker for predicting
tumor sensitivity to treatment with genotoxic agents, irrespective
of knowledge of the causative DNA repair lesion.
Example 3
[0353] In this study, we utilized two preoperative clinical trials
in women with triple negative breast cancer treated with cisplatin,
in which pathologic response at the time of surgery provided an
experimental endpoint. Sporadic triple negative breast cancers are
heterogeneous in their responses to platinum salts,
chemotherapeutic agents that depend in part on DNA repair defects
for their cytotoxic activity (Sakai, W., et al. Secondary mutations
as a mechanism of cisplatin resistance in BRCA2-mutated cancers.
Nature 2008; 451: 1116-1120; Edwards, S. L., et al. Resistance to
therapy caused by intragenic deletion in BRCA2. Nature 2008; 451:
1111-1115). Lesions in DNA repair caused by BRCA1 or BRCA2
dysfunction lead to platinum sensitivity; we reasoned that the
types of chromosomal aberrations arising in the context of BRCA
dysfunction might also be associated with platinum sensitivity in
wtBRCA (wild type BRCA) cancers. Based on results in cell lines, we
chose to enumerate one such chromosomal abnormality, telomeric
allelic imbalance (NtAI) in pre-treatment tumor genomes and to
relate this to pathologic response after cisplatin, an exemplary
platinum comprising therapy.
[0354] NtAI was associated with response to platinum treatment in
our TNBC cisplatin trials and in platinum treated serous ovarian
cancer and suggests the burden of this genomic abnormality exposes
an underlying deficiency of DNA repair in the platinum-sensitive
subset of these cancers. Allelic imbalance propagated from a given
chromosomal location to the telomere suggests the operation of
error-prone processes giving rise to abnormal crossover or template
switching events, rather than error-free DNA repair.
[0355] We found the breakpoints of tAI regions are non-random and
enriched for CNVs. This pattern also suggests defective DNA repair.
CNVs are associated with other repeat sequences such as Alu
repeats, are concentrated in pericentromeric and subtelomeric
regions, and are associated also with common fragile sites (McVean,
G. What drives recombination hotspots to repeat DNA in humans?
Philos Trans R Soc Lond B Biol Sci 2010; 365: 1213-1218; Puliti,
A., et al. Low-copy repeats on chromosome 22q11.2 show replication
timing switches, DNA flexibility peaks and stress inducible
asynchrony, sharing instability features with fragile sites. Mutat
Res 2010; 686: 74-83). These repeat elements are thought to result
in replication "slow zones" prone to replication stalling and
formation of DNA double strand breaks (Richard, G. F., Kerrest, A.,
and Dujon, B. Comparative genomics and molecular dynamics of DNA
repeats in eukaryotes. Microbiol Mol Biol Rev 2008; 72: 686-727;
Cha, R. S. and Kleckner, N. ATR homolog Mec1 promotes fork
progression, thus averting breaks in replication slow zones.
Science 2002; 297: 602-606). Furthermore, downregulation of Rad51
or inhibition of BRCA1 increases the fragility at such sites when
cells are under replication stress (Arlt, M. F., et al., BRCA1 is
required for common-fragile-site stability via its G2/M checkpoint
function. Mol Cell Biol 2004; 24: 6701-6709; Schwartz, M., et al.
Homologous recombination and nonhomologous end-joining repair
pathways regulate fragile site stability. Genes Dev 2005; 19:
2715-2726). The observed association of low BRCA1 expression levels
in many tumors with high NtAI suggests deficient homologous
recombination, impaired S or G2/M checkpoint function, or a
combination of these factors underlies the generation of this type
of genomic abnormality.
[0356] Cisplatin forms inter-strand crosslinks on DNA that lead to
stalled replication forks and DNA double stand breaks that must be
repaired if the cell is to survive. It is likely these breaks are
repaired using similar mechanisms to those employed at stalled
replication forks and DNA breaks generated at sites of CNVs.
Therefore, high pre-treatment NtAI identifies tumors unable to
accurately repair breaks and restart stalled replication forks at
sites of CNV. These same tumors are also unable to contend with
stalled forks at sites of cisplatin crosslinks.
[0357] While allelic imbalance at sites of CNV may reflect
inefficient error-free repair, other explanations should be
considered. Both triple negative cohorts showed a significant
relationship between NtAI and pathologic response to cisplatin
chemotherapy. Nevertheless, there were patients in both trials
whose tumors showed poor response to cisplatin therapy despite
having high NtAI. Similarly, a few of the BRCA1-mutated ovarian
cancers had high NtAI yet were resistant to platinum therapy. Since
NtAI is a summation of ongoing and past DNA lesions, resistance
mechanisms acquired after generation of tAI would confound the
relationship between NtAI and response. In carriers of BRCA1 or
BRCA2 mutations, some tumors that become resistant to platinum
agents carry a reversion mutation that partially or completely
restores BRCA1 or BRCA2 function and restores homologous
recombination (Sakai, W., et al. Secondary mutations as a mechanism
of cisplatin resistance in BRCA2-mutated cancers. Nature 2008; 451:
1116-1120; Edwards, et al. Resistance to therapy caused by
intragenic deletion in BRCA2. Nature 2008; 451: 1111-1115; Swisher,
E. M., et al., Secondary BRCA1 mutations in BRCA1-mutated ovarian
carcinomas with platinum resistance. Cancer Res 2008; 68:
2581-2586). Reversion has also been seen in a cell line with a
BRCA2 mutation selected for PARP inhibitor resistance (Edwards, et
al. Resistance to therapy caused by intragenic deletion in BRCA2.
Nature 2008; 451: 1111-1115). Reversion mutations and in cis
compensating mutations were observed in Fanconi anemia patients,
resulting in improvement in their bone marrow function (Kalb, R.,
et al., Fanconi anemia: causes and consequences of genetic
instability. Genome Dyn 2006; 1:218-242). Inactivation of TP53BP1
restores the balance between homologous recombination and
non-homologous end joining in BRCA1-mutated cells and renders them
resistant to PARP inhibitors (Bouwman, P., et al. 53BP1 loss
rescues BRCA1 deficiency and is associated with triple-negative and
BRCA-mutated breast cancers. Nat Struct Mol Biol 2010; 17: 688-695;
Bunting, S. F., et al. 53BP1 inhibits homologous recombination in
Brca1-deficient cells by blocking resection of DNA breaks. Cell
2010; 141: 243-254). Finally, drug transporters may prevent
accumulation of platinum agents in tumor cells (Burger, H., et al.,
Drug transporters of platinum-based anticancer agents and their
clinical significance. Drug Resist Updat 2011). Therefore,
reversion of or compensation for a preexisting DNA repair defect
may generate a tumor with high NtAI but resistance to platinum
treatment; other platinum resistance mechanisms unrelated to DNA
repair would have the same effect.
[0358] Our analysis suggests an outline of the molecular taxonomy
of TNBC and ovarian cancer with respect to DNA repair and drug
sensitivity. Most platinum resistant breast or ovarian cancers are
tumors with repair proficiency and low NtAI. Two subsets of wtBRCA
tumors possess high NtAI and are sensitive to platinum-containing
drugs. In one of these subsets, repair deficiency may be the
consequence of low BRCA1 expression and in the other subset, repair
may be crippled by mechanisms that do not depend upon BRCA1
expression. These observations will no doubt be further refined;
inclusion of reversion mutations, compensations by other events in
DNA repair pathways, other mechanisms of drug resistance, and other
as yet unappreciated factors may help to enhance our prediction of
drug sensitivity in the future.
[0359] In conclusion, a summary measure of telomeric chromosome
aberrations in the tumor genome, NtAI, predicts sensitivity to
platinum treatment. Our findings implicate NtAI as a marker of
impaired DNA double-strand break repair. Assays to determine NtAI
are feasible using formalin fixed paraffin embedded tumor material
and recent algorithms such as ASCAT permit accurate determination
of copy number and allelic imbalance in a majority of samples
despite low tumor cell content. NtAI may prove useful in predicting
response to a variety of therapeutic strategies exploiting
defective DNA repair.
[0360] Materials and Methods
[0361] Cell lines and drug sensitivity assays: Drug sensitivity
measurements in breast cancer cell lines BT20, BT549, HCC1187,
HCC1143, MDA-MB-231, MDA-MB-468, HCC38, MDA-MB-453 (triple
negative), CAMA-1, MCF7, T47D (ER positive), BT474, HCC1954 and
MDA-MB-361 (HER2positive) was originally generated for a separate
study in which it was reported as "data not shown" in a recently
published manuscript (Li, Y., et al. Amplification of LAPTM4B and
YWHAZ contributes to chemotherapy resistance and recurrence of
breast cancer. Nat Med 2010; 16: 214-218). Briefly, cells were
exposed to a series of concentrations of various chemotherapeutic
agents for 48 hours. Viable cell number was quantified using
CellTiter 96 AQueous One Solution Cell Proliferation Assay
according to the manufacturer's instructions (Promega). Drug
sensitivity was quantified as the dose of drug resulting in a 50%
reduction of growth (IC50). We found MCF7 to be highly resistant to
all of the chemotherapeutic agents tested, consistent with its
reported caspase-3 deficiency and resistance to drug induced
apoptosis (Yang, X. H., et al., Reconstitution of caspase 3
sensitizes MCF-7 breast cancer cells to doxorubicin- and
etoposide-induced apoptosis. Cancer Res 2001; 61: 348-354). In our
analyses with measures of genomic aberration, MCF7 was the only
clear outlier and for these reasons, was excluded from our
analyses.
[0362] Breast Cancer Cohorts and Assessment of Therapeutic
Response
[0363] For this study, subjects were included for analysis of
response to cisplatin if they progressed on therapy or if they
received at least 3 of 4 cycles of the planned cisplatin therapy,
had received no other non-protocol therapy before surgery, and if
an adequate amount of tumor was available from the pre-treatment
biopsy. Therapeutic response was measured using the
semiquantitative Miller-Payne grading system, which estimates the
percent reduction in invasive tumor volume and cellularity based on
pathological assessment of surgical samples after therapy (Ogston,
K. N., et al., A new histological grading system to assess response
of breastcancers to primary chemotherapy: prognostic significance
and survival. Breast 2003; 12: 320-327). Cisplatin-1 consists of 28
mainly sporadic TNBC patients treated with preoperative cisplatin
monotherapy, of whom 4 progressed on therapy and 24 completed 4
cycles of cisplatin therapy (Silver, D. P., et al. Efficacy of
neoadjuvant Cisplatin in triple-negative breast cancer. J Clin
Oncol 2010; 28: 1145-1153). Cisplatin-2 consists of 51 TNBC
patients treated with preoperative cisplatin and bevacizumab, of
which one patient progressed on therapy and 44 patients completed 4
cycles of cisplatin therapy prior to surgery (Ryan, P. D., et al.
Neoadjuvant cisplatin and bevacizumab in triple negative breast
cancer (TNBC): Safety and Efficacy. J Clin Oncol 2009; 27: 551).
Two patients included in this study were taken to surgery after
completing 3 cycles of cisplatin therapy due to the development of
toxicity; in both cases there was no appreciable pathologic
response in the excised tumor after 3 cycles of cisplatin.
[0364] Preparation of Breast Cancer Samples
[0365] For both trials, core biopsies of tumor were obtained before
initiation of treatment. Adequate tumor for analysis was present
for 27 of 28 subjects in Cisplatin-1 and 37 of 51 subjects in
Cisplatin-2. H&E stained tissue sections of pre-treatment core
needle biopsies were examined microscopically; for all biopsies for
which enrichment was deemed feasible, sections were manually
microdissected using an 18-gauge needle. DNA was extracted by
proteinase K and RNase A digestions, phenol/chloroform extraction,
and ethanol precipitation. Paired normal DNA from patients was
obtained from peripheral blood lymphocytes for all cases in
Cisplatin-1 and from 10 cases in Cisplatin-2.
[0366] TCGA Ovarian and Breast Cancer Cohorts
[0367] Public SNP array data, expression data, and clinical
annotation data was obtained for the TCGA ovarian (Bell, D., et
al., Integrated genomic analyses of ovarian carcinoma. Nature 2011;
474: 609-615) and breast cancer cohorts from the TCGA web site
(http://tcga-data.nci.nih.gov/tcga/). BRCA1 and BRCA2 mutation
status for the ovarian cancers was obtained from cBIO data portal
(http://bit.ly/wpwRXd). In the ovarian cohort, we identified 218
samples with SNP data that passed ASCAT, BRCA mutation status, and
interpretable clinical annotations for treatment and outcomes
indicating initial treatment with adjuvant platinum-based
chemotherapy, predominantly the combination of carboplatin and
docetaxel. We classified "treatment sensitive" as those annotated
as partial or complete response to initial treatment and no
progression or recurrence within 6 months of initial treatment
(n=187); "treatment resistant" were those annotated as stable or
progressive disease on initial therapy or disease recurrence or
progression within 6 months (n=31). In the breast cohort, we
identified 78 samples with matched gene expression and SNP data
that passed ASCAT, which were classified as ER-/HER2- based on
clustering of the ESR1 and ERBB2 gene (see supplementary
methods).
[0368] Genotyping and Copy Number Analysis
[0369] DNA was sent to Affymetrix, Inc. (Santa Clara, Calif.) for
determination of genotypes using the molecular inversion probe
based genotyping system, OncoScan FFPE Express (Wang, Y., et al.
Analysis of molecular inversion probe performance for allele copy
number determination. Genome Biol 2007; 8: R246). The commercial
assay, which determines genotype of 330,000 SNPs was used for
analysis of the Cisplatin-2 trial. An early version of the OncoScan
assay which genotypes 42,000 SNPs was used for the Cisplatin-1
trial. Allele signal intensity and genotypes from the OncoScan
genotyping assay were processed and provided to us by Affymetrix.
The OncoScan SNP genotype data for the cisplatin therapy trials is
submitted to the NCBI GEO database under accession GSE28330. Public
SNP array raw data for the breast cancer cell lines were obtained
from the Sanger Institute Catalogue Of Somatic Mutations In Cancer
web site, world wide web "dot" sanger "dot" ac "dot" uk/cosmic
(Bamford, S., et al. The COSMIC (Catalogue of Somatic Mutations in
Cancer) database and website. Br J Cancer 2004; 91: 355-358),
public SNP array data from an independent breast cancer cell line
study, Heiser et al. (Heiser, L. M., et al. Subtype and pathway
specific responses to anticancer compounds in breast cancer. Proc
Natl Acad Sci USA 2011), and public SNP array data from the TCGA
ovarian (Bell, D., et al., Integrated genomic analyses of ovarian
carcinoma. Nature 2011; 474: 609-615) and breast cancer cohorts
were preprocessed by the AROMAv2 and CalMaTe algorithms (Bengtsson,
H., Wirapati, P., and Speed, T. P. A single-array preprocessing
method for estimating full-resolution raw copy numbers from all
Affymetrix genotyping arrays including GenomeWideSNP 5 & 6.
Bioinformatics 2009; 25: 2149-2156) and, when a paired normal
samples was available, TumorBoost (Bengtsson, H., Neuvial, P., and
Speed, T. P. TumorBoost: normalization of allele-specific tumor
copy numbers from a single pair of tumor-normal genotyping
microarrays. BMC Bioinformatics 2010; 11: 245). Processed genotype
data from OncoScan genotyping and public SNP array data was
analyzed for allele-specific copy numbers and tumor cell content by
the algorithm "Allele-specific copy number analysis of tumors",
ASCAT (Van Loo, P., et al. Allele-specific copy number analysis of
tumors. Proc Natl Acad Sci USA 2010; 107: 16910-16915). ASCAT is
designed to correct for normal cell contamination and tumor cell
ploidy, but occasionally fails to fit a model to a given sample. In
this study, ASCAT failed to process 3 of 14 cell lines from Sanger,
15 of 42 cell lines from Heiser et al., and 5 of 37 samples from
the Cisplatin-2 trial. Allelic imbalance was defined as any time
the copy number of the two alleles were not equal, and at least one
allele was present (FIG. 16). To ensure that all trial cases were
comparable, we eliminated cases estimated by ASCAT to have less
than 36% tumor cell content, the highest level of normal cell
admixture in the Cisplatin-1 trial, which was the trial with an
overall greater tumor purity. Thus we included all 27 samples with
SNP array data from the Cisplatin-1 trial, 26 out of 32 samples
with SNP array data that passed ASCAT from the Cisplatin-2
trial.
[0370] A minimum number of consecutive probes showing an aberration
was required in order to call regions of AI and CNA with
confidence. To ensure similar aberration detection across the three
platforms that were used, the minimum number of probes required to
define a region of aberration was set to be proportional to the
overall SNP density of the platform. The probe densities of the
platforms were 42,000/genome OncoScan (prototype), 330,000/genome
OncoScan FFPE Express, and 900,000/genome SNP6.0 for an approximate
ratio of 1:8:20. Minimum probe requirements of 25 probes for 42k
OncoScan prototype, 200 probes for 330k OncoScan FFPE Express, and
500 probes for SNP6.0 platform were chosen based on optimizing for
correlation of aberration measurement in a subset of samples with
replicate data generated on both versions of the OncoScan platform
(See also Supplementary Methods).
[0371] Telomeric AI and telomeric CNA are defined as regions that
extend to one of the sub-telomeres but do not cross the centromere.
Copy number of telomeric AI regions was defined as the mean copy
number of the probes mapping to the region. Copy loss was defined
as a mean of less than 1.5 copies and copy gain was defined as a
mean of greater than 2.5 copies. Association between NtAI and
response to cisplatin in the TNBC clinical trials was measured by
the AUC of the ROC curve for binary response. Statistical
significance was assessed by Wilcoxon's rank sum test. All P values
are two-sided.
[0372] Enrichment of Copy Number Variants at Site of DNA
Breakpoints
[0373] The genomic location of common copy number variants (CNVs)
was acquired from the Database of Genomic Variants
(http://projects.tcag.ca/variation/). Mapping for HG17 and HG18 was
acquired in order to match the SNP probe mapping of the 42K
prototype and 330K commercial OncoScan platforms, respectively.
CNVs were considered associated with a breakpoint if they
overlapped within a 25 kb window on either side of the breakpoint.
To test for enrichment, we performed 1000 permutations for each
cohort, where we randomly shuffled the location of the DNA
breakpoints based on the location of the SNP probes, and determined
how many were associated with CNVs.
[0374] BRCA1 Transcript Quantitation and Promoter Methylation
Analysis
[0375] BRCA1 exon 16/17 and RPLPO (control) quantitative polymerase
chain reaction assay was performed as previously described (Silver,
D. P., et al. Efficacy of neoadjuvant Cisplatin in triple-negative
breast cancer. J Clin Oncol 2010; 28: 1145-1153) using amplified
tumor cDNA generated using Ovation RNA Amplification System V2 kit
(NuGen Technologies, Inc., San Carlos, Calif.). BRCA1 promoter
methylation assay was performed as previously described (Silver, D.
P., et al. Efficacy of neoadjuvant Cisplatin in triple-negative
breast cancer. J Clin Oncol 2010; 28: 1145-1153).
[0376] BRCA1 Expression in Public TCGA Cohorts.
[0377] Public normalized and summarized Agilent based gene
expression data was acquired from the TCGA for all breast cancer
samples (level 3). Raw Affymetrix CEL files were obtained for
ovarian cancer samples (level 1). Expression data for all TCGA
ovarian cancer samples were normalized and summarized using RMA,
and the probe set "204531_s_at" was identified as the optimum probe
set for measuring BRCA1 expression using the R package "JetSet"
(Li, Q., et al., Jetset: selecting the optimal microarray probe set
to represent a gene. BMC Bioinformatics 2011; 12: 474).
INCORPORATION BY REFERENCE
[0378] All publications, patents, and patent applications mentioned
in the specification, including the examples, are hereby
incorporated by reference in their entirety as if each individual
publication, patent or patent application was specifically and
individually indicated to be incorporated by reference. In case of
conflict, the present application, including any definitions
herein, will control.
[0379] Also incorporated by reference in their entirety are any
polynucleotide and polypeptide sequences which reference an
accession number correlating to an entry in a public database, such
as those maintained by The Institute for Genomic Research (TIGR) on
the world wide web and/or the National Center for Biotechnology
Information (NCBI) on the world wide web.
[0380] Equivalents
[0381] Those skilled in the art will recognize, or be able to
ascertain using no more than routine experimentation, many
equivalents to the specific embodiments of the invention described
herein. Such equivalents are intended to be encompassed by the
following paragraphs.
* * * * *
References