Method and material for evaluating homologous recombination deficiency

Abstract

To provide a method and a material involved in evaluating a sample regarding homologous recombination deficiency (HRD) or the presence of HRD signature.SOLUTION: An in vitro method for predicting patient reaction to a DNA damaging agent, anthracycline, a topoisomerase I inhibitor, or a cancer therapeutic regimen containing PARP inhibitor includes: a step of determining, in a sample including a cancer cell, the number of indicator CA regions containing at least two types selected from indicator LOH region, indicator TAI region or indicator LST region in at least a pair of human chromosomes of a cancer cell of a cancer patient; and a step of diagnosing that a patient who has a larger number of indicator LOH regions, indicator TAI regions or indicator LST regions in the sample than a reference number is highly likely to react the cancer therapeutic regimen.SELECTED DRAWING: None

Description

Technical Field

[0001] Related Applications This application claims priority to U.S. Provisional Application No. 61 / 809,105, filed on April 05, 2013, and No. 61 / 913,762, filed on December 09, 2013, the entire contents of which are incorporated herein by reference.

[0002] 1. Technical Field This document relates to methods and materials involved in evaluating a sample (e.g., cancer cells or nucleic acids derived therefrom) for homologous recombination deficiency (HRD) (e.g., an HRD signature) based on the detection of specific chromosomal aberrations (“CAs”). For example, this document provides methods and materials for detecting CA regions to determine whether a cell (e.g., a cancer cell) has HRD (e.g., exhibits an HRD signature). This document also provides materials and methods for identifying cancer patients likely to respond to a particular cancer treatment regimen based on the presence, absence, or severity of HRD. Throughout this document, unless otherwise indicated, HRD and homologous-dependent repair (HDR) deficiency are used synonymously.

Background Art

[0003] 2. Background Information Cancer is a major public health problem, with 562,340 cancer deaths in the United States in 2009 alone. American Cancer Society, Cancer Facts & Figures 2009 (available on the American Cancer Society website). One of the most important challenges in cancer treatment is to discover clinically useful characteristics associated with a patient's cancer and then, based on these characteristics, implement a treatment plan most suitable for the patient's cancer. Although this field of personalized medicine has advanced, there is still a great need for better molecular diagnostic tools for characterizing a patient's cancer.

Summary of the Invention

[0004] Summary As a whole, one aspect of the present invention features a method for evaluating homologous recombination deficiency (HRD) in cancer cells or DNA derived therefrom (e.g., genomic DNA). In some embodiments, the method comprises, or consists essentially of, (a) detecting in a sample or DNA derived therefrom, a CA region (as defined herein) in at least one pair of human chromosomes (e.g., any pair of human chromosomes other than the human X / Y sex chromosome pair) in the sample or DNA derived therefrom, and (b) determining the number, size (e.g., length), and / or characteristics of the CA region. In some embodiments, the CA regions are analyzed in several chromosome pairs representative of the entire genome (e.g., analyzing chromosomes sufficient such that the number and size of the CA regions are expected to be representative of the number and size of CA regions across the entire genome).

[0005] Various aspects of the present invention involve using a combined analysis of two or more types of CA regions to evaluate (e.g., detect) HRD in a sample. Three types of CA regions useful in such methods include: (1) chromosomal regions showing loss of heterozygosity (a "LOH region" as defined herein), (2) chromosomal regions showing telomere allelic imbalance (a "TAI region" as defined herein), and (3) chromosomal regions showing large-scale transitions (a "LST region" as defined herein). CA regions having a particular size, chromosomal location, or characteristic (e.g., an "indicator CA region" as defined herein) are particularly useful in various aspects of the present invention described herein.

[0006] Accordingly, in one aspect, the present invention provides a method for evaluating (e.g., detecting) HRD in a sample, comprising: (1) determining the total number of LOH regions having a particular size or characteristic (e.g., "indicator LOH regions" as defined herein) in the sample; (2) determining the total number of TAI regions having a particular size or characteristic (e.g., "indicator TAI regions" as defined herein) in the sample; and (3) evaluating the HRD in the sample based at least in part on the determinations made in (1) and (2). In another aspect, the present invention provides a method for evaluating (e.g., detecting) HRD in a sample, comprising: (1) determining the total number of LOH regions having a particular size or characteristic (e.g., "indicator LOH regions" as defined herein) in the sample; (2) determining the total number of LST regions having a particular size or characteristic (e.g., "indicator LST regions" as defined herein) in the sample; and (3) evaluating the HRD in the sample based at least in part on the determinations made in (1) and (2). In yet another aspect, the present invention provides a method for evaluating (e.g., detecting) HRD in a sample, comprising: (1) determining the total number of TAI regions having a particular size or characteristic (e.g., "indicator TAI regions" as defined herein) in the sample; (2) determining the total number of LST regions having a particular size or characteristic (e.g., "indicator LST regions" as defined herein) in the sample; and (3) evaluating the HRD in the sample based at least in part on the determinations made in (1) and (2).In another aspect, the present invention provides a method for evaluating (e.g., detecting) HRD in a sample, the method comprising: (1) determining the total number of LOH regions having a particular size or characteristic (e.g., an "indicator LOH region" as defined herein) in the sample; (2) determining the total number of TAI regions having a particular size or characteristic (e.g., an "indicator TAI region" as defined herein) in the sample; (3) determining the total number of LST regions having a particular size or characteristic (e.g., an "indicator LST region" as defined herein) in the sample; and (4) evaluating (e.g., detecting) HRD in the sample based at least in part on the determinations made in (1), (2), and (3).

[0007] In one aspect, the present invention provides a method for diagnosing the presence or absence of HRD in a patient sample, the method comprising: (1) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of LOH regions having a particular size or characteristic (e.g., an "indicator LOH region" as defined herein) in the sample; (2) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of TAI regions having a particular size or characteristic (e.g., an "indicator TAI region" as defined herein) in the sample; and (3) either (a) diagnosing that HRD is present in the patient sample if the number from (1) and / or the number from (2) exceeds some reference number; or (b) diagnosing that HRD is absent in the patient sample if neither the number from (1) nor the number from (2) exceeds some reference number. In another aspect, the present invention provides a method for diagnosing the presence or absence of HRD in a patient sample, the method comprising: (1) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of LOH regions having a particular size or characteristic (e.g., an "indicator LOH region" as defined herein) in the sample; (2) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of LST regions having a particular size or characteristic (e.g., an "indicator LST region" as defined herein) in the sample; and (3) either (a) diagnosing that HRD is present in the patient sample if the number from (1) and / or the number from (2) exceeds some reference number; or (b) diagnosing that HRD is absent in the patient sample if neither the number from (1) nor the number from (2) exceeds some reference number.In another aspect, the present invention provides a method for diagnosing the presence or absence of HRD in a patient sample, the method comprising: (1) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of TAI regions (e.g., "indicator TAI regions" as defined herein) having a particular size or characteristic in the sample; (2) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of LST regions (e.g., "indicator LST regions" as defined herein) having a particular size or characteristic in the sample; and (3) either (a) diagnosing that HRD is present in the patient sample if the number from (1) and / or the number from (2) exceeds some reference number; or (3)(b) diagnosing that HRD is not present in the patient sample if neither the number from (1) nor the number from (2) exceeds some reference number. In another aspect, the present invention provides a method for diagnosing the presence or absence of HRD in a patient sample, the method comprising: (1) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of LOH regions (e.g., "indicator LOH regions" as defined herein) having a particular size or characteristic in the sample; (2) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of TAI regions (e.g., "indicator TAI regions" as defined herein) having a particular size or characteristic in the sample; (3) analyzing (e.g., assaying) one or more patient samples to determine (e.g., detect) the total number of LST regions (e.g., "indicator LST regions" as defined herein) having a particular size or characteristic in the sample; and (3) either (a) diagnosing that HRD is present in the patient sample if the number from (1), the number from (2) and / or the number from (3) exceeds some reference number; or (3)(b) diagnosing that HRD is not present in the patient sample if none of the numbers from (1), (2) or (3) exceeds some reference number.

[0008] Various aspects of the present invention involve using the average (e.g., arithmetic mean) of three types of CA regions to evaluate (e.g., detect) HRD in a sample. Three types of CA regions useful in such methods include: (1) chromosomal regions showing loss of heterozygosity (the "LOH regions" as defined herein), (2) chromosomal regions showing telomere allelic imbalance (the "TAI regions" as defined herein), and (3) chromosomal regions showing large-scale transitions (the "LST regions" as defined herein). CA regions having a particular size or characteristic (e.g., the "indicator CA regions" as defined herein) may be particularly useful in various aspects of the present invention described herein. Thus, in one aspect, the present invention is a method for evaluating (e.g., detecting) HRD in a sample, comprising: (1) determining the total number of LOH regions having a particular size or characteristic (e.g., the "indicator LOH regions" as defined herein) in the sample; (2) determining the total number of TAI regions having a particular size or characteristic (e.g., the "indicator TAI regions" as defined herein) in the sample; (3) determining the total number of LST regions having a particular size or characteristic (e.g., the "indicator LST regions" as defined herein) in the sample; (4) calculating the average (e.g., arithmetic mean) of the determinations made in (1), (2), and (3); and (5) evaluating the HRD in the sample based at least in part on the calculated average (e.g., arithmetic mean) obtained in (4).

[0009] In some embodiments, the assessment (e.g., detection) of HRD is based on a score (a "CA region score" as defined herein) derived from or calculated (e.g., representative of or corresponding to) the detected CA region. The score will be described in further detail below. In some embodiments, HRD is detected when the CA region score for a sample exceeds some threshold (e.g., a reference score or an index CA region score), and optionally HRD is not detected when the CA region score for the sample (e.g., a reference score or an index CA region score, which may be the same threshold as for positive detection in some embodiments) does not exceed some threshold. One of ordinary skill in the art will readily appreciate that the score could be reversed in direction (e.g., HRD is detected when the CA region score is less than a particular threshold and not detected when the score exceeds a particular threshold) in the present disclosure.

[0010] In some embodiments, the CA region score is a combination of scores derived from or calculated (e.g., representative of or corresponding to) two or more of (1) the detected LOH region (a "LOH region score" as defined herein), (2) the detected TAI region (a "TAI region score" as defined herein), and / or (3) the detected LST region (a "LST region score" as defined herein). In some embodiments, the LOH region score and the TAI region score are combined as follows to obtain the CA region score: CA region score = A * (LOH region score) + B * (TAI region score)

[0011] In some embodiments, the LOH region score and the TAI region score are combined as follows to obtain the CA region score: CA region score = 0.32 * (LOH region score) + 0.68 * (TAI region score)

[0012] In some embodiments, the LOH region score and the LST region score are combined as follows to obtain a CA region score: CA region score = A * (LOH region score)+B * (LST region score)

[0013] In some embodiments, the TAI region score and the LST region score are combined as follows to obtain a CA region score: CA region score = A * (TAI region score)+B * (LST region score)

[0014] In some embodiments, the LOH region score, the TAI region score and the LST region score are combined as follows to obtain a CA region score: CA region score = A * (LOH region score)+B * (TAI region score)+C * (LST region score)

[0015] In some embodiments, the LOH region score, the TAI region score and the LST region score are combined as follows to obtain a CA region score: CA region score = 0.21 * (LOH region score)+0.67 * (TAI region score)+0.12 * (LST region score)

[0016] In some embodiments, the CA region score is a combination of scores derived from or calculated (e.g., representative of or corresponding to) the average (e.g., arithmetic mean) of (1) the detected LOH region (the "LOH region score" as defined herein), (2) the detected TAI region (the "TAI region score" as defined herein), and / or (3) the detected LST region (the "LST region score" as defined herein) to obtain the CA region score: TIFF2025090619000001.tif10162

[0017] In another aspect, the present invention provides a method for predicting the status of BRCA1 and BRCA2 genes in a sample. Such a method is similar to the above method, except that the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these is used to evaluate (e.g., detect) BRCA1 and / or BRCA2 deficiency in the sample. In another aspect, the present invention provides a method for predicting the response of a cancer patient to a cancer treatment regimen comprising a DNA damaging agent, anthracycline, topoisomerase I inhibitor, radiation, and / or PARP inhibitor. Such a method is similar to the above method, except that the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these is used to predict the likelihood that a cancer patient will respond to the cancer treatment regimen. In some embodiments, the patient is an untreated patient. In another aspect, the present invention provides a method for treating cancer. Such a method is similar to the above method, except that a specific treatment regimen is administered (recommended, prescribed, etc.) based at least in part on the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these. In another aspect, the present invention features the use of one or more drugs selected from the group consisting of DNA damaging agents, anthracyclines, topoisomerase I inhibitors, and PARP inhibitors in the manufacture of a medicament useful for treating cancer in a patient identified as having (or having had) cancer cells determined to have the HRD (e.g., HRD signature) described herein. In another aspect, the present document features a method for evaluating a sample with respect to the presence of mutations within genes originating from HDR. Such a method is similar to the above method, except that the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these is used to detect the presence (or absence) of mutations within genes originating from HDR.

[0018] In another aspect, the present invention provides a method for evaluating a patient. The method comprises: (a) determining whether the patient has (or had) cancer cells that exceed the reference number of CA regions (or, for example, a CA region score that exceeds a reference CA region score); and (b) (1) diagnosing that the patient has cancer cells associated with HRD if it is determined that the patient has (or had) cancer cells that exceed the reference number of CA regions (or, for example, a CA region score that exceeds a reference CA region score); or (b) (2) diagnosing that the patient does not have cancer cells associated with HRD if it is determined that the patient does not have (or has never had) cancer cells that exceed the reference number of CA regions (or, for example, the patient does not have (or has never had) cancer cells with a CA region score that exceeds a reference CA region score). The method may include or consist essentially of these steps.

[0019] In another aspect, the present invention features the use of a plurality of oligonucleotides capable of hybridizing to a plurality of polymorphic regions of human genomic DNA in the manufacture of a diagnostic kit that is useful for determining the total number or combined length of CA regions in at least one pair of chromosomes (or DNA derived therefrom) in a sample obtained from a cancer patient, and is also useful for detecting (a) HRD or the likelihood of HRD (e.g., an HRD signature) in the sample, (b) a deletion (or the likelihood of a deletion) of the BRCA1 gene or the BRCA2 gene in the sample, or (c) the high likelihood that a cancer patient will respond to a cancer treatment regimen comprising a DNA-damaging agent, anthracycline, topoisomerase I inhibitor, radiation, or PARP inhibitor.

[0020] In another aspect, the invention features a system for detecting HRD (e.g., an HRD signature) in a sample. The system includes, or consists essentially of, (a) a sample analyzer configured to generate a plurality of signals regarding genomic DNA of at least one pair of human chromosomes (or DNA derived therefrom) in the sample, and (b) a computer subsystem programmed to calculate the number or total length of CA regions in at least one pair of human chromosomes based on the plurality of signals. The computer subsystem can be programmed to compare the number or total length of CA regions to a reference number to detect (a) HRD or the likelihood of HRD (e.g., an HRD signature) in the sample, (b) a deletion (or the likelihood of a deletion) of the BRCA1 or BRCA2 gene in the sample, or (c) that a cancer patient is likely to respond to a cancer treatment regimen that includes a DNA damaging agent, anthracycline, topoisomerase I inhibitor, radiation, or PARP inhibitor. The system may include an output module configured to display (a), (b), or (c). The system may include an output module configured to display a recommendation regarding the use of a cancer treatment regimen.

[0021] In another aspect, the invention provides a computer program product embodied in a computer-readable medium that, when executed on a computer, provides instructions for detecting the presence or absence of any CA regions (the CA regions being optionally indicator CA regions) present on one or more of the human chromosomes other than the human X and Y sex chromosomes; and for determining the total number or total length of CA regions in one or more pairs of chromosomes. The computer program product may include other instructions.

[0022] In another aspect, the present invention provides a diagnostic kit. The kit includes at least 500 oligonucleotides capable of hybridizing to a plurality of polymorphic regions of human genomic DNA (or DNA derived therefrom); and includes or consists essentially of the computer program product provided herein. The computer program product may be incorporated into a computer-readable medium and, when executed on a computer, is for detecting the presence or absence of any CA region (the CA region is optionally an indicator CA region) present on one or more of the human chromosomes other than the human X and Y sex chromosomes; and for determining the total number or total length of CA regions in one or a plurality of pairs of chromosomes. The computer program product may include other instructions.

[0023] In some embodiments of any one or more of the aspects of the invention described in the foregoing paragraphs, any one or more of the following can be applied as appropriate. The CA region can be determined in at least 2, 5, 10 or 21 pairs of human chromosomes. The cancer cells can be ovarian cancer cells, breast cancer cells, lung cancer cells or esophageal cancer cells. The reference number can be 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 or 20 or more. Human chromosome 17 can be excluded from at least one pair of human chromosomes. The DNA-damaging agent can be cisplatin, carboplatin, oxalaplatin, or picoplatin, the anthracycline can be epirubincin or doxorubicin, the topoisomerase I inhibitor can be campothecin, topotecan or irinotecan, or the PARP inhibitor can be iniparib, olaparib or velapirib. The patient can be an untreated patient.

[0024] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Although methods and materials similar or equivalent to those described herein can be used in the practice or testing of the present invention, suitable methods and materials are described below. All publications, patent applications, patents, and other references mentioned herein are incorporated herein by reference in their entirety. In case of conflict, the present specification, including definitions, will control. In addition, the materials, methods, and examples are illustrative only and not intended to be limiting.

[0025] Details of one or more aspects of the invention are set forth in the following description and the accompanying drawings. The materials, methods, and examples are illustrative only and not intended to be limiting. Other features, objects, and advantages of the invention will be apparent from the description and drawings, and from the claims.

Brief Description of the Drawings

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DETAILED DESCRIPTION OF THE INVENTION

[0027] Detailed Description Overall, one aspect of the present invention features a method for assessing HRD in cancer cells or DNA derived therefrom (e.g., genomic DNA). In some embodiments, the method comprises (a) determining CA regions in at least one pair of human chromosomes or DNA derived therefrom in a sample or DNA derived therefrom; and (b) determining the number, size (e.g., length), and / or characteristics of said CA regions, or consisting essentially of these steps.

[0028] As used herein, "chromosomal aberration" or "CA" means a somatic change in the chromosomal DNA of a cell that is classified into at least one of three overlapping categories: LOH, TAI, or LST. Polymorphic loci (e.g., single nucleotide polymorphisms (SNPs)) within the human genome are generally heterozygous in an individual's germline because the individual typically receives one copy from the biological father and one copy from the biological mother. However, in somatic cells, this heterozygosity can change (through mutation) to homozygosity. This change from heterozygosity to homozygosity is called loss of heterozygosity (LOH). LOH can occur by several mechanisms. For example, in some cases, a locus on one chromosome may be deleted in a somatic cell. Since the locus present in the genome of the affected cell has only one copy (instead of two), the locus that still exists on the other chromosome (the other non-sex chromosome in the case of a male) becomes an LOH locus. This type of LOH event results in a decrease in copy number. In another case, a locus on one chromosome in a somatic cell (e.g., one of the non-sex chromosomes in the case of a male) may be replaced by a copy of the locus from the other chromosome, thereby eliminating any possible heterozygosity that may have been present within the replaced locus. In such a case, the locus that still exists on each chromosome becomes an LOH locus, which can be referred to as a copy neutral LOH locus. The determination of LOH and its use in the determination of HRD are described in detail in International Application No. PCT / US2011 / 040953 (published as WO / 2011 / 160063), the contents of which are hereby incorporated by reference in their entirety.

[0029] A broader class of chromosomal abnormalities that includes LOH is allelic imbalance. Allelic imbalance occurs when the relative copy number (i.e., the ratio of copies) at a specific locus in somatic cells differs from that in the germline. For example, if the germline has one copy of allele A and one copy of allele B at a specific locus, and the somatic cells have two copies of A and one copy of B, there is allelic imbalance at that locus because the ratio of copies in the somatic cells (2:1) differs from that in the germline (1:1). Since somatic cells have a different ratio of copies (1:0 or 2:0) from the germline (1:1), LOH is an example of allelic imbalance. However, allelic imbalance encompasses a greater variety of chromosomal abnormalities, such as a change from 2:1 in the germline to 1:1 in somatic cells; a change from 1:0 in the germline to 1:1 in somatic cells; a change from 1:1 in the germline to 2:1 in somatic cells, and so on. Analysis of regions of allelic imbalance at the telomeres of chromosomes is particularly useful in the present invention. Thus, a "telomeric allelic imbalance region" or "TAI region" is defined as a region that (a) extends towards one of the subtelomeres but (b) does not cross the centromere and is associated with allelic imbalance. The determination of TAI and its use in the determination of HRD are described in detail in International Application No. PCT / US2011 / 048427 (published as WO / 2012 / 027224), the contents of which are hereby incorporated by reference in their entirety.

[0030] A class of chromosomal abnormalities that are broader but still include LOH and TAI is referred to herein as large-scale transitions (“LST”). LST refers to any somatic copy number transition (i.e., discontinuity point) that exists along the length of a chromosome, which, after filtering out regions shorter than some maximum length (e.g., 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4 megabases, or more), exists between two regions having at least some minimum length (e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 megabases, or more). For example, after filtering out regions shorter than 3 megabases, if a somatic cell has a 1:1 copy number over at least 10 megabases, followed by a discontinuous point transition to a region of at least 10 megabases with a copy number of 2:2, for example, this is an LST. An alternative way to define the same phenomenon is as an LST region, which refers to a genomic region that has a stable copy number over at least some minimum length (e.g., at least 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, or 20 megabases) and has a discontinuity point (i.e., transition) where the copy number changes towards another region that also has at least this minimum length and is contiguous with it. For example, after filtering out regions shorter than 3 megabases, if a somatic cell has a region of at least 10 megabases with a copy number of 1:1, and at one boundary there is a discontinuous point transition to a region of at least 10 megabases with a copy number of 2:2, for example, and at the other boundary there is a discontinuous point transition to a region of at least 10 megabases with a copy number of 1:2, for example, this is two LSTs. Note that such copy number changes are not considered allelic imbalance (since the ratios of 1:1 and 2:2 copies are the same, i.e., there is no change in the ratio of copies), and this is more extensive than allelic imbalance.Its use in the determination of LST and HRD is described in detail in Popova et al., Ploidy and large-scale genomic instability consistently identify basal-like breast carcinomas with BRCA1 / 2 inactivation, CANCER RES. (2012) 72:5454-5462.

[0031] Various cut-offs for the LST score can be used for "near-diploid" and "near-tetraploid" tumors to separate BRCA1 / 2-intact samples from BRCA1 / 2-deficient samples. The LST score may sometimes increase with ploidy in both intact and deficient samples. As an alternative to using ploidy-specific cut-offs, in some embodiments, a modified LST score adjusted by ploidy, LSTm = LST - kP, can be used, where P is the ploidy and k is a constant. Based on a multivariate logistic regression analysis with deficiency as the outcome and LST and P as predictors, k = 15.5, provided that this conditions the best separation of intact and deficient samples (however, one of ordinary skill in the art can envision other values of k).

[0032] Chromosomal abnormalities can spread across numerous loci and define the extent of the chromosomal abnormality region, referred to herein as the "CA region." Such a CA region can be of any length (e.g., from a length of less than about 1.5 Mb to a length equal to the full length of the chromosome). The presence of many large CA regions ("indicator CA regions") indicates a defect in the cell's homologous-dependent repair (HDR) mechanism. The definition of what constitutes the region of CA, and thus the "indicator" region, for each type of CA (e.g., LOH, TAI, LST) depends on the unique characteristics of the CA. For example, an "LOH region" means at least some minimum number of consecutive loci that exhibit LOH, or some minimum continuous stretch of genomic DNA having consecutive loci that exhibit LOH. A "TAI region," on the other hand, means at least some minimum number of consecutive loci that exhibit allelic imbalance and extend from the telomere to the rest of the chromosome (or some minimum continuous stretch of genomic DNA having consecutive loci that exhibit allelic imbalance and extend from the telomere to the rest of the chromosome). For LST, it has already been defined with respect to a region of genomic DNA of at least some minimum size, and thus "LST" and "LST region" are used interchangeably in this document to refer to the minimum number of consecutive loci (or some minimum continuous stretch of genomic DNA) having the same copy number that border a discontinuity or transition from one copy number to another.

[0033] In some embodiments, a CA region (either a LOH region, a TAI region, or a LST region) is an indicator CA region (either an indicator LOH region, an indicator TAI region, or an indicator LST region) if it is at least 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 25, 30, 35, 40, 45, 50, 60, 70, 80, 90 or 100 megabases or longer in length. In some embodiments, an indicator LOH region is about 1.5, 5, 12, 13, 14, 15, 16, 17 megabases or longer (preferably 14, 15, 16 megabases or longer, more preferably 15 megabases or longer), but is a LOH region that is shorter than the total length of each chromosome within which the LOH region is located. Alternatively or additionally, the total combined length of such indicator LOH regions may be determined. In some embodiments, an indicator TAI region (a) extends into one of the subtelomeres, (b) does not cross the centromere, and (c) is 1.5, 5, 12, 13, 14, 15, 16, 17 megabases or longer (preferably 10, 11, 12 megabases or longer, more preferably 11 megabases or longer), and is a TAI region with allelic imbalance. Alternatively or additionally, the total combined length of such indicator TAI regions may be determined. Since the concept of LST already includes some region of minimum size (such minimum size is determined based on its ability to discriminate HRD from HDR intact samples), the indicator LST region used herein is the same as the LST region. Moreover, the LST region score can be derived from either the number of regions showing the above LST or the number of LST discontinuities.In some embodiments, the minimum length of the region of stable copy number that abuts the boundary at the LST discontinuity is at least 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19 or 20 megabases (preferably 8, 9, 10, 11 megabases or longer, more preferably 10 megabases), and the maximum region that remains without being filtered out is 0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4 megabases or less (preferably 2, 2.5, 3, 3.5 or 4 megabases or less, more preferably less than 3 megabases).

[0034] As used herein, a sample has an "HRD signature" if such sample has a number of indicator CA regions (as described herein) or CA region scores (as described herein) that exceeds the reference number as described herein, where such number or score in excess of the reference indicates homologous recombination deficiency.

[0035] Accordingly, the present invention generally involves detecting and quantifying indicator CA regions in a sample to determine whether cells in the sample (or cells from which the DNA in the sample is derived) have HRD. Often, this involves comparing the number of indicator CA regions (or a test value or score derived from or calculated to correspond to such number) to a reference or index number (or score).

[0036] Various aspects of the present invention involve using a combined analysis of two or more types of CA regions (including two or more types of indicator CA regions) to evaluate (e.g., detect, diagnose) HRD in a sample. Thus, in one aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining the total number (or combined length) of indicator LOH regions in the sample; (2) determining the total number (or combined length) of indicator TAI regions in the sample; and (3) determining the presence or absence of HRD in the sample (e.g., detecting, diagnosing) based at least in part on the determinations made in (1) and (2). In another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining the total number (or combined length) of indicator LOH regions in the sample; (2) determining the total number (or combined length) of indicator LST regions in the sample; and (3) determining the presence or absence of HRD in the sample (e.g., detecting, diagnosing) based at least in part on the determinations made in (1) and (2). In yet another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining the total number (or combined length) of indicator TAI regions in the sample; (2) determining the total number (or combined length) of indicator LST regions in the sample; and (3) determining the presence or absence of HRD in the sample (e.g., detecting, diagnosing) based at least in part on the determinations made in (1) and (2).In another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, the method comprising: (1) determining the total number (or combined length) of indicator LOH regions in the sample; (2) determining the total number of indicator TAI regions in the sample; (3) determining the total number (or combined length) of indicator LST regions in the sample; and (4) determining the presence or absence of HRD in the sample (e.g., detecting, diagnosing) based at least in part on the determinations made in (1), (2), and (3).

[0037] Various aspects of the present invention involve using a combined analysis of the average of three different CA regions to evaluate (e.g., detect, diagnose) HRD in a sample. Thus, in one aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, the method comprising: (1) determining the total number of LOH regions having a particular size or characteristic (e.g., "indicator LOH regions" as defined herein) in the sample; (2) determining the total number of TAI regions having a particular size or characteristic (e.g., "indicator TAI regions" as defined herein) in the sample; (3) determining the total number of LST regions having a particular size or characteristic (e.g., "indicator LST regions" as defined herein) in the sample; (4) calculating the average (e.g., arithmetic mean) of the determinations made in (1), (2), and (3); and (5) evaluating HRD in the sample based at least in part on the calculated average (e.g., arithmetic mean) obtained in (4).

[0038] As used herein, a "CA region score" means a test value or score (e.g., a score or test value derived from or calculated from, e.g., representative of or corresponding to, the number of indicator CA regions detected in a sample) derived from or calculated from an indicator CA region detected in a sample. Similarly, as used herein, an "LOH region score" is a subset of the CA region score and means a test value or score (e.g., a score or test value derived from or calculated from, e.g., representative of or corresponding to, the number of indicator LOH regions detected in a sample) derived from or calculated from an indicator LOH region detected in a sample, and the same is true for the TAI region score and the LST region score. Such scores may, in some embodiments, simply be the number of indicator CA regions detected in a sample. In some embodiments, the score is more complex and takes into account the length of each detected indicator CA region or subset of indicator CA regions.

[0039] As discussed above, the present invention generally involves combining the analysis of two or more types of CA region scores (which may include the number of such regions). Thus, in one aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining an LOH region score for the sample; (2) determining a TAI region score for the sample; and (3) (a) detecting (or diagnosing) HRD in the sample based at least in part on either an LOH region score exceeding a reference number or a TAI region score exceeding a reference number; or optionally (3) (b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on both an LOH region score not exceeding a reference number and a TAI region score not exceeding a reference number. In another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining an LOH region score for the sample; (2) determining an LST region score for the sample; and (3) (a) detecting (or diagnosing) HRD in the sample based at least in part on either an LOH region exceeding a reference number or an LST region score exceeding a reference number; or optionally (3) (b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on both an LOH region score not exceeding a reference number and an LST region score not exceeding a reference number. In yet another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining a TAI region score for the sample; (2) determining an LST region score for the sample; and (3) (a) detecting (or diagnosing) HRD in the sample based at least in part on either a TAI region score exceeding a reference number or an LST region score exceeding a reference number; or optionally (3) (b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on both a TAI region score not exceeding a reference number and an LST region score not exceeding a reference number.In another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, the method comprising: (1) determining a LOH region score for the sample; (2) determining a TAI region score for the sample; (3) determining a LST region score for the sample; and (4) (a) detecting (or diagnosing) HRD in the sample based at least in part on any of a LOH region score exceeding a reference number, a TAI region score exceeding a reference number, or a LST region score exceeding a reference number; or optionally (4) (b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on a LOH region score not exceeding a reference number, a TAI region score not exceeding a reference number, and a LST region score not exceeding a reference number.

[0040] In some embodiments, the CA region score is a combination of scores derived from or calculated from (e.g., representative of or corresponding to) two or more of (1) the detected LOH regions (the "LOH region score" as defined herein), (2) the detected TAI regions (the "TAI region score" as defined herein), and / or (3) the detected LST regions (the "LST region score" as defined herein). In some embodiments, the LOH region score and the TAI region score are combined as follows to obtain the CA region score: CA region score = A * (LOH region score) + B * (TAI region score)

[0041] In some embodiments, the LOH region score and the TAI region score are combined as follows to obtain the CA region score: CA region score = 0.32 * (LOH region score) + 0.68 * (TAI region score) Or CA region score = 0.34 * (LOH region score) + 0.66 * (TAI region score)

[0042] In some embodiments, the LOH region score and the LST region score are combined as follows to obtain a CA region score: CA region score = A * (LOH region score) + B * (LST region score)

[0043] In some embodiments, the LOH region score for a sample and the LST region score for a sample are combined as follows to obtain a CA region score: CA region score = 0.85 * (LOH region score) + 0.15 * (LST region score)

[0044] In some embodiments, the TAI region score and the LST region score are combined as follows to obtain a CA region score: CA region score = A * (TAI region score) + B * (LST region score)

[0045] In some embodiments, the LOH region score, the TAI region score, and the LST region score are combined as follows to obtain a CA region score: CA region score = A * (LOH region score) + B * (TAI region score) + C * (LST region score)

[0046] In some embodiments, the LOH region score, the TAI region score, and the LST region score are combined as follows to obtain a CA region score: CA region score = 0.21 * (LOH region score) + 0.67 * (TAI region score) + 0.12 * (LST region score) Or CA region score = [0.24] *(LOH region score) + [0.65] * (TAI region score) + [0.11] * (LST region score) Or CA region score = [0.11] * (LOH region score) + [0.25] * (TAI region score) + [0.12] * (LST region score)

[0047] In some embodiments, the CA region score is a combination of scores derived from or calculated (e.g., representative of or corresponding to) from the average (e.g., arithmetic mean) of (1) the detected LOH region (“LOH region score” as defined herein), (2) the detected TAI region (“TAI region score” as defined herein), and / or (3) the detected LST region (“LST region score” as defined herein) to obtain the CA region score from one of the following equations: TIFF2025090619000002.tif53161

[0048] In some embodiments, including some specifically exemplified herein, one or more of these coefficients (i.e., A, B, or C, or any combination thereof) is 1, and in some embodiments, all three coefficients (i.e., A, B, and C) are 1.

[0049] In some cases, the formula may not have all of the specified coefficients (and thus does not incorporate the corresponding variables). For example, the aspect mentioned immediately above may be applied to formula (2) where A in formula (2) is 0.95 and B in formula (2) is 0.61. C and D are considered inapplicable as these coefficients, and their corresponding variables are not seen in formula (2) (although clinical variables are incorporated into the clinical score seen in formula (2)). In some aspects, A is 0.9 - 1, 0.9 - 0.99, 0.9 - 0.95, 0.85 - 0.95, 0.86 - 0.94, 0.87 - 0.93, 0.88 - 0.92, 0.89 - 0.91, 0.85 - 0.9, 0.8 - 0.95, 0.8 - 0.9, 0.8 - 0.85, 0.75 - 0.99, 0.75 - 0.95, 0.75 - 0.9, 0.75 - 0.85, or 0.75 - 0.8. In some aspects, B is 0.40 - 1, 0.45 - 0.99, 0.45 - 0.95, 0.55 - 0.8, 0.55 - 0.7, 0.55 - 0.65, 0.59 - 0.63, or 0.6 - 0.62. In some aspects, C, when applicable, is 0.9 - 1, 0.9 - 0.99, 0.9 - 0.95, 0.85 - 0.95, 0.86 - 0.94, 0.87 - 0.93, 0.88 - 0.92, 0.89 - 0.91, 0.85 - 0.9, 0.8 - 0.95, 0.8 - 0.9, 0.8 - 0.85, 0.75 - 0.99, 0.75 - 0.95, 0.75 - 0.9, 0.75 - 0.85, or 0.75 - 0.8. In some aspects, D, when applicable, is 0.9 - 1, 0.9 - 0.99, 0.9 - 0.95, 0.85 - 0.95, 0.86 - 0.94, 0.87 - 0.93, 0.88 - 0.92, 0.89 - 0.91, 0.85 - 0.9, 0.8 - 0.95, 0.8 - 0.9, 0.8 - 0.85, 0.75 - 0.99, 0.75 - 0.95, 0.75 - 0.9, 0.75 - 0.85, or 0.75 - 0.8.

[0050] In some embodiments, A is between 0.1 and 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.2 and 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.3 and 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.4 and 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.5 and 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.6 and 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.7 and 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.8 and 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.9 and 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1 and 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1.5 and 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2 and 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2.5 and 3, 3.5, 4, 4...between 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3 and 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3.5 and 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4 and 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4.5 and 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 5 and 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 6 and 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 7 and 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 8 and 9, 10, 11, 12, 13, 14, 15 or 20; or between 9 and 10, 11, 12, 13, 14, 15 or 20; or between 10 and 11, 12, 13, 14, 15 or 20; or between 11 and 12, 13, 14, 15 or 20; or between 12 and 13, 14, 15 or 20; or between 13 and 14, 15 or 20; or between 14 and 15 or 20; or between 15 and 20; B is between 0.1 and 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.2 and 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.3 and 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.4 and 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.5 and 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.Between 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.6 and 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.7 and 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.8 and 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.9 and 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1 and 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1.5 and 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2 and 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2.5 and 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3 and 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3.5 and 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4 and 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4.Between 5 and 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 5 and 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 6 and 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 7 and 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 8 and 9, 10, 11, 12, 13, 14, 15 or 20; or between 9 and 10, 11, 12, 13, 14, 15 or 20; or between 10 and 11, 12, 13, 14, 15 or 20; or between 11 and 12, 13, 14, 15 or 20; or between 12 and 13, 14, 15 or 20; or between 13 and 14, 15 or 20; or between 14 and 15 or 20; or between 15 and 20; C is, where applicable, between 0.1 and 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.2 and 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.3 and 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.4 and 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.5 and 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.6 and 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.7 and 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.8 and 0.9, 1, 1.5, 2, 2.5...between 5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.9 and 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1 and 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1.5 and 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2 and 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2.5 and 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3 and 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3.5 and 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4 and 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4.5 and 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 5 and 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 6 and 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 7 and 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 8 and 9, 10, 11, 12, 13, 14, 15 or 20; or between 9 and 10, 11, 12, 13, 14, 15 or 20; or between 10 and 11, 12, 13, 14, 15 or 20; or between 11 and 12, 13, 14, 15 or 20; or between 12 and 13, 14, 15 or 20; or between 13 and 14, 15 or 20; or between 14 and 15 or 20; or between 15 and 20; and, D, where applicable, is between 0.1 and 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.2 and 0.3, 0.4, 0.5, 0.between 6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.3 and 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.4 and 0.5, 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.5 and 0.6, 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.6 and 0.7, 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.7 and 0.8, 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.8 and 0.9, 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 0.9 and 1, 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1 and 1.5, 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 1.5 and 2, 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2 and 2.5, 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 2.5 and 3, 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3 and 3.5, 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 3.5 and 4, 4.5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4 and 4.Between 5, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 4.5 and 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 5 and 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 6 and 7, 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 7 and 8, 9, 10, 11, 12, 13, 14, 15 or 20; or between 8 and 9, 10, 11, 12, 13, 14, 15 or 20; or between 9 and 10, 11, 12, 13, 14, 15 or 20; or between 10 and 11, 12, 13, 14, 15 or 20; or between 11 and 12, 13, 14, 15 or 20; or between 12 and 13, 14, 15 or 20; or between 13 and 14, 15 or 20; or between 14 and 15 or 20; or between 15 and 20. In some embodiments, A, B, and / or C are within the range of the rounded values of any of these values (e.g., A is between 0.45 and 0.54, etc.).

[0051] Thus, in one aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining an LOH region score for the sample; (2) determining a TAI region score for the sample; and (3) (a) detecting (or diagnosing) HRD in the sample based at least in part on a combination of LOH region score and TAI region score (e.g., composite CA region score) that exceeds a reference number; or optionally (3)(b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on a combination of LOH region score and TAI region score (e.g., composite CA region score) that does not exceed a reference number. In another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining an LOH region score for the sample; (2) determining an LST region score for the sample; and (3) (a) detecting (or diagnosing) HRD in the sample based at least in part on a combination of LOH region score and LST region score (e.g., composite CA region score) that exceeds a reference number; or optionally (3)(b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on a combination of LOH region score and LST region score (e.g., composite CA region score) that does not exceed a reference number. In yet another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, comprising: (1) determining a TAI region score for the sample; (2) determining an LST region score for the sample; and (3) (a) detecting (or diagnosing) HRD in the sample based at least in part on a combination of TAI region score and LST region score (e.g., composite CA region score) that exceeds a reference number; or optionally (3)(b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on a combination of TAI region score and LST region score (e.g., composite CA region score) that does not exceed a reference number.In another aspect, the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, the method comprising: (1) determining a LOH region score for the sample; (2) determining a TAI region score for the sample; (3) determining a LST region score for the sample; and (4) detecting (or diagnosing) HRD in the sample based at least in part on a combination of LOH region score, TAI region score, and LST region score (e.g., a composite CA region score) that exceeds a reference number; or optionally (4)(b) detecting (or diagnosing) the absence of HRD in the sample based at least in part on a combination of LOH region score, TAI region score, and LST region score (e.g., a composite CA region score) that does not exceed a reference number.

[0052] Accordingly, another aspect of the present invention provides a method for evaluating (e.g., detecting, diagnosing) HRD in a sample, the method comprising: (1) determining the total number of LOH regions (e.g., "indicator LOH regions" as defined herein) in the sample that have a particular size or characteristic; (2) determining the total number of TAI regions (e.g., "indicator TAI regions" as defined herein) in the sample that have a particular size or characteristic; (3) determining the total number of LST regions (e.g., "indicator LST regions" as defined herein) in the sample that have a particular size or characteristic; (4) calculating the average (e.g., arithmetic mean) of the determinations made in (1), (2), and (3); and (5) evaluating HRD in the sample based at least in part on the calculated average (e.g., arithmetic mean) obtained in (4).

[0053] In some embodiments, the reference (or index) considered above with respect to the CA region score (e.g., the number of indicator CA regions) may be well 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20 or more, preferably 5, preferably 8, more preferably 9 or 10, and most preferably 10. The reference with respect to the total (e.g., summed) length of the indicator CA 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 more, preferably about 75 megabases or more, preferably about 90 or 105 megabases or more, more preferably about 120 or 130 megabases or more, more preferably about 135 megabases or more, and most preferably about 150 megabases or more. In some embodiments, the reference considered above with respect to the composite CA region score (e.g., the sum count of indicator LOH regions, indicator, TAI regions and / or indicator LST regions) may be well 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19, 20 or more, preferably 5, preferably 8, more preferably 9 or 10, and most preferably 10. The reference with respect to the total (e.g., summed) length of the indicator LOH regions, indicator TAI regions and / or indicator LST 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 more, preferably about 75 megabases or more, preferably about 90 or 105 megabases or more, more preferably about 120 or 130 megabases or more, more preferably about 135 megabases or more, and most preferably about 150 megabases or more.

[0054] In some embodiments, the number (or total length, CA region score or composite CA region score) of indicator CA regions in a sample is determined to be "greater" than a reference if it is at least 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold or 10-fold greater than the reference, and in some embodiments it is determined to be "greater" if it is at least 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations or 10 standard deviations greater than the reference. Conversely, in some embodiments, the number (or total length, CA region score or composite CA region score) of indicator CA regions in a sample is determined to be "not greater" than a reference if it is 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold or 10-fold or less greater than the reference, and in some embodiments it is determined to be "not greater" if it is 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations or 10 standard deviations or less greater than the reference.

[0055] In some embodiments, the reference number (or length, value or score) is derived from a suitable reference population. Such a reference population can include (a) patients having the same cancer as the patient being tested, (b) patients having the same cancer subtype, (c) patients having cancer with similar genetic characteristics or other clinical or molecular characteristics, (d) patients who responded to a particular treatment, (e) patients who did not respond to a particular treatment, (f) patients who appear healthy (e.g., patients who do not have any cancer or at least do not have the cancer of the patient being tested), and the like. The reference number (or length, value or score) can be (a) representative of the number (or length, value or score) observed in the reference population as a whole, (b) the average (mean, median, etc.) of the number (or length, value or score) observed in the reference population as a whole or in a particular subpopulation, (c) the number (or length, value or score) recognized as, for example, the average (e.g., mean or median, etc.) of the tertiles, quartiles, quintiles, etc. of the reference population that are ranked by (i) each of those numbers (or lengths, values or scores) or (ii) clinical characteristics (e.g., strength of response, prognosis including time to cancer-specific death, etc.) found to be possessed by them.

[0056] In some embodiments, the reference or index indicates that HRD is the same as the reference if exceeded by the test value or score from the sample, and indicates that there is no HRD (or functional HDR) if not exceeded by the test value or score from the sample. In some embodiments, they are different.

[0057] In another aspect, the present invention provides a method for predicting the status of the BRCA1 gene and the BRCA2 gene in a sample. Such a method is similar to the above method, but differs in that the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these is used to evaluate (e.g., detect) BRCA1 and / or BRCA2 deficiency in the sample.

[0058] In another aspect, the present invention provides a method for predicting the response of a cancer patient to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, and / or a PARP inhibitor. Such a method is similar to the above method, but differs in that the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these is used to predict the likelihood that a cancer patient will respond to a cancer treatment regimen.

[0059] In some embodiments, the patient is an untreated patient. In another aspect, the present invention provides a method of treating cancer. Such a method is similar to the above method, but differs in that a particular treatment regimen is administered (recommended, prescribed, etc.) at least in part based on the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these.

[0060] In another aspect, the present invention features the use of one or more drugs selected from the group consisting of DNA damaging agents, anthracyclines, topoisomerase I inhibitors, and PARP inhibitors in the manufacture of a medicament useful for treating cancer in a patient identified as having (or having had) cancer cells determined to have the HRD (e.g., HRD signature) described herein.

[0061] In another aspect, the present document features a method for evaluating a sample with respect to the presence of mutations within genes originating from HDR. Such a method is similar to the above method, but differs in that the determination of the CA region, LOH region, TAI region, LST region, or a score incorporating these is used to detect the presence (or absence) of mutations within genes originating from HDR.

[0062] In another aspect, the present document features a method for evaluating a patient's cancer cells for the presence of an HRD signature. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region in at least one pair of human chromosomes of the cancer cells of a cancer patient that exceeds a reference number, and (b) identifying the patient as having cancer cells with an HRD signature. In another aspect, the present document features a method for evaluating a patient's cancer cells for the presence of an HDR-deficient state. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region in at least one pair of human chromosomes of the cancer cells of a cancer patient that exceeds a reference number, and (b) identifying the patient as having cancer cells with an HDR-deficient state. In another aspect, the present document features a method for evaluating a patient's cancer cells for the presence of gene mutations within genes derived from HDR. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region in at least one pair of human chromosomes of the cancer cells of a cancer patient that exceeds a reference number, and (b) identifying the patient as having cancer cells with gene mutations.

[0063] In another aspect, the present document features a method for determining whether a patient is likely to respond to a cancer treatment regimen that includes administering a drug selected from the group consisting of radiation, or a DNA damaging agent, anthracycline, topoisomerase I inhibitor, and PARP inhibitor. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of cancer cells of a cancer patient, and (b) identifying the patient as likely to respond to the cancer treatment regimen. In another aspect, the present document features a method for evaluating a patient. The method includes, or consists essentially of, (a) determining that the patient has cancer cells having an HRD signature, wherein the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of cancer cells of a cancer patient indicates that the cancer cells have an HRD signature, and (b) diagnosing the patient as having cancer cells with an HRD signature. In another aspect, the present document features a method for evaluating a patient. The method includes, or consists essentially of, (a) determining that the patient has cancer cells having a HDR-deficient state, wherein the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of cancer cells of a cancer patient indicates that the cancer cells have a HDR-deficient state, and (b) diagnosing the patient as having cancer cells with a HDR-deficient state. In another aspect, the present document features a method for evaluating a patient. The method includes, or consists essentially of, (a) determining that the patient has cancer cells having a gene mutation within a gene derived from HDR, wherein the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of cancer cells of a cancer patient indicates that the cancer cells have a gene mutation, and (b) diagnosing the patient as having cancer cells with a gene mutation.In another aspect, the present document features a method for assessing a patient's likelihood of responding to a cancer treatment regimen that includes administering the patient a drug selected from the group consisting of radiation, or a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, and a PARP inhibitor. The method includes, or consists essentially of, (a) determining that the patient has cancer cells having an HRD signature, wherein the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of the cancer cells of the cancer patient indicates that the cancer cells have an HRD signature, and (b) diagnosing the patient as likely to respond to the cancer treatment regimen, at least in part based on the presence of the HRD signature.

[0064] In another aspect, the present document features a method for performing a diagnostic analysis of a patient's cancer cells. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of the cancer cells, and (b) identifying or classifying the patient as having cancer cells with an HRD signature. In another aspect, the present document features a method for performing a diagnostic analysis of a patient's cancer cells. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of the cancer cells, and (b) identifying or classifying the patient as having cancer cells with an HDR-deficient state. In another aspect, the present document features a method for performing a diagnostic analysis of a patient's cancer cells. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region that is relatively long and exceeds a reference number in at least one pair of human chromosomes of the cancer cells, and (b) identifying or classifying the patient as having cancer cells with gene mutations within genes originating from HDR. In another aspect, the present document features a method for performing a diagnostic analysis of a patient's cancer cells to determine whether a cancer patient is likely to respond to a cancer treatment regimen that includes administering a drug selected from the group consisting of radiation, or a DNA-damaging agent, anthracycline, topoisomerase I inhibitor, and PARP inhibitor. The method includes, or consists essentially of, (a) detecting the presence of an indicator CA region that exceeds a reference number in at least one pair of human chromosomes of the cancer cells, and (b) identifying or classifying the patient as being likely to respond to the cancer treatment regimen.

[0065] In another aspect, the present document features a method for diagnosing a patient as having cancer cells with an HRD signature. The method includes, or consists essentially of, (a) a step of determining that the patient has cells with an HRD signature, indicated by the presence of an indicator CA region in at least one pair of human chromosomes of the cancer cells of the cancer patient that exceeds a reference number, and (b) a step of diagnosing the patient as having cancer cells with an HRD signature. In another aspect, the present document features a method for diagnosing a patient as having cancer cells with an HDR deficiency state. The method includes, or consists essentially of, (a) a step of determining that the patient has cancer cells with an HDR deficiency state, indicated by the presence of an indicator CA region in at least one pair of human chromosomes of the cancer cells of the cancer patient that exceeds a reference number, and (b) a step of diagnosing the patient as having cancer cells with an HDR deficiency state. In another aspect, the present document features a method for diagnosing a patient as having cancer cells with a gene mutation in a gene derived from HDR. The method includes, or consists essentially of, (a) a step of determining that the patient has cancer cells with a gene mutation, indicated by the presence of an indicator CA region in at least one pair of human chromosomes of the cancer cells of the cancer patient that exceeds a reference number, and (b) a step of diagnosing the patient as having cancer cells with a gene mutation. In another aspect, the present document features a method for diagnosing a patient as a candidate for a cancer treatment regimen that includes administering radiation or a drug selected from the group consisting of DNA damaging agents, anthracyclines, topoisomerase I inhibitors, and PARP inhibitors.The method includes, or consists essentially of, the steps of: (a) determining that the patient's cancer cells contain cancer cells having an HRD signature, wherein the presence of an indicator CA region in at least one pair of human chromosomes of the cancer patient's cancer cells that exceeds a reference number indicates that the cancer cells have an HRD signature; and (b) diagnosing the patient as likely to respond to a cancer treatment regimen based at least in part on the presence of the HRD signature.

[0066] In another aspect, the invention provides a method for evaluating a patient. The method includes, or consists essentially of, the steps of: (a) determining whether the patient has (or had) cancer cells (or, e.g., a CA region score exceeding a reference CA region score) that exceed the reference number of CA regions; and (b) (1) diagnosing that the patient has cancer cells associated with HRD if it is determined that the patient has (or had) cancer cells (or, e.g., a CA region score exceeding a reference CA region score) that exceed the reference number of CA regions; or (b) (2) diagnosing that the patient does not have cancer cells associated with HRD if it is determined that the patient does not have (or has never had) cancer cells that exceed the reference number of CA regions (or, e.g., the patient does not have (or has never had) cancer cells with a CA region score exceeding a reference CA region score).

[0067] In another aspect, the invention features the use of a plurality of oligonucleotides capable of hybridizing to a plurality of polymorphic regions of human genomic DNA in the manufacture of a diagnostic kit useful for determining the total number or combined length of CA regions in at least one pair of chromosomes (or DNA derived therefrom) in a sample obtained from a cancer patient and for detecting (a) HRD or the likelihood of HRD (e.g., an HRD signature) in the sample, (b) a deficiency (or likelihood of deficiency) of the BRCA1 or BRCA2 gene in the sample, or (c) a high likelihood that the cancer patient will respond to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, or a PARP inhibitor.

[0068] In another aspect, the invention features a system for detecting HRD (e.g., an HRD signature) in a sample. The system includes or consists essentially of: (a) a sample analyzer configured to generate a plurality of signals regarding genomic DNA of at least one pair of human chromosomes (or DNA derived therefrom) in the sample; and (b) a computer subsystem programmed to calculate the number or total length of CA regions in at least one pair of human chromosomes based on the plurality of signals. The computer subsystem can be programmed to compare the number or total length of CA regions to a reference number to detect (a) HRD or the likelihood of HRD (e.g., an HRD signature) in the sample, (b) a deletion (or the likelihood of a deletion) of the BRCA1 or BRCA2 gene in the sample, or (c) that a cancer patient is likely to respond to a cancer treatment regimen that includes a DNA damaging agent, anthracycline, topoisomerase I inhibitor, radiation, or PARP inhibitor. The system may include an output module configured to display (a), (b), or (c). The system may include an output module configured to display recommendations regarding the use of a cancer treatment regimen.

[0069] In another aspect, the invention provides a computer program product incorporated in a computer-readable medium that, when executed on a computer, provides instructions for detecting the presence or absence of any CA regions (the CA regions are optionally indicator CA regions) present on one or more of the human chromosomes other than the human X and Y sex chromosomes; and for determining the total number or total length of CA regions in one or more pairs of chromosomes. The computer program product may include other instructions.

[0070] In another aspect, the present invention provides a diagnostic kit. The kit includes at least 500 oligonucleotides capable of hybridizing to a plurality of polymorphic regions of human genomic DNA (or DNA derived therefrom); and includes or consists essentially of a computer program product provided herein. The computer program product may be incorporated into a computer-readable medium and, when executed on a computer, is for detecting the presence or absence of any CA region (the CA region is optionally an indicator CA region) present on one or more of the human chromosomes other than the human X and Y sex chromosomes; and for giving instructions for determining the total number or total length of CA regions in one or a plurality of pairs of chromosomes. The computer program product may include other instructions.

[0071] In some embodiments of any one or more of the aspects of the present invention described in the foregoing paragraphs, any one or more of the following can be applied as appropriate. The CA region can be determined in at least 2, 5, 10 or 21 pairs of human chromosomes. The cancer cells can be ovarian cancer cells, breast cancer cells, lung cancer cells or esophageal cancer cells. The reference number can be 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18 or 20 or more. Human chromosome 17 can be excluded from at least one pair of human chromosomes. The DNA damaging agent can be cisplatin, carboplatin, oxalaplatin, or picoplatin, the anthracycline can be epirubincin or doxorubicin, the topoisomerase I inhibitor can be campothecin, topotecan or irinotecan, or the PARP inhibitor can be iniparib, olaparib or velapirib. The patient can be an untreated patient.

[0072] As described herein, a sample (e.g., a cancer cell sample, or a sample containing DNA derived from one or more cancer cells) can be identified as having an "HRD signature" (alternatively referred to as an "HDR deficiency signature") if the genome of the cell being evaluated includes (a) an LOH region score, a TAI region score, or an LST region score that exceeds a reference number, or (b) a composite CA region score that exceeds a reference number. Conversely, a sample (e.g., a cancer cell sample, or a sample containing DNA derived from one or more cancer cells) can be identified as lacking an "HRD signature" (alternatively referred to as an "HDR deficiency signature") if the genome of the cell being evaluated includes (a) an LOH region score, a TAI region score, and an LST region score that do not exceed a reference number, respectively, or (b) a composite CA region score that does not exceed a reference number.

[0073] Cells identified as having an HRD signature (e.g., cancer cells) can be classified as likely to have an HDR deficiency and / or likely to have a deficiency state of one or more genes in the HDR pathway. For example, cancer cells identified as having an HRD signature can be classified as likely to have an HDR deficiency state. In some cases, cancer cells identified as having an HRD signature can also be classified as likely to have a deficiency state regarding one or more genes in the HDR pathway. As used herein, the deficiency state regarding a gene means that the sequence, structure, expression, and / or activity of the gene or its product is deficient compared to normal. Examples thereof include, but are not limited to, low or no expression of mRNA or protein, harmful mutations, hypermethylation, reduced activity (e.g., enzyme activity, ability to bind to another biomolecule), etc. As used herein, the deficiency state regarding a pathway (e.g., the HDR pathway) means that at least one gene (e.g., BRCA1) in the pathway is deficient. Examples of highly harmful mutations include frameshift mutations, stop codon mutations, and mutations leading to changes in RNA splicing. The deficiency state of genes in the HDR pathway can result in a deficiency or reduced activity of homologous recombination repair in cancer cells. Examples of genes in the HDR pathway include, but are not limited to, the genes listed in Table 1.

[0074] (Table 1) Selected HDR Pathway Genes TIFF2025090619000003.tif235147

[0075] As described herein, the identification of the CA locus (as well as the size and number of CA regions) can, first, determine the genotype of a sample at various genomic loci (e.g., SNP loci, individual bases in large-scale sequencing), and second, may include determining whether the locus exhibits any of LOH, TAI, or LST. The genotype at a locus of interest within the genome of a cell can be determined using any suitable method. For example, single nucleotide polymorphism (SNP) arrays (e.g., human genome-wide SNP arrays), targeted sequencing of loci of interest (e.g., sequencing of SNP loci and their flanking sequences), and even large-scale sequencing (e.g., whole exome, transcriptome, or genome sequencing) can be used to identify the locus as homozygous or heterozygous. Typically, the length of the CA region can be determined by analyzing the homozygosity or heterozygosity of loci over a length of a chromosome. For example, by evaluating a series of SNP positions spaced along the length of a chromosome (e.g., spaced at intervals of about 25 kb to about 100 kb) using the results of an SNP array, not only the presence of homozygous regions (e.g., LOH) along the length of the chromosome but also the length of that region can be determined. Using the results from an SNP array, a graph can be created plotting the allele amounts along the length of the chromosome. The allele amount d i for an SNPi can be calculated from the adjusted signal intensities (A i and B i ) of the two alleles: d i = A i / (A i + B i)。An example of such graphs is presented in FIGS. 1 and 2, which show the differences between fresh frozen samples and FFPE samples, and the differences between SNP microarray analysis and SNP sequencing analysis. A very large number of variants on nucleic acid arrays useful in the present invention are known in the art. These include arrays used in the following various examples (e.g., the Affymetrix 500K GeneChip array in Example 3; the Affymetrix OncoScan™ FFPE Express 2.0 Services (formerly MIP CN Services) in Example 4).

[0076] Once the genotype of a sample has been determined for multiple loci (e.g., SNPs), loci and regions of LOH, TAI, and LST can be identified using common techniques (International Application No. PCT / US2011 / 040953 (published as WO / 2011 / 160063); International Application No. PCT / US2011 / 048427 (published as WO / 2012 / 027224); including those described in Popova et al., Ploidy and large-scale genomic instability consistently identify basal-like breast carcinomas with BRCA1 / 2 inactivation, CANCER RES. (2012) 72:5454-5462). In some embodiments, determination of chromosomal imbalances or large-scale transitions includes determining whether they are somatic abnormalities or germline abnormalities. One method for doing this is to compare the somatic genotype to the germline. For example, genotypes for multiple loci (e.g., SNPs) can be determined in both germline (e.g., blood) samples and somatic (e.g., tumor) samples. By comparing the genotypes for each sample (typically by computer calculation), locations where the germline cell genome is heterozygous and the somatic genome is homozygous can be determined. Such loci are LOH loci, and regions of such loci are LOH regions.

[0077] To determine whether an abnormality is germline or somatic, computer algorithms can also be used. Such techniques are particularly useful when germline samples for analysis and comparison are not available. For example, by using algorithms such as those described elsewhere, regions of loss of heterozygosity (LOH) can be detected using information from SNP arrays (Nannya et al., Cancer Res. (2005) 65:6071-6079 (2005)). Typically, these algorithms do not explicitly account for the contamination of tumor samples with benign tissue. See International Application No. PCT / US2011 / 026098 to Abkevich et al.; Goransson et al., PLoS One (2009) 4(6):e6057. This contamination is often highly advanced enough to make the detection of LOH regions difficult. The improved analytical methods according to the present invention for identifying LOH, TAI, and LST despite contamination include those incorporated into computer software products such as the following.

[0078] The following is an example. When the observed ratio of the signals of two alleles A and B is 2:1, there are two possibilities. The first possibility is that in a sample contaminated with 50% normal cells, the cancer cells have LOH with deletion of allele B. The second possibility is that in a sample without contamination by normal cells, there is no LOH but allele A is duplicated. The algorithm can be executed as a computer program described herein to reconstruct the LOH region based on genotype (e.g., SNP genotype) data. One of the key points of this algorithm is to first reconstruct the allele-specific copy number (ASCN) at each locus (e.g., SNP). The ASCN is the copy number of both the paternal and maternal alleles. Subsequently, the LOH region is determined as a continuous series of SNPs where one (paternal or maternal) of the ASCNs is 0. This algorithm can be based on maximizing a likelihood function and may conceptually be similar to previously described algorithms designed to reconstruct the total copy number (not ASCN) at each locus (e.g., SNP). See International Application No. PCT / US2011 / 026098 to Abkevich et al. The likelihood function can be maximized with respect to the ASCNs of all loci, the contamination level of benign tissue, the total copy number averaged across the entire genome, and the sample-specific noise level. The input data to the algorithm can include, or can consist of, (1) the sample-specific normalized signal intensities for both alleles at each locus, and (2) a set of assay-specific (specific to different SNP arrays and sequence-based approaches) parameters determined based on the analysis of a number of samples with known ASCN profiles.

[0079] In some cases, genotyping of a locus can be performed using nucleic acid sequencing techniques. For example, genomic DNA can be extracted and fragmented from a cell sample (e.g., a cancer cell sample). Any suitable method can be used for extracting and fragmenting genomic nucleic acids, including, but not limited to, commercially available kits such as the QIAamp™ DNA Mini Kit (Qiagen™), MagNA™ Pure DNA Isolation Kit (Roche Applied Science™), and GenElute™ Mammalian Genomic DNA Miniprep Kit (Sigma-Aldrich™). Once extraction and fragmentation are performed, the genotype of the sample at the locus can be determined by performing either targeted or untargeted sequencing. For example, by sequencing the whole genome, whole transcriptome, or whole exome, genotypes can be determined for millions or even billions of base pairs (i.e., the base pairs may be the "locus" to be evaluated).

[0080] In some cases, targeted sequencing of known polymorphic loci (e.g., SNPs and flanking sequences) can be performed as an alternative to microarray analysis. For example, genomic DNA can be enriched for fragments containing the locus to be analyzed (e.g., SNP positions) using kits designed for this purpose (e.g., Agilent SureSelect™, Illumina TruSeq Capture™, and Nimblegen SeqCap EZ Choice™). For example, genomic DNA containing the locus to be analyzed can be hybridized to biotinylated capture RNA fragments to form biotinylated RNA / genomic DNA complexes. Alternatively, DNA capture probes can be utilized to form biotinylated DNA / genomic DNA hybrids. Using magnetic beads coated with streptavidin and magnetic force, the biotinylated RNA / genomic DNA complexes can be separated from genomic DNA fragments that are not present within the biotinylated RNA / genomic DNA complexes. The resulting biotinylated RNA / genomic DNA complexes can be processed to remove the captured RNA from the magnetic beads, thereby leaving intact genomic DNA fragments containing the locus to be analyzed. These intact genomic DNA fragments containing the locus to be analyzed can be amplified, for example, using the PCR method. The amplified genomic DNA fragments can be sequenced using high-throughput sequencing technologies or next-generation sequencing technologies such as Illumina HiSeq™, Illumina MiSeq™, Life Technologies SoLID™ or Ion Torrent™, or Roche 454™.

[0081] Similar to the microarray analysis described in this specification, using the sequencing results from genomic DNA fragments, loci can be identified as presenting or not presenting CA. In some cases, by analyzing the genotype of loci over a certain length of a chromosome, the length of the CA region can be determined. For example, a series of SNP positions spaced along the length of the chromosome (e.g., spaced at intervals of about 25 kb to about 100 kb) are evaluated by sequencing, and using the sequencing results, not only the presence of the CA region existing along the length of the chromosome but also the length of the CA region can be determined. Using the obtained sequencing results, a graph plotting the allele amounts along the length of the chromosome can be created. The allele amount d i for SNPi can be calculated from the adjusted integers (A i and B i ) of the capture probes for the two alleles: d i = A i / (A i + B i ). An example of such a graph is presented in FIGS. 1 and 2. The determination of whether the abnormality is germline or somatic can be made as described in this specification.

[0082] In some cases, by using a selection process, an assay configured to perform genotyping of a locus (e.g., SNP array-based assays and sequencing-based assays) can be used to select a locus to be evaluated (e.g., an SNP locus). For example, any human SNP position can be selected for inclusion in an SNP array-based assay or a sequencing-based assay configured to perform genotyping of a locus. In some cases, 500,000, 1,000,000, 1,500,000, 2,000,000, 2,500,000 or more SNP positions present in the human genome are evaluated to identify SNPs that (a) are not present on the Y chromosome, (b) are not mitochondrial SNPs, (c) have a minor allele frequency of at least about 5% in Caucasians, (d) have a minor allele frequency of at least about 1% in three non-Caucasian ethnic groups (e.g., Chinese, Japanese, and Yoruba), and / or (e) do not significantly deviate from Hardy-Weinberg equilibrium in any of the four ethnic groups. In some cases, more than 100,000, more than 150,000, or more than 200,000 human SNPs that meet the criteria from (a) to (e) can be selected. Among the human SNPs that meet the criteria from (a) to (e), a group of SNPs (e.g., the top 110,000 SNPs) can be selected such that the SNPs have a high allele frequency in Caucasians, cover the human genome at somewhat uniform intervals (e.g., at least one SNP every about 25 kb to about 500 kb), and are not in linkage disequilibrium with another selected SNP in any of the four ethnic groups. In some cases, about 40,000, 50,000, 60,000, 70,000, 80,000, 90,000, 100,000, 110,000, 120,000, 130,000 or more SNPs are selected as meeting these criteria and can be included in an assay configured to identify CA regions across the entire human genome. For example, for analysis using an SNP array-based assay, about 70,000 to about 90,000 (e.g., about 80,000) SNPs can be selected. For analysis using a sequencing-based assay, about 45,000 to about 55,000 (e.g., about 54,000) SNPs can be selected.

[0083] As described herein, any suitable type of sample can be evaluated. For example, a sample containing cancer cells can be evaluated to determine whether the genome of the cancer cells contains an HRD signature, lacks an HRD signature, has an increased number of indicator CA regions, or has an increased CA region score. Examples of samples containing cancer cells that can be evaluated as described herein include tumor biopsy samples (e.g., breast tumor biopsy samples), formalin-fixed paraffin-embedded cancer cell-containing tissue samples, core needle biopsy samples, fine needle aspirates, and samples containing cancer cells shed from a tumor (e.g., blood, urine, or other body fluids), which are non-limitingly included. In the case of formalin-fixed paraffin-embedded tissue samples, the sample can be prepared by DNA extraction using a genomic DNA extraction kit optimized for FFPE tissues, which non-limitingly includes the above kits (e.g., QuickExtract™ FFPE DNA Extraction Kit (Epicentre™) and QIAamp™ DNA FFPE Tissue Kit (Qiagen™)).

[0084] In some cases, laser dissection can be performed on tissue samples to minimize the number of non-cancer cells in the cancer cell sample to be evaluated. In some cases, antibody-based purification methods can be used to enrich cancer cells and / or deplete non-cancer cells. Examples of antibodies that can be used for cancer cell enrichment non-limitingly include anti-EpCAM, anti-TROP-2, anti-c-Met, anti-folate binding protein, anti-N-cadherin, anti-CD318, anti-anti-mesenchymal stem cell antigen, anti-Her2, anti-MUC1, anti-EGFR, anti-cytokeratin (e.g., cytokeratin 7, cytokeratin 20, etc.), anti-caveolin-1, anti-PSA, anti-CA125, and anti-surfactant protein antibodies.

[0085] Using the methods and materials described herein, any type of cancer cell can be evaluated. For example, breast cancer cells, ovarian cancer cells, liver cancer cells, esophageal cancer cells, lung cancer cells, head and neck cancer cells, prostate cancer cells, colon cancer cells, rectal cancer cells, or colorectal cancer cells, and pancreatic cancer cells can be evaluated to determine whether the genome of the cancer cells contains an HRD signature, lacks an HRD signature, whether the number of CA regions covering the entire chromosome has increased, or whether the CA region score has increased. In some embodiments, the cancer cells are primary or metastatic cancer cells of ovarian cancer, breast cancer, lung cancer, or esophageal cancer.

[0086] When evaluating the genome of cancer cells for the presence or absence of an HRD signature, one or more pairs (e.g., 1 pair, 2 pairs, 3 pairs, 4 pairs, 5 pairs, 6 pairs, 7 pairs, 8 pairs, 9 pairs, 10 pairs, 11 pairs, 12 pairs, 13 pairs, 14 pairs, 15 pairs, 16 pairs, 17 pairs, 18 pairs, 19 pairs, 20 pairs, 21 pairs, 22 pairs, or 23 pairs) of chromosomes can be evaluated. In some cases, the genome of the cancer cells is evaluated for the presence or absence of an HRD signature using one or more pairs (e.g., 1 pair, 2 pairs, 3 pairs, 4 pairs, 5 pairs, 6 pairs, 7 pairs, 8 pairs, 9 pairs, 10 pairs, 11 pairs, 12 pairs, 13 pairs, 14 pairs, 15 pairs, 16 pairs, 17 pairs, 18 pairs, 19 pairs, 20 pairs, 21 pairs, 22 pairs, 23 pairs) of chromosomes.

[0087] In some cases, it may be beneficial to exclude certain identified chromosomes from this analysis. For example, in females, the pair to be evaluated may include the X sex chromosome pair; while in males, any pair of autosomes (i.e., any pair other than the pair of X and Y sex chromosomes) can be evaluated. As another example, in some cases, the 17th chromosome pair may be excluded from the analysis. In certain cancers, it has been shown that a particular chromosome has a higher level of CA than normal, and thus, when analyzing samples as described herein, it may be beneficial to exclude such chromosomes from patients with these cancers. In some cases, the sample is from a patient with ovarian cancer and the chromosome to be excluded is the 17th chromosome.

[0088] Therefore, a predetermined number of chromosomes may be analyzed to determine the number of indicator CA regions (or the CA region score or composite CA region score), preferably the total number of CA regions having a length greater than 9 megabases, greater than 10 megabases, greater than 12 megabases, greater than 14 megabases, and more preferably greater than 15 megabases. Alternatively or additionally, the sizes of all identified indicator CA regions may be summed to obtain the total length of the indicator CA regions.

[0089] As described herein, a patient having cancer cells (or a sample derived therefrom) identified as having an HRD signature state can be classified as likely to respond to a particular cancer treatment regimen, at least in part based on such HRD signature state. For example, a patient having cancer cells with a genome associated with an HRD signature can be classified as likely to respond to a cancer treatment regimen that includes the use of DNA damaging agents, synthetic lethal agents (e.g., PARP inhibitors), radiation, or combinations thereof, at least in part based on such HRD signature state. In some embodiments, the patient is an untreated patient. Examples of DNA damaging agents include, without limitation, platinum-based chemotherapeutic agents (e.g., cisplatin, carboplatin, oxaliplatin, and picoplatin), anthracyclines (e.g., epirubicin and doxorubicin), topoisomerase I inhibitors (e.g., campothecin, topotecan, and irinotecan), DNA cross-linking agents such as mitomycin C, and triazene compounds (e.g., dacarbazine and temozolomide). A synthetic lethality-based therapeutic approach typically involves administering an agent that inhibits at least one critical component of a biological pathway that is particularly important for the survival of a particular tumor cell. For example, when a tumor cell has a homologous repair pathway deficiency (e.g., as determined by the present invention), an inhibitor of poly ADP ribose polymerase (or a platinum-based drug, a double-strand break repair inhibitor, etc.) may be particularly effective against such a tumor, because two pathways that are critically important for survival are blocked (one biologically, e.g., by a BRCA1 mutation, and the other synthetically, e.g., by administration of a pathway drug). Synthetic lethality approaches to cancer therapy are described, for example, in O'Brien et al., Converting cancer mutations into therapeutic opportunities, EMBO MOL. MED. (2009) 1:297-299.Examples of synthetic lethal 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, and the like. Examples of PARP inhibitors include, without limitation, olaparib, iniparib, and veliparib. Examples of double-strand break repair inhibitors include, without limitation, KU55933 (an ATM inhibitor) and NU7441 (a DNA-PKcs inhibitor). Examples of information that can be used in addition to the presence of an HRD signature that underlies the classification of being likely to respond to a particular cancer treatment regimen include previous treatment outcomes, germline or somatic DNA mutations, gene or protein expression profiling (e.g., ER / PR / HER2 status, PSA level), tumor histology (e.g., adenocarcinoma, squamous cell carcinoma, serous papillary carcinoma, mucinous carcinoma, invasive ductal carcinoma, non-invasive ductal carcinoma (non-invasive), etc.), disease stage, tumor or cancer grade (e.g., well-differentiated, moderately-differentiated, or poorly-differentiated (e.g., Gleason, modified Bloom Richardson), etc.), the number of previous treatment courses, and the like.

[0090] Once classified as likely to respond to a particular cancer treatment regimen (e.g., a cancer treatment regimen that includes the use of DNA damaging agents, PARP inhibitors, radiation, or combinations thereof), cancer patients can be treated with such a cancer treatment regimen. In some embodiments, the patient is an untreated patient. The present invention thus provides a method of treating a patient, the method comprising the steps of detecting an HRD signature as described herein, and administering (or recommending or prescribing) a treatment regimen that includes the use of a DNA damaging agent, a PARP inhibitor, radiation, or combinations thereof. Any suitable method for treating the cancer in question can be used to treat cancer patients identified as having cancer cells with an HRD signature state. For example, platinum-based chemotherapeutic agents or combinations of platinum-based chemotherapeutic agents can be used to treat cancer as described elsewhere (see, e.g., U.S. Pat. Nos. 3,892,790, 3,904,663, 7,759,510, 7,759,488, and 7,754,684). In some cases, anthracyclines or combinations of anthracyclines can be used to treat cancer as described elsewhere (see, e.g., U.S. Pat. Nos. 3,590,028, 4,138,480, 4,950,738, 6,087,340, 7,868,040, and 7,485,707). In some cases, topoisomerase I inhibitors or combinations of topoisomerase I inhibitors can be used to treat cancer as described elsewhere (see, e.g., U.S. Pat. Nos. 5,633,016 and 6,403,563). In some cases, PARP inhibitors or combinations of PARP inhibitors can be used to treat cancer as described elsewhere (see, e.g., U.S. Pat. Nos. 5,177,075, 7,915,280, and 7,351,701). In some cases, radiation can be used to treat cancer as described elsewhere (see, e.g., U.S. Pat. No. 5,295,944).In some cases, cancer can be treated using combinations that include different agents, with or without radiotherapy, such as combinations that include any of a platinum-based chemotherapeutic agent, an anthracycline, a topoisomerase I inhibitor, and / or a PARP inhibitor. In some cases, the combination therapy may include any of the above agents or treatments (e.g., a DNA damaging agent, a PARP inhibitor, radiation, or combinations thereof) together with another agent or treatment, such as a taxane agent (e.g., docetaxel, paclitaxel, abraxane), a growth factor inhibitor or growth factor receptor inhibitor (e.g., erlotinib, gefitinib, lapatinib, sunitinib, bevacizumab, cetuximab, trastuzumab, panitumumab), and / or an antimetabolite (e.g., 5-fluorouracil, methotrexate).

[0091] In some cases, patients identified as having cancer cells with a genome lacking an HRD signature, based at least in part on a sample lacking an HRD signature, can be classified as likely to have a low response to a treatment regimen comprising a DNA damaging agent, a PARP inhibitor, radiation, or a combination thereof. Subsequently, such patients can be classified as likely to respond to a cancer treatment regimen comprising the use of one or more cancer therapeutics not associated with HDR, such as taxane agents (e.g., docetaxel, paclitaxel, abraxane), growth factor inhibitors or growth factor receptor inhibitors (e.g., erlotinib, gefitinib, lapatinib, sunitinib, bevacizumab, cetuximab, trastuzumab, panitumumab), and / or antimetabolites (e.g., 5-fluorouracil, methotrexate). In some embodiments, the patient is an untreated patient. Once classified as likely to respond to a particular cancer treatment regimen (e.g., a cancer treatment regimen comprising the use of a cancer therapeutic not associated with HDR), the cancer patient can be treated with such a cancer treatment regimen. The invention thus provides a method of treating a patient, the method comprising detecting the absence of an HRD signature as described herein, and administering (or recommending or prescribing) a treatment regimen that does not include the use of a DNA damaging agent, a PARP inhibitor, radiation, or a combination thereof. In some embodiments, the treatment regimen comprises one or more of a taxane agent (e.g., docetaxel, paclitaxel, abraxane), a growth factor inhibitor or a growth factor receptor inhibitor (e.g., erlotinib, gefitinib, lapatinib, sunitinib, bevacizumab, cetuximab, trastuzumab, panitumumab), and / or an antimetabolite (e.g., 5-fluorouracil, methotrexate). A cancer patient identified as having cancer cells lacking an HRD signature can be treated using any method appropriate for the cancer being treated.Examples of information that can be used in addition to the absence of an HRD signature that underlies the classification of being likely to respond to a particular cancer treatment regimen include, without limitation, previous treatment outcomes, germline or somatic DNA mutations, gene or protein expression profiling (e.g., ER / PR / HER2 status, PSA level), tumor histology (e.g., adenocarcinoma, squamous cell carcinoma, serous papillary carcinoma, mucinous carcinoma, invasive ductal carcinoma, non-invasive ductal carcinoma (non-invasive), etc.), disease stage, tumor or cancer grade (e.g., well-differentiated, moderately differentiated, or poorly differentiated (e.g., Gleason, modified Bloom Richardson), etc.), the number of previous treatment courses, and the like.

[0092] Once a patient has been treated over a certain period (e.g., 1 month to 6 months), the patient can be evaluated to determine whether the treatment regimen is effective. If a beneficial effect is detected, the patient can continue with the same or a similar cancer treatment regimen. If only a slight beneficial effect is detected or no beneficial effect is detected at all, the cancer treatment regimen can be adjusted. For example, the dose, dosing frequency, or treatment duration can be increased. In some cases, additional anti-cancer drugs can be added to the treatment regimen, or a particular anti-cancer drug can be replaced with one or more different anti-cancer drugs. The patient being treated can be continuously monitored as appropriate, and the cancer treatment regimen can be changed as appropriate.

[0093] In addition to predicting a likely treatment response or selecting a desirable treatment regimen, the HRD signature can also be used to determine a patient's prognosis. Thus, in one aspect, the present document features a method for determining a patient's prognosis, based at least in part on detecting the presence or absence of an HRD signature in a sample from the patient. The method includes (a) determining whether a sample from the patient contains cancer cells having the HRD signature described herein (or whether the sample contains DNA derived from such cells) (e.g., the presence of an indicator CA region above a reference number or a higher-order CA region score or a composite CA region score), and (b) (1) determining that the patient has a relatively favorable prognosis, based at least in part on the presence of the HRD signature, or (b) (2) determining that the patient has a relatively poor prognosis, based at least in part on the absence of the HRD signature, or consisting essentially of these steps. The prognosis may include the patient's survival prospects (e.g., progression-free survival, overall survival), where a relatively favorable prognosis is considered to include a higher survival prospect compared to some reference population (e.g., the average patient with this patient's cancer type / subtype, the average patient without an HRD signature, etc.). Conversely, a relatively poor prognosis with respect to survival is considered to include a lower survival prospect compared to some reference population (e.g., the average patient with this patient's cancer type / subtype, the average patient with an HRD signature, etc.).

[0094] As described herein, this document provides a method for evaluating a patient with respect to cells (e.g., cancer cells) having a genome with an HRD signature. In some embodiments, one or more clinicians or healthcare providers can determine whether a sample from the patient contains cancer cells having an HRD signature (or whether the sample contains DNA derived from such cells). Optionally, one or more clinicians or healthcare providers can obtain a cancer cell sample from the patient and evaluate the DNA of the cancer cells in the cancer cell sample to determine the presence or absence of an HRD signature as described herein, thereby determining whether the patient contains cancer cells having an HRD signature.

[0095] Optionally, one or more clinicians or healthcare providers can obtain a cancer cell sample from the patient and provide the sample to a testing institution capable of evaluating the DNA of the cancer cells in the cancer cell sample to indicate the presence or absence of an HRD signature as described herein. In some embodiments, the patient is an untreated patient. In such cases, one or more clinicians or healthcare providers can determine whether the patient contains cancer cells having an HRD signature (or whether the sample contains DNA derived from such cells) by receiving information directly or indirectly from the testing institution regarding the presence or absence of the HRD signature. For example, after evaluating the DNA of the cancer cells for the presence or absence of an HRD signature as described herein, the testing institution can provide or make accessible to the clinician or healthcare provider a written, electronic, or oral report or medical record indicating the presence or absence of the HRD signature for the specific patient (or patient sample) being evaluated. With such a written, electronic, or oral report or medical record, one or more clinicians or healthcare providers can determine whether the specific patient being evaluated contains cancer cells having an HRD signature.

[0096] Once a clinician or healthcare provider, or a group of clinicians or healthcare providers, determines that a particular patient being evaluated contains cancer cells having an HRD signature, the clinician or healthcare provider (or group) can classify that patient as having cancer cells whose genome contains the presence of the HRD signature. In some embodiments, the patient is an untreated patient. In some cases, the clinician or healthcare provider, or a group of clinicians or healthcare providers, can diagnose a patient determined to have cancer cells whose genome contains the presence of the HRD signature as having cancer cells with a deficient (or likely deficient) HDR. Such a diagnosis may be based solely on a determination of whether a sample from the patient contains cancer cells having the HRD signature (or whether the sample contains DNA derived from such cells), or may be based at least in part on a determination of whether a sample from the patient contains cancer cells having the HRD signature (or whether the sample contains DNA derived from such cells). For example, a patient determined to have cancer cells having the HRD signature can be diagnosed as likely having a deficient HDR based on a combination of the deficiency status of the HRD signature and one or more tumor suppressor genes (e.g., BRCA1 / 2, RAD51C), family history of cancer, or presence of behavioral risk factors (e.g., smoking).

[0097] In some cases, a clinician or healthcare provider, or a group of clinicians or healthcare providers, can diagnose a patient determined to have cancer cells whose genome contains the presence of an HRD signature as having cancer cells that are likely to contain gene mutations in one or more genes in the HDR pathway. In some embodiments, the patient is an untreated patient. Such a diagnosis may be based solely on the determination that the particular patient being evaluated has cancer cells having a genome that contains the HRD signature, or may be based at least in part on the determination that the particular patient being evaluated has cancer cells having a genome that contains the HRD signature. For example, a patient determined to have cancer cells whose genome contains the presence of an HRD signature can be diagnosed as having cancer cells that are likely to contain gene mutations in one or more genes in the HDR pathway based on a combination of the presence of the HRD signature and a family history of cancer, or the presence of behavioral risk factors (e.g., smoking).

[0098] In some cases, a clinician or healthcare provider, or a group of clinicians or healthcare providers, can diagnose a patient determined to have cancer cells with an HRD signature as having cancer cells likely to respond to a particular cancer treatment regimen. In some embodiments, the patient is a treatment-naive patient. Such a diagnosis may be based solely on a determination of whether a sample from the patient contains cancer cells with an HRD signature (or whether the sample contains DNA derived from such cells), or may be based at least in part on a determination of whether a sample from the patient contains cancer cells with an HRD signature (or whether the sample contains DNA derived from such cells). For example, a patient determined to have cancer cells with an HRD signature can be diagnosed as likely to respond to a particular cancer treatment regimen based on a combination of the HRD signature and the status of the deficiency of one or more tumor suppressor genes (e.g., BRCA1 / 2, RAD51C), family history of cancer, or the presence of behavioral risk factors (e.g., smoking). As described herein, a patient determined to have cancer cells with an HRD signature can be diagnosed as likely to respond to a cancer treatment regimen that includes the use of platinum-based chemotherapeutic agents, such as cisplatin, carboplatin, oxaliplatin or picoplatin, anthracyclines, such as epirubicin or doxorubicin, topoisomerase I inhibitors, such as campothecin, topotecan or irinotecan, PARP inhibitors, radiation, combinations thereof, or combinations of any of the foregoing with another anti-cancer drug. In some embodiments, the patient is a treatment-naive patient.

[0099] Once a clinician or healthcare provider, or a group of clinicians or healthcare providers, determines that a sample from a patient contains cancer cells having a genome lacking an HRD signature (or the sample contains DNA derived from such cells), the clinician or healthcare provider (or group) can classify the patient as having cancer cells with a genome lacking an HRD signature. In some embodiments, the patient is a treatment-naive patient. Optionally, a clinician or healthcare provider, or a group of clinicians or healthcare providers, can diagnose a patient determined to have cancer cells having a genome lacking an HRD signature as having cancer cells that are likely to have functional HDR. Optionally, a clinician or healthcare provider, or a group of clinicians or healthcare providers, can diagnose a patient determined to have cancer cells having a genome lacking an HRD signature as having cancer cells that are likely to have a low likelihood of containing a genetic mutation in one or more genes in the HDR pathway. Optionally, a clinician or healthcare provider, or a group of clinicians or healthcare providers, can diagnose a patient determined to have cancer cells having a genome lacking an HRD signature or having a large number of CA regions covering the entire chromosome as having cancer cells that are likely to respond to a cancer treatment regimen that includes the use of a platinum-based chemotherapeutic agent such as cisplatin, carboplatin, oxaliplatin or picoplatin, an anthracycline such as epirubicin or doxorubicin, a topoisomerase I inhibitor such as campothecin, topotecan or irinotecan, a PARP inhibitor, or a cancer therapeutic agent that is unlikely to respond to radiation and / or is not associated with HDR, such as one or more taxane agents, a growth factor inhibitor or a growth factor receptor inhibitor, an antimetabolite, etc. In some embodiments, the patient is a treatment-naive patient.

[0100] As described herein, this document also provides a method for performing a diagnostic analysis of a nucleic acid sample from a cancer patient (e.g., a genomic nucleic acid sample or a genomic nucleic acid sample amplified therefrom) to determine whether the sample contains cancer cells containing an HRD signature and / or a number of CA regions covering the entire chromosome (or whether the sample contains DNA derived from such cells). In some embodiments, the patient is a treatment-naive patient. For example, one or more laboratory technicians or laboratory personnel can detect the presence or absence of an HRD signature in the genome of the patient's cancer cells (or DNA derived therefrom), or the presence or absence of a number of CA regions covering the entire chromosome in the genome of the patient's cancer cells. In some cases, one or more laboratory technicians or laboratory personnel can (a) receive a cancer cell sample obtained from the patient, a genomic nucleic acid sample obtained from the cancer cells obtained from the patient, or a concentrated and / or amplified such genomic nucleic acid sample obtained from the cancer cells obtained from the patient, and (b) perform an analysis (e.g., an SNP array-based assay or a sequencing-based assay) using the received material to detect the presence or absence of an HRD signature as described herein, or the presence or absence of a number of CA regions covering the entire chromosome, thereby detecting the presence or absence of an HRD signature in the genome of the patient's cancer cells, or the presence or absence of a number of CA regions covering the entire chromosome. In some cases, one or more laboratory technicians or laboratory personnel can receive, directly or indirectly from a clinician or healthcare provider, a sample to be analyzed (e.g., a cancer cell sample obtained from the patient, a genomic nucleic acid sample obtained from the cancer cells obtained from the patient, or a concentrated and / or amplified such genomic nucleic acid sample obtained from the cancer cells obtained from the patient). In some embodiments, the patient is a treatment-naive patient.

[0101] Once a technician or examiner, or a group of technicians or examiners, detects the presence of an HRD signature as described herein, the technician or examiner (or group) can associate that HRD signature or the result(s) of the diagnostic analysis performed (or the combination of results or summary of results) with the name of the corresponding patient, medical record, symbol / numeric identifier, or a combination thereof. Such identification may be based solely on detecting the presence of the HRD signature or may be based at least in part on detecting the presence of the HRD signature. For example, a technician or examiner can identify a patient having cancer cells detected as having an HRD signature as potentially having cancer cells with a defective HDR (or being highly likely to respond to a particular treatment as described herein in terms of length) based on a combination of the HRD signature and the results of other genetic and biochemical tests performed at the testing institution. In some embodiments, the patient is an untreated patient.

[0102] The reverse is also true. That is, once a technician or examiner, or a group of technicians or examiners, detects the absence of an HRD signature, the technician or examiner (or group) can associate that HRD signature or the result(s) of the diagnostic analysis performed (or the combination of results or summary of results) with the name of the corresponding patient, medical record, symbol / numeric identifier, or a combination thereof. In some cases, a technician or examiner, or a group of technicians or examiners, can identify a patient having cancer cells detected as lacking an HRD signature as potentially having cancer cells with an intact HDR (or being less likely to respond to a particular treatment as described herein in terms of length) based solely on the absence of the HRD signature or based on a combination of the presence of the HRD signature and the results of other genetic and biochemical tests performed at the testing institution. In some embodiments, the patient is an untreated patient.

[0103] The results of any analysis according to the present invention are, in many cases, conveyed or communicable to physicians, genetic counselors, and / or patients (or other parties such as researchers), in a communicable form that can be conveyed to any of the above parties. Such forms can vary and may or may not be tangible. The results can be embodied in a description, diagram, photograph, chart, image, or any other visual form. For example, when explaining the results, a graph or diagram showing genotype or LOH (or HRD status) information can be used. The description and visual forms can be recorded on a tangible medium, such as paper, a computer-readable medium, such as a floppy disk, compact disk, flash memory, etc., or an intangible medium, such as an electronic medium in the form of an email or recorded on a website on the Internet or an intranet. Further, the results can be recorded in an audio form and transmitted via any suitable medium, such as an analog cable line or a digital cable line, an optical fiber cable, etc., via a telephone, facsimile, wireless mobile phone, Internet phone, etc.

[0104] Thus, information and data regarding test results can be created anywhere in the world and transmitted to different locations. As one exemplary example, when an assay is performed outside the United States, information and data regarding the test results are created, cast in a communicable form as described above, and then imported into the United States. Accordingly, the present invention also encompasses a method for generating communicable form information regarding an HRD signature for at least one patient sample. The method includes: (1) determining an HRD signature according to the method of the present invention; and (2) embodying the result of the determining step in a communicable form. The communicable form is the result of such a method.

[0105] Some aspects of the invention described herein involve correlating an HRD signature according to the invention (e.g., the total number of indicator CA regions above a reference number, or the CA region score or composite CA region score) with certain clinical features (e.g., a high likelihood of a BRCA1 or BRCA2 gene deletion; a high likelihood of an HDR deficiency; a high likelihood of response to a treatment regimen including DNA damaging agents, anthracyclines, topoisomerase I inhibitors, radiation, and / or PARP inhibitors), and optionally correlating the absence of an HRD signature with one or more other clinical features. Throughout this document, whenever such aspects are described, another aspect of the invention may optionally involve, in addition to or instead of the correlating step, one or both of the following steps: (a) concluding that a patient has a clinical feature based at least in part on the presence or absence of an HRD signature; or (b) communicating that a patient has a clinical feature based at least in part on the presence or absence of an HRD signature.

[0106] By way of illustration, but not limitation, one aspect described in this document is a method for predicting the response of cancer patients to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, and / or a PARP inhibitor, the method comprising: (1) determining, in a sample, two or more of (a) an LOH region score for the sample; (b) a TAI region score for the sample; or (c) an LST region score for the sample; and (2) correlating (a) a combination of two or more of the LOH region score, TAI region score, and LST region score that exceeds a reference number (e.g., a composite CA region score) with a high likelihood of responding to the treatment regimen; or optionally (2)(b) correlating a combination of two or more of the LOH region score, TAI region score, and LST region score that does not exceed a reference number (e.g., a composite CA region score) with a low likelihood of responding to the treatment regimen; or optionally (2)(c) correlating the average (e.g., arithmetic mean) of the LOH region score, TAI region score, and LST region score. According to the preceding paragraph, this description of this aspect is to be construed as including descriptions of two related alternative aspects.One such embodiment is a method for predicting the response of a cancer patient to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, and / or a PARP inhibitor, the method comprising: (1) determining, in a sample, (a) an LOH region score for the sample; (b) a TAI region score for the sample; or (c) an LST region score for the sample; or (d) two or more of an LOH region score, a TAI region score, and an LST region score for the sample, or the average (e.g., arithmetic mean) of the LOH region score, the TAI region score, and the LST region score; and (2) concluding, based at least in part on a combination (e.g., a composite CA region score) of two or more of an LOH region score, a TAI region score, and an LST region score that exceeds a reference number, that the patient is likely to respond to the cancer treatment regimen; or optionally (2)(b) concluding, based at least in part on a combination (e.g., a composite CA region score) of two or more of an LOH region score, a TAI region score, and an LST region score that does not exceed a reference number, or the average (e.g., arithmetic mean) of the LOH region score, the TAI region score, and the LST region score, that the patient is unlikely to respond to the cancer treatment regimen.Another such aspect is a method for predicting the response of a cancer patient to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, and / or a PARP inhibitor, the method comprising: (1) determining, in a sample, (a) a LOH region score for the sample; (b) a TAI region score for the sample; or (c) a LST region score for the sample; or (d) two or more of an average (e.g., arithmetic mean) of the LOH region score, the TAI region score, and the LST region score; and (2) (a) communicating that the patient has a high likelihood of responding to the cancer treatment regimen, based at least in part on a combination (e.g., a composite CA region score) of two or more of the LOH region score, the TAI region score, and the LST region score that exceeds a reference number; or an average (e.g., arithmetic mean) of the LOH region score, the TAI region score, and the LST region score; or optionally (2)(b) communicating that the patient has a low likelihood of responding to the cancer treatment regimen, based at least in part on a combination (e.g., a composite CA region score) of two or more of the LOH region score, the TAI region score, and the LST region score that does not exceed a reference number; or an average (e.g., arithmetic mean) of the LOH region score, the TAI region score, and the LST region score.

[0107] Correlating the output of a particular assay or analysis (e.g., the total number of indicator CA regions above a reference number, the presence of an HRD signature, etc.) with some likelihood (e.g., increase, no increase, decrease, etc.) of some clinical feature (e.g., response to a particular treatment, cancer-specific death, etc.), or additionally or alternatively, concluding or communicating such a clinical feature at least in part based on the output of such a particular assay or analysis. In each aspect described herein, such correlating, concluding, or communicating may include assigning a risk or likelihood that a clinical feature will occur based at least in part on the output of the particular assay or analysis. In some aspects, such risk is the percent probability that an event or outcome will occur. In some aspects, a patient is assigned to a risk group (e.g., low risk, medium risk, high risk, etc.). In some aspects, "low risk" is any percent probability less than 5%, less than 10%, less than 15%, less than 20%, less than 25%, less than 30%, less than 35%, less than 40%, less than 45%, or less than 50%. In some aspects, "medium risk" is any percent probability greater than 5%, greater than 10%, greater than 15%, greater than 20%, greater than 25%, greater than 30%, greater than 35%, greater than 40%, greater than 45%, or greater than 50% and less than 15%, less than 20%, less than 25%, less than 30%, less than 35%, less than 40%, less than 45%, less than 50%, less than 55%, less than 60%, less than 65%, less than 70%, or less than 75%. In some aspects, "high risk" is any percent probability greater than 25%, greater than 30%, greater than 35%, greater than 40%, greater than 45%, greater than 50%, greater than 55%, greater than 60%, greater than 65%, greater than 70%, greater than 75%, greater than 80%, greater than 85%, greater than 90%, greater than 95%, or greater than 99%.

[0108] As used herein, "communicating" a particular piece of information means informing another person of such information or transferring such information to a thing (e.g., a computer). In some methods of the present invention, the prognosis or likelihood of a patient's response to a particular treatment is communicated. In some embodiments, the information used to arrive at such a prognosis or prediction of response (e.g., an HRD signature according to the present invention, etc.) is communicated. This communication may be by auditory (e.g., oral), visual (e.g., written), electronic (e.g., data transferred from one computer system to another computer system), etc. In some embodiments, communicating a cancer classification (e.g., prognosis, likelihood of response, appropriate treatment, etc.) includes creating a report communicating 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 computer computing device (e.g., a handheld device, a desktop computer, a smart device, a 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). The cancer classification can also be communicated by transferring information (e.g., data) that embodies the classification to a server computer and enabling an intermediate user or end user to access such information (e.g., by viewing the information when displayed from the server, by downloading the information in the form of one or more files transferred from the server to the device of the intermediate user or end user, etc.).

[0109] When an aspect of the present invention includes concluding some fact (e.g., a patient's prognosis or the likelihood that a patient will respond to a particular treatment regimen), this will necessarily, in some embodiments, typically include a computer program that concludes such fact after executing an algorithm that applies information regarding the CA region according to the present invention.

[0110] In each aspect described herein, where several CA regions (e.g., indicator CA regions), or the total combined length of such CA regions, or the average (e.g., arithmetic mean) of the composite CAR region scores are involved, the invention encompasses related aspects involving test values or scores (e.g., CA region scores, LOH region scores, etc.) that are derived from, incorporate, and / or reflect to at least some extent such numbers or lengths. In other words, in various methods, systems, etc. of the present invention, it is not necessary to use the number or length of the bare CA regions as they are, and test values or scores derived from such numbers or lengths may be used instead.For example, one aspect of the present invention is a method for treating cancer in a patient, comprising: (1) determining, in a sample from the patient, (a) the number of indicator LOH regions, (b) the number of indicator TAI regions, or (c) the number of indicator LST regions, two or more or the average (e.g., arithmetic mean); (2) providing one or more test values derived from the number of the indicator LOH regions, indicator TAI regions, and / or indicator LST regions; (3) comparing the test values with one or more reference values (e.g., reference values derived from the number of indicator LOH regions, indicator TAI regions, and / or indicator LST regions in a reference population (e.g., mean value, median value, quartile value, quintile value, etc.)); and (4) (a) administering an anti-cancer drug to the patient, or recommending, prescribing, or initiating a treatment regimen comprising chemotherapy and / or synthetic lethal agents, at least partially based on the comparing step that reveals that one or more of the test values are greater than at least one of the reference values (e.g., at least 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, or 10-fold greater; at least 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations, or 10 standard deviations greater); or optionally (4)(b) recommending, prescribing, or initiating a treatment regimen not comprising chemotherapy and / or synthetic lethal agents, at least partially based on the comparing step that reveals that one or more of the test values are not greater than at least one of the reference values (e.g., 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, or 10-fold or less; 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations, or 10 standard deviations or less).The present invention includes corresponding aspects that are used to determine, with modifications as necessary, whether test values or scores can be used to determine the prognosis of a patient, the likelihood that a patient will respond to a particular treatment regimen, the likelihood that a patient or a patient's sample has BRCA1 deficiency, BRCA2 deficiency, RAD51C deficiency, or HDR deficiency, etc. within the scope.

[0111] Figure 8 shows an exemplary process by which a computer calculation system (or a computer program including computer-executable instructions, e.g., software) can identify LOH loci or regions from genotype data as described herein. This process can be adapted to be used to determine TAI and LST, as will be apparent to those skilled in the art. When the observed ratio of the signals of two alleles A and B is 2:1, there are two possibilities. The first possibility is that the cancer cells have LOH with deletion of allele B in a sample that is 50% contaminated with normal cells. The second possibility is that there is no LOH, but allele A is duplicated in a sample that is not contaminated with normal cells. The process starts at box 1500. In box 1500, the following data: (1) the sample-specific normalized signal intensities of both alleles at each locus and (2) an assay-specific (specific to different SNP arrays and sequence-based approaches) parameter set defined based on the analysis of a number of samples with known ASCN profiles are collected by the computer calculation system. As described herein, any suitable assay, such as an SNP array-based assay or a sequencing-based assay, can be used to evaluate loci along a chromosome for homozygosity or heterozygosity. Optionally, a system including a signal detector and a computer can be used to collect data (e.g., fluorescence signals or sequencing results) (e.g., the sample-specific normalized signal intensities of both alleles at each locus) regarding the homozygosity or heterozygosity of multiple loci. In box 1510, the allele-specific copy number (ASCN) is reconstructed at each locus (e.g., each SNP). The ASCN is the copy number of both the paternal and maternal alleles. In box 1530, a likelihood function is used to determine whether a homozygous locus or a region of homozygous loci is due to LOH. This may be conceptually similar to the previously described algorithm designed to reconstruct the total copy number (not the ASCN) at each locus (e.g., SNP).See International Application No. PCT / US2011 / 026098 to Abkevich et al. The likelihood function can be maximized over the ASCN of all loci, the level of contamination by benign tissue, the total copy number averaged across the entire genome, and the sample-specific noise level. In Box 1540, the LOH region is determined as a series of SNPs where one of the ASCNs (paternal or maternal) is 0. In some embodiments, the computer process further includes a step of querying whether the patient is untreated or a step of determining whether the patient is untreated.

[0112] Figure 3 shows an exemplary process by which a computer computing system can determine the presence or absence of an LOH signature, which is included to illustrate how this process can be applied to both TAI and LST, as will be apparent to those skilled in the art. The process starts at box 300, where data regarding the homozygosity or heterozygosity of multiple loci along a chromosome is collected by the computer computing system. As described herein, any suitable assay, such as an SNP array-based assay or a sequencing-based assay, can be used to evaluate the loci along the chromosome for homozygosity or heterozygosity. In some cases, a system comprising a signal detector and a computer can be used to collect data regarding the homozygosity or heterozygosity of multiple loci (e.g., fluorescence signals or sequencing results). At box 310, the computer computing system evaluates the data regarding the homozygosity or heterozygosity of the multiple loci and the position or spatial relationship of each locus to determine the length of any LOH regions present along the chromosome. At box 320, the computer computing system evaluates the data regarding the number of detected LOH regions and the length of each detected LOH region to determine the number of LOH regions that have a length (a) greater than or equal to a preset number of Mbs (e.g., 15 Mbs) and (b) shorter than the total length of the chromosome containing the LOH region. Alternatively, the computer computing system can determine the total length of the LOH as described above or sum the lengths of the LOH. At box 330, the computer computing system formats an output indicating the presence or absence of an HRD signature. Once formatted, the computer computing system can present the output to a user (e.g., a laboratory technician, clinician, or healthcare provider). As described herein, the presence or absence of an HRD signature can be used to indicate a patient's likely HDR status, a likely presence or absence of genetic mutations in genes in the HDR pathway, and / or a possible cancer treatment regimen.

[0113] FIG. 4 is a diagram of an example of a computer device 1400 and a mobile computer device 1450 that can be used with the techniques described herein. The computer computing device 1400 is intended to be various types of digital computers, such as, for example, laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other suitable computers. The computer computing device 1450 is intended to be various types of mobile devices, such as, for example, personal digital assistants, cellular phones, smartphones, and other similar computer computing devices. It is intended that the components shown here, their connections and relationships, and their functions are merely exemplary and are not intended to limit the implementation of the invention described and / or claimed in this document.

[0114] The computer computing device 1400 includes a processor 1402, a memory 1404, a storage device 1406, a high-speed interface 1408 connected to the memory 1404 and a high-speed expansion port 1410, and a low-speed interface 1415 connected to the low-speed bus 1414 and the storage device 1406. The components 1402, 1404, 1406, 1408, 1410, and 1415 are interconnected using various buses respectively and may be mounted on a common motherboard or otherwise as appropriate. The processor 1402 can process instructions for execution within the computer computing device 1400, including instructions stored in the memory 1404 or the storage device 1406, to display graphical information for a GUI in a display 1416, for example, connected to the high-speed interface 1408. In other implementations, multiple processors and / or multiple buses may be used as appropriate, along with multiple memories and memory types. Also, multiple computer computing devices 1400 may be connected, with each device providing a portion of the necessary operations (e.g., as a server bank, a collection of blade servers, or a multiprocessor system).

[0115] Memory 1404 stores information within computer computing device 1400. In one implementation, memory 1404 is a volatile memory unit. In another implementation, memory 1404 is a non-volatile memory unit. Memory 1404 may also be another type of computer-readable medium, such as a magnetic disk or an optical disk.

[0116] Storage device 1406 can provide mass storage to computer computing device 1400. In one implementation, storage device 1406 may be 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 may include and be equipped with a number of various devices including devices in a storage area network or other configurations. A computer program product can be incorporated into an information carrier so as to be touchable by hand. A computer program product may also include instructions that, when executed, perform one or more methods, such as the methods described herein. The information carrier is a computer-readable medium or a machine-readable medium, such as memory 1404, storage device 1406, memory mounted on processor 1402, or a propagated signal.

[0117] The high-speed controller 1408 manages bandwidth-intensive operations for the computer computing device 1400, while the low-speed controller 1415 manages operations with low bandwidth intensity. Such a functional assignment is merely exemplary. In one implementation, the high-speed controller 1408 is connected to the memory 1404, the display 1416 (e.g., via a graphics processor or accelerator), and the high-speed expansion port 1410, and the high-speed expansion port 1410 may receive various expansion cards (not shown). In this implementation, the low-speed controller 1415 is connected to the storage device 1406 and the low-speed expansion port 1414. The low-speed expansion port may include various communication ports (e.g., USB, Bluetooth, Ethernet, or wireless Ethernet), and may be connected to one or more input / output devices, such as a keyboard, a pointing device, a scanner, an optical reader, a fluorescence signal detector, or a networking device, such as a switch or a router, for example, via a network adapter.

[0118] As shown in the drawings, the computer computing device 1400 can be implemented in a number of different forms. For example, the computer computing device 1400 may be implemented as a standard server 1420, and may be implemented multiple times in a collection of such servers. The computer computing device 1400 may be implemented as part of a rack server system 1424. Further, the computer computing device 1400 may be implemented in a personal computer, such as a laptop computer 1422. Or, components from the computer computing device 1400 may be combined with other components in a mobile device (not shown), such as the device 1450. Such devices may each include one or more of the computer computing devices 1400, 1450, and the entire system may consist of multiple computer computing devices 1400, 1450 that communicate with each other.

[0119] The computer computing device 1450 includes, among other components (such as scanners, optical readers, fluorescence signal detectors), a processor 1452, a memory 1464, an input / output device, such as a display 1454, a communication interface 1466, and a transceiver 1468. The device 1450 may also be provided with a storage device, such as a microdrive or other device, to provide additional storage. The components 1450, 1452, 1464, 1454, 1466, and 1468 are interconnected using various buses, and some of the components may be mounted on a common motherboard or otherwise as appropriate.

[0120] The processor 1452 can execute instructions within the computer computing device 1450, including instructions stored in the memory 1464. The processor may be implemented as a chipset of separate and multiple analog and digital processors. The processor may, for example, provide control of the user interface, applications run by the device 1450, and wireless communication by the device 1450, in order to properly coordinate the other components of the device 1450.

[0121] Processor 1452 can communicate with the user via a display interface 1456 connected to a control interface 1458 and 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 suitable display technology. The display interface 1456 may include appropriate circuitry for driving the display 1454 to present graphic information and other information to the user. The control interface 1458 may receive commands from the user and convert the commands for transmission to the processor 1452. Further, an external interface 1462 may communicate with the processor 1452 to enable near area communication between the device 1450 and other devices. The external interface 1462 may provide, for example, wired communication in some implementations, wireless communication in other implementations, or multiple interfaces may be used.

[0122] Memory 1464 stores information within the computer computing device 1450. The memory 1464 can be implemented as one or more of a computer-readable medium, a volatile memory unit, or a non-volatile memory unit. An extended memory 1474 may be installed via an extended interface 1472 and connected to the device 1450. The extended interface 1472 may include, for example, a SIMM (Single In-line Memory Module) card interface. Such extended memory 1474 may provide additional storage space for the device 1450 and may store applications or other information for the device 1450. For example, the extended memory 1474 may include instructions for implementing or supplementing the processes described herein and may also include secure information. Thus, for example, the extended memory 1474 may be provided as a security module for the device 1450 and may be programmed with instructions to enable secure use of the device 1450. Further, secure applications may be provided along with additional information via a SIMM card, such as by placing identification information on the SIMM card so that it cannot be hacked.

[0123] The memory may include, for example, flash memory and / or NVRAM memory as discussed below. In one implementation, the computer program product is incorporated into an information carrier so as to be touchable by hand. The computer program product includes instructions for performing one or more methods, for example, the methods described herein, when executed. The information carrier is a computer-readable medium or a machine-readable medium, such as memory 1464, extended memory 1474, the memory mounted on processor 1452, or a propagated signal that can be received, such as a propagated signal that can be received by transceiver 1468 or external interface 1462.

[0124] Device 1450 may communicate wirelessly via communication interface 1466. Communication interface 1466 may include digital signal processing circuitry if necessary. Communication interface 1466 may provide communication under various modes or protocols, such as, in particular, GSM voice calls, SMS, EMS, or MMS messaging, CDMA, TDMA, PDC, WCDMA, CDMA2000, or GPRS. Such communication may occur, for example, via radio frequency transceiver 1468. Further, short-range communication may occur, for example, using Bluetooth, WiFi, or other such transceivers (not shown). Further, a GPS (Global Positioning System) receiver module 1470 may provide additional navigation-related wireless data and location-related wireless data to device 1450, and the navigation-related wireless data and location-related wireless data may be used, as appropriate, by an application operating on device 1450.

[0125] Device 1450 may also perform audible communication using an audio codec 1460. The audio codec 1460 may receive voice information from a user and convert it into usable digital information. Further, the audio codec 1460 may generate audible sound for the user, for example, via a speaker, such as in a handset of device 1450. Such sound may include sound from a voice telephone call, may include recorded voice (such as voice mail, music files, etc.), and may also include sound created by an application operating on device 1450.

[0126] As shown in the drawings, computer computing device 1450 can be implemented in many different forms. For example, computer computing device 1450 may be implemented as a mobile phone 1480. Computer computing device 1450 may also be implemented as part of a smartphone 1482, a personal digital assistant, or other similar mobile device.

[0127] 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 may include implementations in one or more computer programs that are executable and / or interpretable on a programmable system including at least one programmable processor coupled to receive data and instructions from, and to transmit data and instructions to, a memory system, at least one input device, and at least one output device. The programmable processor may be special purpose or general purpose.

[0128] These computer programs (also known as programs, software, software applications, or code) include machine instructions for a programmable processor and can be executed in a high-level procedural programming language and / or an object-oriented programming language and / or 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 disks, optical disks, memory, and programmable logic devices (PLDs)) used to provide machine instructions and / or data to a programmable processor that includes a machine-readable medium that receives the 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.

[0129] 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 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). Input from the user can be received in any form including acoustic, speech, or tactile input.

[0130] The systems and methods described herein can be executed in a computer computing system that includes a back-end component (e.g., as a data server), or a middleware component (e.g., an application server), or 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 the execution of the systems and methods described herein), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by digital data communication in any form or medium (e.g., a communication network). Examples of communication networks include local area networks ("LANs"), wide area networks ("WANs"), and the Internet.

[0131] The computer computing system may include clients and servers. The clients and servers are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by computer programs that operate on respective computers and have a client-server relationship to each other.

[0132] In some cases, the computer calculation system provided herein may be configured to include one or more sample analyzers. The sample analyzer may be configured to generate a plurality of signals for genomic DNA of at least one pair of human chromosomes from cancer cells. For example, the sample analyzer can generate signals that can be interpreted in a way that identifies the homozygosity or heterozygosity of loci along the chromosome. In some cases, the sample analyzer may be configured to perform one or more steps of an SNP array-based assay or a sequencing-based assay, and may be configured to generate and / or capture signals from such assays. In some cases, the computer calculation system provided herein may be configured to include a computer calculation device. In such a case, the computer calculation device may be configured to receive signals from the sample analyzer. The computer calculation device may include computer-executable instructions or a computer program (e.g., software) including computer-executable instructions for performing one or more of the methods or steps described herein. In some cases, such computer-executable instructions may be able to instruct the computer calculation device to analyze signals from the sample analyzer, another computer calculation device, an SNP array-based assay, or a sequencing-based assay.Analyzing such signals to determine the genotype, homozygosity at a particular locus or other chromosomal abnormalities, CA regions, the number of CA regions, the size of the CA regions, the number of CA regions having a particular size or size range, whether the sample is positive for an HRD signature, the number of indicator CA regions in at least one pair of human chromosomes, the likelihood of a BRCA1 gene and / or BRCA2 gene deletion, the likelihood of an HDR deficiency, the likelihood that a cancer patient will respond to a particular cancer treatment regimen (e.g., a regimen including a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, a PARP inhibitor, or a combination thereof), or a combination of these items can be determined.

[0133] In some cases, the computer computing system provided herein may include computer executable instructions or a computer program (e.g., software) including computer executable instructions for formatting an output that provides an indication of the number of CA regions, the size of the CA regions, the number of CA regions having a particular size or size range, whether the sample is positive with respect to the HRD signature, the number of indicator CA regions in at least one pair of human chromosomes, the likelihood of a BRCA1 gene and / or BRCA2 gene deletion, the determination of the likelihood of an HDR deficiency, the likelihood that a cancer patient will respond to a particular cancer treatment regimen (e.g., a regimen including a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, a PARP inhibitor, or a combination thereof), or a combination of these items. In some cases, the computer computing system provided herein may include computer executable instructions or a computer program (e.g., software) including computer executable instructions for determining a desired cancer treatment regimen for a particular patient, at least in part based on the presence or absence of an HRD signature or the number of indicator CA regions.

[0134] In some cases, the computer calculation system provided in this specification may include a pretreatment device configured to process a sample (e.g., cancer cells) so as to be able to perform an SNP array-based assay or a sequencing-based assay. Examples of the pretreatment device include, but are not limited to, a device configured to enrich a cell population for cancer cells as opposed to non-cancer cells, a device configured to lyse cells and / or extract genomic nucleic acids, and a device configured to enrich a sample for specific genomic DNA fragments.

[0135] This document also provides a kit for evaluating a sample (e.g., cancer cells) as described herein. For example, this document provides a kit for evaluating cancer cells with respect to the presence of an HRD signature or for determining the number of indicator CA regions in at least one pair of human chromosomes. The kit provided herein may be combined with a computer program product that includes either SNP probes (e.g., an array of SNP probes for performing the SNP array-based assays described herein) or primers (e.g., primers designed to sequence SNP regions via a sequencing-based assay), and computer-executable instructions (e.g., computer-executable instructions for determining the number of CA regions having a particular size or size range) for performing one or more of the methods or steps described herein. Optionally, the kit provided herein may include at least 500, 1000, 10,000, 25,000, or 50,000 SNP probes capable of hybridizing to polymorphic regions of human genomic DNA. Optionally, the kit provided herein may include at least 500, 1000, 10,000, 25,000, or 50,000 primers capable of sequencing polymorphic regions of human genomic DNA. Optionally, the kit provided herein may include one or more other components for performing SNP array-based assays or sequencing-based assays. Examples of such other components include, but are not limited to, buffers, sequencing nucleotides, enzymes (e.g., polymerase), etc. This document also provides for the use of any suitable number of materials provided herein in the manufacture of a kit for performing one or more of the methods or steps described herein. For example, this document provides for the use of a collection of SNP probes (e.g., a collection of 10,000 to 100,000 SNP probes) and the computer program product provided herein in the manufacture of a kit for evaluating cancer cells with respect to the presence of an HRD signature.As another example, the present document provides for the use of a collection of primers (e.g., a collection of 10,000 to 100,000 primers for sequencing SNP regions) and the computer program product provided herein in the manufacture of a kit for assessing cancer cells with respect to the presence of an HRD signature.

[0136] Specific embodiments The following are specific embodiments of the present disclosure, namely, exemplary but non-limiting details of the methods and systems according to the more general description above.

[0137] In some embodiments, the sample used is a frozen tumor sample. In some embodiments, the sample is derived from a specific breast cancer subtype selected from triple negative, ER+ / HER2-, ER- / HER2+, or ER+ / HER2+. In some embodiments, the assay portion of the method, system, etc. includes assaying the sample to sequence the BRCA1 gene and / or the BRCA2 gene (as well as any one or more other genes in Table 1). In some embodiments, the assay portion of the method, system, etc. includes assaying the sample to determine allelic amounts (e.g., genotype, copy number, etc.) for at least 10,000, 20,000, 30,000, 40,000, 50,000, 60,000, 70,000, 80,000, 90,000, 100,000 or more selected SNPs across the genome. In some embodiments, the SNP analysis is performed using an oligonucleotide microarray as discussed above. In some embodiments, the BRCA sequence analysis, SNP analysis or both are performed by using probe capture (e.g., probes for each SNP to be analyzed, and / or probes for capturing the entire coding region of BRCA1 and / or BRCA2), followed by a PCR enrichment technique (e.g., Agilent™ SureSelect XT). In some embodiments, the BRCA sequence analysis, SNP analysis or both are performed by processing the output from an enrichment technique using a "next generation" sequencing platform (e.g., Illumina™ HiSeq2500). In some embodiments, the sample is analyzed for somatic and / or germline mutations in BRCA1 / 2 that may include large scale rearrangements. In some embodiments, the sample is analyzed for methylation of the BRCA1 promoter (e.g., by a qPCR assay (e.g., SA Biosciences)).In some embodiments, if the sample has greater than 10% (or 5%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%) methylation (e.g., percentage of methylation of the promoter CpGs of BRCA1 or BRCA2), the sample is determined to have high methylation (or “being methylated”). In some embodiments, for example, to determine whether a mutation in BRCA1 or BRCA2 is germline or somatic, DNA from a patient's matched normal (non-tumor) tissue may be analyzed.

[0138] In some embodiments, an LOH region score can be calculated by counting the number of LOH regions that are greater than 15 Mb in length but shorter than the length of the entire chromosome. In some embodiments, a TAI region score can be calculated by counting the number of telomere regions that are greater than 11 Mb in length, extend into one of the subtelomeres but do not cross the centromere, and are associated with allelic imbalance. In some embodiments, an LST region score can be calculated by counting the number of discontinuities between regions greater than 10 Mb in length that have a stable copy number after filtering out regions shorter than 3 megabases. In some embodiments, the LST region score can be modified by adjusting it by ploidy: LSTm = LST - kP, where P is the ploidy and k is a constant (in some embodiments, k = 15.5). In some embodiments, BRCA1 / 2 deficiency can be defined as a loss of function resulting from a mutation in BRCA1 or BRCA2, or methylation of the promoter region of BRCA1 or BRCA2, accompanied by LOH in the affected gene. In some embodiments, the response to treatment may be a partial complete response (“pCR”), which can be defined in some embodiments as the Miller-Payne 5 state after treatment (e.g., neoadjuvant).

[0139] In some embodiments, the claimed method is for BRCA deficiency at least 8 * 10 -12, 6 * 10 -6 , 0.0009, 0.01, 0.03, 2 * 10 -16 , 3 * 10 -6 , 10 -6 , 0.0009, 8 * 10 -12 , 2 * 10 -16 , 8 * 10 -8 , 6 * 10 -6 , 3 * 10 -6 Or predict with a p-value of 0.0002 (e.g., pre-define each CA region score and optionally combine multiple scores so that these p-values are obtained). In some embodiments, the p-value is calculated by the Kolmogorov-Smirnov test. In some embodiments, the HRD score and age at diagnosis can be encoded as numerical (e.g., integer) variables, the breast cancer stage and subtype can be encoded as categorical variables, and the grade can be analyzed as either a numerical variable or a categorical variable or both.

[0140] In some embodiments, the p-value is two-sided. In some embodiments, logistic regression analysis can be used to predict BRCA1 / 2 deficiency based on the HRD score (including the HRD-composite score) as disclosed herein. In some embodiments, various CA region scores are correlated according to the following correlation coefficients (e.g., defined for the purpose of achieving the following): LOH region score and TAI region score = 0.69 (p = 10 -39 ), between LOH and LST = 0.55 (p = 2 * 10 -19 ), and between TAI and LST = 0.39 (p = 10 -9 ).

[0141] In some embodiments, the method combines the LOH region score and the TAI region score as follows to detect BRCA1 / 2 deficiency and / or predict treatment response (e.g., response to platinum therapy, e.g., cisplatin): Composite CA region score = 0.32 * LOH region score + 0.68 * TAI region score. In some embodiments, the method combines the LOH region score, the TAI region score, and the LST region score as follows to detect BRCA1 / 2 deficiency and / or predict treatment response (e.g., response to platinum therapy, e.g., cisplatin): Composite CA region score = 0.21 * LOH region score + 0.67 * TAI region score + 0.12 * LST region score. In some embodiments, the method combines the LOH region score, the TAI region score, and the LST region score as follows to detect BRCA1 / 2 deficiency and / or predict treatment response (e.g., response to platinum therapy, e.g., cisplatin): Composite CA region score = 0.11 * LOH region score + 0.25 * TAI region score + 0.12 * LST region score. In some embodiments, the method combines the LOH region score, the TAI region score, and the LST region score as follows to detect BRCA1 / 2 deficiency and / or predict treatment response (e.g., response to platinum therapy, e.g., cisplatin): Composite CA region score = the arithmetic mean of the LOH region score, the TAI region score, and the LST region score.

[0142] In some embodiments, by combining the BRCA-deficient state and the HRD state, the treatment response can be predicted. For example, the present disclosure provides a method for predicting the response of a patient (e.g., a triple-negative breast cancer patient) to a cancer treatment regimen comprising a DNA-damaging agent (e.g., a platinum agent, e.g., cisplatin), an anthracycline, a topoisomerase I inhibitor, radiation, and / or a PARP inhibitor, comprising: determining, in cancer cells derived from a patient sample, the number of indicator CA regions (e.g., indicator LOH regions, indicator TAI regions, indicator LST regions, or any combination thereof) in at least one pair of human chromosomes of the cancer cells of the cancer patient; determining whether the cancer cells derived from the patient sample have a deficiency (e.g., a deleterious mutation, high promoter methylation) of BRCA1 or BRCA2; and diagnosing a patient whose sample is (a) the number of the indicator CA regions is greater than a reference number, or (b) either BRCA1 or BRCA2 is deficient, or both (a) and (b) as likely to respond to the cancer treatment regimen. A method may include the above steps.

[0143] Further specific embodiments Embodiment 1. An in vitro method for predicting the response of a patient to a cancer treatment regimen comprising a DNA-damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor, comprising: (1) determining, in a sample containing cancer cells, the number of indicator CA regions comprising at least two selected from indicator LOH regions, indicator TAI regions, or indicator LST regions in at least one pair of human chromosomes of the cancer cells of the cancer patient; and (2) diagnosing a patient in which the number of indicator LOH regions, indicator TAI regions, or indicator LST regions in the sample is greater than a reference number as likely to respond to the cancer treatment regimen. A method including the above steps. Aspect 2. The method according to Aspect 1, wherein at least one pair of human chromosomes represents the entire genome. Aspect 3. The method according to Aspect 1 or 2, wherein the indicator CA region is determined in at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or 21 pairs of human chromosomes. Aspect 4. The method according to any one of Aspects 1 to 3, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells. Aspect 5. The reference number of the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, the reference number of the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, and the reference number of the indicator LST region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more. The method according to any one of Aspects 1 to 4. Aspect 6. The method according to any one of Aspects 1 to 5, wherein the indicator LOH region is defined as an LOH region having a length 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, 30, 35, 40, 45, or 50 megabases or more, but shorter than either a complete chromosome or a complete chromosomal arm; the indicator TAI region is defined as a TAI region having a length 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, 30, 35, 40, 45, or 50 megabases or more, but not extending beyond the centromere; and the indicator LST region is defined as an LST region having a length 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, 30, 35, 40, 45, or 50 megabases or more. Aspect 7. The method according to any one of Aspects 1 to 6, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin, or picoplatin; the anthracycline is epirubicin or doxorubicin; the topoisomerase I inhibitor is campothecin, topotecan, or irinotecan; or the PARP inhibitor is iniparib, olaparib, or velapirib. Aspect 8. The method according to any one of Aspects 1 to 7, further comprising administering a cancer treatment regimen to a patient diagnosed as likely to respond to the cancer treatment regimen. Aspect 9. An in vitro method for predicting a patient's response to a cancer treatment regimen comprising a platinum agent, comprising: (1) determining the number of indicator CA regions, including at least two selected from the indicator LOH region, the indicator TAI region, or the indicator LST region, in at least one pair of human chromosomes of cancer cells of a cancer patient, in a sample containing cancer cells; (2) determining whether a sample containing cancer cells is deficient in BRCA1 or BRCA2; and (3) diagnosing, in the sample, a patient in which (a) the number of indicator LOH regions, indicator TAI regions, or indicator LST regions is greater than the reference number, or (b) BRCA1 or BRCA2 is deficient, or any one of (a) and (b) as having a high likelihood of responding to the cancer treatment regimen A method comprising the above steps. Aspect 10. The method according to aspect 9, wherein at least one pair of human chromosomes represents the entire genome. Aspect 11. The method according to aspect 9 or aspect 10, wherein the indicator CA region is determined in at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21 pairs of human chromosomes. Aspect 12. The method according to any one of aspects 9 to 11, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells. Aspect 13. The method according to any one of aspects 9 to 12, wherein the reference number of the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, the reference number of the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, and the reference number of the indicator LST region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more. Aspect 14. The indicator LOH region is defined as an LOH region that has a length 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, 30, 35, 40, 45, 50 megabases or more but is shorter than either a complete chromosome or a complete chromosomal arm. The indicator TAI region is defined as a TAI region that has a length 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, 30, 35, 40, 45, 50 megabases or more but does not extend beyond the centromere. And the indicator LST region is defined as an LST region that has a length 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, 30, 35, 40, 45, 50 megabases or more. The method according to any one of Aspects 9 to 13. Aspect 15. The DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin; the anthracycline is epirubicin or doxorubicin; the topoisomerase I inhibitor is campothecin, topotecan or irinotecan; or the PARP inhibitor is iniparib, olaparib or velapirib. The method according to any one of Aspects 9 to 14. Aspect 16. When a harmful mutation, loss of heterozygosity or hypermethylation in either BRCA1 or BRCA2 is detected in the sample, the sample lacks BRCA1 or BRCA2. The method according to any one of Aspects 9 to 15. Aspect 17. Hypermethylation is detected when methylation is detected in at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45% or 50% or more of the promoter CpGs of the analyzed BRCA1 or BRCA2. The method according to Aspect 16. An in vitro method for predicting a patient's response to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor, comprising: (1) determining the number of indicator CA regions, including at least two selected from indicator LOH regions, indicator TAI regions, or indicator LST regions, in at least one pair of human chromosomes of cancer cells in a sample containing cancer cells; (2) providing a test value derived from the number of the indicator CA regions; (3) comparing the test value with one or more reference values derived from the number of the indicator CA regions in a reference population; and (4) diagnosing a patient in whom the test value in the sample is greater than the one or more reference values as likely to respond to the cancer treatment regimen. A method comprising the above steps. The method according to embodiment 18, wherein at least one pair of human chromosomes represents the entire genome. The method according to embodiment 18 or 19, wherein the indicator CA region is determined in at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, or 21 pairs of human chromosomes. The method according to any one of embodiments 18 to 20, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells. Aspect 22. The method according to any one of Aspects 18 to 21, wherein the reference count of the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more than that, the reference count of the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more than that, and the reference count of the indicator LST region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more than that. Aspect 23. The method according to any one of Aspects 18 to 22, wherein the indicator LOH region is defined as an LOH region having a length 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, 30, 35, 40, 45, 50 megabases or more but shorter than either a complete chromosome or a complete chromosomal arm, the indicator TAI region is defined as a TAI region having a length 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, 30, 35, 40, 45, 50 megabases or more but not extending beyond the centromere, and the indicator LST region is defined as an LST region having a length 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, 30, 35, 40, 45, 50 megabases or more. Aspect 24. The method according to any one of aspects 18 to 23, wherein the DNA-damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubicin or doxorubicin, the topoisomerase I inhibitor is camptothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib. Aspect 25. Diagnosing that a patient in which the test value in the sample is not greater than the one or more reference values is unlikely to respond to the cancer treatment regimen, and (5)(a) recommending, prescribing, initiating or continuing a treatment regimen comprising a DNA-damaging agent, an anthracycline, a topoisomerase I inhibitor or a PARP inhibitor to a patient diagnosed as likely to respond to the cancer treatment regimen; or (5)(b) recommending, prescribing, initiating or continuing a treatment regimen not comprising a DNA-damaging agent, an anthracycline, a topoisomerase I inhibitor or a PARP inhibitor to a patient diagnosed as unlikely to respond to the cancer treatment regimen, the method according to any one of aspects 18 to 24, further comprising any one of the above. Aspect 26. The test value is calculated as the arithmetic mean of the number of indicator LOH regions, indicator TAI regions and indicator LST regions in the sample as follows: Derived by TIFF2025090619000004.tif9170, and one or more reference values are calculated as the arithmetic mean of the number of indicator LOH regions, indicator TAI regions and indicator LST regions in the sample from the reference population as follows: The method according to any one of aspects 18 to 25, derived by TIFF2025090619000005.tif9170. Aspect 27. The method according to any one of Aspects 18 to 26, comprising the step of diagnosing that a patient in which a test value in the sample is at least 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times or 10 times greater than one or more reference values, or at least 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations or 10 standard deviations greater, or at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95% greater, is likely to respond to the cancer treatment regimen. Aspect 28. A method for treating a cancer patient, comprising: (1) determining, in a sample containing cancer cells, the number of indicator CA regions, which include an indicator LOH region, an indicator TAI region, and an indicator LST region, in at least one pair of human chromosomes of the cancer patient's cancer cells; (2) providing a test value derived from the number of the indicator CA regions; (3) comparing the test value with one or more reference values derived from the number of the indicator CA regions in a reference population; and (4)(a) recommending, prescribing, initiating, or continuing a treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor, to a patient in which the test value in the sample is greater than at least one of the reference values; or (4)(b) recommending, prescribing, initiating, or continuing a treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor, to a patient in which the test value in the sample is not greater than at least one of the reference values, wherein the method comprises any of the above. Aspect 29. The method according to Aspect 28, wherein at least one pair of human chromosomes represents the entire genome. Aspect 30. The method according to aspect 28 or aspect 29, wherein the indicator CA region is determined in at least 2 pairs, 3 pairs, 4 pairs, 5 pairs, 6 pairs, 7 pairs, 8 pairs, 9 pairs, 10 pairs, 11 pairs, 12 pairs, 13 pairs, 14 pairs, 15 pairs, 16 pairs, 17 pairs, 18 pairs, 19 pairs, 20 pairs or 21 pairs of human chromosomes. Aspect 31. The method according to any one of aspects 28 to 30, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells. Aspect 32. The reference number of the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more than that, the reference number of the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more than that, and the reference number of the indicator LST region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more than that. The method according to any one of aspects 28 to 31. Aspect 33. The indicator LOH region is defined as an LOH region that has a length 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, 30, 35, 40, 45, 50 megabases or more but is shorter than either a complete chromosome or a complete chromosomal arm, the indicator TAI region is defined as a TAI region that has a length 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, 30, 35, 40, 45, 50 megabases or more but does not extend beyond the centromere, and the indicator LST region is defined as an LST region that has a length 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, 30, 35, 40, 45, 50 megabases or more, the method according to any one of aspects 28 to 32. Aspect 34. The DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubincin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib, the method according to any one of aspects 28 to 33. Aspect 35. Calculate the arithmetic mean of the number of indicator LOH regions, indicator TAI regions and indicator LST regions in the sample for the test value as follows: Derived by TIFF2025090619000006.tif10170, and calculate the arithmetic mean of the number of indicator LOH regions, indicator TAI regions and indicator LST regions in the sample from the reference population for one or more reference values as follows: The method according to any one of aspects 28 to 34, derived by TIFF2025090619000007.tif9170. Aspect 36. The method according to any one of aspects 28 to 35, including the step of diagnosing a patient in which the test value in the sample is at least 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times or 10 times greater than one or more reference values, or at least 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations or 10 standard deviations greater, or at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95% greater, as having a high likelihood of responding to the cancer treatment regimen. Aspect 37. A method for evaluating HRD in cancer cells or their genomic DNA, comprising: (a) detecting the indicator CA region of the cancer cells in at least one pair of human chromosomes in the cancer cells or genomic DNA derived therefrom, wherein the at least one pair of human chromosomes is not the human X / Y sex chromosome pair; and (b) determining the total number of indicator CA regions in the at least one pair of human chromosomes. A method comprising the above steps. Aspect 38. A method for predicting the status of the BRCA1 gene and the BRCA2 gene in cancer cells, comprising: determining, in the cancer cells, the total number of indicator CA regions in at least one pair of human chromosomes of the cancer cells; and diagnosing a patient in which the total number in the cancer cells is greater than the reference number as having a high likelihood of a defect in the BRCA1 gene or the BRCA2 gene. A method comprising the above steps. Aspect 39. A method for predicting the status of HDR in cancer cells, comprising: determining, in the cancer cells, the total number of indicator CA regions in at least one pair of human chromosomes of the cancer cells; and Diagnosing a patient with a high likelihood of HDR deficiency when the total number in cancer cells is greater than the reference number; A method comprising. Aspect 40. A method for predicting the response of a cancer patient to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, and / or a PARP inhibitor, Determining the number of indicator CA regions in at least one pair of human chromosomes of the cancer cells of the cancer patient in the cancer cells derived from the cancer patient; and Diagnosing a patient with a high likelihood of responding to the cancer treatment regimen when the total number in cancer cells is greater than the reference number, A method comprising. Aspect 41. A method for predicting the response of a cancer patient to a treatment regimen, Determining the total number of indicator CA regions in at least one pair of human chromosomes of the cancer cells of the cancer patient in the cancer cells derived from the cancer patient; and Diagnosing a patient with a high likelihood of not responding to a treatment regimen comprising paclitaxel or docetaxel when the total number in cancer cells is greater than the reference number, A method comprising. Aspect 42. A method for treating cancer, (a) Determining the total number of indicator CA regions in at least one pair of human chromosomes of cancer cells in cancer cells derived from a cancer patient or genomic DNA obtained therefrom; and (b) Administering to the cancer patient a cancer treatment regimen comprising one or more drugs selected from the group consisting of a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor and a PARP inhibitor when the total number of the indicator CA regions is greater than the reference number, A method comprising. Use of one or more drugs selected from the group consisting of a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor and a PARP inhibitor for the manufacture of a medicament useful for treating cancer in a patient identified as having cancer cells determined to have a total of five or more indicator CA regions. Aspect 44. A system for determining the LOH status of cancer cells in a cancer patient, comprising: (a) a sample analyzer configured to generate a plurality of signals regarding genomic DNA of at least one pair of human chromosomes of the cancer cells; and (b) a computer subsystem programmed to calculate the number of indicator CA regions in the at least one pair of human chromosomes based on the plurality of signals. A system comprising the above. Aspect 45. The system according to aspect 8, wherein the computer subsystem is programmed to compare the number of indicator CA regions with a reference number to determine (a) the likelihood of a deletion of the BRCA1 gene and / or the BRCA2 gene in the cancer cells, (b) the likelihood of a deficiency in HDR in the cancer cells, or (c) the likelihood that the cancer patient will respond to a cancer treatment regimen comprising a DNA damaging agent, anthracycline, topoisomerase I inhibitor, radiation, or PARP inhibitor. A system as described in aspect 8, which is programmed to perform the above. Aspect 46. A computer program product incorporated into a computer-readable medium, which, when executed on a computer, performs detecting the presence or absence of any indicator CA region present on one or more of the human chromosomes; and determining the total number of the indicator CA regions in one or more pairs of chromosomes. A computer program product as described above. Aspect 47. At least 500 oligonucleotides capable of hybridizing to a plurality of polymorphic regions of human genomic DNA; and the computer program product according to aspect 10. A diagnostic kit comprising the above. Aspect 48. For determining the total number of indicator CA regions in at least one chromosome pair of human cancer cells obtained from a cancer patient, and (a) a high likelihood of a deletion of the BRCA1 gene or the BRCA2 gene in the cancer cells, (b) a high likelihood of HDR deficiency in said cancer cells, or (c) a high likelihood that said cancer patient will respond to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation or a PARP inhibitor, Use of a plurality of oligonucleotides capable of hybridizing to a plurality of polymorphic regions of human genomic DNA for producing a diagnostic kit useful for detecting Aspect 49. The method according to any one of aspects 37 to 42, wherein the indicator CA region is an indicator LOH region, an indicator TAI region and an indicator LST region, and is determined in optionally at least 2 pairs, 5 pairs, 10 pairs or 21 pairs of human chromosomes. Aspect 50. The method according to any one of aspects 36 to 42, wherein the cancer cells are ovarian cancer cells, breast cancer cells or esophageal cancer cells. Aspect 51. The method according to any one of aspects 36 to 42, wherein the total number of the indicator LOH region, the indicator TAI region or the indicator LST region is 9, 15, 20 or more. Aspect 52. The method according to any one of aspects 36 to 42, wherein the indicator LOH region, the indicator TAI region or the indicator LST region is defined as having a length of about 6, 12 or 15 megabases or more. Aspect 53. The method according to any one of aspects 36 to 42, wherein the reference number is 6, 7, 8, 9, 10, 11, 12 or 13 or more. Aspect 54. The use according to aspect 43 or 48, wherein the indicator CA region is an indicator LOH region, an indicator TAI region and an indicator LST region, and is determined in optionally at least 2 pairs, 5 pairs, 10 pairs or 21 pairs of human chromosomes. Aspect 55. The use according to aspect 43 or 48, wherein the cancer cells are ovarian cancer cells, breast cancer cells or esophageal cancer cells. Aspect 56. The use according to aspect 43 or 48, wherein the total number of the indicator LOH region, the indicator TAI region or the indicator LST region is 9, 15, 20 or more. Aspect 57. The use according to aspect 43 or 48, wherein the indicator LOH region, the indicator TAI region, or the indicator LST region is defined as having a length of about 6, 12, or 15 megabases, or more. Aspect 58. The system according to aspect 44 or 45, wherein the indicator CA region is the indicator LOH region, the indicator TAI region, and the indicator LST region, and is optionally determined in at least 2 pairs, 5 pairs, 10 pairs, or 21 pairs of human chromosomes. Aspect 59. The system according to aspect 44 or 45, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells. Aspect 60. The system according to aspect 44 or 45, wherein the total number of the indicator LOH region, the indicator TAI region, or the indicator LST region is 9, 15, 20, or more. Aspect 61. The system according to aspect 44 or 45, wherein the indicator LOH region, the indicator TAI region, or the indicator LST region is defined as having a length of about 6, 12, or 15 megabases, or more. Aspect 62. The computer program product according to aspect 46, wherein the indicator CA region is the indicator LOH region, the indicator TAI region, and the indicator LST region, and is optionally determined in at least 2 pairs, 5 pairs, 10 pairs, or 21 pairs of human chromosomes. Aspect 63. The computer program product according to aspect 46, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells. Aspect 64. The computer program product according to aspect 46, wherein the total number of the indicator LOH region, the indicator TAI region, or the indicator LST region is 9, 15, 20, or more. Aspect 65. The computer program product according to aspect 46, wherein the indicator LOH region, the indicator TAI region, or the indicator LST region is defined as having a length of about 6, 12, or 15 megabases, or more. Aspect 66. The method according to any one of Aspects 36 to 42, wherein at least one pair of human chromosomes is not human chromosome 17. Aspect 67. The use according to Aspect 43 or 48, wherein the indicator CA region is not in human chromosome 17. Aspect 68. The system according to Aspect 44 or 45, wherein the indicator CA region is not in human chromosome 17. Aspect 69. The computer program product according to Aspect 46, wherein the indicator CA region is not in human chromosome 17. Aspect 70. The method according to Aspect 40 or 42, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubincin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib. Aspect 71. The use according to Aspect 48, wherein the DNA damaging agent is a platinum-based chemotherapeutic agent, the anthracycline is epirubincin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib. Aspect 72. The system according to Aspect 45, wherein the DNA damaging agent is a platinum-based chemotherapeutic agent, the anthracycline is epirubincin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib. Aspect 73. The computer program product according to aspect 46, wherein the DNA-damaging agent is a platinum-based chemotherapeutic agent, the anthracycline is epirubicin or doxorubicin, the topoisomerase I inhibitor is camptothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib. Aspect 74. (a) Detecting, in a cancer cell or genomic DNA derived therefrom, an indicator CA region comprising at least two selected from an indicator LOH region, an indicator TAI region, or an indicator LST region, in a representative number of pairs of human chromosomes of the cancer cell; and (b) Determining the number and size of the indicator CA region. A method comprising the above. Aspect 75. The method according to aspect 74, wherein a representative number of pairs of human chromosomes represents the entire genome. Aspect 76. The method according to aspect 74, further comprising correlating an increase in the number of indicator CA regions of a specific size with the likelihood of a deficiency in HDR. Aspect 77. The method according to aspect 76, wherein the specific 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 shorter than the length of the entire chromosome containing the indicator CA region. Aspect 78. The method according to aspect 76 or 77, wherein an indicator CA region of a specific size of 6, 7, 8, 9, 10, 11, 12 or 13 or more is correlated with a high likelihood of a deficiency in HDR. Aspect 79. A method for determining the prognosis of a cancer patient, comprising: (a) A step of determining whether a sample containing cancer cells has an HRD signature, wherein the presence of an indicator CA region exceeding a reference number including at least two types selected from an indicator LOH region, an indicator TAI region, or an indicator LST region in at least one pair of human chromosomes of the cancer cells of a cancer patient indicates that the cancer cells have an HRD signature, and (b)(1) A step of diagnosing a patient in whom an HRD signature is detected in a sample as having a relatively good prognosis, or (b)(2) A step of diagnosing a patient in whom an HRD signature is not detected in a sample as having a relatively poor prognosis, A method comprising the above steps. Aspect 80. A composition for use in the treatment of a disease that is 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 in whom the indicator CA region in at least one pair of human chromosomes of the patient's cancer cells is more than the reference number, the composition comprising a therapeutic agent selected from the group consisting of DNA damaging agents, anthracyclines, topoisomerase I inhibitors, and PARP inhibitors. Aspect 81. The composition according to aspect 80, wherein the indicator CA region is determined in at least 2 pairs, 5 pairs, 10 pairs, or 21 pairs of human chromosomes. Aspect 82. The composition according to aspect 80, wherein the total number of indicator CA regions is 9, 15, 20, or more than that. Aspect 83. The composition according to aspect 80, wherein the initial length is about 6, 12, or 15 megabases, or more than that. Aspect 84. The composition according to aspect 80, wherein the reference number is 6, 7, 8, 9, 10, 11, 12, or 13, or more than that. Aspect 85. A method for treating cancer in a patient, comprising: Determining the number of indicator CA regions in at least two types selected from the indicator LOH region, indicator TAI region, or indicator LST region on at least one pair of human chromosomes of cancer cells in the patient-derived sample, wherein it is indicated that the cancer cells have an HRD signature; Providing a test value derived from the number of the indicator CA regions; Comparing the test value with one or more reference values (e.g., mean value, median value, quartile value, quintile value, etc.) derived from the number of the indicator CA regions in a reference population; and Based at least in part on the comparing step of revealing that the test value is greater than at least one of the reference values (e.g., at least 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times, or 10 times greater; at least 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations, or 10 standard deviations greater), administering an anticancer drug to the patient, or recommending, or prescribing, or initiating a treatment regimen including chemotherapy and / or synthetic lethal agents; or Based at least in part on the comparing step of revealing that the test value is not greater than at least one of the reference values (e.g., 2 times, 3 times, 4 times, 5 times, 6 times, 7 times, 8 times, 9 times, or 10 times or less; 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations, or 10 standard deviations or less), recommending, or prescribing, or initiating a treatment regimen not including chemotherapy and / or synthetic lethal agents, A method comprising. Aspect 86. The method according to aspect 85, wherein the indicator CA region is determined in at least 2 pairs, 5 pairs, 10 pairs, or 21 pairs of human chromosomes. Aspect 87. The method according to aspect 85, wherein the total number of the indicator CA regions is 9, 15, 20 or more. Aspect 88. The method according to aspect 85, wherein the initial length is about 6, 12 or 15 megabases or more. Aspect 89. The method according to aspect 85, wherein the reference number is 6, 7, 8, 9, 10, 11, 12 or 13 or more. Aspect 90. The method according to aspect 85, wherein the chemotherapy is selected from the group consisting of DNA damaging agents, anthracyclines and topoisomerase I inhibitors, and / or the synthetic lethal agent is a PARP inhibitor. Aspect 91. The method according to aspect 85, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubincin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, and / or the PARP inhibitor is iniparib, olaparib or velapirib. Aspect 92. A method for evaluating HRD in cancer cells or their genomic DNA, comprising: (a) detecting, in cancer cells or genomic DNA derived therefrom, at least two types of indicator CA regions selected from indicator LOH regions, indicator TAI regions or indicator LST regions in at least one pair of human chromosomes of the cancer cells, wherein the at least one pair of human chromosomes is not the human X / Y sex chromosome pair; and (b) determining an average (e.g., arithmetic mean) over the total number of indicator CA regions by calculating the average of the numbers of various indicator CA regions detected in the at least one pair of human chromosomes (e.g., if there are 16 indicator LOH regions and 18 indicator LST regions, the arithmetic mean is calculated as 17), The method comprising. Aspect 93. A method for predicting the status of BRCA1 gene and BRCA2 gene in cancer cells, comprising: In cancer cells, determining an average (e.g., arithmetic mean) over the total number of various types of indicator CA regions, which include at least two types selected from the indicator LOH region, the indicator TAI region, or the indicator LST region, in at least one pair of human chromosomes of the cancer cells; and correlating the average (e.g., arithmetic mean) over the total number, which is greater than a reference number, with the likelihood of a deficiency in the BRCA1 gene or the BRCA2 gene, comprising a method. Aspect 94. A method for predicting the state of HDR in cancer cells, In cancer cells, determining an average (e.g., arithmetic mean) over the total number of various types of indicator CA regions, which include at least two types selected from the indicator LOH region, the indicator TAI region, or the indicator LST region, in at least one pair of human chromosomes of the cancer cells; and correlating the average (e.g., arithmetic mean) over the total number, which is greater than a reference number, with the likelihood of a deficiency in HDR, comprising a method. Aspect 95. A method for predicting the response of a cancer patient to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, radiation, and / or a PARP inhibitor, In a sample containing cancer cells, determining an average (e.g., arithmetic mean) over the total number of various types of indicator CA regions, which include at least two types selected from the indicator LOH region, the indicator TAI region, or the indicator LST region, in at least one pair of human chromosomes of the sample (e.g., if there are 16 indicator LOH regions and 18 indicator LST regions, the arithmetic mean is determined to be 17); and determining that a patient in whom the average (e.g., arithmetic mean) over the total number in the sample is greater than a reference number is likely to respond to the cancer treatment regimen, comprising a method. Aspect 96. A method for predicting the response of a cancer patient to a treatment regimen, Determining an average (e.g., arithmetic mean) over the total number of indicator CA regions, including at least two selected from indicator LOH regions, indicator TAI regions, or indicator LST regions, in at least one pair of human chromosomes of the patient sample, in a patient sample containing cancer cells; and Diagnosing a patient in which the average (e.g., arithmetic mean) over the total number in the sample is greater than a reference number as likely to be non-responsive to a treatment regimen comprising paclitaxel or docetaxel, A method comprising. Aspect 97. A method of treating cancer, comprising: (a) Determining an average (e.g., arithmetic mean) over the total number of various indicator CA regions, including at least two selected from indicator LOH regions, indicator TAI regions, or indicator LST regions, in at least one pair of human chromosomes of cancer cells, in a patient sample containing cancer cells or genomic DNA obtained therefrom; and (b) Administering a cancer treatment regimen comprising one or more drugs selected from the group consisting of DNA damaging agents, anthracyclines, topoisomerase I inhibitors, and PARP inhibitors, to a patient in which the total number of indicator CA regions in the sample is greater than a reference number, A method comprising. Aspect 98. The method according to aspect 95 or 97, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubincin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib. Aspect 99. A composition for use in the treatment of a disease which is 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 in which the average (e.g., arithmetic mean) across various types of an indicator CA region comprising at least two types selected from among indicator LOH regions, indicator TAI regions, or indicator LST regions in at least one pair of human chromosomes of the cancer cells of the patient is greater than a reference number, the composition comprising a therapeutic agent selected from the group consisting of DNA damaging agents, anthracyclines, topoisomerase I inhibitors and PARP inhibitors. Aspect 100. A method of treating cancer in a patient, comprising: determining, in a sample from the patient, the average (e.g., arithmetic mean) of the total number of indicator CA regions in at least one pair of human chromosomes of the cancer cells of the cancer patient, at which stage it is indicated that the cancer cells have an HRD signature; providing a test value derived from the average (e.g., arithmetic mean) across various types of the indicator CA region comprising at least two types selected from among indicator LOH regions, indicator TAI regions or indicator LST regions; comparing the test value with one or more reference values (e.g., mean value, median value, quartile value, quintile value, etc.) derived from the average (e.g., arithmetic mean) across various types of the indicator CA region in a reference population; and administering an anti-cancer drug to the patient, or recommending, or prescribing, or initiating a treatment regimen comprising chemotherapy and / or synthetic lethal agents, at least partially based on the comparing step, in which it is revealed that the test value is greater than at least one of the reference values (e.g., at least 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold, or 10-fold greater; at least 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations, or 10 standard deviations greater); or Based at least in part on said comparing step to demonstrate that the test value is not greater than at least one of said reference values (e.g., not more than 2-fold, 3-fold, 4-fold, 5-fold, 6-fold, 7-fold, 8-fold, 9-fold or 10-fold; not more than 1 standard deviation, 2 standard deviations, 3 standard deviations, 4 standard deviations, 5 standard deviations, 6 standard deviations, 7 standard deviations, 8 standard deviations, 9 standard deviations, or 10 standard deviations), the step of recommending, or prescribing, or initiating a treatment regimen that does not include chemotherapy and / or synthetic lethal agents. A method comprising. Aspect 101. The method according to aspect 100, wherein the average (e.g., arithmetic mean) across various indicator CA regions is determined in at least 2 pairs, 5 pairs, 10 pairs or 21 pairs of human chromosomes. Aspect 102. The method according to aspect 100, wherein the chemotherapy is selected from the group consisting of DNA damaging agents, anthracyclines and topoisomerase I inhibitors, and / or the synthetic lethal agent is a PARP inhibitor. Aspect 103. The method according to aspect 100, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubincin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, and / or the PARP inhibitor is iniparib, olaparib or velapirib.

[0144] The present invention will be further illustrated by the following examples, which do not limit the scope of the present invention described in the claims.

Examples

[0145] Example 1 - LOH region scores and TAI region scores across breast cancer subtypes, and their association with BRCA1 / 2 deficiency An LOH signature based on a genome-wide tumor LOH profile that highly correlates with loss of BRCA1 / 2 and other HDR pathway genes in ovarian cancer has been developed (Abkevich, et al., Patterns of Genomic Loss of Heterozygosity Predict Homologous Recombination Repair Defects, BR. J. CANCER (2012)), which predicts response to DNA-damaging agents (e.g., platinum-based neoadjuvant) therapy in breast cancer (Telli et al., Homologous Recombination Deficiency (HRD) score predicts response following neoadjuvant platinum-based therapy in triple-negative and BRCA1 / 2 mutation-associated breast cancer (BC), CANCER RES. (2012)). A second score based on TAI also shows a strong correlation with BRCA1 / 2 loss and predicts response to platinum-based drug therapy in triple-negative breast cancer (Birkbak et al., Telomeric allelic imbalance indicates defective DNA repair and sensitivity to DNA-damaging agents, CANCER DISCOV. (2012)). In this study, we examined the frequency of BRCA1 / 2 loss and the increase in LOH region score or TAI region score across breast cancer subtypes defined by ER / PR / HER2 status.

[0146] Frozen tumors were purchased from three commercial tissue biobanks. Approximately 50 tumors confirmed at random from each of the four breast cancer subtypes (triple negative, ER+ / HER2-, ER- / HER2+, ER+ / HER2+) were selected for analysis. A targeted custom hybridization panel targeting BRCA1, BRCA2 and 50,000 selected SNPs across the whole genome was developed. This panel was used in combination with sequencing on an Illumina HiSeq2500 to analyze tumors for BRCA1 / 2 somatic and germline mutations, including large rearrangements, and SNP allele dosage. Methylation of the BRCA1 promoter was determined by qPCR assay (SA Biosciences). When available, DNA from normal tissue was used to determine whether a deleterious mutation was germline or somatic.

[0147] SNP data were analyzed using an algorithm that determines the most likely allele-specific copy number at each SNP position. The LOH region score was calculated by counting the number of LOH regions that are longer than 15 Mb but shorter than the length of the entire chromosome. The TAI region score was calculated by counting the number of telomeric regions with allelic imbalance that are longer than 11 Mb but do not cross the centromere. Samples with poor quality SNP data and / or high contamination with normal DNA were excluded. Robust scores were obtained for 191 out of 213 samples.

[0148] (Table 2) BRCA1 / 2 deficiency in breast cancer IHC subtypes TIFF2025090619000008.tif56143

[0149] (Table 3) Mutation screening was performed on corresponding normal tissues from 17 BRCA1 / 2 mutants. Thirteen out of 17 individuals (76.5%) had germline mutations. TIFF2025090619000009.tif105128 *Each individual had one germline mutation and one somatic mutation in BRCA1.

[0150] (Table 4): Association between LOH score or TAI score and BRCA1 / 2 deficiency TIFF2025090619000010.tif67169

[0151] Figure 5 shows the LOH region score and TAI region score for different IHC subtypes of breast cancer. 5A: LOH score; 5B: TAI score. Blue bar: BRCA1 / 2-deficient samples. Red bar: BRCA1 / 2-intact samples. Figure 6 shows the correlation between the LOH region score and the TAI region score (correlation coefficient = 0.69). X-axis: LOH score; Y-axis: TAI score; Red dots: intact samples; Blue dots: BRCA1 / 2-deficient samples. The area under the dots is proportional to the number of samples having a combination of LOH score and TAI score (p = 10 -39 )

[0152] Logistic regression analysis was used to predict BRCA1 / 2 deficiency based on the LOH score and TAI score. Both scores were significant in the multivariate analysis (chi-square value for LOH was 10.8 and for TAI was 44.7; p = 0.001 and 2.3 * 10 -11 ). The best model for discriminating between BRCA1 / 2-deficient samples and intact samples was 0.32 * LOH region score + 0.68 * TAI region score (p = 9 * 10 -18 ).

[0153] Conclusion: An increase in the LOH region score and the TAI region score is highly associated with BRCA1 / 2 deficiency in all subtypes of breast cancer, respectively; the LOH region score and the TAI region score are highly significantly correlated; the composite CA region score (i.e., the combination of LOH and TAI) shows the optimal correlation with BRCA1 / 2 deficiency in this dataset. Based on the present disclosure, the combination of the LOH-HRD score and the TAI-HRD score can predict the response to DNA-damaging agents and other drugs (e.g., platinum-based chemotherapy) in triple-negative breast cancer and enable the expansion of the use of platinum-based drugs for other breast cancer subtypes.

[0154] Example 2 - Association of LOH region score, TAI region score, and LST region score across breast cancer subtypes and BRCA1 / 2 deficiency As described in Example 1, the ratio of SNP allele frequencies was determined and used to calculate the LOH region score, the TAI region score, and the LST region score. The LST score was defined as the number of discontinuities between regions longer than 10 megabases with stable copy numbers after filtering out regions shorter than 3 megabases. The inventors observed that the LST score increased with ploidy in both intact and deficient samples. Therefore, in this Example 2, instead of using a ploidy-specific cutoff, the inventors modified the LST region score by adjusting it by ploidy: LSTm = LST - kP, where P is the ploidy and k is a constant. According to the multivariate logistic regression analysis using deficiency as the outcome and LST and P as predictors, k = 15.5.

[0155] Scores meeting the QC criteria used were obtained for 191 out of 214 samples. 38 of these samples had BRCA1 / 2 deficiency. The corresponding p-value by the Kolmogorov-Smirnov test for the LOH region score was 8 * 10 -12 and for the TAI region score was 2 * 10 -16 and for the LST region score was 8* 10 -8 Of the 191 samples, 53 were triple-negative breast cancers, including 22 that had BRCA1 / 2 deficiency. The corresponding p-values were 6 * 10 -6 、3 * 10 -6 and 0.0002 for the LOH region score, TAI region score, and LST region score, respectively. When the same analysis was performed for each of the individual breast cancer subtypes, significant p-values were observed for at least one score for all subtypes (Table 5). The score distributions are shown in FIGS. 7A-C for the comparison between BRCA1 / 2-deficient samples and BRCA1 / 2-intact samples.

[0156] Next, the scores were analyzed to determine whether they were correlated (FIGS. 2D-F). The correlation coefficient between the LOH region score and the TAI region score was 0.69 (p = 10 -39 ), and that between LOH and LST was 0.55 (p = 2 * 10 -19 ), and that between TAI and LST was 0.39 (p = 10 -9 ).

[0157] Logistic regression analysis was used to predict BRCA1 / 2 deficiency based on the LOH region score, TAI region score, and LST region score. All three scores were significant in the multivariate analysis (the chi-square value for LOH was 5.1 (p = 0.02), for TAI was 44.7 (p = 2 * 10 -11 ), and for LST was 5.4 (p = 0.02)). The best model for discriminating between BRCA1 / 2-deficient and intact samples in this dataset was 0.21 * LOH + 0.67 * TAI + 0.12 * LST (p = 10 -18) It was. This Example 2 extends the conclusion by Example 1 (i.e., the model that combines the LOH region score and the TAI region score) to a model that combines the LOH region score, the TAI region score, and the LST region score.

[0158] Other clinical data that were available for many of the samples included stage, grade, and age at diagnosis. Stage information was available for 64 out of 191 samples. The correlation coefficient between stage and the LOH region score (0.07) and the TAI region score (0.1) was not significant. Grade information was available for 164 out of 191 samples. The correlation coefficient between grade and the LOH region score (0.33) and the TAI region score (0.23) was significant (p = 2 * 10 -5 and 0.004). The age at diagnosis was known for 184 out of 191 samples. The correlation coefficient between age and the LOH region score (-0.13) was not significant. The correlation coefficient between age and the TAI region score (-0.25) was significant (p = 0.0009).

[0159] (Table 5) TIFF2025090619000011.tif122159

[0160] Example 3 - Arithmetic means of the LOH region score, the TAI region score, and the LST region score across breast cancer subtypes, and their association with BRCA1 / 2 deficiency The following studies show how the HRD score as described herein can predict the efficacy of drugs targeting BRCA1 / 2 deficiency and HR deficiency in triple-negative breast cancer (TNBC). To examine the rate of BRCA1 / 2 deficiency across breast cancer subtypes, breast tumor samples were assayed for BRCA1 / 2 mutations and promoter methylation. Three HRD scores described in Example 2 were determined for the samples, and subsequently examined for association with BRCA1 / 2 deficiency using the arithmetic mean of the LOH / TAI / LST scores. Analysis of the neoadjuvant TNBC cohort treated with cisplatin was further performed for the relationship between all three HRD scores and response.

[0161] Invasive breast tumor samples and corresponding normal tissues were obtained from three vendors. Samples were selected so that approximately equal numbers were obtained for all subtypes of breast cancer defined by IHC analysis for ER, PR, and HER2. BRCA1 promoter methylation analysis was performed by qPCR. BRCA1 / 2 mutation screening and genome-wide SNP profiling were generated using sequencing on an Illumina HiSeq2500 after custom Agilent SureSelect XT capture. Using these data, HRD-LOH scores, HRD-TAI scores, and HRD-LST scores were calculated.

[0162] SNP microarray data and clinical data were downloaded from public repositories for the cisplatin-1 and cisplatin-2 trial cohorts. BRCA1 / 2 mutation data were not available for one of these cohorts. All three HRD scores were calculated from the public data and analyzed for association with response to cisplatin. Two cohorts were combined to increase the power of detection.

[0163] To calculate the HRD score, SNP data was analyzed using an algorithm that determines the most likely allele-specific copy number at each SNP position. HRD-LOH was calculated by counting the number of LOH regions that are longer than 15 Mb but shorter than the length of the entire chromosome. The HRD-TAI score was calculated by counting the number of regions with allelic imbalance that are longer than 11 Mb, extend to one of the subtelomeres but do not cross the centromere. The HRD-LST score was taken as the number of discontinuities between regions longer than 10 Mb after filtering out regions shorter than 3 Mb.

[0164] The composite score was taken as the arithmetic mean of the LOH / TAI / LST scores. All p-values were obtained from a logistic regression model with BRCA deficiency or response to cisplatin as the dependent variable.

[0165] Table 6 shows the BRCA1 / 2 mutation and BRCA1 promoter methylation frequencies across four breast cancer subtypes. BRCA1 / 2 variant analysis was successful in 100% of the samples, but large-scale rearrangement analysis was less robust, and qualified data were obtained for 198 out of 214 samples. Harmful mutations were observed in 24 out of 214 individuals (one individual had a somatic mutation in BRCA1 and a germline mutation in BRCA2). Corresponding normal DNA was available for 23 out of 24 mutants, and this was used to determine whether the identified mutation was germline or somatic. BRCA1 promoter methylation analysis was successfully performed in 100% of the samples. Figure 9 illustrates the HRD score in BRCA1 / 2-deficient samples.

[0166] (Table 6) TIFF2025090619000012.tif44170 * One individual still retains an intact functional copy of BRCA1. † One individual for whom the functional status regarding BRCA1 could not be determined is included.

[0167] Table 7 shows the association between three HRD scores and BRCA1 / 2 deficiency in the breast cohort of all participants. The composite score was the arithmetic mean of the three HRD scores.

[0168] (Table 7) TIFF2025090619000013.tif150170

[0169] Table 8 shows the association between the HRD score and pCR (Miller-Payne 5) in TNBC treated with cisplatin in the neoadjuvant setting. The data were available from samples from the Cisplatin-1 trial (Silver et al., Efficacy of neoadjuvant Cisplatin in triple-negative breast cancer. J. CLIN. ONCOL. 28:1145-53 (2010)) and the Cisplatin-2 trial (Birkbak et al, (2012)). pCR was defined as patients being in the Miller-Payne 5 state after neoadjuvant treatment. The HRD-composite was the arithmetic mean of the three HRD scores.

[0170] (Table 8) TIFF2025090619000014.tif39170

[0171] Conclusion: BRCA1 / 2 deficiency and increased HRD scores were observed in all breast cancer subtypes, and BRCA1 / 2 deficiency was detected by the HRD score. Treatment response to cisplatin in TNBC was predicted / detected by all three HRD scores. The mean (arithmetic mean) of the three HRD scores detected the BRCA1 / 2 status in the breast cohort of all participants and detected the cisplatin response in a second independent TNBC cohort. The HRD-composite by arithmetic mean was a stronger predictor / detector of BRCA1 / 2 deficiency or treatment response than the individual HRD scores.

[0172] Example 4 - Multivariate Analysis of BRCA1 / 2 Status and DNA-Based Assays for Homologous Recombination Deficiency In previous examples, DNA-based scores for measuring homologous recombination deficiency (HRD) have been described, demonstrating that each score is significantly associated with BRCA1 / 2 deficiency, and the same is true for the HRD-composite score defined as the arithmetic mean of three HRD scores. In this example, the results of previous examples are extended by examining (1) the relationship between each of the three scores and the HRD-composite score, (2) the relationship between clinical variables and the HRD-composite score, and (3) the relationship between clinical variables and the HRD-composite score and BRCA1 / 2 deficiency.

[0173] Methods: The analysis in this Example 4 included the same 197 patient samples described in previous examples. Briefly, 215 breast tumor samples were purchased as fresh frozen specimens from three vendors. Samples were selected such that approximately equal numbers were representative of breast cancer subtypes by IHC analysis for ER, PR, and HER2. Reliable HRD scores were obtained for 198 samples according to the Kolmogorov-Smirnov quality criterion. One patient who passed the HRD score had an unusual breast cancer subtype (ER / PR+ HER2-), so was excluded from the analysis. Details of the patients' tumor and clinical characteristics are shown in Table 9.

[0174] Clinical data for the patients were provided for 91 variables, but data for most variables were poor for inclusion in the analysis. Breast cancer subtypes (TNBC, ER+ / HER2-, ER- / HER2+, ER+ / HER2+) were available for all patients. Other variables considered were age at diagnosis (obtained for 196 of 197 patients), stage (obtained for 191 of 197 patients), and grade (obtained for 190 of 197 patients).

[0175] (Table 9) TIFF2025090619000015.tif129170

[0176] BRCA1 / 2 mutation screening and genome-wide SNP profiling were generated using sequencing on an Illumina HiSeq2500 after custom Agilent SureSelect XT capture. Methylation of the BRCA-1 promoter region was determined by qPCR. Samples with methylation above 10% were classified as methylated.

[0177] The HRD score was calculated from three HRD scores that are combined in the "HRD - Composite Score" discussed in this Example 4, namely, the loss of heterozygosity (LOH) profile of the whole-genome tumor (HRD-LOH), telomeric allelic imbalance (HRD-TAI), and large-scale state transitions (HRD-LST).

[0178] BRCA1 / 2 deficiency was defined as a loss of function due to a mutation in BRCA1 or BRCA2, or methylation of the promoter region of BRCA1 or BRCA2, accompanied by loss of heterozygosity (LOH) in the affected gene.

[0179] All statistical analyses were performed using R version 3.0.2. All reported p-values are two-sided. Statistical tools used included Spearman rank test correlation, Kruskal-Wallis one-way analysis of variance, and logistic regression.

[0180] For logistic regression modeling, the HRD score and age at diagnosis were coded as numerical variables. Breast cancer stage and subtype were coded as categorical variables. Grade was coded as both a numerical variable and a categorical variable, but was treated as a categorical variable except where otherwise stated. Coding grade as a numerical variable is inappropriate except when the odds increase of BRCA1 / 2 deficiency is the same when comparing grade 2 patients to grade 1 patients and when comparing grade 3 patients to grade 2 patients.

[0181] The p-values reported for the univariate logistic regression model are based on the partial likelihood ratio. The multivariate p-values are based on the change in deviance in the comparison between the full model (including all relevant predictors) and the reduced model (including all predictors except the predictor being evaluated and all interaction terms involving the predictor being evaluated). The odds ratios for the HRD score are reported for the interquartile range.

[0182] Results: The pairwise correlations of the HRD-LOH score, HRD-TAI score, and HRD-LST score were examined graphically (Figure 1) and quantified by Spearman rank test correlation. The Spearman rank test correlation is preferred over the more commonly used Pearson product-moment correlation because the HRD score distribution has a right tail and outliers were observed. All pairwise comparisons of the scores showed a positive correlation significantly different from 0 (p < 10 -16 ).

[0183] The degree of independent BRCA1 / 2 deficiency information captured by each of the HRD-LOH score, HRD-TAI score, and HRD-LST score was measured by considering all three scores as predictors of the BRCA1 / 2 deficiency status and examining a multivariate logistic regression model (Table 10). The HRD-TAI score captured significant BRCA1 / 2 deficiency information independent of that obtained by the other two scores (p = 0.00016), and the same was true for the HRD-LST score (p = 0.00014). At the 5% significance level, the HRD-LOH score did not significantly add independent BRCA1 / 2 deficiency information (p = 0.069).

[0184] (Table 10) TIFF2025090619000016.tif29165

[0185] Table 10 illustrates the results of a three-way multivariate logistic regression model using HRD-LOH, HRD-TAI, and HRD-LST as predictors of BRCA1 / 2 deficiency.

[0186] To evaluate whether the HRD - composite score appropriately captures the BRCA1 / 2 deficiency information of its three components, the inventors verified three bivariate logistic regression models. Each model included the HRD - composite score and one of the HRD - LOH score, HRD - TAI score, or HRD - LST score. None of the component scores made a significant additional contribution to the HRD - composite score at the 5% significance level (HRD - LOH p = 0.89, HRD - TAI p = 0.090, HRD - LST p = 0.28). This suggests that the HRD - composite score appropriately captures the BRCA1 / 2 deficiency information of the HRD - LOH score, HRD TAI score, and HRD - LST score.

[0187] Furthermore, the HRD - composite score was also compared with a model - based composite score optimized to predict BRCA1 / 2 deficiency in this patient set. The HRD - composite score equally weights the HRD - LOH score, HRD - TAI score, and HRD - LST score, while the model - based score weights the HRD - TAI score approximately twice as much as the HRD - LOH score or HRD - LST score. The formula for the model - based score is HRD - model = 0.11×(HRD - LOH)+0.25×(HRD - TAI)+0.12×(HRD - LST) as given by.

[0188] The results by univariate analysis (Table 11) show that the HRD - model score is approximately one order of magnitude better than the HRD - composite score (HRD model p = 2.5×10 -25 , HRD - composite p = 1.1×10 -24 ).

[0189] (Table 11) TIFF2025090619000017.tif103164

[0190] Table 11 shows the results of univariate logistic regression. The odds ratio for the HRD score is reported per IQR of the score. The odds ratio for age is reported per year. The odds ratio for grade (numeric) is per unit.

[0191] In the bivariate logistic regression model, the HRD-model score did not add significant independent BRCA1 / 2 deficiency information to the HRD-composite score (p = 0.089). This further suggests that the HRD-composite score appropriately captures the BRCA1 / 2 deficiency information of the HRD-LOH score, HRD-TAI score, and HRD-LST score.

[0192] The relationship between clinical variables and the HRD-composite score is shown in Figure 12. The HRD-composite score was significantly correlated with tumor grade (Spearman correlation 0.23, p = 0.0017). The correlations with breast cancer stage and age at diagnosis were not significantly different from 0 at the 5% level. According to the Kruskal-Wallis one-way analysis of variance, the mean HRD-composite score was significantly different for each breast cancer subtype (p = 1.6×10 -5 )

[0193] Regarding the heterogeneity of the HRD-composite score among clinical subgroups, it was verified by examining the significance of the interaction terms in the multivariate logistic regression model. For each clinical variable, the inventors added an interaction term with the HRD-composite score to the model including all clinical variables and the HRD-composite score. None of the interaction terms reached significance at the 5% significance level. Therefore, there is no evidence that the probability of BRCA1 / 2 deficiency conferred by the HRD-composite score differs among clinical subgroups.

[0194] Similar tests for each of the HRD-LOH score, HRD-TAI score, and HRD-LST score indicated a significant interaction between the HRD-TAI score and age (p = 0.0072) and grade (p = 0.015), and a significant interaction between the HRD-LST score and breast cancer subtype (p = 0.021). In the adjustment for multiple comparisons, only the interaction between the HRD-TAI score and age remained significant at the 5% level (p = 0.029). The significance of this interaction suggests that the increase in the probability of BRCA1 / 2 deficiency per unit increase in the HRD-TAI score decreases as age increases.

[0195] The associations between clinical variables and BRCA1 / 2 deficiency are presented in Figure 13. Clinical variables and the HRD-composite score were evaluated in univariate (Table 11) and multivariate (Table 12) logistic regression models. Odds ratios for the HRD score are reported per IQR. Odds ratios for age at diagnosis are reported per year.

[0196] (Table 12) TIFF2025090619000018.tif78165

[0197] Table 12 shows the results from multivariate logistic regression. Odds ratios for the HRD score are reported per IQR of the score. Odds ratios for age are reported per year.

[0198] In univariate analysis, each of the HRD scores (HRD-LOH, HRD-TAI, HRD-LST, HRD-composite, and HRD-model) was significantly associated with BRCA1 / 2 deficiency. A higher score indicated a higher likelihood of deficiency. A significant association was found that the risk of BRCA1 / 2 deficiency was lower with a higher age at diagnosis (p = 0.0071). Univariate results for breast cancer subtype and tumor grade (both categorical and numerical) were also statistically significant. No association was found between cancer stage and BRCA1 / 2 status.

[0199] In multivariate analysis, we examined a model based on the HRD - composite score and all available clinical variables. The HRD - composite score captured significant BRCA1 / 2 deficiency information that was not captured by some clinical variables (p = 1.2×10 -16 ). Among the available clinical variables, only age at diagnosis maintained significance in the multivariate setting (p = 0.027). When grade was encoded as a categorical variable, it was not statistically significant (p = 0.40). Grade was also not significant when encoded as a numerical variable (p = 0.28). The quadratic and cubic effects on the HRD - composite score were verified in a multivariate model including all clinical variables, but were not statistically significant.

[0200] Discussion. In this Example 4, the frequency of BRCA1 / 2 deficiency across the four subtypes of breast cancer defined by IHC subtype classification was in the range of approximately 9% to approximately 16%. Sequencing of paired tumor samples and normal DNA samples suggested that approximately 75% of the observed mutations were of germline origin. The main method for loss of the second allele in breast cancer is via LOH, but approximately 24% of tumors also harbored subsequent somatic harmful mutations in the second allele. In addition, a sporadic - appearing breast tumor was identified in one individual who harbored a somatic harmful mutation in BRCA2.

[0201] All three HRD scores showed a strong correlation with BRCA1 / 2 deficiency regardless of subtype, and the frequency of increasing scores suggested that a significant proportion of all breast tumor subtypes harbored deficiencies in the homologous recombination DNA repair pathway. Considering these findings, especially in combination with Example 3 above, drugs that target or utilize DNA damage repair (e.g., platinum - based anticancer drugs) may be effective through a subset of tumors from all subtypes of breast cancer (those with homologous recombination deficiency as detected by the present disclosure).

[0202] In a clinical setting, to incorporate these HRD scores alone or in combination, it is optimal to use an assay that is compatible with formalin-fixed paraffin-embedded core needle biopsy samples ("FFPE"). In this type of sample, only extremely small amounts and poor-quality DNA can be obtained. In DNA extracted from these FFPE-treated samples, sufficient results are often not obtained in SNP microarray analysis.

[0203] For the generation of libraries for next-generation sequencing, target enrichment technologies based on liquid hybridization have been developed. These methods enable targeted sequencing of regions of interest after reduction of genomic complexity, resulting in a reduction of sequencing costs. In preliminary tests, it has been indicated that available assays are compatible with DNA derived from FFPE DNA. In this Example 4, the inventors report the development of a capture panel targeting approximately 54,000 SNPs distributed across the genome. The allelic numbers from the sequencing information obtained by this panel can be used for copy number and LOH reconstruction, as well as for all calculations of the three HRD scores. Additionally, as in this Example 4, BRCA1 and BRCA2 capture probes may be included in the panel, thereby enabling high-quality mutation screening for harmful variants in these genes with the same assay.

[0204] All three scores are significantly correlated with each other, suggesting that they all measure the same core genomic phenomenon. However, logistic regression analysis indicates that combining the scores can result in a stronger association with BRCA1 / 2 deficiency in this dataset.

[0205] The combination of a robust score that can identify tumors having a defect in homologous recombination DNA repair and assay compatibility with formalin-fixed paraffin-embedded clinical pathology specimens facilitates the diagnostic identification and classification of patients with a high likelihood of response to agents targeting double-strand DNA damage repair. Additionally, such agents may be useful across all subtypes of breast cancer in which HRD is detected in accordance with the present disclosure.

[0206] Other aspects Although the invention has been described in detail with its illustrations, the above description is intended as an illustration of the invention and not as a limitation, and it should be understood that it is defined by the appended claims. Other aspects, advantages and modifications are within the scope of the following claims.

Claims

1. 1. An in vitro method for predicting patient response to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor, comprising: (1) determining the number of indicator CA regions, including at least two of indicator LOH regions, indicator TAI regions, or indicator LST regions, in at least one pair of human chromosomes in a cancer patient in a sample containing cancer cells; and (2) diagnosing a patient having a higher likelihood of responding to the cancer treatment regimen if the patient has a higher number of indicator LOH regions, indicator TAI regions, or indicator LST regions in the sample than the reference number; A method comprising:

2. 2. The method of claim 1, wherein at least one pair of human chromosomes represents the entire genome.

3. 3. The method of claim 1 or claim 2, wherein the indicator CA regions are determined in at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or 21 human chromosomes.

4. The method of any one of claims 1 to 3, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells.

5. The number of references in the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, and the number of references in the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more.

5. The method of any one of claims 1 to 4, wherein the reference number of indicator LST regions is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40 45, 50 or more.

6. Indicator LOH regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm, and indicator TAI regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm.

6. The method of any one of claims 1-5, wherein the TAI region is defined as a TAI region that is 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 megabases or more but does not extend beyond the centromere, and the indicator LST region is defined as an LST region that is 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, 30, 35, 40, 45, 50 megabases or more in length.

7. 7. The method of any one of claims 1 to 6, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubicin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib.

8. The method of any one of claims 1 to 7, further comprising administering a cancer treatment regimen to a patient diagnosed as likely to respond to the cancer treatment regimen.

9. 1. An in vitro method for predicting a patient's response to a cancer treatment regimen that includes a platinum-based anticancer agent, comprising: (1) determining the number of indicator CA regions, including at least two selected from indicator LOH regions, indicator TAI regions, or indicator LST regions, in at least one pair of human chromosomes in a cancer patient's cancer cells in a sample containing cancer cells; (2) determining whether a sample containing cancer cells is deficient in BRCA1 or BRCA2; and (3) diagnosing, in the sample, a patient in which the number of indicator LOH regions, indicator TAI regions, or indicator LST regions is greater than the reference number, or (b) BRCA1 or BRCA2 is deleted, or both (a) and (b), as likely to respond to the cancer treatment regimen. A method comprising:

10. 10. The method of claim 9, wherein at least one pair of human chromosomes represents the entire genome.

11. 11. The method of claim 9 or claim 10, wherein the indicator CA regions are determined in at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or 21 pairs of human chromosomes.

12. The method of any one of claims 9 to 11, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells.

13. The number of references in the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, and the number of references in the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 13. The method of any one of claims 9 to 12, wherein the number of references of the indicator LST region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more.

14. Indicator LOH regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm, and indicator TAI regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm.

14. The method of any one of claims 9-13, wherein the TAI region is defined as a TAI region that is 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 megabases or more but does not extend beyond the centromere, and the indicator LST region is defined as an LST region that is 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, 30, 35, 40, 45, 50 megabases or more in length.

15. 15. The method of any one of claims 9 to 14, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubicin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib.

16. 16. The method of any one of claims 9 to 15, wherein the sample is deficient in BRCA1 or BRCA2 if a deleterious mutation, loss of heterozygosity or hypermethylation in either BRCA1 or BRCA2 is detected in the sample.

17. The method of claim 16, wherein hypermethylation is detected when methylation is detected in at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, or 50% or more of the analyzed BRCA1 or BRCA2 promoter CpGs.

18. 1. An in vitro method for predicting patient response to a cancer treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor, comprising: (1) determining the number of indicator CA regions, including at least two selected from indicator LOH regions, indicator TAI regions, or indicator LST regions, in at least one pair of human chromosomes in a cancer patient's cancer cells in a sample containing cancer cells; (2) providing a test value derived from the number of indicator CA regions; (3) comparing the test value to one or more reference values ​​derived from the number of the indicator CA regions in a reference population; and (4) diagnosing a patient whose sample has a test value greater than the one or more reference numbers as likely to respond to the cancer treatment regimen. A method comprising:

19. 20. The method of claim 18, wherein at least one pair of human chromosomes represents the entire genome.

20. 20. The method of claim 18 or claim 19, wherein the indicator CA regions are determined in at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or 21 pairs of human chromosomes.

21. The method of any one of claims 18 to 20, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells.

22. The number of references in the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, and the number of references in the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more.

22. The method of any one of claims 18-21, wherein the reference number of indicator LST regions is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more.

23. Indicator LOH regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm, and indicator TAI regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm.

23. The method of any one of claims 18-22, wherein the TAI region is defined as a TAI region that is 1, 22, 23, 24, 25, 30, 35, 40, 45, 50 megabases or more but does not extend beyond the centromere, and the indicator LST region is defined as an LST region that is 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, 30, 35, 40, 45, 50 megabases or more in length.

24. 24. The method of any one of claims 18 to 23, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubicin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib.

25. The method of any one of claims 18 to 24, further comprising the steps of: diagnosing a patient whose sample does not have a test value greater than the one or more reference numbers as not likely to respond to the cancer treatment regimen; and (5)(a) recommending, prescribing, initiating or continuing a treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor to a patient diagnosed as not likely to respond to the cancer treatment regimen; or (5)(b) recommending, prescribing, initiating or continuing a treatment regimen not comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor to a patient diagnosed as not likely to respond to the cancer treatment regimen.

26. Calculate the arithmetic mean of the number of Indicator LOH Regions, Indicator TAI Regions and Indicator LST Regions in the sample, where the test value is as follows: and calculating an arithmetic mean of the number of indicator LOH regions, indicator TAI regions and indicator LST regions in samples from the reference population, wherein one or more reference values ​​are as follows: The method of any one of claims 18 to 25, wherein the method is derived by:

27. 27. The method of any one of claims 18 to 26, comprising diagnosing as likely to respond to said cancer treatment regimen a patient whose sample has a test value that is at least 2, 3, 4, 5, 6, 7, 8, 9 or 10 times greater, or at least 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 standard deviations greater, or at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95% greater than one or more reference numbers.

28. 1. A method of treating a cancer patient, comprising: (1) determining, in a sample containing cancer cells, the number of indicator CA regions, including indicator LOH regions, indicator TAI regions, and indicator LST regions, in at least one pair of human chromosomes in the cancer cells of the cancer patient; (2) providing a test value derived from the number of indicator CA regions; (3) comparing the test value to one or more reference values ​​derived from the number of the indicator CA regions in a reference population; and (4)(a) recommending, prescribing, initiating, or continuing a treatment regimen comprising a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor to a patient whose sample has a test value greater than at least one of the reference values; or (4)(b) recommending, prescribing, initiating, or continuing a treatment regimen that includes a DNA damaging agent, an anthracycline, a topoisomerase I inhibitor, or a PARP inhibitor to a patient whose sample has a test value not greater than at least one of the reference values. A method comprising:

29. 30. The method of claim 28, wherein at least one pair of human chromosomes represents the entire genome.

30. 30. The method of claim 28 or claim 29, wherein the indicator CA regions are determined in at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20 or 21 human chromosomes.

31. The method of any one of claims 28 to 30, wherein the cancer cells are ovarian cancer cells, breast cancer cells, or esophageal cancer cells.

32. The number of references in the indicator LOH region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more, and the number of references in the indicator TAI region is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more.

32. The method of any one of claims 28-31, wherein the reference number of indicator LST regions is 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 30, 35, 40, 45, 50 or more.

33. Indicator LOH regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm, and indicator TAI regions were defined as LOH regions that were 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, 30, 35, 40, 45, 50 megabases in length or greater, but shorter than either a complete chromosome or a complete chromosome arm.

33. The method of any one of claims 28-32, wherein the TAI region is defined as a TAI region that is 1, 22, 23, 24, 25, 30, 35, 40, 45, 50 megabases or more but does not extend beyond the centromere, and the indicator LST region is defined as an LST region that is 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, 30, 35, 40, 45, 50 megabases or more in length.

34. 34. The method of any one of claims 28-33, wherein the DNA damaging agent is cisplatin, carboplatin, oxalaplatin or picoplatin, the anthracycline is epirubicin or doxorubicin, the topoisomerase I inhibitor is campothecin, topotecan or irinotecan, or the PARP inhibitor is iniparib, olaparib or velapirib.

35. Calculate the arithmetic mean of the number of Indicator LOH Regions, Indicator TAI Regions and Indicator LST Regions in the sample, where the test value is as follows: and calculating an arithmetic mean of the number of indicator LOH regions, indicator TAI regions and indicator LST regions in samples from the reference population, wherein one or more reference values ​​are as follows: The method of any one of claims 28 to 34, wherein the method is derived by:

36. 36. The method of any one of claims 28 to 35, comprising diagnosing as likely to respond to said cancer treatment regimen a patient whose test value in the sample is at least 2, 3, 4, 5, 6, 7, 8, 9 or 10 times greater, or at least 1, 2, 3, 4, 5, 6, 7, 8, 9 or 10 standard deviations greater, or at least 5%, 10%, 15%, 20%, 25%, 30%, 35%, 40%, 45%, 50%, 55%, 60%, 65%, 70%, 75%, 80%, 85%, 90%, 95% greater than one or more reference numbers.

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