Cancer methods

Abstract

The present invention provides an in vitro method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of cancer in a subject, said method comprising providing a biological sample obtained from the subject, wherein said sample comprises tumor DNA; determining the allele-specific copy number value of each allele for each of at least 5 gene-regions in the tumor DNA; and determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value, as defined herein. The present invention also provides an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject.

Description

[0001] CANCER METHODS

[0002] Field of the Invention

[0003] The present invention relates to methods of staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of cancer in a subject. Also provided herein is an in vitro assay for use in methods of the present invention.

[0004] Introduction

[0005] Clinical implementable molecular stratification underlies the drive for precision medicine in cancer. Prostate cancer is a leading cause of cancer death among men. For example, when castration-resistant prostate cancer develops, metastatic prostate cancer is often a rapidly lethal disease. Taxanes remain a mainstay of treatment for metastatic castrationresistant prostate cancer (mCRPC) but the magnitude of benefit is variable, resistance rapidly develops and fewer than half of patients are offered this treatment (de Bono JS, et al. Lancet. 2010;376(9747):1147-54; de Wit R, et al. N Engl J Med. 2019;381(26):2506-18; 3; Annala M, et al. Ann Oncol. 2021;32(7):896-905). In the past few years, studies investigating the genomic landscape of metastatic prostate cancer have led to the identification of targetable molecular alterations, emerging resistance mechanisms, and new therapeutic options.

[0006] Recently, liquid biopsies have proved to be a promising alternative to tissue biopsy for detecting genomic aberrations and molecular subtype characterization (Maia et al., Nat Rev Urol 2020, Nat Rev Urol. 2020;17(5):271-291), also allowing for serial testing, through non-invasive blood draws. Liquid biopsies could also help to readily identify possible resistance mechanisms and to detect minimal residual disease (Heitzer et al., Nature Reviews Genetics 2019, Nat Rev Genet. 2019; 20(2) :71-88). Additionally, liquid biopsies give real-time information that offers an opportunity to predict patient outcomes and better select treatment and consequently improve long-term outcomes (Wyatt AW, et al. J Natl Cancer Inst. 2017;109(12)). The feasibility of repeated sampling gives liquid biopsies potential advantages over tissue sampling: whereas multi-region sampling of primary lung and other cancers identifies intra-tumor heterogeneity that is characterized by subclone diversity, it is poorly prognostic, and extensive sampling of metastases is often not feasible. This is especially the case in prostate cancer where metastatic disease is often primarily in the bone. Liquid biopsies that involve the analysis of circulating free (cfDNA), and specifically circulating tumor DNA (ctDNA), have shown promise in the stratification and treatment selection of mCRPC patients (Chi et al., Journal of Clinical Oncology 2020 38:15_suppl, 5551-5551).

[0007] In view of the above, liquid biopsies (in particular using plasma DNA) are increasingly used in solid cancers to monitor disease genomics, tumour burden and treatment response. However, biological and technical issues influence the ability to accurately stratify patients using current methods, especially for copy number change rich cancers, such as prostate cancer (Hieronymus et al., Elife. 2018 Sep 4;7:e37294 and Li et al., Nature. 2020 Feb;578(7793):112-121). Biological and technical challenges for accurate detection of genomic lesions in ctDNA, such as metastatic prostate cancer (mPC) plasma ctDNA, include broad ranges of tumor fractions, intra-patient genomic heterogeneity, frequent aneuploidy, and common imbalanced copy number changes.

[0008] Intra-patient genomic heterogeneity is characterized by subclonal diversity in tumor biopsies. Unlike biopsies that are representative of a single spatial lesion, plasma putatively contains DNA from multiple spatially separated metastases. Intra-tumour heterogeneity has been linked with poor outcomes when measured in tumour biopsies but has not been explored using ctDNA. Previous studies have suggested non-integer copy numbers in circulation could be a possible indicator of subclonality (Beltran, H. et al, J Clin Invest. 2020;130(4):1653-1668; Orlando, F. et al, NAR Cancer. 2022;4(2):zcac016). However, no clinical impact of non-integer copy numbers in circulation, let alone as a measure of subclonality, have not been investigated or reported.

[0009] There remains a significant need for improved diagnostic and analytical methods for the stratification and monitoring of cancers, particularly methods that display greater sensitivity and accuracy to provide more detailed information on the genetic aberrations, and in particular the subclonality and intra-patient heterogeneity, of cancers. Such improved diagnostic and analytical methods are necessary to lead to better and more effective treatment decisions for patients, and more reliable treatments and prognosis for patients. Summary of Invention

[0010] The present invention provides an in vitro method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of cancer in a subject, said method comprising the steps of: i) providing a biological sample obtained from the subject, wherein said sample comprises tumor DNA; ii) determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 and Table 2 in the tumor DNA; iii) determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value; wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

[0011] The present invention further provides an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject, said in vitro assay comprising the method steps of: a) providing a biological sample obtained from the subject, wherein said sample comprises tumor DNA; b) determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA; c) determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value; wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

[0012] The present inventors have found that the methods and assays of the present invention are surprisingly effective and sensitive at determining non-integer allele-specific copy number values for gene-regions in biological samples comprising tumor DNA, and in particular samples comprising ctDNA. Further, not only have the present inventors been able to accurately determine non-integer allele-specific copy number values for gene-regions, they have surprisingly found that allele-specific copy number values determined according to the present invention for multiple gene-regions can be used directly to accurately establish circulating tumor subclonality (also referred to herein as circulating tumor index) in biological samples, and that the circulating tumor subclonality as determined using the methods and assays of the invention is a direct indicator of prognosis and can be used in clinical practice to inform treatment decisions and lead to more effective and reliable treatments for patients. To the best of the inventors' knowledge, the methods and assays of the present invention are the first that allow intra-patient tumour heterogeneity in liquid biopsies to be determined and directly used in clinical practice. Although heterogeneity in tissue has been linked with poor outcomes (van Dijk E, et al., Nat Commun.

[0013] 2021;12(l):3188; Dentro SC, et al., Cell. 2021;184(8):2239-54 e39) inter-metastasis heterogeneity within a patient as measured by circulating tumour DNA (ctDNA) clonal architecture remains largely unexplored and its clinical impact unknown.

[0014] Methods and assays of the present invention utilize a selected panel of bespoke generegions including the exonic, intronic and flanking regions of a number of selected genes, in combination with using a non-integer event threshold of at least 0.1 more or at least 0.1 less than the closest integer value to distinguish between true non-integer events indicating subclonality. The combination of the genes, the gene-region designs, and non- integer event threshold, have been found by the inventors to lead to the method and assay of the invention being especially effective and sensitive at detecting true noninteger allele-specific copy numbers for the gene-regions, and thus is especially accurate at measuring subclonality in a biological sample obtained from the subject, the biological sample being one that comprises tumor DNA. The SNPs selected within each region in the preferred methods and assays of the invention further increase the effectiveness, sensitivity and accuracy of the methods and assays.

[0015] As can be seen from the examples described herein, in establishing the present invention, the inventors utilized an optimized targeted sequencing panel and computational approach that assessed clonality in tumour for use in plasma DNA (as described in, for example, (Orlando F, et al., NAR Cancer. 2022;4(2):zcac016 and in WO2022 / 258975) and then tested clonality in plasma DNA from a prospective biomarker cohort of patients treated with cabazitaxel. A second independent cohort of patients treated with docetaxel in the PRESIDE trial were used for validation. In more detail, the present inventors found that allele-specific non-integer copy number values can be used as an accurate measure of subclonality, and established a circulating subclonality index (CSI) to optimise the measurement of subclonality. In the examples the circulating subclonality index was the proportion of nonwild type target gene regions having an allele specific copy number aberration as found using by CLONETv2 (Prandi D and Demichelis F. Ploidy- and purity-adjusted allele-specific DNA analysis using CLONETv2. Curr Protoc Bioinformatics. 2019;67:e81. doi: 10.1002 / cpbi.81) assessment, where the CLONETv2-estimated copy number value of either allele A (CNA) or allele B (CNB) had a deviation distance of >0.1 from the nearest integer value. This threshold was surprisingly found to be the optimum balance between sensitivity and specificity in picking up true non-integer events, and thus an accurate and reliable threshold for determining subclonality. Fifty-two baseline samples were assessed for association of CSI with outcome. The median CSI for a cohort was confirmed as a suitable cut-off for outcome associations. Surprisingly, a strong correlation between a lower proportion of non-integer versus integer allele specific copy number value of gene-regions (i.e. "low" CSI, for example a CSI of less than the median for the patient cohort) and poor survival suggesting the presence of a dominant subclone already at start of treatment (in the case of the cohort of patients treated with cabazitaxel, a taxane-resistant dominant subclone). Patients with lower CSI had worse progression-free survival compared to those with higher CSI (median 2.7 vs 5.6 months); the same was seen for overall survival (median 7.8 vs 12.1 months). A second independent cohort of patients treated with docetaxel in the PRESIDE trial (NCT02288247) was analysed for validation. In PRESIDE, patients were treated with docetaxel and enzalutamide or docetaxel and placebo after enzalutamide progression. Fifty-one samples were analysed. Confirming the results seen in the cabazitaxel cohort, PRESIDE patients with lower CSI had worse outcomes than those with higher values.

[0016] As such, the present inventors have demonstrated that the method of the invention is especially useful for the real-time strategic assessment of circulating tumour subclonality and intra-patient heterogeneity in cancer patients, and thus allows for the optimization of treatments and the monitoring of disease progression / regression in patients undergoing treatments. The present methods find particular utility for the detection and monitoring of subclonality in subjects known or suspected of having prostate cancer, and optimizing patient treatment in view of this as described herein.

[0017] Brief description of the drawings

[0018] Figure 1 shows the circulating subclonality index assessment. Figure 1A shows the proportion of non-wildtype integer and non-integer copy number gene-regions for each baseline sample assessed (ctDNA fraction >0.20), wherein a non-wildtype gene region is one having an allele specific copy number aberration (asCNA). Figure IB shows a density plot showing the distribution of the circulating subclonality index around the median value (black vertical line). Figure 1C shows a plot showing the loglO of the Cox hazard ratio model obtained splitting the samples in two groups based on different thresholds of the score (grid search). The line was smoothed (loess() function from the R Stats Package) to highlight the trend of the p value. The vertical line corresponds to the score median value. Figure ID shows the association of circulating subclonality index with progression-free survival (PFS) using a different threshold (copy number value of either allele A or allele B with a distance >0.2 from the nearest integer value for non-wild type genes, wherein a non-wildtype is a gene wherein at least one allele of the gene-region has an asCNA) to call non-integer copy numbers. Figure IE shows the association of circulating subclonality index with overall survival (OS) using a different threshold (copy number value of either allele A or allele B with a distance >0.2 from the nearest integer value for non-wild type genes, wherein a non-wildtype is a gene wherein at least one allele of the gene-region has an asCNA) to call non-integer copy numbers. Figure IF shows the association of baseline circulating subclonality index and PFS in the PRESIDE cohort (only patients with ctDNA fraction >0.20 assessed). Patients were split by cohort's median CSI value (0.80); restricted mean survival time analysis showed a significant difference in the two groups. Figure 1G shows survival curves for PFS highlighting the restricted mean survival time (RSMT) estimates (observation time: 7 months) in the PRESIDE validation cohort in patients with high (left panel) and low CSI (right panel). The areas highlighted in pink and orange are the RMST and the restricted mean time lost, respectively. WT, wildtype; n, number; CN, copy number. CSI, circulating subclonality index; OS, overall survival; PFS, progression-free survival; ctDNA, circulating tumour DNA.; no., number; HR, hazard ratio; Cl, confidence interval; ref, reference; RMST, restricted mean survival time.

[0019] Figure 2 provides an overview of IRSTB030 trial patients, plasma collection and circulating tumour DNA features. Figure 2A shows then enrolled patients and plasma sample collection CONSORT diagram for the IRSTB030 multicentre biomarker trial. Figure 2B shows the proportion of ctDNA detection in plasma samples by timepoint. Only significant p-values for comparison between groups are shown. Figure 2C shows the ctDNA fraction in plasma samples with detectable ctDNA by timepoint. Only significant p-values for comparison between groups are shown. Figure 2D shows an overview of sample collection, baseline clinical features and survival for each enrolled patient. Clinical parameters classified by the presence of adverse features at BL (top panel); sample collection timepoints, ctDNA fractions, progression-free survival and overall survival are specified for each patient (bottom panel). CRPC, castration resistant prostate cancer; pts, patients; tx, treatment; ctDNA, circulating tumour DNA; BL, baseline; OT, on treatment; EOT, end of treatment; PD, disease progression; ECOG, Eastern Cooperative Oncology Group - Performance Status; ARSI, androgen receptor signalling inhibitor; PSA, prostatespecific antigen; ALP, alkaline phosphatase; LDH, lactate dehydrogenase; ULN, upper limit of normal; mets, metastases.

[0020] Figure 3A shows the patient baseline characteristics in the IRSTB030 biomarker prospective multicentre trial cohort. Abbreviations. Cl: confidence interval; ECOG-PS: Eastern Cooperative Oncology Group - Performance Status; no.: number; IQR: interquartile range; PSA: prostate-specific antigen; cfDNA: cell free DNA; ARSI: androgen receptor signalling inhibitors). Figure 3B shows the patient treatment characteristics in the IRSTB030 biomarker prospective multicentre trial cohort. (Abbreviations. CRPC: castration resistant prostate cancer; no.: number; IQR: interquartile range.)

[0021] Figure 4 shows a comparison of cell free-DNA (cfDNA) and prostate specific antigen levels in samples with detectable ctDNA by timepoint. Figure 4A shows the cfDNA levels in plasma samples with detectable ctDNA by timepoint. Only significant p-values for comparison between groups are shown. Figure 4B shows the prostate-specific antigen levels in plasma samples with detectable ctDNA by timepoint. Only significant p-values for comparison between groups are shown. BL, baseline; OT, on treatment; EOT, end of treatment; PD, disease progression; cfDNA, cell free-DNA; PSA, prostate-specific antigen.

[0022] Figure 5 shows the association of baseline ctDNA and circulating biomarkers dynamics with treatment response and outcomes. Figure 5A shows the overall survival (OS) grouped by above or below baseline median ctDNA fraction in ctDNA detectable samples and Figure 5B shows the progression-free survival grouped by above or below baseline median ctDNA fraction in ctDNA detectable samples. Multivariable analysis of baseline clinical parameters and circulating biomarkers for OS is shown in Figure 5C and for PFS is shown in Figure 5D. Association of ctDNA kinetics and outcomes by ctDNA changes from baseline to C3 for OS is shown in Figure 5E and for PFS is shown in Figure 5F. Figure 5G shows association of PSA and ctDNA dynamics and radiographic response. PSA and ctDNA changes from baseline to C3 are represented in the waterfall plot; computed-tomography scan / bone scintigraphy response is shown (*=pa rtia I response). Figure 5H shows a Forest plot representation of baseline-C3 dynamics and their impact on OS at univariable analysis. Figure 51 shows a Forest plot representation of baseline-C3 dynamics and their impact on PFS at univariable analysis. Multivariable analysis of baseline-C3 dynamics and association with OS is shown in Figure 5J. Multivariable analysis of baseline-C3 dynamics and association with PFS is shown in Figure 5K. ctDNA, circulating tumour DNA; HR, hazard ratio; Cl, confidence interval; ND, not detected; ref, reference; No., number; OS, overall survival; PFS, progression-free survival; OR, odds ratio; ECOG, Eastern Cooperative Oncology Group - Performance Status; PSA, prostate-specific antigen; cfDNA, cell-free DNA; LDH, lactate dehydrogenase; ULN: upper limit of normal. Figure 6 shows the association of baseline clinical parameters and circulating biomarkers with outcomes. Figure 6A shows a Forest plot representation of baseline parameters and their impact on overall survival at univariable analysis. Figure 6B shows a Forest plot representation of baseline parameters and their impact on progression free survival at univariable analysis. OS, overall survival; PFS, progression-free survival; ECOG, Eastern Cooperative Oncology Group - Performance Status; ARSI, androgen receptor signalling inhibitors; PSA, prostate-specific antigen; ALP, alkaline phosphatase; LDH, lactate dehydrogenase; ULN: upper limit of normal; mets, metastases; cfDNA, cell-free DNA; ctDNA, circulating tumour DNA.

[0023] Figure 7 shows the association of ctDNA kinetics at Cl with outcomes. Figure 7A shows the overall survival by ctDNA fraction changes from baseline to Cl (after one treatment cycle). Figure 7B shows the progression free survival by ctDNA fraction changes from baseline to Cl (after one treatment cycle). Patients were classified by ctDNA detection at Cl. ctDNA, circulating tumour DNA; HR, hazard ratio; Cl, confidence interval; ND, not detected; D, detected; ref, reference; No., number.

[0024] Figure 8 shows the prevalence of copy number alterations (CNAs) and mutations at baseline and at progression. The bar charts of Figure 8 represent the prevalence of copy number aberrations by gene in samples with detectable ctDNA at baseline (Figure 8A) and at progression (Figure 8B) and mutations at baseline (Figure 8C) and at progression (Figure 8D). Genes are ordered by chromosome location. CNNL, copy number-neutral loss-of- heterozygosity; del, deletion; n, number.

[0025] Figure 9 shows the genomic landscape of CRPC patients upon cabazitaxel treatment. Figure 9A shown an OncoPrint showcasing copy number alterations (CNAs) and mutations of the PCF_SELECT genes in matched baseline and progression samples from patients with at least one ctDNA-detectable sample (left). The bar charts (right) represent the overall prevalence of CNAs and mutations by gene in ctDNA detectable samples. Genes are ordered (top to bottom) by prevalence difference in CNAs from baseline to progression. Significant differences are shown with asterisks. Figure 9B shows a bar-plot showing the presence of TP53, MDM2 and MDM4 CNAs in samples harbouring at least one of these alterations (no.107) (top panel). Contingency tables showing mutual exclusivity of TP53 hemideletions with MDM2 (p<0.0001) and MDM4 (p=0.0085) gains and co-occurrence of MDM2 and MDM4 gains (p=0.0001) in the overall cohort (bottom panel). Figure 9C shows a contingency table showing the frequency of AR CN gains and AR mutations (L702H, T878A, H875Y, D891N) (p=0.78) in samples with detectable ctDNA (no.142). In samples with more than one AR mutation, only one case was counted. Figure 9D shows bar charts showing the proportion of AR mutations clonality in samples with normal AR CN and AR CN gains. Subclonal mutations are significantly more frequent in AR gained samples than in wildtype (p=0.03). WT, wild type; CNNL, copy number-neutral loss-of-heterozygosity; del, deletion; mut, mutation; ND, not detected; ctDNA, circulating tumour DNA; mo., months.

[0026] Figure 10A shows circulating subclonality index and association with outcomes. Schematic representation of samples with low (left panel) and high (right panel) CSI in the CNA / CNB space. Small circles represent genes included in the panel; larger circled areas highlight the integer CNA / CNB space and the clonal space thresholds (<0.1). Genes outside the integer space are considered subclonal. Figure 10B shows the association of high or low CSI with PFS. Figure 10C shows the association of high or low CSI with OS. CSI was dichotomized by median value. Figure 10D shows a Forest plots of baseline clinical features, circulating biomarkers and CSI and their impact on PFS at univariable analysis. Figure 10E shows a Forest plots of baseline clinical features, circulating biomarkers and CSI and their impact on OS at univariable analysis. Figure 10F shows multivariable analysis of baseline clinical features, circulating biomarkers and CSI and their association with PFS. Figure 10G shows multivariable analysis of baseline clinical features, circulating biomarkers and CSI and their association with OS. Figure 10H shows the median CSI values (left) and ctDNA fraction (right) at baseline (no. 52) and progression (no. 20) samples. P-values for comparison between groups are shown. HR, hazard ratio; Cl, confidence interval; PFS, progression-free survival; OS, overall survival; ECOG, Eastern Cooperative Oncology Group - Performance Status; ARSI, androgen-receptor signalling inhibitor; PSA, prostate-specific antigen; ALP, alkaline phosphatase; ULN, upper limit normal; LDH, lactate dehydrogenase; cfDNA, cell-free DNA; ctDNA, circulating tumour DNA; CSI, circulating subclonality index.

[0027] Figure 11 shows the characteristics of patients in the IRSTB030 biomarker prospective multicentre trial cohort with baseline ctDNA >0.20 assessed for circulating subclonality index (Abbreviations. Pts: patients; ctDNA: circulating tumour DNA; no.: number; Cl: confidence interval; ECOG-PS: Eastern Cooperative Oncology Group - Performance Status;

[0028] PSA: prostate-specific antigen; ULN: upper limit normal; cfDNA: cell free DNA; ARSI: androgen receptor signalling inhibitors; IQR: interquartile range).

[0029] Figure 12A-C shows the association of overall survival with the recalibrated CSI scores from samples containing different tumour DNA contents (A: >20%, B: >5% and C: >0%). The association with outcome is preserved with lower tumour DNA contents with a slight increase in hazard ratios (HR) when low tumour DNA samples (>5%) were included.

[0030] Definitions

[0031] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly recognized by one of ordinary skill in the art to which this invention belongs.

[0032] As used herein, the term "biological sample" refers to a biological sample derived from a subject to be screened. The biological sample may be any suitable sample known in the art in which the expression of the selected markers can be detected. Included are individual cells and cell populations obtained from bodily tissues or fluids. Examples of suitable body fluids to be tested are plasma, blood, lymph, cerebral fluid, urine and saliva. Examples of suitable body tissues to be tested include prostate tissue, bladder tissue, breast tissue, ovarian tissue and pancreatic tissue.

[0033] As used herein, the term "non-tumor DNA" refers to chromosomal genomic DNA present in, or derived from, a non-cancerous cell. For example, non-tumor DNA may be derived from a white blood cell (WBC).

[0034] As used herein, the term "target gene" refers to a gene that is known or suspected of being commonly mutated in certain types of cancer and / or frequently altered in signalling pathways known or suspected of being druggable pathways for treating a cancer. Examples of such genes include: AR, AKT1, AKT2, AKT3, APC, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRIP1, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CHD1, CHEK2, CLU, CTNNB1, CUL1, CYLD, ERCC1, KDM6A, ERCC2, ERCC3, MED12, ERCC4, ERCC5, ERG_TMPRSS2, SMARCA1, FAM183B, FAM60A, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, FBXW7, FOXA1, FOXP1, GNAS, HDAC2, HSD3B1, IDH1, IDH2, KMT2C, KMT2D, KRAS, MDM2, MDM4, MET, MLH1, MSH2, MSH6, MYC, MYCN, NC0A2, NFE2L2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RUNX1, RYBP, SPOP, TP53, ZBTB16 and ZFHX3. Preferred examples of target genes include: AKT1, AKT2, AKT3, APC, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRIP1, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CH DI, CLU, CTNNB1, CUL1, CYLD, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, ERG_TMPRSS2, FAM183B, FAM60A, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, FBXW7, F0XA1, F0XP1, GNAS, HSD3B1, IDH1, KMT2C, KMT2D, KRAS, MDM2, MDM4, MET, MLH1, MSH2, MSH6, MYC, MYCN, NC0A2, NFE2L2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RUNX1, RYBP, SPOP, TP53, ZBTB16 and ZFHX3.

[0035] As used herein, the term "control gene" is a gene that is known to not be commonly mutated in a cancer and / or to not acquire mutations during the progression of a cancer. Examples of such genes include: ADAM2, APBB1IP, AQP8, ATG14, ATXN7, C9orf47, CACNG5, CST7, CSTF2T, DRD1, ENPEP, EPN1, FAM183B, FAM60A, FCER1A, HDAC8, GRHPR, IL1RL2, KRT85, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NAPG, NFXL1, NIT2, N0TCH3, OR3A3, PTAFR, PTGER4, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, VNN3 and ZBTB9. Preferred examples of control genes include: ADAM2, APBB1IP, AQP8, ATG14, ATXN7, C9orf47, CACNG5, CST7, CSTF2T, DRD1, ENPEP, EPN1, FAM183B, FAM60A, FCER1A, GRHPR, IL1RL2, KRT85, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NAPG, NFXL1, NIT2, N0TCH3, OR3A3, PTAFR, PTGER4, PXDNL, RNF125, RSF1, SPDYA, TK2, TOP3B, UGT2B17, VNN3 and ZBTB9. The control genes for one type of cancer may be different to the control genes for a different cancer, or they may be the same. For example, control genes for prostate cancer may be one or more control genes selected from the lists of control genes above.

[0036] As used herein, the term "gene-region" refers to a region of the genome that covers a gene in the genome, e.g. the genome of a subject, for example a human, and includes a gene and a maximum extension of 200 Kbp per side of the gene. A gene-region may cover the intronic (i.e. non-coding), exonic (i.e. coding) and flanking regions of a gene. Preferably, a generegion of the invention covers intronic, exonic and flanking regions of a gene. A gene-region may be referred to using the genomic location of the region, for example using the coordinates of the start position and end position of the location in a specific chromosome. For a human subject a genomic region is suitably described by a genomic location, and in particular a genomic location with reference to a reference genome (for example, a digital nucleic acid sequence database, assembled a representative example of a species' set of genes). For example, for a human subject, with reference to the human reference genome GRCh37 (also referred to as Human Genome 19 (hgl9)) or human reference genome GRCh38 (also referred to as Human Genome 38 (hg38)). For the present inventions, preferably the reference genome is human reference genome GRCh37 (also known as hgl9).

[0037] As used herein, the term "target gene-region" refers to a gene-region that includes a target gene (supra), and the term "control gene-region" refers to a gene-region that includes a control target (supra).

[0038] As used herein, the term "allelic fraction" or "AF" refers to the number of times a mutated base / variant is observed at a genomic locus, divided by the total number of times any base is observed at the genomic locus. For example, in a sample comprising DNA derived from a diploid genome, an allelic fraction of 0.5 implies that there is one copy of an allele with base X at position Y and one copy of an allele with base Z at position Y. That is to say, that 50% of the DNA in the sample contains the allele with base X at position Y and the other 50% of the DNA in the sample contains the allele having base Z at position Y. In a DNA sample derived from an aneuploid cell (for example a cell that contains three copies of a chromosome), an AF of 0.33 for a first allele and an AF of 0.67 for a second implies that there is one copy of an allele with base X at position Y and two copy of an allele with base Z at position Y. That is to say, that 33% of the DNA in the sample contains the allele with base X at position Y and the other 67% of the DNA in the sample contains the allele having base Z at position Y.

[0039] As used herein, the term "single nucleotide polymorphism" or "SNP" refers to a polymorphism that occurs at a polymorphic site occupied by a single nucleotide. The site of the SNP is usually preceded by and followed by highly conserved sequences (e.g., sequences that vary in less than 1 / 100 or 1 / 1000 members of a population). As used herein, "SNPs" is the plural of SNP. SNPs are most frequently diallelic. The most common allele of a SNP is called a "major" or "wild-type" allele and an alternative allele of said SNP is called a "minor" or "mutant" allele. A SNP usually arises due to substitution of one nucleotide for another at the polymorphic site. SNPs can also arise from a deletion of a nucleotide or an insertion of a nucleotide relative to a reference allele.

[0040] As used herein, the term "SNP location" and "SNP locus" refer to a polymorphic site at which a polymorphism occurs. The term "SNP loci" is the plural form of the term "SNP locus". A "SNP location" or "SNP locus" can be referred to using its unique dbSNP Reference SNP ID. (also referred to as the rsid) in the National Center for Biotechnology Information's dbSNP database. A dbSNP Reference SNP (rsid or RefSNP) number is a locus accession for a variant type assigned by dbSNP. The RefSNP catalog is a non-redundant collection of submitted variants which were clustered, integrated and annotated. RefSNP number is the stable accession regardless of the differences in genomic assemblies. They provide a stable variant notation for mutation and polymorphism analysis, annotation, reporting, data mining, and data integration. A RefSNP is represented by a number preceded by the letters "rs". A "SNP location" or "SNP locus" can alternatively be referred to using the coordinates of the position of the polymorphic site in a specific chromosome. For a human subject a genomic location is suitably described by reference to a reference genome (for example, a digital nucleic acid sequence database, assembled from a representative example of a species' set of genes). For example, for a human subject, with reference to the human reference genome GRCh37 (also referred to as Human Genome 19 (hgl9)) or human reference genome GRCh38 (also referred to as Human Genome 38 (hg38)). For the present inventions preferably the reference genome is human reference genome GRCh37 (also known as hgl9).

[0041] As used herein, the term "polymorphism" refers to a genetic variation, or the occurrence of two or more genetically determined alternative sequences at a single genetic locus in a population. Each version of the sequence with respect to the polymorphic site is referred to as an "allele" of the polymorphic site. Typically, polymorphisms have two alleles, with the minor allele occurring at a frequency of greater than 1%, and more preferably greater than 5% or 10% of a selected population. The allelic form occurring most frequently in a selected population is sometimes referenced as the "wild-type" form. Diploid organisms may be homozygous or heterozygous for allelic forms. A biallelic polymorphism has two forms. A tria llelic polymorphism has three forms. Examples of polymorphisms include restriction fragment length polymorphisms (RFLPs), variable number of tandem repeats (VNTRs), single nucleotide polymorphisms (SNPs), single nucleotide variants (SNVs), dinucleotide repeats, trinucleotide repeats, tetranucleotide repeats, simple sequence repeats, indels, and insertion elements such as Alu.

[0042] As used herein, the terms "single nucleotide variant" or "SNV" refer to a single nucleotide variation in a genome sequence. SNVs may be rare or common in a population. If an SNV is present in at least 1% of the population, the SNV may be referred to as a "single nucleotide polymorphism" or "SNP".

[0043] SNPs tend to be evolutionarily stable from generation to generation and, as such, can be used to study specific genetic abnormalities throughout a population. If SNPs occur in the protein coding region (i.e. exonic region) it can lead to the expression of a variant, sometimes defective, form of the protein that may lead to development of a genetic disease. Such SNPs can therefore serve as effective indicators of the genetic disease. Some SNPs may occur in non-coding regions, but nevertheless, may result in differential or defective splicing, or altered protein expression levels. SNPs can therefore be used as diagnostic tools for identifying individuals with a predisposition for certain diseases, genotyping the individual suffering from the disease in terms of the genetic causes underlying the condition, and facilitating drug development based on the insight revealed regarding the role of target proteins in the pathogenesis process.

[0044] As used herein, the terms "heterozygous single nucleotide polymorphism" and "heterozygous SNP" refer to a SNP that is present in the DNA of a sample at an AF of between 0.05 to 0.95. In certain embodiments, the terms a heterozygous single nucleotide polymorphism" and "heterozygous SNP" refers a SNP that is present in the DNA of a sample at an AF of between 0.2 to 0.8.

[0045] As used herein, the term "minor allele frequency" or "MAF" refers to the frequency at which the second most common allele occurs in a given population. The frequency may be considered high or low. As used here, a "high MAF" is typically an allele that occurs at a frequency of 0.2 to 0.5 in a population, for example at a frequency of 0.2 to 0.5 in the 1000 Genomes Project Genotype Data (release 20130502; PMID: 26432245). As used herein, a "low MAF" is typically an allele that occurs at frequency of less than 0.2, for example less than 0.2 to around 0.01 in a population, for example at a frequency of 0.2 to 0.5 in the 1000 Genomes Project Genotype Data (release 20130502).

[0046] As used herein, the term "informative single nucleotide polymorphism", "informative SNP" or "iSNP" refers to a heterozygous SNP that is present in a gene-region in the genome of a subject. The term "iSNPs" is the plural form of the term "iSNP".

[0047] As used herein, the terms "iSNP location" or "iSNP locus" refer to a polymorphic site at which an iSNP occurs. The term "iSNP loci" is the plural form of the term "iSNP locus". A "iSNP location" or "iSNP locus" can be referred to using its unique dbSNP Reference SNP ID. (also referred to as the rsid) in the National Center for Biotechnology Information's dbSNP database. A "iSNP location" or "iSNP locus" can alternatively be referred to using the coordinates of the position of the polymorphic site in a specific chromosome as described supra. For the present inventions, preferably the reference genome is human reference genome GRCh37 (also known as hgl9).

[0048] As used herein, the terms "allele imbalance", "allelic imbalance" and "Al" refer to an imbalance in the identity of the allele present in the genome of a subject. For Al to be present in a genome there must be at least two different alleles for a gene-region. A genome having identical alleles for a gene-region does not exhibit Al. A loss of heterozygosity (LOH) is a common form of allelic imbalance.

[0049] As used herein, the term "copy number" refers to the number of copies of a gene-region, gene, or part thereof, present in the chromosomal DNA of an individual or in chromosomal DNA derived from a cell of an individual. A "normal copy number" when used herein refers to the copy number of a normal or wild-type allele present in a normal cell of a subject. The copy number for any given gene-region, gene or part thereof, may range from 0 to 3 (for example 0, 1, 2 or 3), 0 to 4 (for example 0, 1, 2, 3 or 4), 0 to 5, 0 to 6, or 0 to more than 6. A change in copy number may arise from copy number alteration such as gains or losses of large segments of the genome.

[0050] As used herein, the terms "allele-specific copy number aberration", "allele-specific informed copy number aberration" and "asCNA" refer to alteration in the total copy number (i.e. the allele-specific number) of a gene-region, or part thereof, and the specific number of copies of each chromosome. More specifically, allele-specific copy number aberrations (asCNAs) may be defined as alterations in the allele-specific copy number of a gene-region, or part thereof, relative to the expected number of copies of that gene-region, or part thereof, derived from each parental chromosome (e.g. as determined from a reference model generated from a control sample, as described herein above). Types of asCNAs include: copy number gain, copy number loss, and copy number-neutral loss of heterozygosity. A gain in copy number may be a gain of either one or both of the two inherited copies. An gain may be referred to as "unbalanced" when the gain differs in magnitude between the alleles (for example a 2,1 gain, 3,2 gain, a 4,2 gain, a 4,3 gain etc.). A gain may be referred to as "balanced" when both alleles gained equally much (for example a 2,2 gain, 3,3 gain, a 4,4, gain, a 5,5, gain, etc.). A copy number loss may be the loss of one of the parental copies of a gene-region, or part thereof (this may be referred to as a mono-allelic copy number loss). Such a loss may result in loss of heterozygosity (LOH) if the parental copies were heterozygous for that gene. A copy number loss may be the loss of both of the parental copies of a gene-region, or part thereof (this may be referred to as a bi-allelic copy number loss). The loss of one parental copy of a gene-region, or part thereof, accompanied by a simultaneous gain of the other parental copy of the same gene-region, or part thereof can also occur. If the parental copies were heterozygous for that gene, such an aberration may result in a copy number-neutral loss of heterozygosity (i.e. a loss of heterozygosity without a change in total copy number). This may also be referred to as a loss of heterozygosity 0,2. The loss of one parental copy of a gene-region, or part thereof, accompanied by a simultaneous gain of multiple copies, for example 2, 3, 4, 5, or more than 5 copies, of the other parental copy of the same gene-region, or part thereof can also occur. Such an aberration can be referred to as a loss of heterozygosity 0,3 when two copies of the other parental copy of the same gene-region are gained; a loss of heterozygosity 0,4 when three copies of the other parental copy of the same gene-region are gained; and a loss of heterozygosity 0, X when X-l copies of the other parental copy of the same gene-region are gained wherein X is 4, 5, 6, 7, or a higher integer.

[0051] As used herein, the term "allele-specific copy number" is the number of copies of a generegion, gene, or part thereof, for each allele present in the chromosomal DNA of an individual or in chromosomal DNA derived from a cell of an individual. As used herein, the term "allele-specific copy number value" is the observed allele specific copy number of cells in a sample (for example in a sample comprising ctDNA, for example a blood or plasma sample comprising ctDNA). In a single cell the observed allele specific copy number will be an integer value (e.g. 0, 1, 2, 3, 4 etc) and will be the actual allele specific copy number of the cell. However, in a sample where multiple cells and / or DNA from multiple cells are present (for example in a sample comprising multiple tumour cells and / or DNA from multiple tumour cells (for example a sample comprising cfDNA and / or ctDNA)), the observed allele specific copy number (i.e. the allele-specific copy number value) and the real copy number of each tumour cell may differ. That is because the observed allele specific copy number represents the allele specific copy number from a mixture of DNA from multiple cells (for example, from multiple tumour cells). If all cells in the sample are clones and / or all the DNA in the sample is from cells that are clones, the real allele-specific copy number value from a sample will be the same as the observed allele specific copy number (i.e. the allele-specific copy number value), and the allele specific copy number will be an integer value. However, if not all cells in the sample are clones, i.e. the sample includes two or more subclones and / or if not all the DNA in the sample is from cells that are clones of each other (i.e. the sample includes DNA from two of more subclones), the real allelespecific copy number value from a sample may not be the same as the observed allele specific copy number (i.e. the allele-specific copy number value). In this case, the allele specific copy number may be an integer value (i.e. if for that allele there is no difference in copy number between the subclones), or it may diverge from an integer value (i.e. if for that allele there is a difference in copy number between one or more of the subclones).

[0052] As used herein, the term "clone" means cells that are genetically identical in a clonal population (for example in a population of tumour cells). As used herein, the term "subclone" means a clone that is descended from another clone but has acquired additional genetic aberration(s) (for example asCNA and / or mutations, such as somatic mutations) and therefore is not genetically identical to one or more other clones in a clonal population (for example in a population of tumour cells). As used herein, the term "dominant subclone" means the population that occurs at the highest frequency in a clonal population (for example in a population of tumour cells). As used herein, the terms "circulating clone" and "circulating subclone" means a clone or subclone, respectively, that has its DNA circulating the blood stream and / or in the urine (for example a clone or subclone that has its DNA present in cfDNA and / or ctDNA).

[0053] As used herein, the term "subclonality" means the presence of genetic aberrations(s) (for example asCNA and / or mutations, such as somatic mutations) only in a subset of tumor cells within a population of tumour cells. As used herein, the term "circulating subclonality" means the presence of genetic aberration(s) (for example asCNA and / or mutations, such as somatic mutations) only in a subset of tumor cells that have their DNA circulating in the blood stream and / or in the urine (for example only in a subset of tumor cells that have their DNA present in cfDNA and / or ctDNA).

[0054] As used herein, the term "androgen receptor (AR) associated" means a gene-region that includes a gene associated with the function in the androgen (receptor) signalling pathway. Examples of such genes include: AR, F0XA1, FOXP1, HSD3B1, NC0A2 and ZBTB16. Aberrant activity of the androgen receptor is associated with certain types of prostate cancer. Aberrant activity of the androgen receptor has also been associated with breast cancer, ovarian cancer, pancreatic cancer and bladder cancer. If a genetic aberration, such as an asCNA, or a somatic or germline mutation, is detected in one or more gene-region of this type in a subject, it indicates that a subject would benefit from ceasing or altering treatment with one or more class of drug that is known or suspected of targeting AR function. An example of this class of drug include hormonal agents, such as LHRH agonists (for example leuprolide, goserelin, triptorelin, or histrelin), LHRH antagonists (for example degarelix), androgen blockers (for example abiraterone or ketoconazole), anti-androgens (for example flutamide, bicalutamide, nilutamide, enzalutamide, apalutamide or darolutamide), androgen synthesis inhibitors (for example abiraterone), estrogens and steroids (for example prednisone or dexamethasone); and in particular androgen blockers (for example abiraterone or ketoconazole), anti-androgens (for example flutamide, bicalutamide, nilutamide, enzalutamide, apalutamide or darolutamide) and androgen synthesis inhibitors (for example abiraterone). It also indicates that a subject would benefit from ceasing or altering treatment with one or more class of drug that is known or suspected of targeting AR function from treatment with one or more alternative cancer treatment, for example a chemotherapy such as a taxane (for example docetaxel and cabazitaxel) or a platinum-based antineoplastic drugs (for example carboplatin). As used herein, the term "cell cycle associated" means a gene-region that includes a gene associated with the process of growth and proliferation of a cell. Examples of such genes include: AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53. Genetic aberrations in genes associated with growth and proliferation of a cell are known to occur in cancer such as prostate cancer, breast cancer, ovarian cancer, pancreatic cancer and bladder cancer, and in metastatic cancer. If a genetic aberration, such as an asCNA, or a somatic or germline mutation, is detected in one or more gene-region of this type in a subject, it indicates that a subject might benefit from treatment with one or more class of drug that is known or suspected of targeting cell cycle perturbations. Examples of such class of drug include: ATR inhibitors (for example Berzosertib), CDK inhibitors (for example Flavopiridol (alvocidib), abemaciclib, ribociclib, Olomoucine, Roscovitine (Seliciclib), Purvalanol, Paullones, Butryolactone, Thio / oxoflavopiridols, Oxindoles, Aminothiazoles, Benzocarbazoles, and Pyrimidines; and in particular Flavopiridol, Palbociclib, ribociclib and abemaciclib) chemotherapies (for example a taxane (for example docetaxel or cabazitaxel), and c-Met inhibitors (for example cabozantinib)), WEE1 inhibitors (for example adavosertib), Aurora kinase inhibitors (for example Alisertib, ZM447439, hesperidin, and VX-680) and alkylating agents (for example nitrogen mustards (such as cyclophosphamide, chlormethine, uramustine, melphalan, chlorambucil, ifosfamide, and bendamustine), nitrosoureas (such as carmustine, lomustine, and streptozocin) and alkyl sulfonates (such as busulfan)).

[0055] As used herein, the term "chromatin remodelling associated" means a gene-region that includes a gene that is associated with cell growth and cell division steps, such as cell-cycle progression and chromosome segregation. Genes associated with chromatin remodelling typically exert a suppressive effect on tumor growth. Examples of such genes include: ARID1A, CHD1, KDM6A, MED12, SMARCA1, KMT2C, KMT2D and RYBP. Genetic aberrations in genes associated with chromatin remodelling functions are known to occur in cancer such as prostate cancer, breast cancer, ovarian cancer, pancreatic cancer and bladder cancer, and in metastatic cancer. If a genetic aberration, such as an asCNA, or a somatic or germline mutation, is detected in one or more gene-region of this type in a subject, it indicates that a subject might benefit from treatment with one or more class of drug that is known or suspected to target chromatin remodelling functions. Examples of such class of drug include DNMTl inhibitors (for example 5-azacitidine), HDAC inhibitors (for example vorinostat and romidepsin) and BET inhibitors (for example l-BET 151, l-BET 762, OTX-015, TEN-010, CPI- 203, CPI-0610, olinone, RVX-208, ABBV-744, AZD5153, MT-1, and MS645).

[0056] As used herein, the term "DNA repair associated" means a gene-region that includes a gene associated with the identification and correction of damage to DNA. Examples of such genes include: ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C. Genetic aberrations in genes associated with DNA repair functions are known to occur in cancer such as prostate cancer, breast cancer, ovarian cancer, pancreatic cancer and bladder cancer, and in metastatic cancer. If a genetic aberration, such as an asCNA, or a somatic or germline mutation, is detected in one or more gene-region of this type in a subject, it indicates that a subject might benefit from treatment with one or more class of drug that is known or suspected to target a DNA repair function. Examples of such class of drug include PARP inhibitors (for example olaparib, rucaparib, niraparib or talazoparib, Veliparib, Pamiparib, Rucaparib, and Veliparib; and in particular example olaparib, rucaparib, niraparib and talazoparib), ATR inhibitors (for example Berzosertib), CDK inhibitors (for example Flavopiridol (alvocidib), abemaciclib, ribociclib, Olomoucine, Roscovitine (Seliciclib), Purvalanol, Paullones, Butryolactone, Thio / oxoflavopiridols, Oxindoles, Aminothiazoles, Benzocarbazoles, and Pyrimidines; and in particular Flavopiridol, Palbociclib, ribociclib and abemaciclib), DNA-PK inhibitors (for example AZD7648, M3814, CC-122 and CC-115) , immune checkpoint therapies (for example PD-1 inhibitors (e.g. pembrolizumab, nivolumab, cemiplimab, and spartalizumab), PD-L1 inhibitors (e.g. atezolizumab, avelumab and durvalumab), or CTLA-4 inhibitord (e.g. ipilimumab)), CHK1 inhibitors (for example V158411, PF-477736 and AZD7762), CHK2 inhibitors (for example CCT241533 and Aminopyridine 7), WEE1 inhibitors (for example adavosertib), platinumbased antineoplastic drugs (for example cisplatin, carboplatin, oxaliplatin, nedaplatin, triplatin tetranitrate, picoplatin, satraplatin and phenanthriplatin, and in particular cisplatin, carboplatin, oxaliplatin, nedaplatin), radionuclide and radiation therapies (for example radium-223 and PSMA-targeting radionuclide therapies (for example 225Ac-Labeled PSMA- 617 and 177Lu-Labeled PSMA-617). As used herein, the term "PI 3 K Associated" means a gene-region that includes a gene associated with the phosphoinositide 3-kinase (PI3K) signalling pathway. Typically, genes associated with the PI3K signalling pathway are involved in the stimulation of cell proliferation and growth, and the inhibition of cell apoptosis. Examples of such genes include: AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN. Genetic aberrations in genes associated with the PI3K signalling pathway are known to occur in cancer such as prostate cancer, breast cancer, ovarian cancer, pancreatic cancer and bladder cancer, and in metastatic cancer. If a genetic aberration, such as an asCNA, or a somatic or germline mutation, is detected in one or more gene-region of this type in a subject, it indicates that a subject might benefit from treatment with one or more class of drug that is known or suspected to target the PI3K signalling pathway. Examples of such class of drug include PI3K inhibitors (for example idelalisib, copanlisib, duvelisib, alpelisib, umbralisib, dactolisib, voxtalisib, Taselisib, Idelalisib, Buparlisib, Duvelisib, and Copanlisib and in particular idelalisib, copanlisib, duvelisib, alpelisib, and umbralisib) and mTOR inhibitors (for example rapamycin, deforolimus, dactolisib, voxtalisib, temsirolimus, everolimus, sapanisertib, AZD8055, and AZD2014).

[0057] As used herein, the term "Wnt signalling associated" means a gene-region that includes a gene associated with the Wnt signalling pathway. Typically, genes associated with the Wnt signalling pathway are involved in cell fate, cell migration, cell polarity and neural development. Examples of such genes include: APC, CTNNB1 and RNF43. Genetic aberrations in genes associated with the Wnt signalling pathway are known to occur in cancer such as prostate cancer, breast cancer, ovarian cancer, pancreatic cancer and bladder cancer, and in metastatic cancer. If a genetic aberration, such as an asCNA, or a somatic or germline mutation, is detected in one or more gene-region of this type in a subject, it indicates that a subject might benefit from treatment with one or more class of drug that is known or suspected to target the Wnt signalling pathway. Examples of such class of drug include PORCN inhibitors (for example WNT974, ETC-1922159 and CGX1321), FZD antagonists / monoclonal antibodies (for example Vantictumab, Ipafricept, and OTSA101-DTPA-90Y) and Inhibitor of Wnt target genes (for example SM08502).

[0058] As used herein, the term "ploidy" refers to the number of copies of each chromosome present in the genome of a cell. Haploid, diploid, triploid, tetrapioid, pentapioid and hexapioid are kinds of ploidy. Specifically, the term "haploid" refers to a cell that has one copy of each chromosome. The term "diploid" refers to a cell that has two copies of each chromosome. The term "triploid" refers to a cell that has three copies of each chromosome. The term "tetrapioid" refers to a cell that has four copies of each chromosome. The term "pentapioid" refers to a cell that has five copies of each chromosome. The term "hexapioid" refers to a cell that has six copies of each chromosome. A human cell is typically diploid. That is to say that a typical human cell comprises two sets of chromosomes (i.e. 46 chromosomes). However, may types of cancer cells harbour genetic aberrations that result in gain or loss of whole, or parts of, one or more chromosomes. Thus, a human cancer cell cannot be assumed to be diploid. A cell having an abnormal number of chromosomes due to a loss or gain of specific chromosome(s) may be described as aneuploid. A cell having an abnormal number of chromosomes due to a loss or gain of a whole set of chromosomes may be described as aneuploid.

[0059] As used herein, the term "Log2R" refers a function of the percentage of aberrant tumor cells (%AC) that contribute to the copy number alteration and of the copy number in a sample of tumor DNA.

[0060] The term "whole exome sequencing" or "WES" refers the nucleotide sequencing of the protein coding regions (i.e. exons) of the genes in the genome.

[0061] As used herein, the term "circulating free DNA" (cfDNA) means the DNA fragments that have been released into the blood plasma and are found freely circulating the blood stream, as well as in the urine, released from any cell type in the body. cfDNA is generally doublestranded DNA consisting of small fragments (70 to 200bp). For the avoidance of doubt, the term "cfDNA" encompasses circulating free DNA that is either non-tumor derived (i.e. "nontumor cfDNA") or tumor derived (i.e. "circulating tumor DNA" or "ctDNA").

[0062] As used herein, the term "circulating tumor DNA" (ctDNA) refers to DNA fragments that have been released from tumor cells into the blood plasma and are found freely circulating the blood stream, as well as in the urine (i.e. ctDNA refers to circulating free DNA that is derived from tumor cells). ctDNA is generally double-stranded DNA consisting of small fragments (70 bp to 200 bp). As used herein, the terms "tumor fraction" and "tumor content" or "TC" of a DNA sample refers to the fraction or percentage of DNA molecules derived from tumor cells in the DNA sample compared to the DNA molecules that are not derived from a cancer cell. For example, for a sample comprising cfDNA, the terms "tumor fraction", "tumor content" and "ctDNA fractions" of a cfDNA refer to the fraction of cfDNA molecules derived from tumor cells (i.e. the ctDNA) in a cfDNA sample compared to the cfDNA molecules that are not derived from a cancer cell. cfDNA that is not derived from cancer cells in a cfDNA sample may be derived from blood cells, for example white blood cells (leukocyte), and other non- cancerous tissues. The fraction may be expressed as a percentage (e.g. 20%) or a fraction of 1 (e.g. 0.2).

[0063] As used herein, the term "genomic location" refers to the location of a region of a genome, e.g. the genome of a subject, for example a human. It may be referred to using the coordinates of the start position and end position of the location in a specific chromosome. For a human subject a genomic location is suitably described by reference to a reference genome (for example, a digital nucleic acid sequence database, assembled from a representative example of a species' set of genes). For example, for a human subject, with reference to the human reference genome GRCh37 (also referred to as Human Genome 19 (hgl9)) or human reference genome GRCh38 (also referred to as Human Genome 38 (hg38)). For the present inventions, preferably the reference genome is human reference genome GRCh37 (also known as hgl9). As such, a genomic location for a human may be described using the coordinates of the start position and end position of the location in a specific chromosome, with reference to the Genome Reference Consortium Human Build 37 (GRCh37) (also referred to as Human Genome 19 (hgl9)).

[0064] The term "staging" as used herein refers to the process of determining the extent a cancer has developed by growing and / or spreading in a subject. Typically, classification of a cancer involves assigning the cancer a number from I to IV, wherein I is an isolated cancer and IV is a metastatic cancer that has spread to other parts of the body, distal to the primary cancer site.

[0065] The term "classification" as used herein refers to the process of classifying the type of cancer in a subject by determining the type of tissue in a subject from which a cancer originates and / or by determining the primary site in the body wherein the cancer first developed. For example, a cancer classified based on the type of tissue in the subject from which a cancer originates may be classified as a carcinoma (for example a colon, prostate or bladder carcinoma), sarcoma, myeloma, leukemia, lymphoma or mixed type (for example, adenosquamous carcinoma, mixed mesodermal tumor, carcinosarcoma, teratocarcinoma).

[0066] The term "screening" as used herein refers to the process of checking for a cancer in a subject not known to have cancer. For example, checking for a copy number change or aberration within gene-regions commonly associated with a particular cancer type.

[0067] The term "prognostication" as used herein refers to the process of estimating / predicting the likely course and outcome of a cancer, and / or chance that a subject has of recovering from a cancer. For example, a subject whose cancer is not regressing in response to certain cancer treatment(s), as determined, for example by using a method of the present invention, may be considered to have a poor prognosis.

[0068] The term "stratification" as used herein refers to the process of stratifying a subject into a molecular group based on the molecular profile the subject's cancer and the predicted response of the subject to a certain treatment. For example, stratifying by DNA repair gene associated alteration, such as BRCA1 / 2 alteration, for predicted response to treatment with a PARP inhibitor or other drugs targeting DNA repair.

[0069] As used herein, a "subject" refers to an animal, including mammals such as humans. Preferably, the subject is a human subject. As used herein, an "individual" can be a subject. As used herein, a "patient" refers to a human subject. In one embodiment, the subject is known or suspected to have a cancer (for example prostate cancer), and / or is known or suspected to have a risk of developing cancer (for example prostate cancer), or is known to have cancer and is known or suspected to have metastatic cancer (for example metastatic prostate cancer) or to have a risk of developing metastatic cancer (for example metastatic prostate cancer). In some embodiments, the subject is a subject who has been identified as being at risk of developing a cancer, in particular at risk of developing a prostate cancer. A "subject" may be male or female. In certain embodiments, the subject is male (for example wherein the subject is known or suspected to have prostate cancer / have a risk of developing prostate cancer). As used herein, a "healthy subject" or "healthy volunteer" refers to a subject that has not been diagnosed with a type of cancer (for example prostate cancer), and preferably has not been diagnosed with any type of cancer. Thus, for example, for a method relating to prostate cancer, a "healthy subject" or "healthy volunteer" has no prostate cancer, and preferably no other type of cancer. Preferably, a healthy subject has not been diagnosed with a type of cancer (for example prostate cancer), and is not suspected of having a type of cancer, and suitably has not been diagnosed with any type of cancer (for example prostate cancer), and is not suspected of having any type of cancer.

[0070] As used herein, the term "nucleic acid" means a single or double-stranded deoxyribonucleotide or ribonucleotide polymer of any length, and include as non-limiting examples, coding and non-coding sequences of a gene, sense and antisense sequences, exons, introns, genomic DNA, cDNA, pre-mRNA, mRNA, rRNA, siRNA, miRNA, tRNA, ribozymes, recombinant polynucleotides, isolated and purified naturally occurring DNA or RNA sequences, synthetic RNA and DNA sequences, nucleic acid probes, primers, and fragments thereof. Reference to a polynucleotide(s) is to be similarly understood.

[0071] As used herein, the term "oligonucleotide(s)" refers to nucleic acid molecules that usually comprise between 5 and 100 contiguous bases, for example between 5-10, 5-20, 10-20, 10- 50, 15-50,15-100, 20-50, or 20-100 contiguous bases. An oligonucleotide may be capable of hybridising to a target of interest, e.g., a sequence that includes an iSNP of the present invention (e.g. an iSNP as defined in Table 1 or Table 2). An oligonucleotide for hybridising to a target may comprise at least 5, least 10, at least 15, at least 20, at least 30, at least 40, at least 50 or at least 60 nucleotides. An oligonucleotide can be used as a primer, a probe, included in a microarray, or used in polynucleotide-based identification methods. For example, the oligonucleotide may be a probe that is complementary to, and capable of hybridizes to, a nucleotide sequence of interest. For example, the probe may be capable of hybridizing to a SNP site present in tumor DNA and / or non-tumor DNA obtained from a subject (e.g. capable of hybridizing to a SNP site defined in Table 1 or Table 2).

[0072] As used herein, a "subtype of a cancer" (for example a "subtype of prostate cancer") is a subset of a type of cancer based on characteristics of the cancer cells, and in particular molecular and genetic characteristics of the cells. Different cancer subtypes can have different disease progression and can respond or not respond to different treatments. The subtype of a cancer is, for example, used to assist in planning treatment and determine prognosis of the subject having that cancer subtype. Examples of a subtypes of prostate cancer include hormone sensitive prostate cancer (HSPC) and castration resistant prostate cancer (CRPC).

[0073] Detailed Description of the Invention

[0074] The present invention provides an in vitro method for staging, classification, screening monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of cancer in a subject.

[0075] The in vitro method of the present invention comprises steps i) to iii), as described in further detail below:

[0076] Step i):

[0077] The in vitro method of the invention comprises a step of providing a biological sample obtained from the subject comprising tumor DNA. The biological sample comprising tumor DNA may further comprise non-tumor DNA (for example, non-tumor DNA in a plasma sample or a tissue sample). That is to say, that the biological sample may contain DNA derived from a cancer cell in a subject and DNA derived from a non-cancerous (i.e. healthy) cell in the subject. If the biological sample comprises both tumor DNA and non-tumor DNA, the same sample can be provided as the sample comprising tumor DNA and the biological sample comprising non-tumor DNA.

[0078] Typically, the biological sample is a blood sample (for example a blood sample, plasma sample or a white blood cell sample), urine sample, saliva sample, tissue sample, or cerebral spinal fluid obtained from the subject.

[0079] In certain embodiments, the in vitro method of the invention comprises a step of providing a biological sample obtained from the subject comprising tumor DNA and providing a biological sample obtained from the subject comprising non-tumor DNA. In certain embodiments, the biological sample comprising tumor DNA and the biological sample comprising non-tumor DNA are separate samples. In certain embodiments, the biological sample comprising tumor DNA and the biological sample comprising non-tumor DNA are the same sample, i.e. a sample comprising a mixture of tumor DNA and non-tumor DNA.

[0080] In certain embodiments, the biological sample comprising non-tumor DNA may be a tissue sample from a healthy, non-cancerous organ or tissue within the subject, a saliva sample, a blood sample, or white blood cell sample from a subject. Typically, the biological sample comprising non-tumor DNA is a saliva sample, white blood cell sample, or blood sample from a subject. A white blood cell sample may be obtained from a blood sample from a subject, and in particular, obtained from the buffy coat separated from a blood sample from a subject. The buffy coat may be separated by centrifugation of the blood sample.

[0081] In certain embodiments, the biological sample comprising tumor DNA may be a tissue sample from a tumor within the subject, or it may be a plasma sample comprising ctDNA, or it may be a blood sample from a subject. Typically, the biological sample comprising non- tumor DNA is a plasma sample comprising ctDNA, or a blood sample from a subject. A plasma sample comprising ctDNA may be obtained from a blood sample from a subject. The plasma sample comprising ctDNA may be obtained by separating the plasma from the buffy coat in the blood sample, for example by centrifugation of the blood sample.

[0082] In certain embodiments wherein the method comprises providing a biological sample obtained from the subject comprising tumor DNA and providing a biological sample obtained from the subject comprising non-tumor DNA, the biological sample comprising tumor DNA and the biological sample comprising non-tumor DNA are the same sample. For example, the biological sample provided in step i) is a blood sample (for example a plasma sample), urine sample, tissue sample, or cerebral spinal fluid sample comprising both tumor DNA derived from a cancer cell in the subject and non-tumor DNA derived from a non- cancerous cell in the subject. Typically, the tumor DNA present in a blood sample (for example, a plasma sample) or urine sample is circulating tumor DNA (ctDNA).

[0083] In embodiments wherein the biological sample comprising tumor DNA and the biological sample comprising non-tumor DNA are the same sample, or wherein the sample comprising tumor DNA further comprises non-tumor DNA, and the sample is a blood sample, the sample may be a single blood sample that can be separated into a white blood cell sample (for example obtained from the buffy coat separated from the blood sample) to provide the sample comprising non-tumor DNA, and a plasma sample (for example obtained by separating the plasma from a blood sample) to provide the sample comprising non-tumor DNA. Alternatively, or additionally, the blood sample may be a single plasma sample comprising both tumor and non-tumor DNA. For example, the blood sample may be a single plasma sample comprising ctDNA and non-tumor cfDNA.

[0084] In certain preferred embodiments, the biological sample comprising tumor DNA is a blood sample comprising circulating tumor DNA (ctDNA). The present inventors have found that the method of the invention is especially effective when using a plasma sample comprising ctDNA obtained from a subject. Thus, preferably, the biological sample comprising tumor DNA is a plasma sample comprising ctDNA. More preferably, the blood sample is a plasma sample that comprises, in addition to the ctDNA, non-tumor cell-free DNA (non-tumor cfDNA). In certain embodiments, the biological sample comprising tumor DNA is a blood sample, and the biological sample comprising non-tumor DNA is the same blood sample, and the tumor DNA in the sample is ctDNA present in the plasma of the blood sample, and the non-tumor DNA in the sample is genomic DNA from white blood cells present in the blood sample.

[0085] Typically, the biological sample comprises a plurality of DNA molecules. For example, at least 10,000, at least 50,000, at least 100,000, at least 500,000, at least 1,000,000 (106), at least 5,000,000 (5x 106), at least 10,000,000 (107), at least 100,000,000 (10s), at least 1,000,000,000 (109), 5,000,000,000 (5xl09), at least 10,000,000,000 (1010) or at least 15,000,000,000 (1.5xl010) DNA molecules. Preferably, the biological sample comprises, at least 100,000, at least 500,000, at least 1,000,000 (106), at least 5,000,000 (5xl06), at least 10,000,000 (107), at least 100,000,000 (10s), at least 1,000,000,000 (109), 5,000,000,000 (5xl09), at least 10,000,000,000 (1010) or at least 15,000,000,000 (1.5xlO10) DNA molecules. More preferably, at least 10,000,000 (107), at least 100,000,000 (10s), at least 1,000,000,000 (109) DNA molecules, 5,000,000,000 (5xl09), at least 10,000,000,000 (lxlO10) or at least 15,000,000,000 (1.5xlO10).

[0086] The quantity of DNA molecules in a sample that are tumor DNA molecules is referred to herein as the percentage tumor content (TC) of a sample. That is to say, that TC refers to the percentage of DNA molecules in a sample that are tumor DNA molecules. Suitably, the biological sample comprising tumor DNA provided in step i) has a tumor content of at least about 1%, at least about 2%, at least about 3%, at least about 4%, at least about 5%, at least about 10%, at least about 15%, or at least about 20%. For example, the biological sample comprising tumor DNA may have a tumor content of at least about 2%, at least about 3%, at least about 4%, or at least about 5%, at least 7%, at least 10%, at least 15%, at least 20%, at least 30%, at least 40%, at least 50%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90%, or 100%. Preferably, the biological sample comprising tumor DNA provided in step i) has a tumor content of at least about 10%, or at least 15% or at least about 20%.

[0087] In certain embodiments, the biological sample comprises cfDNA, and at least about 1%, at least about 2%, at least about 3%, at least about 4%, at least about 5%, at least about 10%, at least about 15% or at least about 20% of the total number of cfDNA molecules in the sample are ctDNA molecules; for example wherein the biological sample comprises cfDNA and at least about 20% of the total number of cfDNA molecules in the sample are ctDNA molecules.

[0088] The present inventors have found that the present method is surprising sensitive even when the tumor content of the biological sample is low (for example, about 1% to about 5% tumor content). Thus, in certain embodiments, the biological sample provided in step i) has a tumor content of about 1% to about 100%, for example about 2% to about 100%. In certain embodiments, the biological sample provided in step i) has a tumor content of about 1% to about 100%, for example about 2% to about 100%, about 5% to about 100%, about 10% to about 100%, about 15% to about 100% or about 20% to about 100%.

[0089] In embodiments wherein the biological sample comprising tumor DNA is a tissue sample, the tumor DNA must be extracted from the cells present in the tissue sample. The tumor DNA can be isolated from the biological sample using a variety of techniques known in the art.

[0090] In embodiments wherein the biological sample comprising non-tumor DNA is a tissue sample, saliva sample, or white blood cell sample, the non-tumor DNA must be extracted from the cells present in the sample. The non-tumor DNA can be isolated from the biological sample using a variety of techniques known in the art. In certain embodiments, the tumor DNA and / or non-tumor DNA, is amplified before analysis. Amplification techniques are known to those of ordinary skill in the art and include, but are not limited to, cloning, polymerase chain reaction (PCR), polymerase chain reaction of specific alleles (PASA), polymerase chain ligation, nested polymerase chain reaction, and so forth. The preferred amplification technique for use in the present invention is PCR.

[0091] Step ii):

[0092] The method of the present invention comprises a step of ii) determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 and Table 2 in the tumor DNA.

[0093] Table 1 and 2 are provided below, with column 1 of Table 1 defining the target gene-regions and column 1 of Table 2 defining the control gene-regions.

[0094] To determine the allele-specific copy number value for a gene-region (i.e. a target generegion as defined in Table 1 or a control gene-region as defined in Table 2), this can be determined from whole genome sequencing and / or exome data, or from targeted capture panels, for example using methods known in for art. Examples of such methods include PCF SELECT (Orlando F, et al., NAR Cancer. 2022;4(2):zcac016, and in WO2022 / 258975), ASCAT (Van Loo, P., et al., Allele-specific copy number analysis of tumors. PNAS 2010 Sep;107(39): 16910-16915) FACETS (Shen R, Seshan VE. FACETS: allele-specific copy number and clonal heterogeneity analysis tool for high-throughput DNA sequencing. Nucleic Acids Res. 2016 Sep 19;44(16):el31), TITAN (Ha G., et al., TITAN: inference of copy number architectures in clonal cell populations from tumor whole-genome sequence data. Genome Res. 2014 Nov;24(ll):1881-93) and SEQUENZA (Favero, F., et al., Sequenza: allele-specific copy number and mutation profiles from tumor sequencing data, Annals of Oncology, Volume 26, Issue 1, 2015, Pages 64-70).

[0095] Typically, to determine allele-specific copy number values for a gene-region using whole genome sequencing and / or exome data the total copy number calling is measured. Total copy number is inferred from the coverage data from whole-genome or exome sequencing, including the steps of: bin coverage calculation (typically 5k - 500k pair bases, depending on depth of sequencing) in tumor and normal DNA (and optionally bin size estimation and / or tumour content estimation and / or ploidy correction); normalization and GC correction; and segmentation. Allelic imbalance calling is then performed. Allelic imbalance is inferred from the allelic frequencies of heterozygous SNPs in tumor DNA, including the steps of: heterozygous SNPs are called in tumor DNA and normal DNA; SNP normalization; and quantification of allelic disequilibrium. Finally, the allele specific copy number value is determined: the allele specific copy number value is inferred using the total copy number and allelic imbalance to calculate the relative number of copies for the minor and major alleles: estimation of minor allele, and estimation of major allele.

[0096] An exemplary method for determining allele-specific copy number value for a gene-region in the tumor DNA is described in the Examples section, which uses PCF SELECT (Orlando F, et al., NAR Cancer. 2022;4(2):zcac016, and in WO2022 / 258975 (see, in particular the Examples section of WO2022 / 258975), the contents of which are incorporated herein by reference) in combination with CLONETv2 (Prandi D, Demichelis F. Ploidy- and Purity-Adjusted Allele- Specific DNA Analysis Using CLONETv2. Curr Protoc Bioinformatics. 2019;67(l):e81, the contents of which are incorporated herein by reference). PCF SELECT comprises steps ii-a) to ii-e) as defined herein.

[0097] Therefore, in a very preferred embodiment, the method of the invention comprises steps ii- a) to ii-e) described herein (for example, in a very preferred embodiment, the method of the invention comprises one or more (for example, all) of the steps of the PCF SELECT method as described in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016, and in WO2022 / 258975). This is a preferred method for determining allele-specific copy number value as it allows sequencing of gene-regions of interest at high depths of coverage, which allows allele specific copy number values to be quantitated with high fidelity across gene-regions (in particular the gene-regions defined in Table 1 and Table 2), and with excellent reproducibility across samples.

[0098] To determine allele-specific copy number value using PCF SELECT, the decision tree depicted in Figure 8 of WO2022 / 258975 is applied. Briefly, allele-specific copy number value is defined by integrating read-depth estimations and allelic imbalance calls as described in WO2022 / 258975 and in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016. First, a check for the quality of the control samples is performed. Then, the presence of allelic imbalance is assessed and Log2R corrected for ploidy and purity (i.e. ctDNA level / TC) of the sample (Prandi, D. and Demichelis, F. (2019) Ploidy- and Purity-Adjusted Allele-Specific DNA Analysis Using CLONETv2. Curr Protoc Bioinformatics, 67, e81). Note ploidy / purity correction is only applied if uncorrected signal supports the presence of aberration (i.e. uncorrected Log2R > thrLog2, wherein thrLogz is as defined in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016). Moreover, to be conservative if estimated TC < 15% and E(AI)T< 0.2 (i.e. no allelic imbalance detected), the method reports the likely presence of aberration in a gene-region not at an allele-specific level. If estimated TC < 15% and allelic imbalance is identified in the gene-region, the method reports the allelespecific copy number. To obtain the copy number values of the two alleles, cnA and cnB (by design cnA>=cnB) for each gene-region, the following original equations are applied (Prandi, D. and Demichelis, F. (2019) Ploidy- and Purity-Adjusted Allele-Specific DNA Analysis Using CLONETv2. Curr Protoc Bioinformatics, 67, e81):

[0099] (2 - pT)(pTX 2Log2RP - G) + 2G(1 - pT) cnA =

[0100] (I - G)PT where Log2Rp is the ploidy-corrected Log2R of the gene-region and G is the admixture of the sample (i.e. 1-TC).

[0101] In one especially preferred embodiment, step ii) comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an allele specific copy number aberration (asCNA) (for example, wherein in the tumor DNA one or both alleles of each gene-region has an allele specific copy number aberration (asCNA)).

[0102] To determine the allele-specific copy number value for a gene-region wherein in the tumor DNA at least one allele of the gene-region has an asCNA (i.e. a target gene-region as defined in Table 1, or a control gene-region as defined in Table 2, wherein in the tumor DNA at least one allele of the gene region has an asCNA), it is first necessary to determine if a gene region has an (i.e. one or more) asCNA. To do that it must be determined if each allelic form of the gene-region is the one occurring most frequently in a selected population, or if at least one of the allelic forms of the gene-region has a genetic aberration that is an asCNA, compared to the allelic form of the gene-region that occurs most frequently in a selected population. Examples of types of asCNA include: copy number gain (for example balanced or unbalanced copy number gain), copy number loss (for example homodeletions and hemideletions), and loss of heterozygosity (LOH) events (for example copy number-neutral loss of heterozygosity).

[0103] To determine the presence of allele-specific copy number aberrations (asCNAs), it is first necessary to determine the allelic imbalance for the gene-regions (i.e. the target generegions and / or control gene-regions), in the tumor DNA, and to determine the copy number for each gene-region in the tumor DNA.

[0104] Typically, to determine allelic imbalance, it is necessary to first determine a reference model using a set of control samples. Control samples may comprise genomic DNA from healthy subjects and / or healthy cells, for example white blood cells. Further examples of suitable control samples include: a cfDNA sample from a healthy subject, for example a healthy age and / or gender matched subject; a tissue sample from a healthy subject, for example a prostate tissue sample from a healthy subject; a characterized genome sequence of a white blood cell; a characterized genome sequence of a non-cancerous cell, such as a non-cancerous prostate cell.

[0105] An exemplary method for generating a reference model using a control sample is described in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016, and in WO2022 / 258975 (see, in particular the Examples section of WO2022 / 258975), the contents of which are incorporated herein by reference. Allelic imbalance may be determined for each gene-region in the tumor DNA and non-tumor DNA for a subject. For example, this may be achieved by reference to a reference model. Using a reference model can further improve the sensitivity of the methods of the invention. A reference model may be a collection of statistics obtained from two or more control samples (for example 2 or more, 3 or more, 4 or more, 5 or more, 8 or more, 10 or more, 15 or more, 20 or more, 30 or more, 40 or more, or more than 50 samples), in particular two or more (for example 2 or more, 3 or more, 4 or more, 5 or more, 8 or more, 10 or more, 15 or more, 20 or more, 30 or more, 40 or more, or more than 50 samples) control samples that do not comprise tumor DNA. For example, to build a reference model two or more control samples comprising non-tumor DNA and not comprising tumor DNA may be used. Biological samples comprising non-tumor DNA for different subjects may be used as a sample for the reference model if each biological sample does not comprise tumor DNA (for example if each biological sample comprising non-tumor DNA is a WBC sample). Additionally, or alternatively, one or more control samples as described above may be used to build the reference model. The control samples are sequenced. Preferably, control samples for use in building a reference model are sequenced at the same institution and / or sequenced using the same sequencer. The sequences of the samples are analysed to provide a collection of statistics including local (per each single SNP) and global (aggregating SNPs by similar local coverages observed in control samples used for model building) metrics of SNPs. For each control sample that is used to build the model, only SNPs that are informative (i.e. heterozygous SNPs that are present in a gene-region in the genome of the subject that provided the control sample) are used to compute the statistics. When testing for the presence of imbalance in a biological sample comprising tumor DNA from a subject, the statistics for each SNP that is informative for the subject are extracted and used to generate allelic fraction (AF) distributions mimicking distributions that could be extracted from a pure non-tumor DNA sample and from a mix of non-tumor and tumor DNA at different proportions (for example 0% and 100%, 1% and 99%, 2% and 98%, 3% and 97%, N% and (100-N)% (wherein N is each integer between 3 and 97), 97% and 3%, 98% and 2%, 99% and 1% and 100 and 0%, of non-tumor and tumor DNA respectively). When comparing the observed iSNPs AF distribution from a biological sample comprising tumor DNA against reference model derived distributions, differences between the AF distribution in the biological sample and the model derived distributions indicate the presence of allele imbalance tumor and, if allele imbalance is present, the quantity of the allele imbalance.

[0106] In certain embodiments, the reference model may optionally determine thrLOg2 as described in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016, and in WO2022 / 258975. thrLOg2 may be used to determine if ploidy / purity correction is required in certain preferred methods of the invention (i.e. methods where ploidy / purity correction is applied if uncorrected signal supports the presence of aberration (i.e.

[0107] An exemplary method for determining allelic imbalance in the tumor DNA with reference to a reference model is described in the Examples section. An exemplary method for determining allelic imbalance in the tumor DNA without reference to a reference model is also described in the Examples section.

[0108] The copy number of a gene-region in the tumor DNA or non-tumor DNA may be determined, for example, by integrating the read-depth estimations and allelic imbalance calls. Methods for determining the focal copy number of parts of a gene-region are described herein. Methods for determining the focal copy number of parts of a gene-region are also known in the art, for example DNAcopy (10.18129 / B9.bioc.DNAcopy) and the methods reported in Zare, F., et al. BMC Bioinformatics 18, 286 (2017).

[0109] Allele-specific copy number aberrations (asCNAs) are alterations in the total copy number (i.e. the allele-specific copy number) of a gene-region, or part thereof, and the specific number of copies of each chromosome. More specifically, allele-specific copy number aberrations (asCNAs) may be defined as alterations in the allele-specific copy number of a gene-region, or part thereof, relative to the expected number of copies of that gene-region, or part thereof, derived from each parental chromosome (e.g. as determined from a reference model generated from a control sample, as described herein above). Types of asCNA include: copy number gain (for example balanced or unbalanced copy number gain), copy number loss (for example homodeletions and hemideletions), and loss of heterozygosity (LOH) events (for example copy number-neutral loss of heterozygosity). The asCNA status for each gene-region may be determined by integrating read-depth estimation for each gene-region and allelic imbalance status for each gene-region. Allele-specific copy number value and asCNA status may be corrected for the ploidy and purity of the tumor DNA in the biological sample. Methods for correcting the allele-specific copy number value and asCNA for ploidy and purity are known in the art. For example, CLONETv2 (Prandi et al., 2019, Curr Protoc Bioinformatics. Sep;67(l):e81)), FACETS (PMID: 27270079), ASCAT (PMID: 20837533), Sequenza (PMID: 25319062), or CNVkit (PMID: 27100738). In exemplary embodiments, the method described by Prandi et al., 2019 (Curr Protoc Bioinformatics. 2019 Sep;67(l):e81) is used (i.e. by using the CLONETv2 algorithm).

[0110] Step ii) of the method of the present invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 and Table 2 in the tumor DNA. Typically, step ii) comprises determining the allele-specific copy number value of each allele for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all gene-regions defined in Table 1 and Table 2. In certain preferred embodiments, step ii) comprises determining the allelespecific copy number value of each allele for each of at least 10 gene-regions defined in Table 1 and Table 2 (for example 10, 15, 20, 30, 40, 50, 60, 70 or all gene-regions defined in Table 1 and Table 2). In such embodiments, preferably in the tumor DNA at least one allele of each gene-region has an allele specific copy number aberration (asCNA)).

[0111] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for each of at least 5 target gene-regions defined in Table 1 and at least 3 control gene-regions defined in Table 2 (for example wherein in the tumor DNA at least one allele of each target gene-region and control gene-region has an allele specific copy number aberration (asCNA)).

[0112] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for each of: at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0113] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for each of: at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0114] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for each of: at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0115] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for each of: at least 5 (for example at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all) gene-regions selected from the group consisting of as AKT1, APC, AR, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRIP1, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CH DI, CHEK2, CTNNB1, CYLD, ERCC2, ERCC3, ERG_TMPRSS2, FANCA, FANCC, FANCD2, FANCG, FBXW7, FOXA1, FOXP1, GNAS, HDAC2, HSD3B1, IDH1, IDH2, KDM6A, KMT2C, KMT2D, KRAS, MDM2, MDM4, MED12, MET, MLH1, MSH2, MSH6, MYC, MYCN, NCOA2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RYBP, SMARCA1, SPOP, TP53, ZBTB16, ZFHX3, ATG14, ATXN7, C9orf47, CST7, DRD1, ENPEP, FAM183B, FCER1A, GRHPR, HDAC8, IL1RL2, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NIT2, OR3A3, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, and ZBTB9d as defined in Table 1 and Table 2.

[0116] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for each of: at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of as AKT1, APC, AR, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRI Pl, CCND1, CDK12, CDK4, CDK6, CD KN IB, CD KN 2 A, CH DI, CHEK2, CTNNB1, CYLD, ERCC2, ERCC3, ERG_TMPRSS2, FANCA, FANCC, FANCD2, FANCG, FBXW7, F0XA1, F0XP1, GNAS, HDAC2, HSD3B1, IDH1, IDH2, KDM6A, KMT2C, KMT2D, KRAS, MDM2, MDM4, MED12, MET, MLH1, MSH2, MSH6, MYC, MYCN, NC0A2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RYBP, SMARCA1, SPOP, TP53, ZBTB16, and ZFHX3; and / or at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of as ATG14, ATXN7, C9orf47, CST7, DRD1, ENPEP, FAM183B, FCER1A, GRHPR, HDAC8, IL1RL2, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NIT2, OR3A3, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, and ZBTB9 defined in Table 2.

[0117] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for each of: at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of as AKT1, APC, AR, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRI Pl, CCND1, CDK12, CDK4, CDK6, CD KN IB, CD KN 2 A, CH DI, CHEK2, CTNNB1, CYLD, ERCC2, ERCC3, ERG_TMPRSS2, FANCA, FANCC, FANCD2, FANCG, FBXW7, FOXA1, FOXP1, GNAS, HDAC2, HSD3B1, IDH1, IDH2, KDM6A, KMT2C, KMT2D, KRAS, MDM2, MDM4, MED12, MET, MLH1, MSH2, MSH6, MYC, MYCN, NCOA2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RYBP, SMARCA1, SPOP, TP53, ZBTB16, and ZFHX3; and optionally at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of as ATG14, ATXN7, C9orf47, CST7, DRD1, ENPEP, FAM183B, FCER1A, GRHPR, HDAC8, IL1RL2, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NIT2, OR3A3, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, and ZBTB9 defined in Table 2.

[0118] In certain preferred embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of as AKT1, APC, AR, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRI Pl, CCND1, CDK12, CDK4, CDK6, CD KN IB, CD KN 2 A, CH DI, CHEK2, CTNNB1, CYLD, ERCC2, ERCC3, ERG_TMPRSS2, FANCA, FANCC, FANCD2, FANCG, FBXW7, FOXA1, FOXP1, GNAS, HDAC2, HSD3B1, IDH1, IDH2, KDM6A, KMT2C, KMT2D, KRAS, MDM2, MDM4, MED12, MET, MLH1, MSH2, MSH6, MYC, MYCN, NCOA2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RYBP, SMARCA1, SPOP, TP53, ZBTB16, and ZFHX3; and optionally at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of as ATG14, ATXN7, C9orf47, CST7, DRD1, ENPEP, FAM183B, FCER1A, GRHPR, HDAC8, IL1RL2, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NIT2, OR3A3, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, and ZBTB9 defined in Table 2.

[0119] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4 or 5; typically at least 2, at least 3 or at least 4), at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the target gene-region selected from the group consisting of AKT1, APC, AR, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRIP1, CCND1, CDK12, CDK4, CDK6, CD KN IB, CDKN2A, CH DI, CHEK2, CTNNB1, CYLD, ERCC2, ERCC3, ERG_TMPRSS2, FANCA, FANCC, FANCD2, FANCG, FBXW7, FOXA1, FOXP1, GNAS, HDAC2, HSD3B1, IDH1, IDH2, KDM6A, KMT2C, KMT2D, KRAS, MDM2, MDM4, MED12, MET, MLH1, MSH2, MSH6, MYC, MYCN, NCOA2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RYBP, SMARCA1, SPOP, TP53, ZBTB16, and ZFHX3; and / or at least one (for example 1, 2, 3, 4 or 5; typically at least 2, at least 3 or at least 4), at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of as ATG14, ATXN7, C9orf47, CST7, DRD1, ENPEP, FAM183B, FCER1A, GRHPR, HDAC8, IL1RL2, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NIT2, OR3A3, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, and ZBTB9 defined in Table 2.

[0120] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4 or 5; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of F0XA1, FOXP1, HSD3B1, NC0A2 and ZBTB16 as defined in Table 1.

[0121] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15 or 17; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 as defined in Table 1.

[0122] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4, 5, 6, 7 or 8; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN as defined in Table 1.

[0123] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4, 5, 6, 7 or 8; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of ARID1A, CHD1, KDM6A, MED12, SMARCA1, KMT2C, KMT2D and RYBP as defined in Table 1.

[0124] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4, 5, 6, 8, 10, 12, 15, 20 or 22; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1.

[0125] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4, 5, 6, 8, 10, or 12; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GN AS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1.

[0126] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, or 3; typically at least 2) target generegion selected from the group consisting of APC, CTNNB1 and RNF43 as defined in Table 1. In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one (for example 1, 2, 3, 4, 5, or 6; typically at least 2, at least 3, at least 4, at least 5 or 6) target gene-region selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1. In certain embodiments, preferably step ii-a) comprises detecting at least 3 of the target gene-regions selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1. More preferably, step ii) comprises determining the allele-specific copy number value of each allele for at least BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1.

[0127] In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least one target gene-region selected from the group consisting of F0XA1, FOXP1, HSD3B1, NC0A2 and ZBTB16; and / or at least one target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53; and / or at least one target gene-region selected from the group consisting of ARID1A, CHD1, KMT2C, KMT2D and RYB; and / or at least one target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C; and / or at least one target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3; and / or at least one target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN; and / or at least one target gene-region selected from the group consisting of APC, CTNNB1 and RNF43; and / or at least one target gene-region selected from the group consisting of PIK3CB and RAD51B; and / or at least one target gene-region selected from the group consisting of MYC, AR, NC0A2, NKX3-1, PTEN, MDM4 and BRIP1; and / or at least one target gene-region selected from the group consisting of MYC, NCOA2, NKX3-1, MDM4, BRIP1, AURKA, AR, PTEN, PIK3CB and TP53; and / or at least one target gene-region selected from the group consisting of TP53, AR and ARID1A ; and / or at least one target gene-region selected from the group consisting of TP53, AR, F0XA1 ARID1A, APC, BRCA2 and MED12 ; and / or at least one target gene-region selected from the group consisting of CHEK2 and / or HDAC2. In certain embodiments, step ii) comprises determining the allele-specific copy number value of each allele for at least two, at least three or at least four target gene-region selected from the group consisting of F0XA1, FOXP1, HSD3B1, NC0A2 and ZBTB16; and / or at least two, at least three or at least four target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ARID1A, CHD1, KMT2C, KMT2D and RYB; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C; and / or at least two, at least three or at least four target generegion selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3; and / or at least two, at least three or at least four target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN; and / or at least one, at least two or each target gene-region selected from the group consisting of APC, CTNNB1 and RNF43; and / or each target generegion selected from the group consisting of PIK3CB and RAD51B; and / or at least two, at least three or at least four target gene-region selected from the group consisting of MYC, AR, NC0A2, NKX3-1, PTEN, MDM4 and BRIP1; and / or at least two, at least three or at least four target gene-region selected from the group consisting of MYC, NC0A2, NKX3-1, MDM4, BRIP1, AURKA, AR, PTEN, PIK3CB and TP53; and / or at least two or each target gene-region selected from the group consisting of TP53, AR and ARID1A ; and / or at least two, at least three or at least four target gene-region selected from the group consisting of TP53, AR, F0XA1 ARID1A, APC, BRCA2 and MED12 ; and / or at each target gene-region selected from the group consisting of CHEK2 and / or HDAC2.

[0128] Step ii) of the in vitro method of the present invention preferably comprises steps ii-a) to ii- d), and optionally also step ii-e), as described in further detail below:

[0129] Step ii-a):

[0130] The method of the present invention preferably comprises step ii-a) of detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 or Table 2 for each of at least 5 generegions defined in Table 1 and Table 2.

[0131] In certain embodiments, step ii-a) comprises detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 or Table 2 for each of at least 5 generegions defined in Table 1 and Table 2, wherein in the tumor DNA at least one allele of each gene-region has an allele specific copy number aberration (asCNA).

[0132] In one preferred embodiment, step ii-a) comprises detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 for each of at least 5 target generegions defined in Table 1, and optionally at least 5% of the SNP loci defined in Table 2 for each of at least 3 control gene-regions defined in Table 2.

[0133] In certain embodiments, step ii-a) comprises detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 for each of at least 5 target generegions defined in Table 1, wherein in the tumor DNA at least one allele of each target gene-region has an allele specific copy number aberration (asCNA), and optionally at least 5% of the SNP loci defined in Table 2 for each of at least 3 control gene-regions defined in Table 2, wherein in the tumor DNA at least one allele of each control gene-region has an allele specific copy number aberration (asCNA).

[0134] Tables 1 and 2 are provided below. The genomic locations recited in Tables 1 and 2 are locations with reference to the human reference genome GRCh37 (also known as hgl9). The SNP loci defined in Tables 1 and 2 are collectively referred to herein as the "Example 1 SNP panel". Table 1: target gene-regions and SNPs. tgene-region loci are provided with reference to the Genome Reference Consortium Human Build 37 (GRCh37), which is herein also referred to as "hgl9". The loci are provide in the following form: X:Y-Z, wherein X is the chromosome name, Y is the start position of the gene-region, and Z is the end position of the gene-region.

[0135] The gene-regions recited above in Table 1 are gene-regions that contain genes mutated in prostate cancer and / or altered in signalling pathways known or suspected of being druggable pathways for treating a prostate cancer. The gene-regions defined in Table 1 are hereinafter referred as "target gene-regions".

[0136] Table 2: Control gene-regions and SNPs tgene-region loci are provided with reference to the Genome Reference Consortium Human Build 37 (GRCh37), which is herein also referred to as "hgl9". The loci are provide in the following form: X:Y-Z, wherein X is the chromosome name, Y is the start position of the gene-region, and Z is the end position of the gene-region.

[0137] The gene-regions recited above in Table 2 are gene-regions that contain genes that are known to not be commonly mutated in a cancer. Table 2 also includes gene-regions that contain the genes, UGT2B17 and ZBTB9. UGT2B17 and ZBTB9 are known to exhibit high frequency germline copy number losses. The gene-regions defined in Table 2 are hereinafter referred to as the "control gene-regions".

[0138] Tables 1 and 2 recite the SNPs within each gene-region defined in Tables 1 and 2. The present inventors selected the SNPs recited in Tables 1 and 2 after discovering that selecting high MAF SNPs in the bespoke gene-regions of the selected genes lead to accurate and sensitive results for establishing allele-specific copy number values for the gene-regions and control regions (as well as accurate and sensitive results for establishing allelic imbalance and copy number loss) in samples from subjects having cancer. The inventors determined that the SNPs of Tables 1 and 2 have a high MAF, and a high MAF across subjects of different ethnicities, using the 1000 Genomes Project Genotype Data (release 20130502; PMID: 26432245). The SNPs recited in Tables 1 and 2 are located within the exonic regions, intronic regions or intergenic flanking regions of the gene-regions defined in Table 1 or 2.

[0139] In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4 or 5; typically at least 2, at least 3 or at least 4) at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the target gene-region selected from the group consisting of AKT1, APC, AR, ARID1A, ASXL1, ATM, ATR, AURKA, BRAF, BRCA1, BRCA2, BRIP1, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CHD1, CHEK2, CTNNB1, CYLD, ERCC2, ERCC3, ERG_TMPRSS2, FANCA, FANCC, FANCD2, FANCG, FBXW7, FOXA1, FOXP1, GN AS, HDAC2, HSD3B1, IDH1, IDH2, KDM6A, KMT2C, KMT2D, KRAS, MDM2, MDM4, MED12, MET, MLH1, MSH2, MSH6, MYC, MYCN, NCOA2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RYBP, SMARCA1, SPOP, TP53, ZBTB16, and ZFHX3; and / or detecting at least one (for example 1, 2, 3, 4 or 5; typically at least 2, at least 3 or at least 4) at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions selected from the group consisting of ATG14, ATXN7, C9orf47, CST7, DRD1, ENPEP, FAM183B, FCER1A, GRHPR, HDAC8, IL1RL2, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NIT2, OR3A3, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, and ZBTB9 as defined in Table 2.

[0140] In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4 or 5; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16 as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with the function in the androgen (receptor) signalling pathway.

[0141] In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15 or 17; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CD KN 2 A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with cell cycle dysfunction.

[0142] In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4, 5, 6, 7 or 8; typically at least 2, at least 3 or at least 4) target generegion selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with with the phosphoinositide 3-kinase (PI3K) signalling pathway.

[0143] In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4, 5, 6, 7 or 8; typically at least 2, at least 3 or at least 4) target generegion selected from the group consisting of ARID1A, CHD1, KDM6A, MED12, SMARCA1, KMT2C, KMT2D and RYBP as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with chromatic remodeling dysfunction.

[0144] In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4, 5, 6, 8, 10, 12, 15, 20 or 22; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with DNA repair dysfunction.

[0145] In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4, 5, 6, 8, 10, or 12; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1. Genetic aberrations in such gene-regions are known to be associated with prostate cancer, although their precise role in the development and / or progression of prostate cancer of a subject are currently unknown. In certain embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, or 3; typically at least 2) target gene-region selected from the group consisting of APC, CTNNB1 and RNF43 as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected to dysregulate the Wnt signalling pathway.

[0146] In certain preferred embodiments, step ii-a) of the present method comprises detecting at least one (for example 1, 2, 3, 4, 5, or 6; typically at least 2, at least 3, at least 4, at least 5 or 6) target gene-region selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1. In certain embodiments, preferably step ii-a) of comprises detecting at least 3 of the target gene-regions selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1. More preferably, step ii-a) of the present method comprises detecting the gene-regions of at least BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1.

[0147] In certain embodiments, step ii-a) of the present method comprises detecting at least one target gene-region selected from the group consisting of F0XA1, FOXP1, HSD3B1, NC0A2 and ZBTB16; and / or at least one target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53; and / or at least one target gene-region selected from the group consisting of ARI DI A, CHD1, KMT2C, KMT2D and RYB; and / or at least one target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C; and / or at least one target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH2, NFE2L2, NKX3- 1, RUNX1, SPOP and ZFHX3; and / or at least one target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN; and / or at least one target gene-region selected from the group consisting of APC, CTNNB1 and RNF43; and / or at least one target gene-region selected from the group consisting of PIK3CB and RAD51B; and / or at least one target gene-region selected from the group consisting of MYC, AR, NC0A2, NKX3-1, PTEN, MDM4 and BRIP1; and / or at least one target gene-region selected from the group consisting of MYC, NCOA2, NKX3-1, MDM4, BRIP1, AURKA, AR, PTEN, PIK3CB and TP53; and / or at least one target gene-region selected from the group consisting of TP53, AR and ARID1A; and / or at least one target gene-region selected from the group consisting of TP53, AR, F0XA1 ARID1A, APC, BRCA2 and MED12 ; and / or at least one target gene-region selected from the group consisting of CHEK2 and / or HDAC2.

[0148] In certain embodiments, step ii-a) of the present method comprises detecting at least two, at least three or at least four target gene-region selected from the group consisting of F0XA1, FOXP1, HSD3B1, NC0A2 and ZBTB16; and / or at least two, at least three or at least four target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ARI DI A, CHD1, KMT2C, KMT2D and RYB; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GN AS, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3; and / or at least two, at least three or at least four target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN; and / or at least one, at least two or each target gene-region selected from the group consisting of APC, CTNNB1 and RNF43; and / or each target gene-region selected from the group consisting of PIK3CB and RAD51B; and / or at least two, at least three or at least four target gene-region selected from the group consisting of MYC, AR, NC0A2, NKX3-1, PTEN, MDM4 and BRIP1; and / or at least two, at least three or at least four target gene-region selected from the group consisting of MYC, NC0A2, NKX3-1, MDM4, BRIP1, AURKA, AR, PTEN, PIK3CB and TP53; and / or at least two or each target gene-region selected from the group consisting of TP53, AR and ARID1A ; and / or at least two, at least three or at least four target gene-region selected from the group consisting of TP53, AR, F0XA1 ARID1A, APC, BRCA2 and MED12 ; and / or at each target gene-region selected from the group consisting of CHEK2 and / or HDAC2.

[0149] In certain embodiments, step ii-a) comprises detecting the presence of SNPs in the nontumor DNA present in a biological sample at: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1 (for example wherein in the tumor DNA at least one allele of each target gene-region has an allele specific copy number aberration (asCNA)); and / or at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5 control gene-regions defined in Table 2 (for example wherein in the tumor DNA at least one allele of each control gene-region has an allele specific copy number aberration (asCNA)).

[0150] In certain embodiments, step ii-a) comprises detecting the presence of SNPs in the nontumor DNA present in a biological sample at: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1 (for example wherein in the tumor DNA at least one allele of each target gene-region has an allele specific copy number aberration (asCNA)); and optionally at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5 control gene-regions defined in Table 2 (for example wherein in the tumor DNA at least one allele of each control gene-region has an allele specific copy number aberration (asCNA)).

[0151] In certain embodiments, step ii-a) comprises detecting the presence of SNPs in the nontumor DNA present in a biological sample at: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1; and optionally at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5 control gene-regions defined in Table 2.

[0152] In one preferred embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA present in a biological sample at: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1; and / or at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5 control gene-regions defined in Table 2.

[0153] In one preferred embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA present in a biological sample at: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1; and optionally at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5 control gene-regions defined in Table 2.

[0154] In another preferred embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA present in a biological sample at: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1; and / or at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5 control gene-regions defined in Table 2.

[0155] In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 5% of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2. In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 5% of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0156] In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0157] In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0158] In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0159] In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control generegions defined in Table 2.

[0160] In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0161] In one preferred embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control generegions defined in Table 2.

[0162] Typically, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at about 10 to all of the SNP loci defined in Table 1 a gene-region. In one embodiment, step ii) comprises detecting the presence of SNPs in the non-tumor DNA at least 30 of the SNP loci defined in Table 1 a gene-region. In one preferred embodiment, step ii) comprises detecting the presence of SNPs in the non-tumor DNA at least 60 of the SNP loci defined in Table 1 a gene-region. In one preferred embodiment, step ii) comprises detecting the presence of SNPs in the non-tumor DNA at least 90 of the SNP loci defined in Table 1 a gene-region.

[0163] In one embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 30, at least 60, or at least 90 of the SNP loci defined in Table 1 for each of at least 5 of the target gene-regions defined in Table 1; and / or and at least 30, at least 60, or at least 90 of the SNP loci defined in Table 2 for each of at least 5, control gene-regions defined in Table 2.

[0164] In one embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 30, at least 60, or at least 90 of the SNP loci defined in Table 1 for each of at least 5 of the target gene-regions defined in Table 1; and optionally at least 30, at least 60, or at least 90 of the SNP loci defined in Table 2 for each of at least 5, control gene-regions defined in Table 2.

[0165] Typically, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at about 10 to all of the SNP loci defined in Table 1 for each of at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1. For example, depending on the number of SNPs in a gene region, from 10 up to 500, 10 up to 400, 30 up to 400, 30 up to 300, 30 up to 200, or 30 up to 100 of the SNP loci for each of at least 30, at least 60, at least 90, or all of the target gene-regions defined in Table 1 may be detected in the non-tumor DNA. The present inventors have found that the method of the present invention is especially effective and informative about the asCNAs present in the tumor DNA of a sample when at least 30, at least 60, at least 90 or at least 100 of the SNP loci defined in Table 1 are detected for each of at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1 (and in particular when at least 90 or at least 100 of the SNP loci defined in Table 1 are detected for each of at least 10, at least 25, at least 30, or all of the target gene-regions defined in Table 1).

[0166] In one embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 30, at least 60, at least 90, or at least 100 of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1. In certain preferred embodiments, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at target gene-regions and at control gene-regions. For example, step ii- a) may further comprise detecting the presence of SNPs in the genomic non-tumor DNA at: at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80% of the SNP loci defined in Table 2 for each of at least 10, at least 20, at least 30, or all of the control gene-regions defined in Table 2.

[0167] In embodiments wherein step ii-a) comprises detecting the presence of SNPs in the non- tumor DNA at control gene-regions, typically the step also comprises detecting the presence of SNPs in the non-tumor DNA at about 10 to all of the SNP loci defined in Table 2 for each of at least 10, at least 25, at least 50, or all of the control gene-regions defined in Table 2. For example, , depending on the number of SNPs in a gene region, from 10 up to 500, 10 up to 400, 30 up to 400, 30 up to 300, 30 up to 200, or 30 up to 100 of the SNP loci for each of at least 10, at least 25, at least 30, or all of the control gene-regions defined in Table 2 may be detected in the non-tumor DNA. The present inventors have found that the method of the present invention is especially effective and informative about the asCNAs present in the tumor DNA of a sample when at least 30, at least 60, at least 90 or at least 100 of the SNP loci defined in Table 2 are detected for each of at least 10, at least 25, at least 30, or all of the control gene-regions defined in Table 2 (and in particular when at least 90 or at least 100 of the SNP loci defined in Table 1 are detected for each of at least 10, at least 25, at least 30, or all of the control gene-regions defined in Table 2).

[0168] In one embodiment, step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 30, at least 60, at least 90, or at least 100 of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 30, at least 60, at least 90, or at least 100 of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0169] In certain embodiments, step ii-a) comprises a step of providing a set of probes, wherein said set of probes is capable of specifically hybridizing to: at least 5% of the SNP loci defined in Table 1 for each of at least 5 target generegions defined in Table 1, and / or at least 5% of the SNP loci defined in Table 2 for each of at least 3 control generegions defined in Table 2.

[0170] In certain embodiments, step ii-a) comprises a step of providing a set of probes, wherein said set of probes is capable of specifically hybridizing to: at least 5% of the SNP loci defined in Table 1 for each of at least 5 target generegions defined in Table 1, and optionally at least 5% of the SNP loci defined in Table 2 for each of at least 3 control gene-regions defined in Table 2.

[0171] Preferably, each probe in the set of probes is an oligonucleotide probe that is complementary to, and capable of hybridizing to, one or more SNP loci defined in Table 1 or 2. More preferably, each probe is complementary to only one SNP loci defined in Table 1 or 2. In certain embodiments, step ii-a) comprises a step of providing a set of probes, wherein said set of probes is capable of specifically hybridizing to any embodiment or combination of embodiments described above, i.e. capable of specifically hybridizing to a % or number of SNP loci defined in Table 1 for target gene-regions recited above and / or a number of target gene-regions defined in Table 1 recited above; and / or a % or number of SNP loci defined in Table 2 for control gene-regions recited above and / or a number of control gene-regions defined in Table 2 recited above.

[0172] For example, step ii-a) comprises a step of providing a set of probes, wherein said set of probes is capable of specifically hybridizing to at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0173] In certain preferred embodiments, step ii-a) comprises detecting the presence of at least one SNP in the intronic region of a gene-region and / or at least one SNP in the flanking region of a gene-region.

[0174] In certain preferred embodiments, step ii-a) comprises detecting the presence of at least one SNP in the intronic region and at least one SNP in the flanking regions of a gene-region.

[0175] For example, step ii-a) comprises detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1, wherein at least one SNP locus for each target gene region is in the intronic region of a gene-region, and / or at least one SNP locus for each target gene-region is in the flanking regions of a gene-region; and optionally (or, and / or) at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2, wherein at least one SNP locus for each control gene region is in the intronic region of a gene-region, and / or at least one SNP locus for each control gene-region is in the flanking regions of a gene-region.

[0176] In certain preferred embodiments, step ii-a) comprises detecting the presence of at least 10%, at least 20%, at least 30%, at least 50%, at least 75% or at least 90% of SNP in the intronic region of a gene-region and / or at least 10%, at least 20%, at least 30%, at least 50%, at least 75% or at least 90% of SNP in the flanking region of a gene-region.

[0177] In certain preferred embodiments, step ii-a) comprises detecting the presence of at least 10%, at least 20%, at least 30%, at least 50%, at least 75% or at least 90% of SNP in the intronic region of a gene-region and at least 10%, at least 20%, at least 30%, at least 50%, at least 75% or at least 90% of SNP in the flanking region of a gene-region.

[0178] For example, step ii-a) comprises detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1, wherein at least 10%, at least 20%, at least 30%, or at least 50% of SNP loci for each target gene region are in the intronic region of a gene-region, and / or at least 10%, at least 20%, at least 30%, or at least 50% of SNP loci for each target gene region is in the flanking regions of a gene-region; and optionally (or, and / or) at least 5%, at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2, wherein at least 10%, at least 20%, at least 30%, or at least 50% of SNP loci for each control gene region is in the intronic region of a gene-region, and / or at least 10%, at least 20%, at least 30%, or at least 50% of SNP loci for each control gene region is in the flanking regions of a gene-region.

[0179] Step ii-b):

[0180] The method of the present invention preferably comprises a step of identifying which of the SNPs present in the non-tumor DNA are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA for the subject. For the avoidance of doubt, when used herein, the term iSNP refers to a SNP that is heterozygous in the genomic non-tumor DNA or tumor DNA for the subject, and in particular has an allelic fraction (AF) of between about 0.05 to about 0.95 (the AF of a SNP being the number of times the SNP is observed at its genomic locus (i.e. the SNP locus), divided by the total number of times any base is observed at that genomic locus). In one preferred embodiment, the term iSNP refers to a SNP that is heterozygous in the non-tumor DNA or tumor DNA for the subject and has an allelic fraction (AF) of between about 0.2 to about 0.8. The present inventors have found that by selecting iSNPs in step ii-b) of the present method, it is possible to more accurately determine the type of asCNA present in the tumor DNA of the subject.

[0181] Thus, step ii-b) may comprise identifying which of the SNPs detected in step ii-a) are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA or the tumor DNA of the subject, wherein a SNP is heterozygous in the non-tumor DNA or tumor DNA of the subject when it has an allelic fraction (AF) of between about 0.05 to about 0.95 (e.g. between about 0.2 to about 0.8), wherein the AF of a SNP is the number of times the SNP is observed at its genomic locus (i.e. the SNP locus), divided by the total number of times any base is observed at that genomic locus.

[0182] In certain embodiments, step ii-b) comprises the following steps: contacting the biological sample comprising non-tumor and / or tumor DNA with the set of probes under conditions suitable for one or more of the probes to specifically hybridize to a SNP locus; capturing the non-tumor and / or tumor DNA molecules in the biological sample that have hybridized to one or more of the probes;

[0183] Step ii-b) may further comprise a step of determining the nucleotide sequences of the captured DNA molecules and analysing the nucleotide sequences to identify which of the SNPs present in the non-tumor DNA are informative SNPs (iSNPs) for the subject.

[0184] Step ii-c-1):

[0185] The method of the present invention preferably comprises a step of determining the allelic imbalance for each target gene-region, and / or for each control gene-region, of the tumor DNA by reference to the iSNPs for the subject in each gene-region (i.e. step ii-c-1)).

[0186] The method of the present invention also preferably comprises a step of determining the copy number for each target gene-region, and / or for each control gene-region, in the tumor DNA (i.e. step ii-c-2)).

[0187] In certain preferred embodiments, the step ii-c-2) of the method of the invention further comprises a step of estimating the tumor content (TC) of the sample comprising tumor DNA and / or estimating the ploidy of the sample comprising tumor DNA.

[0188] In certain embodiments, the method further comprises a step of detecting in the tumor DNA the presence of somatic and / or germline mutations in the exonic region of one or more target gene-region defined in Table 1. In certain embodiments, the method further comprises a step of detecting in the tumor DNA the presence of somatic and / or germline mutations, for example insertions, deletions and single nucleotide variant mutations, in the exonic region of one or more target gene-region defined in Table 1. Typically, the method further comprises a step of detecting in the tumor DNA the presence of somatic and / or germline single nucleotide variant mutations in the exonic region of one or more target gene-region defined in Table 1.

[0189] The method may further comprise optionally detecting in the tumor DNA the presence of somatic and / or germline mutations in the exonic region of one or more of gene selected from the group consisting of AR, MED12, SMARCA1, IDH1 and KDM6A. For example, the method may further comprise optionally detecting in the tumor DNA the presence of somatic and / or germline gains, losses and / or single nucleotide variant mutations in the exonic region of one or more of gene selected from the group consisting of AR, MED12, SMARCA1, IDH1 and KDM6A. In particular, the method may further comprise optionally detecting in the tumor DNA the presence of somatic and / or germline gains, losses and / or single nucleotide variant mutations in the exonic region of one or more of gene selected from the group consisting of AR, MED12, SMARCA1, and KDM6A; and / or optionally detecting in the tumor DNA the presence of somatic and / or germline single nucleotide variant mutations in the exonic region of IDH1. In one embodiment, the method may further comprise optionally detecting in the tumor DNA the presence of somatic and / or germline gains, losses and / or single nucleotide variant mutations in the exonic region of one or more of gene selected from the group consisting of MED12, SMARCA1, and KDM6A; and / or optionally detecting in the tumor DNA the presence of somatic and / or germline gains and / or single nucleotide variant mutations in the exonic region of AR; and / or optionally detecting in the tumor DNA the presence of somatic and / or germline single nucleotide variant mutations in the exonic region of IDH1.

[0190] In embodiments wherein the method comprises a step of detecting in the tumor DNA the presence of somatic and / or germline mutations in the exonic region of one or more target gene-region, the presence of one or more somatic and / or germline mutations indicates that the subject would benefit from treatment with one or more cancer treatments, has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments.

[0191] Step ii-d):

[0192] The method of the present invention preferably comprises a step of analyzing the allelic imbalance and copy number for each target gene-region and / or for each control generegion, to determine the allele-specific copy number value of each allele of each generegion.

[0193] The exemplary method for analyzing the allelic imbalance and copy number for each generegion to determine the allele-specific copy number value of each allele of each gene-region is described in the Examples section, which uses PCF SELECT (Orlando F, et al., NAR Cancer. 2022;4(2):zcac016, and in WO2022 / 258975) in combination with CLONETv2 (Prandi D, Demichelis F. Ploidy- and Purity-Adjusted Allele-Specific DNA Analysis Using CLONETv2. Curr Protoc Bioinformatics. 2019;67(l):e81).

[0194] To determine the allele-specific copy number value it is first necessary to determine the allelic imbalance for the gene-regions in the tumor DNA, and to determine the copy number for each gene-region in the tumor DNA. Typically, the tumor content (TC) of the sample comprising tumor DNA and / or the ploidy of the sample comprising tumor DNA are also estimated. The estimated TC and ploidy of the sample are typically used to more accurately determine the copy number for each gene-region in the tumor DNA (for example, to correct the copy number, as described herein). Typically, to determine allelic imbalance, it is necessary to first determine a reference model using a set of control samples. Control samples may comprise genomic DNA from healthy subjects and / or healthy cells, for example white blood cells. Further examples of suitable control samples include: a cfDNA sample from a healthy subject, for example a healthy age and / or gender matched subject; a tissue sample from a healthy subject, for example a prostate tissue sample from a healthy subject; a characterized genome sequence of a white blood cell; a characterized genome sequence of a non-cancerous cell, such as a non-cancerous prostate cell.

[0195] An exemplary method for generating a reference model using a control sample is described in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016, and in WO2022 / 258975 (see, in particular, the Examples section of WO2022 / 258975), the contents of which are incorporated herein by reference.

[0196] Allelic imbalance may be determined for each gene-region in the tumor DNA and non-tumor DNA for a subject. For example, this may be achieved by reference to a reference model. Using a reference model can further improve the sensitivity of the methods of the invention. Such a reference model is described in detail above. An exemplary method for determining allelic imbalance in the tumor DNA with reference to a reference model is described in the Examples section. An exemplary method for determining allelic imbalance in the tumor DNA without reference to a reference model is also described in the Examples section.

[0197] The copy number of a gene-region in the tumor DNA or non-tumor DNA may be determined, for example, by integrating the read-depth estimations and allelic imbalance calls. Methods for determining the focal copy number of parts of a gene-region are described herein. Methods for determining the focal copy number of parts of a gene-region are also known in the art, for example DNAcopy (10.18129 / B9.bioc.DNAcopy) and the methods reported in Zare, F., et al. BMC Bioinformatics 18, 286 (2017).

[0198] Allele-specific copy number aberrations (asCNAs) are alterations in the total copy number (i.e. the allele-specific copy number) of a gene-region, or part thereof, and the specific number of copies of each chromosome. More specifically, allele-specific copy number aberrations (asCNAs) may be defined as alterations in the allele-specific copy number of a gene-region, or part thereof, relative to the expected number of copies of that gene-region, or part thereof, derived from each parental chromosome (e.g. as determined from a reference model generated from a control sample, as described herein above). Types of asCNA include: copy number gain (for example balanced or unbalanced copy number gain), copy number loss (for example homodeletions and hemideletions), and loss of heterozygosity (LOH) events (for example copy number-neutral loss of heterozygosity). The allele-specific copy number value and asCNA status for each gene-region may be determined by integrating read-depth estimation for each gene-region and allelic imbalance status for each gene-region. The allele-specific copy number value and asCNA status may then be corrected for the ploidy and purity of the tumor DNA in the biological sample. Methods for correcting the allele-specific copy number value and asCNA for ploidy and purity are known in the art. For example, CLONETv2 (Prandi et al., 2019, Curr Protoc Bioinformatics. Sep;67(l):e81)), FACETS (PMID: 27270079), ASCAT (PMID: 20837533), Sequenza (PMID: 25319062), or CNVkit (PMID: 27100738). In exemplary embodiments, the method described by Prandi et al., 2019 (Curr Protoc Bioinformatics. 2019 Sep;67(l):e81) is used (i.e. by using the CLONETv2 algorithm).

[0199] To determine allele-specific copy number value, the decision tree depicted in Figure 8 of WO2022 / 258975 may be applied. Briefly, allele-specific copy number value can be determined by integrating read-depth estimations and allelic imbalance calls as described in WO2022 / 258975 and in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016. For example, first, a check for the quality of the control samples is performed. Then, the presence of allelic imbalance is assessed and Log2R corrected for ploidy and purity (i.e. ctDNA level / TC) of the sample (Prandi, D. and Demichelis, F. (2019) Ploidy- and Purity-Adjusted Allele-Specific DNA Analysis Using CLONETv2. Curr Protoc Bioinformatics, 67, e81). Note ploidy / purity correction is only applied if uncorrected signal supports the presence of aberration (i.e. uncorrected Log2R > thrLog2wherein thrLogz is as defined in Orlando F, et al., NAR Cancer. 2022;4(2):zcac016). Moreover, to be conservative if estimated TC < 15% and E(AT)T< 0.2 (i.e. no allelic imbalance detected), the method reports the likely presence of aberration in a gene-region not at an allele-specific level. If estimated TC < 15% and allelic imbalance is identified in the gene-region, the method reports the allele-specific copy number. To obtain the copy number values of the two alleles, cnA and cnB (by design cnA>=cnB) for each gene-region, the following original equations are applied (Prandi, D. and Demichelis, F. (2019) Ploidy- and Purity-Adjusted Allele-Specific DNA Analysis Using CLONETv2. Curr Protoc Bioinformatics, 67, e81):

[0200] (2 - pT)(pTX 2Log2RP - G) + 2G(1 - pT) cnA =

[0201] (I - G)PT where Log2Rp is the ploidy-corrected Log2R of the gene-region and G is the admixture of the sample (i.e. 1-TC).

[0202] In embodiments wherein the biological sample provided in step i) of the method of the invention has a tumor content (TC) of less than about 20% (e.g. less than about 15%, 10%, 5%, 4%, 3%, 2% or 1% TC), the allele-specific copy number values determined in step ii) of the method of the invention may be corrected for purity and ploidy of the tumor DNA in the biological sample by:

[0203] A. Identifying one or more gene-regions defined in Table 1 or Table 2 in the tumor DNA of the biological sample that exhibit allelic imbalance (Beta < 1) and copy number loss (Log2 < 0); B. Modelling combinations of purity and ploidy of the tumor DNA in the biological sample against all possible integer copy number states that correspond to a loss-of- heterozygosity (LoH) state (e.g. 0 / 1, 0 / 2, 0 / 3, ..., 0 / n configurations) for each gene region; and

[0204] C. Selecting the combination of LoH state, purity and ploidy that minimises the aggregate deviation from the nearest integer copy-number state across the at least 5 gene-regions of step ii) of the method of the invention;

[0205] D. Adjusting the allele-specific copy number values determined in step ii) of the method of the invention based on the combination of LoH state, purity and ploidy of the tumor DNA in the biological sample selected in step C. Methods for achieving step D are known in the art, and include, for example, CLONETv2 (Prandi et al., 2019, Curr Protoc Bioinformatics. Sep;67(l):e81)), FACETS (PMID: 27270079), ASCAT (PMID: 20837533), Sequenza (PMID: 25319062), or CNVkit (PMID: 27100738). In exemplary embodiments, the method described by Prandi et al., 2019 (Curr Protoc Bioinformatics. 2019 Sep;67(l):e81) is used (i.e. by using the CLONETv2 algorithm).

[0206] In certain embodiments, step A to D are performed when the biological sample provided in step i) comprises cfDNA, and less than about 20% (e.g. less than about 20%, less than about 15%, less than about 10%, less than about 5%, or less than about 1%) of the total number of cfDNA molecules in the sample are derived from tumor DNA.

[0207] In certain embodiments, step A to D are performed when the biological sample provided in step i) has a tumor content of at least about 1%, at least about 2%, at least about 3%, at least about 4%, at least about 5%, at least about 10%, at least about 15%, or at least about 20%, wherein the tumor content is the percentage of DNA molecules in the biological sample that are tumor DNA molecules.

[0208] In embodiments wherein step A comprises identifying more than one gene-region defined in Table 1 or Table 2 in the tumor DNA of the biological sample that exhibits allelic imbalance (Beta < 1) and copy number loss (Log2 < 0), step B is performed for each of the identified gene-regions, and step C involves selecting the best fitting combination from all the combinations determined in step B, i.e., selecting the combination of LOH state, purity and ploidy that provides the lowest aggregate deviation from the nearest integer copy- number state across the at least 5 gene-regions. The gene-region corresponding to the selected combination is denoted as the anchor genomic lesion within the biological sample; step D is then performed based on the selected combination of LoH state, purity and ploidy for the anchor genomic lesion.

[0209] By adjusting the allele-specific copy number values determined in step ii) of the method of the invention using steps A to D above, it is possible to increase accuracy of the allelespecific copy number values determined when using biological samples that have a tumor content of less than about 20% (e.g. less than about 15%, about 10%, or about 5% TC, such as low tumor content sample (i.e. samples with >5% TC) and very low tumor content samples (i.e. samples with >1% TC)). In turn, by adjusting the allele-specific copy number values, further asCNAs may be identified in the tumor DNA of the biological sample based on the adjusted allele-specific copy number values. Steps A to D facilitate the accurate analysis of biological samples with a tumor content of less than about 20%, such as those obtained from subjects with early-stage cancer or other cancer types that are associated with biological samples that have low (e.g. >5% TC) or very low (e.g. >0% TC, such as >1%) tumor content, or from subjects that are responding well to treatment, and therefore may have reducing tumor content in their biological samples over time.

[0210] Optional further step of step ii):

[0211] The method of the present invention may optionally comprises a step of analyzing the allelic imbalance and copy number for each target gene-region, and / or for each control generegion, to determine the presence, absence, and / or alteration of one or more allele-specific copy number aberration (asCNA) at each target gene-region and / or each control generegion in the tumor DNA.

[0212] The presence, absence, and / or alteration of one or more asCNA in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments, has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments.

[0213] In certain embodiments, the presence, absence, and / or alteration of one or more asCNA in the tumor DNA, in combination with determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value, indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments, would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

[0214] For example, the methods of the invention comprising steps ii-a) to ii-d) as herein may further comprises the step of ii-e) analysing the allelic imbalance and copy number for each gene-region (for example for each target gene-region and / or for each control gene-region), to determine the presence, absence, and / or alteration of one or more allele-specific copy number aberration (asCNA) at each target gene-region in the tumor DNA; and wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA, and the presence, absence, and / or alteration of one or more asCNA in the tumor DNA, indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments, would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

[0215] Step Hi):

[0216] The method of the present invention comprises step iii) of determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value; wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

[0217] In certain preferred embodiment, step iii) comprises determining the proportion of generegions that have an allele-specific copy number value of at least 0.10 more or at least 0.10 less than the closest integer value.

[0218] The present inventors have found that determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value can be used to provide accurate and clinically useful information regarding the subclonality of a subject's cancer. The present inventors have surprisingly found that the subclonality of a subject's cancer as measured according to the methods of the present invention is directly linked to patient prognosis and can be used to make better informed and more effective treatment decisions for a subject, and thus provide more reliable treatments and prognosis for subjects. The present investors have found that divergence of allele specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value is an optimum threshold for establishing the true presence of subclones in a population.

[0219] In an alternative embodiment, step iii) of the present invention may alternatively comprise determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.2 more or at least 0.2 less than the closest integer value (for example, at least 0.20 more or at least 0.20 less than the closest integer value). In another alternative embodiment, step iii) or the present invention may alternatively comprise determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.05 more or at least 0.05 less than the closest integer value.

[0220] The proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value may be referred to as a circulating subclonality index (CSI). The proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value (i.e. the CSI) may alternatively represented as follows:

[0221] Circulating Subclonality Signal ~ (cnA - cn.AJnt) > 0.1 - cn.B.int) > 0.1

[0222] Circulating Subclonality index ,

[0223] Wherein gene is a gene-region; cnA and cnB are the copy number values of the two alleles of a gene region; cn.A.int is the closest integer value to the cnA copy number value; and cn.B.int is the closest integer value to the cnB copy number value.

[0224] In one very preferred embodiment, the method of the invention comprises step ii) determining the allele-specific copy number value of each allele for each of at least 5 generegions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA. In such embodiments, the proportion of generegions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value (i.e. the CSI) may alternatively represented as follows:

[0225] Circulating Subclonality Signal gene^wildtype = (cnA cn.A.int) > 0.1 i (cnB cn.B.int) > 0.1

[0226] £ CSSgene^wildtype

[0227] Circulating Subclonality Index sample

[0228] N gene=twikltype

[0229] Wherein gene^wildtype is a gene-region wherein at least one allele of the gene-region has an asCNA; cnA and cnB are the copy number values of the two alleles of a gene region; cn.A.int is the closest integer value to the cnA copy number value; and cn.B.int is the closest integer value to the cnB copy number value.

[0230] A high proportion of genes with non-integer copy numbers in a biological sample (e.g. cfDNA) could indicate a mixture of two subclones whose combined and non-overlapping aberrant gene allele specific copy numbers manifest as non-integer copy numbers, or it could also indicate a mixture of a multitude of subclones (for example 3 or more, 4 or more, 5 or more subclones) whose combined gene alterations and differing allele specific copy numbers manifest as non-integer copy numbers. The higher the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value, the more likely it is the cancer has multiple subclones and / or does not have a dominant subclone (for example, the more likely the sample has two subclones whose combined and non-overlapping aberrant gene allele specific copy numbers manifest as non-integer copy numbers, or a mixture of a multitude of subclones (for example 3 or more, 4 or more, 5 or more subclones) whose combined gene alterations and differing allele specific copy numbers manifest as non-integer copy numbers). This may be referred to a high CSI. The lower the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value, the more likely it is the cancer does not have multiple subclones and / or has a dominant subclone (this may be referred to a low CSI).

[0231] As shown by the Examples in the application, the inventors have found that subjects with a low CSI, and thus indicative of a cancer likely to not to have multiple subclones and / or have a dominant subclone, the poorer the prognosis for the subject and the less likely that their current treatment will be effective in treating the cancer. The inventors have found that subjects with a high CSI, and thus indicative of a cancer likely to have multiple subclones and / or not have a dominant subclone, the better the prognosis for the subject and the more likely that their current treatment will be effective in treating the cancer.

[0232] What is a "high" or a "low" CSI can depend on multiple factors, including but not limited to the type of cancer, stage of cancer, if the cancer is metastatic previous treatments a subject has had for the cancer, DNA repair gene aberrations in the tumour DNA, oncogene induced replication stress, and / or chromotrypsis.

[0233] In certain embodiments, a "low" CSI (i.e. a "low" proportion of gene-regions with an allelespecific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA) is less than the median CSI (i.e. the median proportion of generegions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA) for a cohort of subjects with a similar cancer to the subject of the method, i.e. a similar type of cancer, stage of cancer, similar metastatic status, and / or previous treatments a subject to the subject of the method.

[0234] In certain embodiments, a "high" CSI (i.e. a "high" proportion of gene-regions with an allelespecific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA) is the same or greater than the median CSI (i.e. the median proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA) for a cohort of subjects with a similar cancer to the subject of the method, i.e. a similar type of cancer, stage of cancer, similar metastatic status, and / or previous treatments a subject to the subject of the method.

[0235] In certain embodiments, the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than median CSI (i.e. less than the median proportion of gene-regions with an allelespecific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA) for a cohort of subjects with a similar cancer to the subject of the method, i.e. a similar type of cancer, stage of cancer, similar metastatic status, and / or previous treatments a subject to the subject of the method, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen.

[0236] In certain embodiments, the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is the same as or greater than the median CSI (i.e. the same as or greater than the median proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA) for a cohort of subjects with a similar cancer to the subject of the method, i.e. a similar type of cancer, stage of cancer, similar metastatic status, and / or previous treatments a subject to the subject of the method that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments.

[0237] In certain embodiments, a "low" CSI is when the proportion of gene-regions with an allelespecific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than an integer value between 50% and 99%, for example less than 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 orTable 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0238] In certain embodiments, a "high" CSI is when the proportion of gene-regions with an allelespecific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is the same or greater than an integer value between 50% and 99%, for example 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater. In certain embodiments a "high" CSI is when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater or 80% or greater. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0239] In certain embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than an integer value between 50% and 99%, for example 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 orTable 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has asCNA.

[0240] In certain embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is the same or greater than an integer value between 50% and 99%, for example 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0241] In certain preferred embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments the cancer may, for example, be metastatic and / or prostate cancer. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has asCNA.

[0242] In certain preferred embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 60% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 60%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments the cancer may, for example, be metastatic and / or prostate cancer. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0243] In certain preferred embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 70% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 70%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments the cancer may, for example, be metastatic and / or prostate cancer. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA. In certain preferred embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 80% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 80%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments, the cancer may be, for example, advanced metastatic and / or prostate cancer (for example advanced and / or metastatic castration resistant prostate cancer) and / or prostate cancer wherein the subject has previously been treated with a taxane (for example docetaxel) and / or prostate cancer wherein the subject has previously been treated with an anti-androgen (for example enzalutamide). In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0244] In certain preferred embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 81% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 81%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments the cancer may be, for example, advanced metastatic and / or prostate cancer (for example advanced and / or metastatic castration resistant prostate cancer) and / or prostate cancer wherein the subject has previously been treated with a taxane (for example docetaxel). In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0245] In certain preferred embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 85% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 85%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments the cancer may be, for example, advanced metastatic and / or prostate cancer (for example advanced and / or metastatic castration resistant prostate cancer) and / or prostate cancer wherein the subject has previously been treated with a taxane (for example docetaxel). In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA. In certain preferred embodiments, if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 87% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 87%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen. In such embodiments the cancer may, for example, be advanced metastatic and / or prostate cancer (for example advanced and / or metastatic castration resistant prostate cancer) and / or prostate cancer wherein the subject has previously been treated with a taxane (for example docetaxel). In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0246] In certain preferred embodiments, the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previously received. In such embodiments, preferably the sample has a "low" CSI as defined herein, for example the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than an integer value between 50% and 99%, for example less than 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%. More preferably, the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%, and especially less than 80%, less than 81%, or less than 85%. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0247] In certain preferred embodiments, the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received. In such embodiments, preferably the sample has a "high" CSI as defined herein, for example the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 is less than the closest integer value in the tumor DNA is the same or greater than an integer value between 50% and 99%, for example 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater. More preferably, the proportion of generegions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater, and especially 80% or greater, 81% or greater, 85% or greater. In such embodiments, preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0248] Further optional method steps:

[0249] In certain embodiments, the method of the invention further comprises step iv-1): determining one or more cancer treatment the subject would benefit from.

[0250] In certain embodiments, the method of the invention further comprises step v-1): treating the subject with one or more cancer treatment determined in step vi), and thereby treating the subject.

[0251] In certain embodiments, the method of the invention further comprises the following steps:

[0252] I) providing a further biological sample obtained from the subject during or after the subject has undergone a treatment for cancer, wherein said sample comprises tumor DNA;

[0253] II) performing steps ii) to iii) of the method of the invention using the further biological sample provided in step I); and wherein a change in the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the further biological sample comprising tumor DNA compared to the biological sample comprising tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

[0254] In such embodiments, preferably the further biological sample obtained from the subject during or after the subject has undergone a treatment for cancer, wherein said sample comprises tumor DNA, is a sample of the same type as the biological sample comprising tumor DNA provided in step i). For example, if the biological sample comprising tumor DNA provided in step i) is a blood sample, preferably the further biological sample comprising tumor DNA is a blood sample; or if the biological sample comprising tumor DNA provided in step i) is a plasma sample, preferably the further biological sample comprising tumor DNA is a plasma sample.

[0255] In embodiments where the method of the invention further comprises:

[0256] I) providing a further biological sample obtained from the subject during or after the subject has undergone a treatment for cancer, wherein said sample comprises tumor DNA; preferably the further biological sample of step I) is obtained at a later time point to the biological sample comprising tumor DNA of step i). For example, the further biological sample of step I) may be obtained around 1 week, around 2 weeks, around 3, weeks, around 4, weeks, around 1 month, around 6 weeks, around 2 months, around 3 months, around 4 months, around 6 months, around 9 months, around 1 year, or more than 1 year after the biological sample comprising tumor DNA of step i) was obtained.

[0257] In embodiments where the method of the invention further comprises step II), preferably step II) comprises performing steps ii-a) to ii-d) (and optionally step ii-e)) and iii) as described herein, using the further biological sample provided in step I).

[0258] In embodiments where the method of the invention further comprises steps I) and II), steps I) and II) may be repeated on one or more additional further biological samples (for example 1, 2 ,3, 4, 5, 10, 15 or more additional further biological samples). For example, the steps may be repeated on one or more additional further biological samples each obtained at different time points during or after the subject has undergone a treatment for cancer compared to the time point the further biological sample was obtained. For example, an additional further biological may be obtained around 1 week, around 2 weeks, around 3, weeks, around 4, weeks, around 1 month, around 6 weeks, around 2 months, around 3 months, around 4 months, around 6 months, around 9 months, around 1 year, or more than 1 year after the further biological sample comprising tumor DNA of step i) was obtained.

[0259] In certain embodiments, the method of the invention further comprises a step of treating the subject for a cancer using a therapeutic agent for the treatment of cancer; or ceasing or altering treatment with a therapeutic agent for the treatment of a cancer; or initiating a non-therapeutic agent treatment for cancer (for example initiation of treatment by surgery or radiation).

[0260] Detecting SNPs

[0261] Typically, step ii) of the method of the present invention is performed by analysing the nucleotide sequence of the DNA in the biological sample. For example, typically, steps ii-a) and ii-b) of the preferred method of the present invention are performed by analysing the nucleotide sequence of the DNA in the biological sample. A variety of procedures suitable for determining the nucleotide sequence of a DNA molecule are known in the art and may be used to practice the methods disclosed herein. Sequencing methods suitable for use in the present invention include, for example, Sanger sequencing, Polony sequencing, 454 pyrosequencing, Combinatorial probe anchor synthesis, SOLiD sequencing, Ion Torrent semiconductor sequencing, DNA nanoball sequencing, Heliscope single molecule sequencing, Single molecule real time (SMRT) sequencing, Nanopore DNA sequencing, Microfluidic Sanger sequencing and Illumina dye sequencing.

[0262] The method of the present invention may further comprise aligning the nucleotide sequences with a reference genome for the subject, for example by aligning the nucleotide sequences with hg38, hgl9, hgl8, hgl7 or hgl6. The alignment can, for example, be carried out using a variety of techniques known in the art. For example, a DNA sequence alignment tool, (e.g., BWA-MEM (for example version BWA-MEM 0.7.17- rll88) (Li, H. and Durbin, R. (2009) Bioinformatics, 25, 1754-1760); BBMap (Bushnell, B. (2014). BBMap: A Fast, Accurate, Splice-Aware Aligner. Lawrence Berkeley National Laboratory); HISAT (PMID: 258751142); Bowtie 2 (PMID: 22388286); and FSVA (PMID: 28155631)) can be used to align the reads to the reference genome (for example hg38, hgl9, hgl8, hgl7 or hgl6). In exemplary embodiments, the method described by Li, H. and Durbin, R., 2009 (Bioinformatics, 25, 1754-1760) is used (i.e. by using BWA-MEM 0.7.17-rll88).

[0263] The genomic location assigned to each nucleotide sequence in the alignment is based on the reference genome adopted. The genomic locations listed in Tables 1 and 2 disclosed herein correspond to reference genome hgl9. The corresponding locations in a different reference genome can be found using public available tools known in the art. An example of such a tool is LiftOver (http: / / genome.ucsc.edu / ).

[0264] In certain embodiments, the method comprises removing duplications of reads of the same DNA molecule (e.g. duplications of reads of the same cfDNA molecule). Sequence reads having exactly the same sequence and start and end base pairs (i.e. the same unclipped alignment start and unclipped alignment end of the sequence) are typically removed, as they are likely to be duplicate sequence reads of the same sequence (i.e. duplicate of reads of the same cfDNA molecule). For example, PCR duplications can be removed as part of the aligning step, such as using Picard tools v2.1.0 (http: / / broadinstitute.github.io / picard).

[0265] In certain embodiments of the invention comprising steps ii-a) to ii-d) and optionally step ii- e), each SNP loci detected in step ii-a) is covered by at least 2 sequence reads in step ii-b), for example at least 2, 3, 4, 5, 6, 7, 8, 9, 10, 12, 15, 20, 25, 50, 100, 200, 300, 400, 500, 1000, or 10,000 sequence reads in step ii-b). Preferably, each SNP loci detected in step ii-a) is covered by at least 5 sequence reads in step iii), for example at least 6, 7, 8, 9, 10, 12, 15, 20, 25, 50, 100, 200, 300, 400, 500, 1000, or 10,000 sequence reads. More preferably, each SNP loci detected in step ii-a) is covered by at least 10 sequence reads in step ii-b), for example at least 12, 15, 20, 25, 50, 100, 200, 300, 400, 500, 1000, or 10,000 sequence reads. Estimation of the read-depth of each gene-region, and therefore the SNPs within each region, can be performed using methods known in the art, for example by using the method described in Carreira et al. (2014) (Science Translational Medicine, 6, 254ral25), which is incorporated herein by reference.

[0266] In vitro assay:

[0267] In certain embodiments, the methods of the present invention are performed using an in vitro assay of the present invention. The in vitro assay of the present invention comprises the method steps of: a) providing a biological sample obtained from the subject, wherein said sample comprises tumor DNA; b) determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA; c) determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value; wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

[0268] Steps b) and c) of the in vitro assay are performed using the same processes as described herein for steps ii), and iii) of the in vitro method of the present invention.

[0269] In certain preferred embodiments, step a) further comprises providing a biological sample obtained from the subject, wherein said sample comprises non-tumor DNA.

[0270] In certain preferred embodiments, step b) of determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA comprises the steps of: b-1) providing a set of probes, wherein said set of probes are capable of specifically hybridizing to: at least 5% of the SNP loci defined in Table 1 or Table 2 for each of at least 5 gene-regions defined in Table 1 and Table 2; b-2) contacting the biological sample comprising non-tumor and / or tumor DNA with the set of probes under conditions suitable for one or more of the probes to specifically hybridize to a SNP locus in the non-tumor and / or tumor DNA; b-3) capturing the non-tumor DNA and / or tumor DNA in the biological sample that has hybridized to one or more of the probes, and determining the nucleotide sequence of the captured DNA; b-4) analysing the nucleotide sequence of the captured non-tumor DNA to identify which of the SNPs present in the non-tumor DNA are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA for the subject; b-5) analysing the nucleotide sequence of the captured tumor DNA to determine the allelic imbalance for each gene-region of the tumor DNA by reference to the iSNPs for the subject in each gene-region; and determining the copy number for each gene-region in the tumor DNA; and b-6) analysing the allelic imbalance and copy number for each gene-region to determine the allele-specific copy number value of each allele of each gene-region.

[0271] In certain very preferred embodiments, step b) of determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 in the tumor DNA comprises the steps of: b-1) providing a set of probes, wherein said set of probes are capable of specifically hybridizing to: at least 5% of the SNP loci defined in Table 1 or Table 2 for each of at least 5 gene-regions defined in Table 1 and Table 2

[0272] (for example, at least 5% of the SNP loci defined in Table 1 for each of at least 5 target generegions defined in Table 1, and optionally at least 5% of the SNP loci defined in Table 2 for each of at least 3 control gene-regions defined in Table 2); b-2) contacting the biological sample comprising non-tumor and / or tumor DNA with the set of probes under conditions suitable for one or more of the probes to specifically hybridize to a SNP locus in the non-tumor and / or tumor DNA; b-3) capturing the non-tumor DNA and / or tumor DNA in the biological sample that has hybridized to one or more of the probes, and determining the nucleotide sequence of the captured DNA; b-4) analysing the nucleotide sequence of the captured non-tumor DNA to identify which of the SNPs present in the non-tumor DNA are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA for the subject; b-5) analysing the nucleotide sequence of the captured tumor DNA to determine the allelic imbalance for each target gene-region and / or for each control gene-region, of the tumor DNA by reference to the iSNPs for the subject in each gene-region; and determining the copy number for each target gene-region, and / or for each control gene-region, in the tumor DNA; and b-6) analysing the allelic imbalance and copy number for each target gene-region, and / or for each control gene-region, to determine the allele-specific copy number value of each allele of each gene-region.

[0273] Steps b-4) and b-6) of the in vitro assay are performed using the same processes as described herein for steps ii-c-1), ii-c-2) and ii-d) of the in vitro method of the present invention.

[0274] Probes:

[0275] Also disclosed herein is a set of probes suitable for use in the method of the present invention, wherein the set of probes are capable of hybridizing to: at least 5% (for example, at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80%) of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1, and / or at least 5% (for example, at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80%) of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 2.

[0276] Also disclosed herein is a set of probes suitable for use in the method of the present invention, wherein the set of probes are capable of hybridizing to: at least 5% (for example, at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80%) of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1, and optionally at least 5% (for example, at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80%) of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 2.

[0277] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, 3, 4 or 5; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16 as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with the function in the androgen (receptor) signalling pathway.

[0278] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16 or 17; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with cell cycle dysfunction.

[0279] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, 3, 4, 5, 6, 7 or 8; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with with the phosphoinositide 3-kinase (PI3K) signalling pathway.

[0280] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, 3, 4, 5, 6, 7 or 8; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting ofARIDlA, CHD1, KDM6A, MED12, SMARCA1, KMT2C, KMT2D and RYBP as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with chromatic remodeling dysfunction.

[0281] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, 3, 4, 5, 6, 8, 10, 12, 15, 20 or 22; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected of being associated with DNA repair dysfunction. In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, 3, 4, 5, 6, 8, 10, or 12; typically at least 2, at least 3 or at least 4) target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1. Genetic aberrations in such gene-regions are known to be associated with prostate cancer, although their precise role in the development and / or progression of prostate cancer of a subject are currently unknown.

[0282] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, or 3; typically at least 2) target gene-region selected from the group consisting of APC, CTNNB1 and RNF43 as defined in Table 1. Genetic aberrations in such gene-regions are known or suspected to dysregulate the Wnt signalling pathway.

[0283] In certain preferred embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one (for example 1, 2, 3, 4, 5, or 6; typically at least 2, at least 3, at least 4, at least 5 or 6) target gene-region selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1. In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least 3 of the target gene-regions selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1. More preferably, a set of probes suitable for use in the method of the present invention are capable of hybridizing to the gene-regions of at least BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1.

[0284] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one target gene-region selected from the group consisting of FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16; and / or at least one target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53; and / or at least one target gene-region selected from the group consisting of ARID1A, CHD1, KMT2C, KMT2D and RYB; and / or at least one target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C; and / or at least one target gene-region selected from the group consisting ofASXLl, CLU, CYLD, ERG_TMPRSS2, GN AS, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3; and / or at least one target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN; and / or at least one target gene-region selected from the group consisting of APC, CTNNB1 and RNF43; and / or at least one target gene-region selected from the group consisting of PIK3CB and RAD51B; and / or at least one target generegion selected from the group consisting of MYC, AR, NC0A2, NKX3-1, PTEN, MDM4 and BRIP1; and / or at least one target gene-region selected from the group consisting of MYC, NCOA2, NKX3-1, MDM4, BRIP1, AURKA, AR, PTEN, PIK3CB and TP53; and / or at least one target gene-region selected from the group consisting of TP53, AR and ARID1A ; and / or at least one target gene-region selected from the group consisting of TP53, AR, F0XA1 ARID1A, APC, BRCA2 and MED12 ; and / or at least one target gene-region selected from the group consisting of CHEK2 and / or HDAC2.

[0285] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least two, at least three or at least four target gene-region selected from the group consisting of F0XA1, FOXP1, HSD3B1, NC0A2 and ZBTB16; and / or at least two, at least three or at least four target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ARID1A, CHD1, KMT2C, KMT2D and RYB; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C; and / or at least two, at least three or at least four target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3; and / or at least two, at least three or at least four target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN; and / or at least one, at least two or each target gene-region selected from the group consisting of APC, CTNNB1 and RNF43; and / or at least one target gene-region selected from the group consisting of PIK3CB and RAD51B; and / or at least one target gene-region selected from the group consisting of MYC, AR, NC0A2, NKX3-1, PTEN, MDM4 and BRIP1; and / or at least one target gene-region selected from the group consisting of MYC, NCOA2, NKX3-1, MDM4, BRIP1, AURKA, AR, PTEN, PIK3CB and TP53; and / or at least one target gene-region selected from the group consisting of TP53, AR and ARID1A ; and / or at least one target gene-region selected from the group consisting of TP53, AR, F0XA1 ARID1A, APC, BRCA2 and MED12 ; and / or at least one target gene-region selected from the group consisting of CHEK2 and / or HDAC2.

[0286] In certain embodiments, a set of probes suitable for use in the method of the present invention are capable of hybridizing to at least one, at least two, at least three, or at least four, or at least five (for example at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all) gene-regions selected from the group consisting of as AKT1, APC, AR, ARID1A, ASXL1, ATM, ATR, AURKA, BRAE, BRCA1, BRCA2, BRIP1, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CH DI, CHEK2, CTNNB1, CYLD, ERCC2, ERCC3, ERG_TMPRSS2, FANCA, FANCC, FANCD2, FANCG, FBXW7, FOXA1, FOXP1, GNAS, HDAC2, HSD3B1, IDH1, IDH2, KDM6A, KMT2C, KMT2D, KRAS, MDM2, MDM4, MED12, MET, MLH1, MSH2, MSH6, MYC, MYCN, NCOA2, NKX3-1, PALB2, PIK3CA, PIK3CB, PIK3R1, PTEN, RAD51B, RAD51C, RBI, RNF43, RYBP, SMARCA1, SPOP, TP53, ZBTB16, ZFHX3, ATG14, ATXN7, C9orf47, CST7, DRD1, ENPEP, FAM183B, FCER1A, GRHPR, HDAC8, IL1RL2, L3MBTL1, LRRC17, MESDC2, MIS18A, MTIF3, NIT2, OR3A3, PXDNL, RNF125, RSF1, SPDYA, TEX11, TK2, TOP3B, UGT2B17, and ZBTB9d as defined in Table 1 and Table 2.

[0287] Preferably, said set of probes is capable of specifically hybridizing to any embodiment or combination of embodiments described herein for step ii-a) of the in vitro method of the present invention, i.e. capable of specifically hybridizing to a % or number of SNP loci defined in Table 1 for target gene-regions recited herein and / or a number of target gene-regions defined in Table 1 recited herein for step ii) of the in vitro method of the present invention; and / or a % or number of SNP loci defined in Table 2 for control gene-regions recited herein and / or a number of control gene-regions defined in Table 2 recited herein for step ii) of the in vitro method of the present invention.

[0288] For example, said set of probes are capable of hybridizing to: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0289] Or, said set of probes are capable of hybridizing to: at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 10%, at least 15%, at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0290] Or, said set of probes are capable of hybridizing to: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0291] Or, said set of probes are capable of hybridizing to: at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 20%, at least 25%, at least 30%, at least 40%, at least 50%, at least 60%, at least 70%, at least 80%, at least 90% or all of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0292] Or, said set of probes are capable of hybridizing to: at least 30, at least 60, at least 90, or at least 100 of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and / or at least 30, at least 60, at least 90, or at least 100 of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0293] Or, said set of probes are capable of hybridizing to: at least 30, at least 60, at least 90, or at least 100 of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 40, at least 50, at least 60, at least 70 or all of the target gene-regions defined in Table 1; and optionally at least 30, at least 60, at least 90, or at least 100 of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 15, at least 20, at least 25, at least 30, at least 35, or all of the control gene-regions defined in Table 2.

[0294] In one embodiment, the set of probes comprises at least 10, at least 20, or at least 30 (for example, at least 100, at least 300, at least 400, at least 500) probes that are capable of specifically hybridizing to at least 10, at least 20, or at least 30 (for example, at least 100, at least 300, at least 400, at least 500) of the SNP loci defined in Tables 1 for each of at least 5 target gene-regions in Table 1. In certain embodiments, the set of probes further comprises at least 10, at least 20, or at least 30 (for example, at least 100, at least 300, at least 400, at least 500) probes that are capable of specifically hybridizing to at least 10, at least 20, or at least 30 (for example, at least 100, at least 300, at least 400, at least 500) of the SNP loci defined in Tables 2 for each of at least 5 control gene-regions in Table 2. Preferably, each probe in the set of probes provided in step ii) is capable of hybridizing to only one of the SNP loci defined in Table 1 or 2. Typically, the total number of different probes in the set is at least 50, at least 500, at least 1000, at least 3000, at least 5000, at least 10,000, at least 15,000, or at least 17,500.

[0295] In certain preferred embodiments, the set of probes is capable of hybridizing to: at least 80% of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1; and / or at least 80% of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 2.

[0296] In certain preferred embodiments, the set of probes is capable of hybridizing to: at least 80% of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1; and optionally at least 80% of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 2.

[0297] In certain preferred embodiments, the set of probes is capable of hybridizing to: at least 80% of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1; and at least 80% of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 2.

[0298] In another embodiment, the set of probes is capable of hybridizing to: at least 90%, at least 95%, or at least 98% of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 25, at least 50, at least 70, or all of the target generegions defined in Table 1; and / or at least 90%, at least 95% ,or at least 98% of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 25, at least 30, or all of the target gene-regions defined in Table 2.

[0299] In another embodiment, the set of probes is capable of hybridizing to: at least 90%, at least 95%, or at least 98% of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 25, at least 50, at least 70, or all of the target generegions defined in Table 1; and optionally at least 90%, at least 95% ,or at least 98% of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 25, at least 30, or all of the target gene-regions defined in Table 2.

[0300] Probes suitable for use in the in vitro method or in vitro assay of the present invention include, but are not limited to, small molecules, peptides (including cyclic peptides), proteins, nucleic acids (e.g. DNA and RNA nucleotides including, but not limited to, antisense nucleotide sequences, triple helices, siRNA or miRNA, and nucleotide sequences encoding biologically active proteins, polypeptides or peptides), synthetic or natural inorganic molecules and synthetic or natural organic molecules that specifically bind to one or more SNP loci defined in Table 1 or 2.

[0301] In preferred embodiments, the set of probes suitable for use in the present invention is a set of oligonucleotide probes. In such embodiments, the set of oligonucleotide probes is complementary to, and capable of hybridizing to, one or more SNP loci defined in Table 1 or 2, and preferably, each probe is complementary to only one SNP loci defined in Table 1 or 2.

[0302] Probes suitable for use in the present invention may comprise a "label" which is suitable for capturing DNA comprising one or more of the SNPs defined in Table 1 or 2.

[0303] Suitable labels for capturing DNA molecules in a sample that comprise one or more of the SNPs include, for example, biotin. The type of label chosen will depend on the desired capture method used. For convenience, the probe may be immobilised on a solid phase support including resins (such as polyacrylamides), carbohydrates (such as sepharose), plastics (such as polycarbonate), and latex beads.

[0304] The probes may be bound to a solid matrix as discussed above or packaged with reagents for binding them to the matrix. The solid matrix or substrate may be in the form of beads, plates, tubes, dip sticks, strips or biochips. Biochips or plates with addressable locating and discreet microtitre plates are particularly useful. Kits:

[0305] The term "kit" refers to any item of manufacture (e.g. a package or container) comprising at least one reagent, e.g. a probe or small molecule, for specifically detecting one or more SNPs of Table 1 and / or Table 2. The kit may be promoted, distributed, or sold as a unit for performing the methods of the present invention.

[0306] A kit suitable for use in the invention comprises means for probing the biological sample to determining the allele-specific copy number value of each allele for each of at least 5 generegions defined in Table 1 and Table 2 in the tumor DNA. A kit suitable for use in the invention when the invention comprises step ii-a) to ii-d) and optionally ii-e), or steps b-1) to b-6) comprises means for probing the biological sample to determining determine the presence of SNPs in a sample obtained from the subject. Preferably, the kit of the invention comprises a set of probes of the present invention.

[0307] The kit may also include additional components to facilitate the particular application for which the kit is designed. For example, the kit may additionally contain means of detecting a label (e.g., enzyme substrates for enzymatic labels, filter sets to detect fluorescent labels, appropriate secondary labels such as a sheep anti-mouse-HRP, etc.) and reagents necessary for controls (e.g., control biological samples or standards). A kit may additionally include buffers and other reagents of the necessary grade for use in a method of the disclosed invention in a health care setting. Non-limiting examples include agents to reduce nonspecific binding, such as a carrier protein or a detergent.

[0308] In certain embodiments the kit comprises one or more containers and may also include sampling equipment, for example, bottles, bags (such as intravenous fluid bags), vials, syringes, and test tubes. Other components may include needles, diluents, wash reagents and buffers. Usefully, the kit may include at least one container comprising a pharmaceutically-acceptable buffer, such as phosphate-buffered saline, Ringer's solution and dextrose solution.

[0309] In one preferred embodiment, the kit comprises instructions for use. In certain embodiments, the kit comprises instructions for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of cancer in a subject using the kit. For example, the kit comprises instructions for use which define how to determine the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 and Table 2 in the tumor DNA (for example at least 5 target gene-regions defined in Table 1 in the tumor DNA). For example, a kit suitable for use in the invention when the invention comprises step ii-a) to ii-d) and optionally ii-e), or steps b-1) to b-6), comprises instructions for use which define how to determine the present of SNPs and / or identify the presence of iSNPs in the non-tumor DNA in a sample, for example by following a method of the invention defined herein comprising step ii-a) to ii-d).

[0310] In one preferred embodiment, the kit comprises a computer product or a computerexecutable software for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of cancer in a subject using the kit. In certain embodiments, the computer product comprises a non-transitory computer readable medium storing a plurality of instructions that when executed control a computer system to perform a method of the invention. In certain embodiments, the computer-executable software comprises software for performing a method of the invention.

[0311] Cancers:

[0312] The method of the present invention is for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer. The present invention also provides methods for treating cancer. The cancer may be selected from the group consisting of prostate cancer, breast cancer, ovarian cancer, pancreatic cancer, bladder cancer, and metastatic cancer.

[0313] In certain embodiments, the cancer is prostate cancer. The prostate cancer may be any type of prostate cancer. Typically, it may be acinar adenocarcinoma prostate cancer, ductal adenocarcinoma prostate cancer, transitional cell cancer of the prostate, squamous cell cancer of the prostate or small cell prostate cancer. For example, it may be acinar adenocarcinoma prostate cancer or ductal adenocarcinoma prostate cancer. Alternatively, or additionally, the prostate cancer may be hormone sensitive prostate cancer (HSPC) or castration resistant prostate cancer (CRPC). Alternatively, or additionally, the prostate cancer may be metastatic prostate cancer, or it may be non-metastatic prostate cancer. In certain embodiments, it may be metastatic prostate cancer. In certain embodiments, the prostate cancer may be metastatic castration resistant prostate cancer or non-metastatic castration resistant prostate cancer. In certain embodiments, the prostate cancer may be metastatic hormone sensitive prostate cancer (mHSPC) or non-metastatic hormone sensitive prostate cancer.

[0314] In certain embodiments, the cancer is metastatic cancer (i.e. a cancer that has metastasised). Metastatic cancer is cancer that has spread from the primary site of origin into one or more different areas of the body. For example, the cancer may be metastatic prostate cancer (i.e. cancer which has spread from the primary prostate site of origin into one or more different areas of the body), or another form of metastatic cancer, such as metastatic breast cancer, metastatic ovarian cancer, metastatic pancreatic cancer, or metastatic bladder cancer.

[0315] The method is especially suitable for the staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer, and more especially metastatic prostate cancer.

[0316] Methods of treatment of the present invention are especially suitable for the treating prostate cancer, and more especially metastatic prostate cancer.

[0317] The method is especially suitable for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of castration-resistant prostate cancer, and more especially metastatic castration-resistant prostate cancer.

[0318] Methods of treatment of the present invention are especially suitable for the treating castration-resistant prostate cancer, and more especially metastatic castration-resistant prostate cancer.

[0319] Methods of treatment of the present invention are especially suitable for the treating prostate cancer, and more especially metastatic prostate cancer (for example castrationresistant prostate cancer, such as metastatic castration-resistant prostate cancer) wherein the subject has previously been treated with a taxane (for example docetaxel and / or cabazitaxel, and especially docetaxel). Methods of treatment of the present invention are especially suitable for the treating prostate cancer, and more especially metastatic prostate cancer (for example castrationresistant prostate cancer, such as metastatic castration-resistant prostate cancer) wherein the subject has previously been treated with an anti-androgen (for example abiraterone and / or enzalutamide, and especially enzalutamide).

[0320] Methods of treatment of the present invention are especially suitable for the treating prostate cancer, and more especially metastatic prostate cancer (for example castrationresistant prostate cancer, such as metastatic castration-resistant prostate cancer) wherein the subject has previously been treated with a taxane (for example docetaxel and / or cabazitaxel, and especially docetaxel) and an anti-androgen (for example abiraterone and / or enzalutamide, and especially enzalutamide).

[0321] The method is especially suitable for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of hormone sensitive prostate cancer, and more especially metastatic hormone sensitive prostate cancer.

[0322] Methods of treatment of the present invention are especially suitable for the treating hormone sensitive prostate cancer, and more especially metastatic hormone sensitive prostate cancer.

[0323] Methods of treatment:

[0324] The methods of the invention can be used for determining a suitable treatment regimen (i.e. one or more drug for the treatment of cancer) for a subject in need of cancer treatment. The methods of the invention can be used for estimating prognosis for a subject having cancer (for example estimating overall survival and progression free survival).

[0325] The screening of subjects using the methods and assays of the present invention (as well as using the kits defined herein) allow the full potential benefits of cancer treatments to be obtained by selecting one or more treatment that have a high likelihood of benefiting the subject in view of the circulating subclonality in the subject's tumor, which the methods and assays of the present invention determine. In particular, the methods and assays of the invention can determine the proportion of subclonally altered genes and thus indicate if there are less subclonal alterations, and as such indicate if there is likely to be a dominant subclone in circulation or multiple subclones in circulation, and treat the subject accordingly. For example, if less subclonal alterations are indicated, this may indicate that treatment of the subject with a cancer treatment they have not previously received and / or adding one or more further cancer treatments to the subject's treatment regimen will benefit the subject. Alternatively, or additionally, screening of subjects using the methods and assays of the present invention (as well as using the kits defined herein) allow the full potential benefits of cancer treatments to be obtained by ceasing or altering one or more cancer treatments, thus minimizing side effects and exposure of a subject to unnecessary and / or potentially harmful treatments. For example, if less subclonal alterations are indicated, this may indicate that ceasing treatment of the subject with a cancer treatment that they have previously received will benefit the subject.

[0326] The methods of the invention (i.e. determining the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates (optionally in combination the presence, absence, and / or alteration of one or more asCNA in the tumor DNA wherein the method comprises step ii-e) as described herein)) can be used for determining that a subject would benefit from treatment with one or more cancer treatments selected from the group consisting of a ATR inhibitor, CDK inhibitor, chemotherapy (such as taxanes, platinum-based antineoplastic drugs), WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, WEE1 inhibitor, platinum-based antineoplastic drug, taxane, c-Met inhibitor, radionuclide and radiation therapy, DNMTl inhibitor, HDAC inhibitor, BET inhibitor, PI3K inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid. The methods of the invention can be used for determining that a subject would benefit from treatment with one or more cancer treatments selected from the group consisting of a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drug (in particular carboplatin)), PARP inhibitor, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid.

[0327] Alternatively, or additionally, methods of the invention (i.e. determining the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates (optionally in combination the presence, absence, and / or alteration of one or more asCNA in the tumor DNA wherein the method comprises step ii-e) as described herein)) can be used for determining that a subject has benefited, or is benefiting, from one or more cancer treatments selected from the group consisting of ATR inhibitor, CDK inhibitor, Chemotherapy (such as taxanes and platinumbased antineoplastic drugs), WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD- L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, WEE1 inhibitor, platinum-based antineoplastic drug, taxane, c-Met inhibitor, radionuclide and radiation therapy, DNMT1 inhibitor, HDAC inhibitor, BET inhibitor, PI3K inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid. Alternatively, or additionally, methods of the invention can be used for determining that a subject has benefited, or is benefiting, from one or more cancer treatments selected from the group consisting of a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drug (in particular carboplatin)), PARP inhibitor, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid.

[0328] Alternatively, or additionally methods of the invention (i.e. determining the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates (optionally in combination the presence, absence, and / or alteration of one or more asCNA in the tumor DNA wherein the method comprises step ii-e) as described herein)) can be used for determining that a subject would benefit from ceasing or altering one or more cancer treatments selected from the group consisting of a ATR inhibitor, CDK inhibitor, Chemotherapy (such as taxanes, platinum-based antineoplastic drugs and c-Met inhibitors), WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, WEE1 inhibitor, platinum-based antineoplastic drug, taxane, c-Met inhibitor, radionuclide and radiation therapy, DNMTl inhibitor, HDAC inhibitor, BET inhibitor, PI3K inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid. Alternatively, or additionally methods of the invention can be used for determining that a subject would benefit from ceasing or altering one or more cancer treatments selected from the group consisting of a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drug (in particular carboplatin)), PARP inhibitor, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid.

[0329] Examples of PARP inhibitors include olaparib, rucaparib, niraparib or talazoparib, Veliparib, Pamiparib, Rucaparib, and Veliparib; and in particular example olaparib, rucaparib, niraparib or talazoparib. Examples of ATR inhibitors include Berzosertib, ceralasertib, M4344, and BAY1895344. Examples of CDK inhibitors include Flavopiridol (alvocidib), abemaciclib, ribociclib, Olomoucine, Roscovitine (Seliciclib), Purvalanol, Paullones, Butryolactone, Thio / oxoflavopiridols, Oxindoles, Aminothiazoles, Benzocarbazoles, and Pyrimidines; and in particular Flavopiridol, Palbociclib, ribociclib and abemaciclib. Examples of DNA-PK inhibitors include AZD7648, M3814, CC-122 and CC-115. Examples of immune checkpoint therapies include PD-1 inhibitors such as pembrolizumab, nivolumab, cemiplimab, and spartalizumab; PD-L1 inhibitors such asatezolizumab, avelumab and durvalumab; and CTLA-4 inhibitors such as ipilimumab. Examples of CHK1 inhibitors include V158411, PF-477736 and AZD7762. Examples of CHK2 inhibitors include CCT241533 and Aminopyridine 7. Examples of WEE1 inhibitors include adavosertib. Examples of platinum-based antineoplastic drugs include cisplatin, carboplatin, oxaliplatin, nedaplatin, triplatin tetranitrate, picoplatin, satraplatin and phenanthriplatin, and in particular cisplatin, carboplatin, oxaliplatin, nedaplatin.

[0330] Examples of taxanes include docetaxel, cabazitaxel, and paclitaxel. Examples of radionuclide or radiation therapies include radium-223, 225Ac-Labeled PSMA-617 and 177Lu-Labeled PSMA-617. Examples of CDK inhibitors include Flavopiridol (alvocidib), abemaciclib, ribociclib, Olomoucine, Roscovitine (Seliciclib), Purvalanol, Paullones, Butryolactone, Thio / oxoflavopiridols, Oxindoles, Aminothiazoles, Benzocarbazoles, and Pyrimidines; and in particular Flavopi ridol, Palbociclib, ribociclib and abemaciclib. Examples of chemotherapies include taxanes (for example docetaxel and cabazitaxel), platinum-based antineoplastic drugs (such as cisplatin and carboplatin) and c-Met inhibitors (for example cabozantinib). Examples of Aurora kinase inhibitors include Alisertib, ZM447439, hesperidin, and VX-680. Examples of PI3K inhibitors i ncl udeidela lisib, copanlisib, duvelisib, alpelisib, umbralisib, dactolisib, voxtalisib, Taselisib, Idelalisib, Buparlisib, Duvelisib, and Copanlisib and in particular idelalisib, copanlisib, duvelisib, alpelisib, and umbralisib. Examples of mTOR inhibitors include rapamycin, deforolimus, dactolisib, voxtalisib, temsirolimus, everolimus, sapanisertib, AZD8055, and AZD2014. Examples of PORCN inhibitors include WNT974, ETC- 1922159 and CGX1321. Examples of FZD antagonists / monoclonal antibodies include Vantictumab, Ipafricept and OTSA101-DTPA-90Y. Examples of inhibitors of Wnt target genes include SM08502. Examples of LHRH agonists include leuprolide, goserelin, triptorelin, and histrelin. Examples of LHRH antagonists include degarelix. Examples of antiandrogens include flutamide, bicalutamide, nilutamide, enzalutamide, apalutamide and darolutamide. Examples of steroids include prednisone and dexamethasone. Example of DNMTl inhibitors include 5-azacitidine. Examples of HDAC inhibitors include vorinostat and romidepsin. Examples of BET inhibitors include l-BET 151, l-BET 762, OTX-015, TEN-010, CPI- 203, CPI-0610, olinone, RVX-208, ABBV-744, AZD5153, MT-1, and MS645. Examples of alkylating agents include nitrogen mustards (such as cyclophosphamide, chlormethine, uramustine, melphalan, chlorambucil, ifosfamide, and bendamustine), nitrosoureas (such as carmustine, lomustine, and streptozocin) and alkyl sulfonates (such as busulfan)).

[0331] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of AR, FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16 (in particular FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16) as defined in Table 1, the presence and / or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of AR, FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16 as defined in Table 1, indicates that the subject would benefit from ceasing or altering treatment with one or more class of drug that is known or suspected of targeting AR function. For example ceasing or altering treatment with a hormonal agent, such as LHRH agonists, LHRH antagonists, androgen blockers, anti-androgens, androgen synthesis inhibitors, estrogens and steroids (in particular androgen blockers, anti-androgens and androgen synthesis inhibitors); and in particular ceasing or altering treatment with one or more of the following cancer treatments: leuprolide, goserelin, triptorelin, histrelin, degarelix, abiraterone, ketoconazole, flutamide, bicalutamide, nilutamide, enzalutamide, apalutamide or darolutamide, estrogens prednisone or dexamethasone (in particular abiraterone, ketoconazole, flutamide, bicalutamide, nilutamide, enzalutamide, apalutamide or darolutamide).

[0332] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of AR, FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16 (in particular FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16) as defined in Table 1, the presence and / or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of AR, FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16 as defined in Table 1, indicates that the subject would benefit from treatment with a chemotherapeutic agent (for example a taxane (such as docetaxel or cabazitaxel) or a platinum-based antineoplastic drug (such as carboplatin)).

[0333] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 as defined in Table 1, the presence and / or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 as defined in Table 1, indicates that the subject would benefit from treatment with one or more class of drug that is known or suspected of targeting cell cycle perturbations. For example, one or more of an ATR inhibitor, CDK inhibitor, chemotherapy, WEE1 inhibitors, Aurora kinase inhibitors or alkylating agent; in particular one or more of Berzosertib, Berzosertib, ceralasertib, M4344, BAY1895344, Flavopiridol (alvocidib), abemaciclib, ribociclib, Olomoucine, Roscovitine (Seliciclib), Purvalanol, Paullones, Butryolactone, Thio / oxoflavopiridols, Oxindoles, Aminothiazoles, Benzocarbazoles, Pyrimidines, taxanes (for example docetaxel and cabazitaxel), c-Met inhibitors (for example cabozantinib), adavosertib, Alisertib, ZM447439, hesperidin, VX-680, nitrogen mustards (for example cyclophosphamide, chlormethine, uramustine, melphalan, chlorambucil, ifosfamide, and bendamustine), nitrosoureas (for example carmustine, lomustine, and streptozocin) and alkyl sulfonates (for example busulfan).

[0334] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CD KN 2 A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 (and in particular TP53) as defined in Table 1, the presence and / or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of AURKA, BRAF, CCND1, CDK12, CDK4, CDK6, CDKN1B, CDKN2A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 (and in particular TP53) as defined in Table 1, indicates that the subject would benefit from ceasing or altering treatment with one or more hormonal agent, such as LHRH agonists, LHRH antagonists, anti-androgens, androgen synthesis inhibitors, estrogens and steroids; and in particular ceasing or altering treatment with one or more of the following cancer treatments: leuprolide, goserelin, triptorelin, histrelin, degarelix, abiraterone, ketoconazole, flutamide, bicalutamide, nilutamide, enzalutamide, apalutamide or darolutamide, estrogens prednisone or dexamethasone.

[0335] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of ARID1A, CHD1, KDM6A, MED12, SMARCA1, KMT2C, KMT2D and RYB as defined in Table 1, and wherein the presence and / or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of ARID1A, CHD1, KDM6A, MED12, SMARCA1, KMT2C, KMT2D and RYBP as defined in Table 1, indicates that the subject would benefit from treatment with one or more class of drug that is known or suspected to target chromatin remodelling functions. For example, one or more DNMTl inhibitors, HDAC inhibitors and BET inhibitors; in particular 5-azacitidine, vorinostat, romidepsin, l-BET 151, l-BET 762, OTX-015, TEN-010, CPI-203, CPI-0610, olinone, RVX-208, ABBV-744, AZD5153, MT-1, and MS645.

[0336] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1, indicates that the subject would benefit from treatment with one or more class of drug that is known or suspected to target a DNA repair function. For example a PARP inhibitor, ATR inhibitor, DNA-PK inhibitor, immune checkpoint therapy (for example a PD-1 inhibitor, PD-L1 inhibitors, or a CTLA-4 inhibitor), CHK1 inhibitor, WEE1 inhibitor, platinum-based antineoplastic drug, or radionuclide or radiation therapy; in particular olaparib, rucaparib, niraparib or talazoparib, Veliparib, Pamiparib, Rucaparib, Veliparib, Berzosertib, ceralasertib, M4344, and BAY1895344Flavopiridol (alvocidib), abemaciclib, ribociclib, Olomoucine, Roscovitine (Seliciclib), Purvalanol, Paullones, Butryolactone, Thio / oxoflavopiridols, Oxindoles, Aminothiazoles, Benzocarbazoles, Pyrimidines, AZD7648, M3814, CC-122, CC- 115, pembrolizumab, nivolumab, cemiplimab, spartalizumab, asatezolizumab, avelumab, durvalumab, ipilimumab, V158411, PF-477736, AZD7762, CCT241533, Aminopyridine 7, adavosertib, cisplatin, carboplatin, oxaliplatin, nedaplatin, triplatin tetranitrate, picoplatin, satraplatin phenanthriplatin, radium-223, 225Ac-Labeled PSMA-617 and 177Lu-Labeled PSMA-617.

[0337] In one embodiment of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1, indicates that the subject would benefit from treatment with a PARP inhibitor, for example olaparib, rucaparib, niraparib or talazoparib, Veliparib, Pamiparib, Rucaparib, and Veliparib; and in particular olaparib, rucaparib, niraparib or talazoparib. In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of ASX LI, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1, indicates that the subject would benefit from treatment with one or more class of drug as follows: ATR inhibitor, CDK inhibitor, Chemotherapy (such as taxanes and platinum-based antineoplastic drugs), WEE1 inhibitor, Aurora kinase inhibitor, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitors, or a CTLA-4 inhibitor), CHK2 inhibitor, WEE1 inhibitors, platinum-based antineoplastic drug, taxane, radionuclide and radiation therapy, PI3K inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid.

[0338] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN as defined in Table 1, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN as defined in Table 1, indicates that the subject would benefit from treatment with one or more class of drug that is known or suspected to target the PI3K signalling pathway. For example a PI3K inhibitor or mTOR inhibitor; in particular idelalisib, copanlisib, duvelisib, alpelisib, umbralisib, dactolisib, voxtalisib, Taselisib, Idelalisib, Buparlisib, Duvelisib, Copanlisib, rapamycin, deforolimus, dactolisib, voxtalisib, temsirolimus, everolimus, sapanisertib, AZD8055, and AZD2014.

[0339] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN (and in particular PTEN) as defined in Table 1, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN (and in particular PTEN) as defined in Table 1, indicates that the subject would benefit from ceasing or altering treatment with one or more hormonal agent, such as LHRH agonists, LHRH antagonists, anti-androgens, androgen synthesis inhibitors, estrogens and steroids; and in particular ceasing or altering treatment with one or more of the following cancer treatments: leuprolide, goserelin, triptorelin, histrelin, degarelix, abiraterone, ketoconazole, flutamide, bicalutamide, nilutamide, enzalutamide, apalutamide or darolutamide, estrogens prednisone or dexamethasone.

[0340] In embodiments of the invention wherein the method comprises step ii-e) and at least one target gene-region is selected from the group consisting of APC, CTNNB1 and RNF43 as defined in Table 1, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of APC, CTNNB1 and RNF43 as defined in Table 1, indicates that the subject would benefit from treatment with one or more class of drug that is known or suspected to target the Wnt signalling pathway. For example a PORCN inhibitor, FZD antagonists / monoclonal antibody, or inhibitor of Wnt target genes; in particular WNT974, ETC-1922159, CGX1321, Vantictumab, Ipafricept, or OTSA101-DTPA-90Y.

[0341] The cancer treatments mentioned above, when used or administered in a method of the invention, may be used, for example, in those amounts indicated in the Physicians' Desk Reference (PDR) or as otherwise determined by one of ordinary skill in the art. The amount of the active ingredient of the cancer treatment which is required to achieve a therapeutic effect will, of course, vary with the particular compound, the route of administration, the subject under treatment, including the type, species, age, weight, sex, and medical condition of the subject and the renal and hepatic function of the subject, and the particular cancer being treated, as well as its severity. An ordinarily skilled physician, veterinarian or clinician can readily determine and prescribe the effective amount of the drug required to benefit the subject.

[0342] The present invention also provides a method for treating cancer in a subject comprising performing a method of the invention or performing an assay of the invention, and further comprising administering to the subject a therapeutically effective dose of a cancer treatment. A method of treatment of the present invention may be performed before and / or after a method of the invention defined herein has been performed, or an assay has been performed.

[0343] In certain embodiments a method for treating cancer of the present invention comprises administering to the subject a therapeutically effective dose of a cancer treatment after a method of the invention has been performed, or after an assay of the invention has been performed, for example after the subject has been determined to benefit from treatment with one or more cancer treatments, or has benefited, or is benefiting, from one or more cancer treatments and / or benefit from ceasing or altering one or more cancer treatments.

[0344] In one embodiment, a method for treating cancer of the present invention comprises administering a therapeutically effective dose of a cancer treatment to the subject for at least 1 week, 2 weeks, 3 weeks, 4 weeks, 1 month, 2 months, 3 months, 6 months, 9 months, 12 months, 24 months or 36 months. A therapeutic agent for the treatment of prostate cancer may be administered, for example, daily, every second day, twice per week, weekly or monthly.

[0345] A therapeutically effective dose of a cancer treatment may be administered in amounts and at frequencies indicated in the Physicians' Desk Reference (PDR) or as otherwise determined by one of ordinary skill in the art.

[0346] In certain preferred methods of the invention, the method further comprises the step of administering one or more cancer treatments that the method indicates would benefit the subject, as described herein.

[0347] In certain preferred methods of the invention, the method further comprises iv-1) determining one or more cancer treatment the subject would benefit from.

[0348] In certain embodiments, the method of the invention further comprises: v-1) treating the subject with one or more cancer treatment determined in step vi), and thereby treating the subject.

[0349] In certain very preferred embodiments, the method of the invention further comprises: iv-1) determining one or more cancer treatment the subject would benefit from; and v-1) treating the subject with one or more cancer treatment determined in step vi), and thereby treating the subject.

[0350] For example, the method of the invention further comprises: iv-1) determining one or more cancer treatment the subject would benefit from, wherein the one or more cancer treatments the subject would benefit from is a cancer treatment that step iii) indicates the subject would benefit from, has benefited, or is benefiting from, and / or would benefit from altering; and v-1) treating the subject with one or more cancer treatment determined in step vi), and thereby treating the subject.

[0351] In embodiments comprising step iv) and / or v) (for example step iv-1) and / or v-1)) preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0352] In certain preferred methods of the invention, the method of the invention further comprises: iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than an integer value between 50% and 99%, for example less than 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%. More preferably, the subject has a proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA of less than 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%, and especially less than 80%, less than 81%, or less than 85%. The two or more cancer treatments may be, for example, chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide). Additionally, or alternatively, in certain preferred methods of the invention, the method of the invention further comprises: iv-2 b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is same or greater than an integer value between 50% and 99%, for example 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater. More preferably, the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater, and especially 80% or greater, 81% or greater, 85% or greater. The one cancer treatment may, for example, be selected from a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example an anti-androgen selected from abiraterone and enzalutamide)).

[0353] In one preferred embodiment, the method of the invention further comprises: iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50% (for example a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an antiandrogen (for example, an anti-androgen selected from abiraterone and enzalutamide), and iv-2b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater (for example, administering one cancer treatment selected from a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example an anti-androgen selected from abiraterone and enzalutamide)).

[0354] In another preferred embodiment, the method of the invention further comprises iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 80% (for example a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an antiandrogen (for example, an anti-androgen selected from abiraterone and enzalutamide), and iv-2b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 80% or greater (for example, administering one cancer treatment selected from a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example an anti-androgen selected from abiraterone and enzalutamide)).

[0355] In another preferred embodiment, the method of the invention further comprises iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 81% (for example a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an antiandrogen (for example, an anti-androgen selected from abiraterone and enzalutamide), and iv-2b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 81% or greater (for example, administering one cancer treatment selected from a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example an anti-androgen selected from abiraterone and enzalutamide)).

[0356] In another preferred embodiment, the method of the invention further comprises iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 85% (for example a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an antiandrogen (for example, an anti-androgen selected from abiraterone and enzalutamide), and iv-2b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 85% or greater (for example, administering one cancer treatment selected from a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example an anti-androgen selected from abiraterone and enzalutamide)).

[0357] In another preferred embodiment, the method of the invention further comprises iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 87% (for example a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an antiandrogen (for example, an anti-androgen selected from abiraterone and enzalutamide), and iv-2b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 87% or greater (for example, administering one cancer treatment selected from a chemotherapy (such as a taxane (for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example an anti-androgen selected from abiraterone and enzalutamide)).

[0358] In embodiments comprising step iv-2a) and / or iv-2b), preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0359] In certain preferred methods of the invention, the method of the invention further comprises iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than an integer value between 50% and 99%, for example less than 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%. More preferably, the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50%, less than 60%, less than 70%, less than 75%, less than 80%, less than 81%, less than 85%, less than 90% or less than 95%, and especially less than 80%, less than 81%, or less than 85%. For example, step iv-3a) may comprise administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example an anti-androgen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment). The method may optionally also comprise administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received.

[0360] Additionally, or alternatively, in certain preferred methods of the invention, the method of the invention further comprises iv-3 b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is same or greater than an integer value between 50% and 99%, for example 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater. More preferably, the gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater, 60% or greater, 70% or greater, 75% or greater, 80% or greater, 81% or greater, 85% or greater, 90% or greater or 95% or greater, and especially 80% or greater, 81% or greater, 85% or greater. The drug class may be, for example, a chemotherapy (such as a taxane), and optionally the treatment is selected from docetaxel and cabazitaxel; or the drug class may be an anti-androgen, and optionally the treatment is selected from abiraterone and enzalutamide. In one preferred embodiment, the method of the invention further comprises iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50% (for example, administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example an antiandrogen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment); and optionally also administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received); and iv-3 b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater (for example, wherein the drug class is a chemotherapy (such as a taxane) and optionally wherein the treatment is selected from docetaxel and cabazitaxel; or wherein the drug class is an anti-androgen and optionally wherein the treatment is selected from abiraterone and enzalutamide).

[0361] In another preferred embodiment, the method of the invention further comprises iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 80% (for example, administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example an antiandrogen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment); and optionally also administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received); and iv-3b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 80% or greater (for example, wherein the drug class is a chemotherapy (such as a taxane) and optionally wherein the treatment is selected from docetaxel and cabazitaxel; or wherein the drug class is an anti-androgen and optionally wherein the treatment is selected from abiraterone and enzalutamide).

[0362] In another preferred embodiment, the method of the invention further comprises iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 81% (for example, administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example an antiandrogen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment); and optionally also administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received); and iv-3 b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 81% or greater (for example, wherein the drug class is a chemotherapy (such as a taxane) and optionally wherein the treatment is selected from docetaxel and cabazitaxel; or wherein the drug class is an anti-androgen and optionally wherein the treatment is selected from abiraterone and enzalutamide). In another preferred embodiment, the method of the invention further comprises iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 85% (for example, administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example an antiandrogen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment); and optionally also administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received); and iv-3 b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 85% or greater (for example, wherein the drug class is a chemotherapy (such as a taxane) and optionally wherein the treatment is selected from docetaxel and cabazitaxel; or wherein the drug class is an anti-androgen and optionally wherein the treatment is selected from abiraterone and enzalutamide).

[0363] In another preferred embodiment, the method of the invention further comprises iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 87% (for example, administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example an antiandrogen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment); and optionally also administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received); and iv-3b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 87% or greater (for example, wherein the drug class is a chemotherapy (such as a taxane) and optionally wherein the treatment is selected from docetaxel and cabazitaxel; or wherein the drug class is an anti-androgen and optionally wherein the treatment is selected from abiraterone and enzalutamide).

[0364] In embodiments comprising step iv-3a) and / or iv-3 b), preferably step ii) of the method of the invention comprises determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each gene-region has an asCNA.

[0365] The present invention also provides a method for treating a subject having a cancer (for example prostate cancer or metastatic cancer) with cancer therapy, the method comprising: performing a method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer of the present invention, or performing an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject of the present invention, administering to the subject determined to benefit from treatment with one or more cancer treatments, or has benefited, or is benefiting, from one or more cancer treatments, a therapeutically effective dose of a cancer treatment, thereby treating the subject.

[0366] A cancer treatment may be selected from the group consisting of a ATR inhibitor, CDK inhibitor, Chemotherapy (such as taxanes and platinum-based antineoplastic drugs), WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, WEE1 inhibitor, platinum-based antineoplastic drug, taxane, c- Met inhibitor, radionuclide and radiation therapy, DNMT1 inhibitor, HDAC inhibitor, BET inhibitor, PI3K inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, antiandrogen, androgen synthesis inhibitor, estrogen or steroid. In certain embodiments a cancer treatment may be selected from the group consisting of a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drug (in particular carboplatin)), PARP inhibitor, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid.

[0367] The present invention also provides a method of treating a subject in need of treatment with chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel) (for example a subject having cancer, prostate cancer and / or metastatic cancer), comprising performing a method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer of the present invention, or performing an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject of the present invention, administering to a subject determined to benefit from treatment with a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel), has benefited, or is benefiting, from treatment with a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel), a therapeutically effective dose of a treatment with a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel), and thereby treating the subject.

[0368] The present invention also provides a method of treating a subject in need of treatment with an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide) (for example a subject having cancer, prostate cancer or metastatic cancer), comprising performing a method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer of the present invention, or performing an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject of the present invention, administering to a subject determined to benefit from treatment with an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide), has benefited, or is benefiting, from treatment with an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide), a therapeutically effective dose of a treatment with an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide), and thereby treating the subject.

[0369] Alternatively, or additionally, the present invention also provides a method for treating a subject having a cancer (for example prostate cancer and / or metastatic cancer) with cancer therapy, the method comprising: performing a method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer of the present invention, or performing an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject of the present invention, administering to the subject determined to benefit from ceasing or altering (e.g. changing the dose or frequency of the dosing) a therapeutically effective dose of an alternative cancer treatment and / or an adjusted dose of a cancer treatment, thereby treating the subject.

[0370] An alternative cancer treatment may be selected from the group consisting of a ATR inhibitor, CDK inhibitor, Chemotherapy (such as taxanes and platinum-based antineoplastic drugs), WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, WEE1 inhibitor, platinum-based antineoplastic drug, taxane, radionuclide and radiation therapy, DNMTl inhibitor, HDAC inhibitor, BET inhibitor, PI3K inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid. In certain embodiments an alternative cancer treatment may be selected from the group consisting of a chemotherapy (such as a taxane (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drug (in particular carboplatin)), PARP inhibitor, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid.

[0371] The present invention also provides a method of treating a subject in need of treatment with a PARP inhibitor (for example a subject having cancer, prostate cancer and / or metastatic cancer), comprising performing a method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer of the present invention, or performing an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject of the present invention, administering to a subject determined to benefit from treatment with a PARP inhibitor, has benefited, or is benefiting, from treatment with a PARP inhibitor, a therapeutically effective dose of a treatment with a PARP inhibitor, and thereby treating the subject. A PARP inhibitor may be selected form the group consisting of olaparib, rucaparib, niraparib or talazoparib, Veliparib, Pamiparib, Rucaparib, and Veliparib; and in particular olaparib, rucaparib, niraparib or talazoparib.

[0372] In such embodiments, the method preferably comprises steps ii-a) to ii-e), and preferably at least one, at least 2, at least 3, at least 5, at least 6, at least 10, at least 15 or at least 20 target gene-regions is / are selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C. In such embodiments, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1, indicates that the subject would benefit from treatment with a PARP inhibitor, for example olaparib, rucaparib, niraparib or talazoparib, Veliparib, Pamiparib, Rucaparib, and Veliparib; and in particular olaparib, rucaparib, niraparib or talazoparib. The present invention also provides a method of treating a subject in need of treatment with an ATR inhibitor (for example a subject having cancer, prostate cancer and / or metastatic cancer), comprising performing a method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer of the present invention, or performing an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject of the present invention, administering to a subject determined to benefit from treatment with an ATR inhibitor, has benefited, or is benefiting, from treatment with an ATR inhibitor, a therapeutically effective dose of a treatment with an ATR inhibitor, and thereby treating the subject. An ATR inhibitor may be Berzosertib, ceralasertib, M4344, and BAY1895344, and in particular Berzosertib and ceralasertib.

[0373] In such embodiments, the method preferably comprises steps ii-a) to ii-e), and preferably at least one, at least 2, at least 3, at least 5, at least 6, at least 10, at least 15, at least 20, at least 30 or at least 35 of target gene-regions is / are selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B, RAD51C, ASXL1, CLU, CYLD, ERG_TMPRSS2, GN AS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3. In such embodiments, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B, RAD51C, ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1, indicates that the subject would benefit from treatment with a ATR inhibitor, for example Berzosertib, ceralasertib, M4344, and BAY1895344, and in particular Berzosertib and ceralasertib.

[0374] The present invention also provides a method of treating a subject in need of treatment with an immune checkpoint therapy (for example a subject having cancer, prostate cancer or metastatic cancer), comprising performing a method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of prostate cancer of the present invention, or performing an in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject of the present invention, administering to a subject determined to benefit from treatment with an immune checkpoint therapy, has benefited, or is benefiting, from treatment with an immune checkpoint therapy, a therapeutically effective dose of a treatment with an immune checkpoint therapy, and thereby treating the subject. An immune checkpoint therapy may be a PD-1 inhibitor such as pembrolizumab, nivolumab, cemiplimab, and spartalizumab; a PD-L1 inhibitor such asatezolizumab, avelumab and durvalumab; or CTLA-4 inhibitor such as ipilimumab.

[0375] In such embodiments, the method preferably comprises steps ii-a) to ii-e), and preferably at least one, at least 2, at least 3, at least 5, at least 6, at least 10, at least 15, at least 20, at least 30 or at least 35 of target gene-regions is / are selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B, RAD51C, ASXL1, CLU, CYLD, ERG_TMPRSS2, GN AS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3. In such embodiments, the presence or alteration of one or more asCNA (and / or the presence of one or more somatic and / or germline mutations) in a target gene-region selected from the group consisting of ATM, ATR, BRCA1, BRCA2, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B, RAD51C, ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH1, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1, indicates that the subject would benefit from treatment with an immune checkpoint therapy, for example a PD-1 inhibitor such as pembrolizumab, nivolumab, cemiplimab, and spartalizumab; a PD-L1 inhibitor such asatezolizumab, avelumab and durvalumab; or CTLA-4 inhibitors such as ipilimumab.

[0376] The listing or discussion of a prior-published document in this specification should not necessarily be taken as an acknowledgement that the document is part of the state of the art or is common general knowledge. In embodiments herein, the word "comprising" may be interpreted as requiring the features mentioned, but not limiting the presence of other features. Alternatively, the word "comprising" may also relate to the situation where only the components / features listed are intended to be present (e.g. the word "comprising" may be replaced by the phrases "consists of" or "consists essentially of"). It is explicitly contemplated that both the broader and narrower interpretations can be applied to all aspects and embodiments of the present invention. In other words, the word "comprising" and synonyms thereof may be replaced by the phrase "consisting of" or the phrase "consists essentially of" or synonyms thereof and vice versa.

[0377] Unless otherwise stated, the singular forms "a", "an", and "the" include the plural reference, and as used herein, the term "and / or" means "and" or "or", or both. The term "about" in the context of a numerical value refer to a range of numerical values (e.g. ± 5% to 10% of the recited value) that those skilled in the art would consider equivalent to the recited value. Numerical ranges can be expressed herein as from "about" one particular value, and / or to "about" another particular value. When such a range is expressed, the range is inclusive of the recited values.

[0378] Equivalents:

[0379] The invention has been described broadly and generically herein. Those of ordinary skill in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and / or configurations will depend upon the specific application or applications for which the teachings of the present invention is / are used. Those skilled in the art will recognize, or be able to ascertain using no more than routine experimentation, many equivalents to the specific embodiments of the invention described herein. It is, therefore, to be understood that the foregoing embodiments are presented by way of example only and that, within the scope of the appended claims and equivalents thereto, the invention may be practiced otherwise than as specifically described and claimed. The present invention is directed to each individual feature, system, article, material, kit, and / or method described herein. In addition, any combination of two or more such features, systems, articles, materials, kits, and / or methods, if such features, systems, articles, materials, kits, and / or methods are not mutually inconsistent, is included within the scope of the present invention. Further, each of the narrower species and subgeneric groupings falling within the generic disclosure also form part of the invention. This includes the generic description of the invention with a proviso or negative limitation removing any subject matter from the genus, regardless of whether or not the excised material is specifically recited herein.

[0380] Incorporation by Reference:

[0381] The contents of the articles, patents, and patent applications, and all other documents and electronically available information mentioned or cited herein, are hereby incorporated by reference in their entirety to the same extent as if each individual publication was specifically and individually indicated to be incorporated by reference. The applicant reserves the right physically to incorporate into this application any and all materials and information from any such articles, patents, patent applications, or other physical and electronic documents.

[0382] The following Examples illustrate the invention.

[0383] Example 1

[0384] Materials and Methods

[0385] Clinical cohorts

[0386] Patients with advanced CRPC and candidates for cabazitaxel treatment were enrolled in the IRSTB030 biomarker prospective multicentre trial (IRB-approved protocol; NCT03381326). Main inclusion criteria were histologically confirmed diagnosis of prostate cancer, advanced or metastatic castration resistant disease progressing to treatment, prior treatment with docetaxel and candidate for cabazitaxel treatment by physician's choice. Cabazitaxel was administered intravenously over a period of 1 hour every 3 weeks, at a dose of 25 mg per square meter of body-surface area. Patients also received oral prednisone at a dose of 10 mg daily. Dose reductions were allowed from cycle 1 or later, according to physician's choice. The study was conducted in accordance with the Declaration of Helsinki and the Good Clinical Practice guidelines of the International Conference of Harmonization. Written informed consent for treatment and study procedures was obtained from all patients. Serum PSA was evaluated within 3 days prior to each treatment cycle. Radiographic disease was assessed with the use of total body computed...

Claims

Claims1. An in vitro method for staging, classification, screening, stratification, monitoring, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of cancer in a subject, said method comprising the steps of: i) providing a biological sample obtained from the subject, wherein said sample comprises tumor DNA; ii) determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 and Table 2 in the tumor DNA; iii) determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value; wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

2. The method of claim 1, wherein step i) further comprises providing a biological sample obtained from the subject, wherein said sample comprises non-tumor DNA; and wherein step ii) of determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 and Table 2 in the tumor DNA comprises the steps of: ii-a) detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 or Table 2 for each of at least 5 gene-regions defined in Table 1 and Table 2;ii-b) identifying which of the SNPs present are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA for the subject; ii-c-1) determining the allelic imbalance for each gene-region of the tumor DNA by reference to the iSNPs for the subject in each gene-region; ii-c-2) determining the copy number for each gene-region in the tumor DNA; and ii-d) analysing the allelic imbalance and copy number for each gene-region gene-region, to determine the allele-specific copy number value of each allele of each gene-region.

3. The method of claim 1 or 2, wherein step i) further comprises providing a biological sample obtained from the subject, wherein said sample comprises non-tumor DNA; and wherein step ii) of determining the allele-specific copy number value of each allele for each of at least 5 target gene-regions defined in Table 1 in the tumor DNA comprises the steps of: ii-a) detecting the presence of single nucleotide polymorphisms (SNPs) in the non-tumor DNA at: at least 5% of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1, and optionally at least 5% of the SNP loci defined in Table 2 for each of at least 3 control gene-regions defined in Table 2; ii-b) identifying which of the SNPs present are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA for the subject; ii-c-1) determining the allelic imbalance for each target gene-region, and optionally for each control gene-region, of the tumor DNA by reference to the iSNPs for the subject in each gene-region; ii-c-2) determining the copy number for each target gene-region, and optionally for each control gene-region, in the tumor DNA; andii-d) analysing the allelic imbalance and copy number for each target gene-region, and optionally for each control gene-region, to determine the allele-specific copy number value of each allele of each target gene-region.

4. The method of claim 2 or 3 wherein step ii-c-2) further comprises a step of estimating the tumor content (TC) of the sample comprising tumor DNA and / or estimating the ploidy of the sample comprising tumor DNA.

5. The method of any preceding claim, wherein step ii) further comprises determining the presence, absence, and / or alteration of one or more allele-specific copy number aberration (asCNA) at each gene-region in the tumor DNA; and wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA, and the presence, absence, and / or alteration of one or more asCNA in the tumor DNA, indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject; for example, wherein the method comprises steps ii-a) to ii-d) as defined in claim 2 or claim 3, and the method further comprises the step of ii-e) analysing the allelic imbalance and copy number for each gene-region (for example for each target gene-region and / or for each control gene-region), to determine the presence, absence, and / or alteration of one or more allele-specific copy number aberration (asCNA) at each gene-region in the tumor DNA; and wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA, and the presence, absence, and / or alteration of one or more asCNA in the tumor DNA, indicates thatthe subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments, would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

6. The method of any preceding claim wherein step ii) comprises determining the allelespecific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA, wherein in the tumor DNA at least one allele of each generegion has an allele-specific copy number aberration (asCNA).

7. The method of any preceding claim wherein the biological sample comprising non-tumor DNA is a blood sample, urine sample, saliva sample, tissue sample, or cerebral spinal fluid sample obtained from the subject, and / or wherein the biological sample comprising nontumor DNA comprises non-tumor cell free DNA (non-tumor cfDNA).

8. The method of any one of claims 2 to 7, wherein the method comprises steps ii-a) to ii-d) as defined in claim 2 or claim 3, wherein the biological sample comprising tumor DNA and the biological sample comprising non-tumor DNA are the same sample, for example, a blood sample comprising both tumor DNA and non-tumor DNA, for example a plasma sample comprising circulating tumor DNA (ctDNA) and non-tumor cfDNA.

9. The method of any preceding claim, wherein the biological sample comprising tumor DNA is a blood sample, urine sample, tissue sample or cerebral spinal fluid sample obtained from the subject, and / or wherein the biological sample comprising tumor DNA comprises ctDNA (for example wherein the biological sample is a plasma sample comprising cfDNA, for example a plasma sample comprising ctDNA).

10. The method of any one of claims 2 to 9, wherein the method comprises steps ii-a) to ii-d) as defined in claim 2 or claim 3, wherein an iSNP is a SNP that is heterozygous in the nontumor DNA for the subject and has an allelic fraction (AF) of between about 0.05 to about 0.95, for example an AF of between about 0.2 to about 0.8.

11. The method of any preceding claim, wherein the subject is known or suspected of suffering from one or more of the cancers selected from the group consisting of prostate cancer (for example castration-resistant prostate cancer), breast cancer, ovarian cancer, pancreatic cancer, bladder cancer, and metastatic cancer; and in particular prostate cancer (for example castration-resistant prostate cancer, hormone sensitive prostate cancer, and / or metastatic prostate cancer); and / or wherein the biological sample obtained from the subject comprising tumor DNA is obtained before the subject has undergone a treatment for cancer, during the subject is undergoing a treatment for cancer, or after a subject has undergone treatment for cancer.

12. The method of any preceding claim, wherein the biological sample has a tumor content of at least about 1%, at least about 2%, at least about 3%, at least about 4%, at least about 5%, at least about 10%, at least about 15%, or at least about 20%, wherein the tumor content is the percentage of DNA molecules in the biological sample that are tumor DNA molecules; for example wherein the biological sample has a tumor content of at least about 20%.

13. The method of any one of claims 2 to 12, wherein the method comprises steps ii-a) to ii- d) as defined in claim 2 or claim 3, wherein step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80% of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1, and / orand at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80% of theSNP loci defined in Table 2 for each of at least 5 control gene-regions defined in Table 2; or wherein the method comprises steps ii-a) to ii-d) as defined in claim 2 or claim 3, wherein step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80% of the SNP loci defined in Table 1 for each of at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1, and / or at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80% of the SNP loci defined in Table 1 for each of at least 10, at least 20, at least 30, or all of the control gene-regions defined in Table 2.

14. The method of any one of claims 2 to 13, wherein the method comprises steps ii-a) to ii- d) as defined in claim 2 or claim 3, wherein step ii-a) comprises detecting the presence of SNPs in the genomic non-tumor DNA at target gene-regions and / or at control gene-regions.

15. The method of any preceding claim, wherein if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen, and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to thesubject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments; or if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 80%, that indicates that the subject would benefit from treatment with two or more cancer treatments and / or the subject would benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen, and if the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 80% or greater, that indicates that the subject would benefit from treatment with one cancer treatment and / or the subject would benefit from a treatment that they have previously received and / or would not benefit from adding one or more further cancer treatments to the subject's treatment regimen, and / or the subject is benefiting from one or more cancer treatments.

16. The method of any preceding claim, wherein the method further comprises the step of: iv-1) determining one or more cancer treatment the subject would benefit from; and optionally wherein the method further comprises the step of: v-1) administering one or more cancer treatment determined in step iv-1) to the subject, and thereby treating the subject.

17. The method of any preceding claim, wherein the method further comprises the step of: iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50% (for example, administering a chemotherapy (such as a taxane, for example, a taxane selected from docetaxel andcabazitaxel) and an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide)), and iv-2b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater (for example, administering one cancer treatment selected from a chemotherapy (such as a taxane, for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide)); or iv-2a) administering two or more cancer treatments when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 80% (for example, a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) and an antiandrogen (for example an anti-androgen selected from abiraterone and enzalutamide)), and iv-2b) administering one cancer treatment when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 80% or greater (for example, administering one cancer treatment selected from a chemotherapy (such as a taxane, for example, a taxane selected from docetaxel and cabazitaxel) and an anti-androgen (for example, an anti-androgen selected from abiraterone and enzalutamide)).

18. The method of any preceding claim, wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previously received.

19. The method of any preceding claim, wherein the method further comprises the step of: iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions withan allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 50% (for example, administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example, an antiandrogen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment); and optionally also administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received), and iv-3 b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 50% or greater (for example wherein the drug class is a chemotherapy (such as a taxane) and optionally wherein the treatment is selected from docetaxel and cabazitaxel; or wherein the drug class is an anti-androgen and optionally wherein the treatment is selected from abiraterone and enzalutamide); or iv-3a) administering one or more cancer treatments that are in a different drug class to treatment(s) the subject has previously received when the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is less than 80% (for example administering one or more cancer treatments that is a chemotherapy (such as a taxane, for example a taxane selected from docetaxel and cabazitaxel) wherein the subject has not previously received a chemotherapy (such as a taxane) treatment, and / or an anti-androgen (for example an antiandrogen is selected from abiraterone and enzalutamide) wherein the subject has not previously received an anti-androgen treatment); and optionally also administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received), and iv-3 b) administering one or more cancer treatments that are the same treatment(s), or treatment(s) in the same drug class, as a treatment(s) the subject has previous received when the proportion of gene-regions with an allele-specific copy number value of at least0.1 more or at least 0.1 less than the closest integer value in the tumor DNA is 80% or greater (for example wherein the drug class is a chemotherapy (such as a taxane) and optionally wherein the treatment is selected from docetaxel and cabazitaxel; or wherein the drug class is an anti-androgen and optionally wherein the treatment is selected from abiraterone and enzalutamide).

20. The method of any preceding claim, wherein at least one gene-region is selected from the group consisting of FOXA1, FOXP1, HSD3B1, NCOA2 and ZBTB16 as defined in Table 1; and / or at least one target gene-region is selected from the group consisting of as AURKA, BRAF, CCND1, CD KI 2, CDK4, CDK6, CD KN IB, CD KN 2 A, CUL1, FBXW7, KRAS, MDM2, MDM4, MYC, MYCN, RBI and TP53 defined in Table 1; and / or at least one gene-region is selected from the group consisting of ARID1A, CHD1, KMT2C, KMT2D and RYBP as defined in Table 1; and / or at least one gene-region is selected from the group consisting of ATM, ATR, BRCA1, BRCA2, CHD1, ERCC1, ERCC2, ERCC3, ERCC4, ERCC5, FANCA, FANCC, FANCD2, FANCE, FANCF, FANCG, MLH1, MSH2, MSH6, PALB2, RAD51B and RAD51C as defined in Table 1; and / or at least one gene-region is selected from the group consisting of AKT1, AKT2, AKT3, MET, PIK3CA, PIK3CB, PIK3R1 and PTEN as defined in Table 1; and / or at least one gene-region is selected from the group consisting of ASXL1, CLU, CYLD, ERG_TMPRSS2, GNAS, IDH2, NFE2L2, NKX3-1, RUNX1, SPOP and ZFHX3 as defined in Table 1; and / or at least one gene-region is selected from the group consisting of APC, CTNNB1 and RNF43 as defined in Table 1; and / or at least one gene-region is selected from the group consisting of PIK3CB and RAD51B as defined in Table 1; and / or at least one gene-region is selected from the group consisting of MYC, AR, NCOA2, NKX3-1,PTEN, MDM4 and BRIP1 as defined in Table 1; and / orat least one gene-region is selected from the group consisting of MYC, NCOA2, NKX3-1,MDM4, BRIP1, AURKA, AR, PTEN, PIK3CB and TP53 as defined in Table 1; and / or at least one gene-region is selected from the group consisting of TP53, AR and ARID1A as defined in Table 1; and / or at least one gene-region is selected from the group consisting of TP53, AR, F0XA1 ARID1A, APC, BRCA2 and MED12 as defined in Table 1; and / or at least one gene-region is selected from the group consisting of CHEK2 and HDAC2 as defined in Table 1; and / or at least one gene-region is selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1; or wherein at least 3 of the gene-regions are selected from the group consisting of BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1; or wherein 6 of the gene-regions are BRCA2, ATM, RBI, NKX3-1, TP53, and PTEN as defined in Table 1.

21. The method of any preceding claim, wherein step ii) further comprises ii-c-3) detecting in the tumor DNA the presence of somatic and / or germline mutations in the exonic region of one or more target gene-region defined in Table 1; and optionally detecting in the tumor DNA the presence of somatic and / or germline mutations in the exonic region of one or more of gene selected from the group consisting of AR, MED12, SMARCA1, IDH1 and KDM6A; wherein the presence of one or more somatic and / or germline mutations in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments, has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments.

22. The method of any preceding claim, wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates (optionally in combination with the presence, absence, and / or alteration of one or more asCNA in the tumor DNA wherein the method comprises a step as defined in claim 6) that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen) selected from the group consisting of, ATR inhibitor, CDK inhibitor, Chemotherapy, WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, platinum-based antineoplastic drug, taxane, radionuclide and radiation therapy, PI3K inhibitor, mTOR inhibitor, PORCN inhibitor, DNMTl inhibitor, HDAC inhibitor, BET inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid (for example one or more cancer treatments selected from the group consisting of a chemotherapy (such as taxanes (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drugs (in particular carboplatin)), PARP inhibitors, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid), has benefited, or is benefiting, from one or more cancer treatments selected from the group consisting of ATR inhibitor, CDK inhibitor, Chemotherapy, WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, platinum-based antineoplastic drug, taxane, radionuclide and radiation therapy, PI3K inhibitor, mTOR inhibitor, DNMTl inhibitor, HDAC inhibitor, BET inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid (for example one or more cancer treatments selected from the group consisting of a chemotherapy (such as taxanes (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drugs (in particular carboplatin)), PARP inhibitors, orhormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid), and / or would benefit from ceasing or altering one or more cancer treatments selected from the group consisting of ATR inhibitor, CDK inhibitor, Chemotherapy, WEE1 inhibitor, Aurora kinase inhibitor, alkylating agent, PARP inhibitor, DNA-PK inhibitor, immune checkpoint therapies (for example a PD-1 inhibitor, PD-L1 inhibitor, or a CTLA-4 inhibitor), CHK2 inhibitor, platinum-based antineoplastic drug, taxane, radionuclide and radiation therapy, PI3K inhibitor, mTOR inhibitor, DNMTl inhibitor, HDAC inhibitor, BET inhibitor, PORCN inhibitor, FZD antagonists / monoclonal antibody, inhibitor of Wnt target genes, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid (for example one or more cancer treatments selected from the group consisting of a chemotherapy (such as taxanes (in particular docetaxel and cabazitaxel) and platinum-based antineoplastic drugs (in particular carboplatin)), PARP inhibitors, or hormonal agent, such as a LHRH agonist, LHRH antagonist, anti-androgen, androgen synthesis inhibitor, estrogen or steroid).

23. The method of claim 5 to 22, wherein the method comprises a step of determining the presence, absence, and / or alteration of one or more allele-specific copy number aberration (asCNA) at each gene-region in the tumor DNA as defined claim 5 (for example wherein the method comprises step ii-e) as defined claim 5), wherein the asCNA is a balanced copy number gain, unbalanced copy number gain, a mono-allelic copy number loss, bi-allelic copy number loss, or a loss of heterozygosity other than mono-allelic deletion (for example a copy number-neutral loss of heterozygosity).

24. The method of any preceding claim, further comprisingI) providing a further biological sample obtained from the subject during or after the subject has undergone a treatment for cancer, wherein said sample comprises tumor DNA;II) performing steps ii) to iii) of any preceding claim using the further biological sample provided in step I) (for example performing steps ii-a) to ii-d) and iii) of any one of claims 2 to 25 using the further biological sample provided in step I); wherein a change in the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the further biological sample comprising tumor DNA compared to the biological sample comprising tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

25. The method of any one of claims 2 to 24, wherein the method comprises steps ii-a) to ii- d) as defined in claim 3, wherein step ii-a) comprises detecting the presence of SNPs in the non-tumor DNA at: at least 30, preferably at least 90, of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 20, at least 30, or all of the target gene-regions defined in Table 1; and / or at least 30, preferably at least 90, of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 20, at least 30, or all of the control gene-regions defined in Table 2.

26. An in vitro assay for staging, classification, screening, monitoring, stratification, selecting treatment for, ascertaining whether treatment is working in, and / or prognostication of a cancer in a subject, said in vitro assay comprising the method steps of: a) providing a biological sample obtained from the subject, wherein said sample comprises tumor DNA;b) determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA; c) determining the proportion of gene-regions that have an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value; wherein the proportion of gene-regions with an allele-specific copy number value of at least 0.1 more or at least 0.1 less than the closest integer value in the tumor DNA indicates that the subject would benefit from treatment with one or more cancer treatments (for example benefit from a treatment that they have previously received, benefit from a treatment that they have not previously received and / or benefit from adding one or more further cancer treatments to the subject's treatment regimen), has benefited, or is benefiting, from one or more cancer treatments and / or would benefit from ceasing or altering one or more cancer treatments, and / or indicates the prognosis for the subject.

27. An in vitro assay as claimed 26, wherein step a) further comprises providing a biological sample obtained from the subject, wherein said sample comprises non-tumor DNA; and wherein step b) of determining the allele-specific copy number value of each allele for each of at least 5 gene-regions defined in Table 1 or Table 2 in the tumor DNA comprises the steps of: b-1) providing a set of probes, wherein said set of probes are capable of specifically hybridizing to: at least 5% of the SNP loci defined in Table 1 or Table 2 for each of at least 5 gene-regions defined in Table 1 and Table 2; b-2) contacting the biological sample comprising non-tumor and / or tumor DNA with the set of probes under conditions suitable for one or more of the probes to specifically hybridize to a SNP locus in the non-tumor and / or tumor DNA; b-3) capturing the non-tumor DNA and / or tumor DNA in the biological sample that has hybridized to one or more of the probes, and determining the nucleotide sequence of the captured DNA;b-4) analysing the nucleotide sequence of the captured non-tumor DNA to identify which of the SNPs present in the non-tumor DNA are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA for the subject; b-5) analysing the nucleotide sequence of the captured tumor DNA to determine the allelic imbalance for each gene-region of the tumor DNA by reference to the iSNPs for the subject in each gene-region; and determining the copy number for each gene-region in the tumor DNA; and b-6) analysing the allelic imbalance and copy number for each gene-region to determine the allele-specific copy number value of each allele of each gene-region.

28. An in vitro assay as claimed 26 or T1 , wherein step a) further comprises providing a biological sample obtained from the subject, wherein said sample comprises non-tumor DNA; and wherein step b) of determining the allele-specific copy number value of each allele for each of at least 5 target gene-regions defined in Table 1 in the tumor DNA comprises the steps of: b-1) providing a set of probes, wherein said set of probes are capable of specifically hybridizing to: at least 5% of the SNP loci defined in Table 1 for each of at least 5 target gene-regions defined in Table 1, and optionally at least 5% of the SNP loci defined in Table 2 for each of at least 3 control gene-regions defined in Table 2; b-2) contacting the biological sample comprising non-tumor and / or tumor DNA with the set of probes under conditions suitable for one or more of the probes to specifically hybridize to a SNP locus in the non-tumor and / or tumor DNA; b-3) capturing the non-tumor DNA and / or tumor DNA in the biological sample that has hybridized to one or more of the probes, and determining the nucleotide sequence of the captured DNA;b-4) analysing the nucleotide sequence of the captured non-tumor DNA to identify which of the SNPs present in the non-tumor DNA are informative SNPs (iSNPs) for the subject, wherein an iSNP is a SNP that is heterozygous in the non-tumor DNA for the subject; b-5) analysing the nucleotide sequence of the captured tumor DNA to determine the allelic imbalance for each target gene-region, and optionally for each control gene-region, of the tumor DNA by reference to the iSNPs for the subject in each gene-region; and determining the copy number for each target gene-region, and optionally for each control gene-region, in the tumor DNA; and b-6) analysing the allelic imbalance and copy number for each target gene-region, and optionally for each control gene-region, to determine the allele-specific copy number value of each allele of each target gene-region.

29. The assay of claim T1 or 28, wherein step b-3) further comprises amplifying the captured DNA using a polymerase chain reaction, and / or wherein step b-5) comprises determining the nucleotide sequences of the amplified DNA by using a next generation sequencing technique selected from the group consisting of Polony sequencing, 454 pyrosequencing, Combinatorial probe anchor synthesis, SOLiD sequencing, Ion Torrent semiconductor sequencing, DNA nanoball sequencing, Heliscope single molecule sequencing, Single molecule real time (SMRT) sequencing, Nanopore DNA sequencing, Microfluidic Sanger sequencing and Illumina dye sequencing; and optionally wherein step f) further comprises a step of removing the duplicate nucleotide sequence reads from the sequencing data obtained for the captured DNA; and optionally wherein steps b-4) and b-5) are performed using the DNA derived from amplifying the DNA captured by one or more probes, and / or optionally wherein step b-5) further comprises aligning the nucleotide sequence reads for each amplified DNA molecule with a reference genome, for example the humanGlKv37 reference genome or genomic DNA sequence derived from a sample of white blood cells obtained from the subject.

30. The assay of any one of claims 1 to 29 wherein step b-1) comprises providing a set of probes, wherein said set of probes is capable of specifically hybridizing to: at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80% of the SNP loci defined in Table 1 for each of at least 10, at least 25, at least 50, or all of the target gene-regions defined in Table 1; and / or at least 30, preferably at least 90, of the SNP loci defined in Table 1 for each of at least 5, at least 10, at least 20, at least 30, or all of the target gene-regions defined in Table 1; and / or at least 10%, at least 20%, at least 30%, at least 40%, at least 60%, or at least 80% of the SNP loci defined in Table 1 for each of at least 10, at least 20, at least 30, or all of the control gene-regions defined in Table 2; and / or at least 30, preferably at least 90, of the SNP loci defined in Table 2 for each of at least 5, at least 10, at least 20, at least 30, or all of the control gene-regions defined in Table 2.

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