Biomarkers for identifying patients having tumors with homologous recombination deficiency

Abstract

The present disclosure relates to biomarkers for identifying patients having tumors with homologous recombination deficiency (i.e., BRCAness patient) responsive to DNA damaging agent treatment.

Description

[0001] BIOMARKERS FOR IDENTIFYING PATIENTS HAVING TUMORS WITH HOMOLOGOUS RECOMBINATION DEFICIENCY

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to biomarkers for identifying patients having tumors with homologous recombination deficiency (i.e., BRCAness patient) responsive to DNA damaging agent treatment.

[0004] BACKGROUND ART

[0005] The intricate role of genetic predisposition, specifically BRCA1 and BRCA2, in oncology has significantly evolved in recent years, with mounting evidence pointing towards their essential function in the tumorigenic process. BRCA genes, typically functioning in maintaining genomic integrity, are involved in the repair of double-strand breaks (DSBs) via homologous recombination repair (HRR). The impairment of these mechanisms, a condition known as homologous repair deficiency (HRD), has been associated with the pathogenesis of a number of cancers. The concept of synthetic lethality, where the simultaneous malfunction of two or more genes results in cell death, provides a potential therapeutic approach for BRCA-associated cancers.

[0006] Sensitivity of BRCA-deficient tumors to certain therapeutic agents, particularly alkylating agents and PARP inhibitors, has revolutionized oncological treatments, leading to major advances in the management of breast and ovarian cancers. Recently, the benefits of such therapies have extended into the adjuvant setting, underscoring the urgent need for reliable, fast, and reproducible testing methods to identify patients most likely to benefit from these interventions.

[0007] The benefits of these treatments are not limited to patients with BRCA mutations, but also extend to a broader category referred to as BRCAness. This term denotes the presence of a BRCA-like phenotype in the absence of identifiable BRCA mutations, a pattern which encompasses a myriad of complex genomic instability phenotypes. Importantly, the presence of BRCAness extends the benefits of BRCA-targeted therapies to a wider patient population, highlighting the importance of its robust identification in cancer patients.

[0008] Despite these advancements, several challenges remain in accurately identifying BRCAness. Previous attempts using genomic alterations, copy number variations, large scale transitions, and mutations have been hindered by a lack of validation in routine testing and adoption in clinical practice. A number of surrogate genomic markers of HRD using high-throughput sequencing, such as HRDetect, Signature 3, SigMA, scarHRD, and ShallowHRD, have been proposed, but their utility has been limited due to technical, logistical, and financial constraints. In addition, several commercial tests exist. So far, no ground truth exists on the BRCAness status of a tumor. SUMMARY

[0009] In the present application, the inventors aim to overcome these limitations by developing a simple, reproducible gene expression signature associated with tumor large-scale state (LST) status. LST are chromosomal breakage that generate 10 Mb or larger fragments. The quantification of these breaks can be used as a surrogate measure for genomic instability, which may be caused by mutation of DNA repair genes.

[0010] The present disclosure relates to an in vitro method for identifying a patient having a tumor with a homologous recombination deficiency (HRD), preferably with a high large-scale transition (LST) status, said method comprising: determining the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 of the genes selected from the group consisting of: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR, preferably at least 1, 2, 3, 4, 5, 6, 7, or 8 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSH6, more preferably at least 1, 2, 3, or 4, of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUMO2, again more preferably comprising determining the gene expression level of: EFTUD1, preferably of each of the following genes: EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUMO2, in a patient sample, wherein a higher gene expression level of the gene(s) in comparison to a control value in a patient sample is indicative that the tumor has homologous recombination deficiency or an in vitro method for determining the therapeutic response of a tumor to DNA damaging agent treatment in a patient, said method comprising: determining the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR, preferably at least 1, 2, 3, 4, 5, 6, 7, or 8 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSH6, more preferably at least 1, 2, 3, or 4, of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUMO2, again more preferably comprising determining the gene expression level of: EFTUD1, preferably of each of the following genes: EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUMO2. in a patient sample, wherein a higher gene expression level of the gene(s) in comparison to a control value in a patient sample is indicative that said tumor is likely responsive to said treatment, preferably the therapeutic response is determined before DNA damaging agent treatment or throughout the course of said treatment for monitoring the therapeutic response over time. In a preferred embodiment, said DNA damaging agent is selected from the group consisting of: an alkylating agent, a platinum-based drug, a topoisomerase inhibitor, a PARP inhibitor, an ATM inhibitor and an ATR inhibitor, preferably a PARP inhibitor.

[0011] In a particular embodiment, said cancer is selected from the group consisting of: ovarian cancer, breast cancer, fallopian tube cancer, peritoneal cancer, lung cancer, pancreatic cancer, head and neck cancer, prostate cancer, stomach or esophagus cancer, colorectal cancer, uterine cancer, cervical cancer, thyroid cancer, brain cancer, liver cancer, kidney cancer and bladder cancer, preferably ovarian or breast cancer. In a preferred embodiment, said patient sample is a tumor tissue sample or a blood sample.

[0012] In some specific embodiments, gene expression level is determined by detecting the mRNA expression of said genes, preferably by RT-qPCR or RNA seq.

[0013] In another aspect, the present disclosure also relates to a DNA damaging agent for use in the treatment of a cancer in a patient in need thereof wherein said DNA damaging agent is administered in a patient previously identified as having a tumor with HRD or as having a tumor likely responsive to said treatment using the method as described above.

[0014] In a preferred embodiment, said DNA damaging agent is selected from the group consisting of: alkylating agents, platinum-based drugs, topoisomerase inhibitors, PARP inhibitors, ATM inhibitors and ATR inhibitors, preferably PARP inhibitor, more preferably selected from the group consisting of: iniparib, olaparib, rucaparib, CEP 9722, niraparib, talazoparib, and 3 -aminobenzamide, veliparib, pamiparib, NU1025, 5154-02-9, E7449, EB-47, GP-L PARP inhibitor, GLXC-26301, DR2313, 489457-67-2, BYK204165, INH2BP, PJ34.

[0015] In a particular embodiment, said PARP inhibitor is administered in combination with ATR or ATM inhibitor, preferably ATM inhibitor.

[0016] Finally, the present disclosure relates to a kit for identifying a patient having a tumor with a homologous recombination deficiency (HRD) comprising a set of reagents that specifically detects the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 of the genes selected from the group consisting of: ETUD1, FANCI, GMNN, HDDC3, KIF23, MCM3, MEF2A, MRPL46, MRPS11, MSH6, POLG, PRC1, RCCD1, SUMO2, TICRR and TK1, preferably at least 1, 2, 3, 4, 5, 6, 7, or 8 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSH6, preferably at least 1, 2, 3, or 4, of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUMO2, again more preferably wherein said reagents are primer pairs and / or probes specific of each gene. In a preferred embodiment, said kit comprises a set of reagents that specifically detects the gene expression level of: EFTUD1, preferably each of the following genes: EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUMO2.

[0017] DETAILED DESCRIPTION

[0018] Biomarkers for identifying a tumor with HR deficiency

[0019] In the present application, the inventors identified biomarkers for accurately identifying a BRCAness tumor, i.e., a tumor with homologous recombination deficiency (HRD) that is likely to respond to treatment with DNA damaging agents.

[0020] The term “biomarker” refers to a distinctive biological or biologically derived indicator (i.e., cellular, biochemical, molecular, genetic, protein, metabolite, specific post-translational modification or physiological or physical sign) of a process, event or condition. According to the present disclosure said biomarker may refer to a gene signature. A gene signature is a single or combined group of genes in a cell with a uniquely characteristic gene expression profile that occurs as a result of an altered or unaltered biological process or pathogenic medical condition.

[0021] According to the method of the present disclosure, the analysis of gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes in a patient sample can be used as biomarkers to determine whether the patient has a tumor with HR deficiency.

[0022] Human EFTUD1 gene, also known as ELF 1 gene encodes several isoforms produced by alternative splicing such as ELF1 transcript variant 1 of 3678 bp (NCBI Reference Sequence: NM_172373.4, updated on 11 June, 2023), ELF1 transcript variant 2 of 3543 bp (NCBI Reference Sequence: NM_001145353, updated on 11 June, 2023), ELF1 transcript variant 3 of 4257 bp (NCBI Reference Sequence: NM_001370329, updated on 11 June, 2023), ELF1 transcript variant 4 of 4138 bp (NCBI Reference Sequence: NM_001370330.1, updated on 11 June, 2023), ELF1 transcript variant 5 of 3631 bp (NCBI Reference Sequence: NM_001370331.1, updated on 11 June, 2023) and ELF1 transcript variant 6 of 3986 bp (NCBI Reference Sequence: NM_001370332 updated on 11 June, 2023).

[0023] Human FANCI gene (Fanconi Anemia complementation group I, Gene ID: 55215 updated on 18 August 2023) encodes a Fanconi anemia group I protein (UniprotKB: Q9NVI1, updated on June 28, 2023) that plays an essential role in the repair of DNA double-strand breaks by homologous recombination and in the repair of interstrand DNA cross-links (ICLs) by promoting FANCD2 monoubiquitination by FANCL and participating in recruitment to DNA repair sites. This protein is required for maintenance of chromosomal stability, specifically binds branched DNA: binds both single-stranded DNA (ssDNA) and double-stranded DNA (dsDNA) and participates in S phase and G2 phase checkpoint activation upon DNA damage. Human FANCI gene encodes several isoforms produced by alternative splicing such as FANCI transcript variant 1 of 4733 bp (NCBI Reference Sequence: NM_001113378.2, updated on 26 June 2023), FANCI transcript variant 2 of 4681 bp (NCBI Reference Sequence: NM_018193.3, updated on 26 June 2023), FANCI transcript variant 3 of 4739 bp (NCBI Reference Sequence: NM_001376910.1, updated on 26 June 2023), and FANCI transcript variant 4 of 4744 bp (NCBI Reference Sequence: NM_001376911, updated on 26 June 2023).

[0024] Human TK1 gene (thymidine kinase 1, Gene ID: 7083, updated on 18 August 2023) encodes a Thymidine kinase, cytosolic (UniprotKB: P04183 updated on June 28, 2023) that catalyzes the first enzymatic step in the salvage pathway converting thymidine into thymidine monophosphate. Human TK1 gene encodes several isoforms produced by alternative splicing such as a TK1 transcript variant 1 of 1431 bp (NCBI Reference Sequence: NM_003258.5, updated on 03 April 2023), TK1 transcript variant 2 of 1269 bp (NCBI Reference Sequence: NM_001346663.2, updated on 03 April 2023) and TK1 transcript variant 3 of 1694 bp (NCBI Reference Sequence: NM_001363848.1, updated on 03 April 2023).

[0025] Human SUMO2 gene (small ubiquitin like modifier 2, Gene ID: 6613, updated on 21 June 2023) encodes a Small ubiquitin-related modifier 2 (UniprotKB: P61956, updated on June 28, 2023). Human SUMO2 gene encodes several isoforms produced by alternative splicing such as a SUMO2 transcript variant 1 of 3166 bp (NCBI Reference Sequence: NM_006937.4, updated on 12 March 2023), and SUMO2 transcript variant 2 of 3094 bp (NCBI Reference Sequence: NM_001005849.2, updated on 15 March 2023).

[0026] Human GMNN gene (geminin DNA replication inhibitor, Gene ID: 51053, updated on 18 August 2023) encodes a geminin (UniprotKB: 075496, updated on June 28, 2023) that inhibits DNA replication by binding to DNA replication factor Cdtl, preventing the incorporation of minichromosome maintenance proteins into the pre-replication complex. The encoded protein is expressed during the S and G2 phases of the cell cycle and is degraded by the anaphase-promoting complex during the metaphase-anaphase transition. Human GMNN gene encodes several isoforms produced by alternative splicing such as GMNN transcript variant 1 of 1263 bp (NCBI Reference Sequence: NM_015895.5, updated on 13 July, 2023), GMNN transcript variant 2 of 1131 bp (NCBI Reference Sequence: NM_001251989.2, updated on 12 July, 2023), GMNN transcript variant 3 of 1055 bp (NCBI Reference Sequence: NM_001251990.2, updated on 13 July, 2023), and GMNN transcript variant 4 of 1051 bp (NCBI Reference Sequence: NM_001251991, updated on 13 July, 2023).

[0027] Human PRC1 gene (protein regulator of cytokinesis 1, Gene ID: 9055, updated on 18 August 2023) encodes a Protein regulator of cytokinesis 1 (UniprotKB: 043663, updated on June 28, 2023). Human PRC1 gene encodes several isoforms produced by alternative splicing such as a PRC1 transcript variant 1 of 3072 bp (NCBI Reference Sequence: NM_003981.4, updated on 18 July 2023), PRC1 transcript variant 2 of 3030 bp (NCBI Reference Sequence: NM_199413.3, updated on 17 July 2023), and PRC1 transcript variant 4 of 2830 bp (NCBI Reference Sequence: NM_001267580, updated on 17 July 2023).

[0028] Human POLG gene (DNA polymerase gamma, catalytic subunit, Gene ID: 5428, updated on 18 August 2023) encodes a DNA polymerase subunit gamma- 1 (UniprotKB: P54098, updated on June 28, 2023). Human POLG gene encodes several isoforms produced by alternative splicing such as a POLG transcript variant 1 of 4462 bp (NCBI Reference Sequence: NM_002693.3, updated on 29 May 2023), and POLG transcript variant 2 of 4450 bp (NCBI Reference Sequence: NM_001126131.2, updated on 29 May 2023).

[0029] Human MSH6 gene (mutS homolog 6, Gene ID: 2956, updated on 18 August 2023) encodes a DNA mismatch repair protein Msh6 (UniprotKB: P52701, updated on June 28, 2023). Human MSH6 gene encodes several isoforms produced by alternative splicing such as a. MSH6 transcript variant 1 of 4265 bp (NCBI Reference Sequence: NM_000179.5, updated on 09 July 2023), MSH6 transcript variant 2 of 3875 bp (NCBI Reference Sequence: NM_001281492.2, updated on 12 July 2023), MSH6 transcript variant 3 of 4095 bp (NCBI Reference Sequence: NM_001281493.2, updated on 12 July 2023), MSH6 transcript variant 3 of 4063 bp (NCBI Reference Sequence: NM_001281494.2, updated on 10 July 2023), and MSH6 transcript variant 4 of 4361 bp (NCBI Reference Sequence: NM_001406795, updated on 15 July 2023).

[0030] Human HDDC3 gene (Guanosine-3', 5'-bis(diphosphate) 3'-pyrophosphohydrolase MESHf Gene ID: 374659, updated on 18 August 2023) encodes a ppGpp hydrolyzing enzyme (UniprotKB: Q8N4P3, updated on June 28, 2023) involved in starvation response. Human HDDC3 gene encodes several isoforms produced by alternative splicing such as HDDC3 transcript variant 1 of 1856 bp (NCBI Reference Sequence: NM_001286451, updated on 27 December, 2022), and HDDC3 transcript variant 2 of 1096 bp (NCBI Reference Sequence: NM_198527, updated on 24 December, 2022).

[0031] Human KIF23 gene (kinesin family member 23. Gene ID: 9493, updated on 18 August 2023) encodes a kinesin like protein (UniprotKB: Q02241, updated on June 28, 2023) that has been shown to cross- bridge antiparallel microtubules and drive microtubule movement in vitro. Human KFF23 gene encodes several isoforms produced by alternative splicing such as KIF23 transcript variant 1 of 3620 bp (NCBI Reference Sequence: NM_138555.4, updated on 12 July, 2023), KIF23 transcript variant 2 of 3308 bp (NCBI Reference Sequence: NM_004856, updated on 13 July, 2023), KIF23 transcript variant 3 of 3231 bp (NCBI Reference Sequence: NM_001281301, updated on 12 July, 2023), KIF23 transcript variant 6 of 3538 bp (NCBI Reference Sequence: NM_001367804, updated on 12 July, 2023), and KIF23 transcript variant 7 of 3660 bp (NCBI Reference Sequence: NM_001367805, updated on 12 July, 2023).

[0032] Human MRPS11 gene (mitochondrial ribosomal protein Sil, Gene ID: 64963, updated on 18 August 2023) encodes a Small ribosomal subunit protein uSl Im (UniprotKB: P82912, updated on June 28, 2023). Human MRPS11 gene encodes several isoforms produced by alternative splicing such as a MRPS11 transcript variant 1 of 3392 bp (NCBI Reference Sequence: NM_022839.5, updated on 14 July 2023), MRPS11 transcript variant 2 of 3293 bp (NCBI Reference Sequence: NM_176805.4, updated on 14 July 2023), MRPS11 transcript variant 3 of 3389 bp (NCBI Reference Sequence: NM_001321970, updated on 14 July 2023), MRPS11 transcript variant 4 of 4513 bp (NCBI Reference Sequence: NM_001321972.2, updated on 14 July 2023), MRPS11 transcript variant 5 of 579 bp (NCBI Reference Sequence: NM_001321973.2, updated on 14 July IQl'FpMRPSll transcript variant 6 of 463 bp (NCBI Reference Sequence: NM_001321974.2, updated on 14 July 2023) and MRPS11 transcript variant 7 of 1700 bp (NCBI Reference Sequence: NM_001321976.5, updated on 14 July 2023).

[0033] Human RCCD1 gene (RCC1 domain containing 1, Gene ID: 91433, updated on 18 August 2023) encodes a RCC1 domain-containing protein 1 (UniprotKB: A6NED2, updated on June 28, 2023). Human RCCD1 gene encodes several isoforms produced by alternative splicing such as a RCCD1 transcript variant 1 of 2759 bp (NCBI Reference Sequence: NM_033544.3, updated on 31 December 2022), and RCCD1 transcript variant 2 of 2675 bp (NCBI Reference Sequence: NM_001017919.2, updated on 30 December 2022).

[0034] Human MCM3 gene (minichromosome maintenance complex component 3. Gene ID: 4172, updated on 18 August 2023) encodes a DNA replication licensing factor MCM3 (UniprotKB: P25205, updated on June 28, 2023) that acts as component of the MCM2-7 complex (MCM complex) which is the replicative helicase essential for “once per cell cycle” DNA replication initiation and elongation in eukaryotic cells. Human MCM3 gene encodes several isoforms produced by alternative splicing such as MCM3 transcript variant 1 of 3068 bp (NCBI Reference Sequence: NM_002388.6, updated on 15 May, 2023), MCM3 transcript variant 2 of 2955 bp (NCBI Reference Sequence: NM_001270472.3, updated on 21 May, 2023), MCM3 transcript variant 3 of 3219 bp (NCBI Reference Sequence: NM_001366369, updated on 21 May, 2023), MCM3 transcript variant 4 of 3119 bp (NCBI Reference Sequence: NM_001366370.2, updated on 21 May, 2023), MCM3 transcript variant 5 of 3168 bp (NCBI Reference Sequence: NM_001366371.2, updated on 22 May, 2023), MCM3 transcript variant 6 of 3017 bp (NCBI Reference Sequence: NM_001366372.2, updated on 21 May, 2023), MCM3 transcript variant 7 of 3202 bp (NCBI Reference Sequence: NM_001366373.2, updated on 22 May, 2023), MCM3 transcript variant 8 of 3064 bp (NCBI Reference Sequence: NM_001366374.2, updated on 21 May, 2023), and MCM3 transcript variant 9 of 2225 bp (NCBI Reference Sequence: NM_001366375.2, updated on 22 May, 2023).

[0035] Human MRPL46 gene (mitochondrial ribosomal protein L46, Gene ID:26589, updated on 6 August 2023) encodes a large ribosomal subunit protein mL46 (UniprotKB: Q9H2W6, updated on June 28, 2023). Human MRPL46 gene encodes a MRPL46 transcript of 986 bp (NCBI Reference Sequence: NM_022163.4, updated on 14 July 2023).

[0036] Human MEF2A gene (myocyte enhancer factor 2A, Gene ID:4205, updated on 18 August 2023) encodes a Myocyte-specific enhancer factor 2A (UniprotKB: Q02078, updated on June 28, 2023) that binds specifically to the MEF2 element, found in numerous muscle-specific genes. Human MEF2A gene encodes several isoforms produced by alternative splicing such as a MEI-2 A transcript variant 8 of 5586 bp (NCBI Reference Sequence: NM_001365203, updated on 31 December, 2022).

[0037] Human TICRR gene (TOPBP1 interacting checkpoint and replication regulator, Gene ID: 90381, updated on 21 June 2023) encodes aTreslin protein (UniprotKB: Q7Z2Z1 updated on June 28, 2023) that regulates the triggering of DNA replication initiation via its interaction with TOPBP 1 by participating in CDK2 -mediated loading of CDC45U onto replication origins. Human TICRR gene encodes several isoforms produced by alternative splicing such as a TICRR transcript variant 1 of 6685 bp (NCBI Reference Sequence: NM_001308025.1, updated on 11 March 2023), and TICRR transcript variant 2 of 6788 bp (NCBI Reference Sequence: NM_152259.4, updated on 11 March 2023).

[0038] According to the present disclosure, the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes, preferably at least 1, 2, 3, 4, 5, 6, 7 or 8 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSH6 genes, more preferably at least 1, 2, 3 or 4 genes selected from the group consisting of: EFTUDI, FANCI, TKI, and SUMO 2 in a patient sample is determined for identifying a patient having a tumor with HR deficiency (i.e., BRCAness patient) that is likely to respond to a DNA damaging agent treatment. The term “gene expression level” or “gene signature” refers to a pattern of expression of at least one gene of the set of genes as described above in a patient sample that is specific to tumor with HR deficiency, preferably with a high large-scale transition (LST) status and is indicative to a likely positive therapeutic response to DNA damaging agent treatment.

[0039] The term " determining the gene expression level of at least one gene” of the set of genes as described above means that the gene expression level of at least one gene of the set of genes is assessed in a patient sample.

[0040] In a preferred embodiment, the method according to the present disclosure involves determining the gene expression level of EFTUD1 gene, preferably of each of the following genes: EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TK1, again more preferably EFTUD1, FANCI, TK1 and SUMO 2, again more preferably EFTUD1, FANCI, TK1, SUMO 2 and GMNN, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN and PRC1, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC I and POLG, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC I, POLG and MSH6, again more preferably EFTUD1, FANCI, TK1, SUMO 2, GMNN, PRC I, POLG, MSH6 and HDDC3, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3 and EKIF23, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23 and MRPS11, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11 and RCCD1, again more preferably EFTUD1, FANCI, TK1, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1 and MCM3, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3 and MRPL46, again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46 and MEF2A or again more preferably EFTUD1, FANCI, TK1, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR in a patient sample.

[0041] The term " determining the gene expression level of each” of the set of genes as described above means that the gene expression level of each of set of genes is assessed in a patient sample.

[0042] The gene expression level of said genes may be determined by any suitable methods known by the person skilled in the art in a patient sample.

[0043] Usually, these methods comprise measuring the quantity of mRNA or protein as described above in a patient sample. Methods for determining the quantity of mRNA are well known in the art. For example, the mRNA contained in the sample is first extracted according to standard methods, for example using lytic enzymes or chemical solutions or extracted by nucleic-acid-binding resins following the manufacturer's instructions. The extracted mRNA is then detected by hybridization (e.g., Northern blot analysis) and / or amplification (e.g., RT-PCR) by using primer pairs and probes specific to said genes as described in the examples of the present disclosure. Quantitative or semi- quantitative RT-PCR is preferred. In another particular embodiment, the mRNA expression level is measured by RNA seq method.

[0044] In some embodiments, the expression level of said genes measured for example by quantitative RT- PCR are normalized by subtracting from each gene, the expression levels of housekeeping genes determined in the same experiment and the gene expression level may correspond to the normalized gene expression level of one gene or to the sum of normalized gene expression level of the set of genes as described above.

[0045] In another embodiments, determining the gene expression level comprises determining the expression level of said gene(s) in a patient sample, in particular by RNA-seq or DNA microarray.

[0046] The terms "subject" and "patient" are used interchangeably herein and refer to both human and nonhuman animals. As used herein, the term “patient” denotes a mammal, such as a rodent, a feline, a canine, and a primate. Preferably, a patient according to the invention is a human.

[0047] According to the present disclosure, said patient or subject is a cancer patient, i.e., a patient having a tumor.

[0048] According to the present disclosure, the “tumor” or “cancer” can be any solid tumor or carcinoma. Preferably, the solid tumor or carcinoma is selected from breast cancer, ovary cancer, colon cancer, lung cancer, prostate cancer, renal cancer, metastatic or invasive malignant melanoma, brain tumor, bladder cancer, fallopian tube cancer, head and neck cancer, peritoneal cancer, liver cancer, bladder, breast, colon, kidney, liver, lung, pancreas, stomach, oesophagus, uterine, cervix, thyroid or skin cancer, including squamous cell carcinoma.

[0049] According to a specific embodiment, the tumor is selected from: ovarian cancer, breast cancer, fallopian tube cancer, peritoneal cancer, lung cancer, pancreatic cancer, head and neck cancer, prostate cancer, stomach or esophagus cancer, colorectal cancer, uterine cancer, cervical cancer, thyroid cancer, brain cancer, liver cancer, kidney cancer and bladder cancer, preferably ovarian or breast cancer.

[0050] According to a preferred embodiment, the tumor is a breast cancer or an ovarian cancer, such as advanced ovarian cancer. The term “patient sample” means any biological sample derived from a patient. Examples of such samples include tissue sample, cell samples, organs, biopsies, preferably tumor sample.

[0051] The tumor “sample” used in the context of the present disclosure is typically obtained from a tumor biopsy. It can e.g. be a fresh or a preserved sample such as a frozen sample, or any tumor sample preserved by other means.

[0052] Said patient sample may also be any biological fluid such as blood sample comprising cell-free circulating tumor DNA (cfcDNA) or circulating tumor DNA (ctDNA). In some embodiments of the present disclosure, the DNA can be obtained from reverse transcription of an RNA sample.

[0053] Method for identifying patient with HRD tumor (i.e., BRCAness patient)

[0054] The biomarkers according to the present disclosure make it possible to classify the patient as having a tumor with or without HR deficiency.

[0055] The method according to the present disclosure allows to identify a patient having a tumor with HR deficiency (a BRCAness patient), i.e. of having a deficient status in one or more genes in the HR pathway.

[0056] As used herein, the expression “homologous recombination (HR) pathway” has its general meaning in the art. It refers to the cellular pathway through which Double Stranded DNA breaks (DSB) are repaired by a mechanism called Homologous Recombination. Inside mammalian cells, DNA is continuously exposed to damage arising from exogenous sources such as ionizing radiation or endogenous sources such as byproducts of cell replication. All organisms have evolved different strategies to cope with these lesions. One of the most deleterious forms of DNA damage is DSB. HR is the most accurate mechanism to repair DSB because it uses an intact copy of the DNA from the sister chromatid or the homologous chromosome as a matrix to repair the break.

[0057] As used herein, “BRCAness” or “HR deficiency” is a term that describes a subset of tumors that have defects in DNA repair mechanisms, similar to those caused by mutations in BRCA1 or BRCA2 genes. Thus, the expression “HR deficiency”, “HRD”, “LST high”, “BRCAness” as used herein, refers to a condition in which one or more of the proteins involved in the HR pathway for repairing DNA is deficient or inactivated.

[0058] As used herein, “deficient status” for a gene means the sequence, structure, expression and / or activity of the gene or its product is / are deficient as compared to normal. Examples include, but are not limited to, low or no mRNA or protein expression, deleterious mutations, hypermethylation, attenuated activity (e.g., enzymatic activity, ability to bind to another biomolecule), etc. As used herein, deficient status for a pathway (e.g., HR pathway) means at least one gene in that pathway (e.g., BRCA1) has a deficient status.

[0059] Examples of genes in the HR pathway include, without limitation, BRCA1, BRCA2, PALB2 / FANCN, BRIP1 / FANCJ, BARD1, RAD51 and RAD51 paralogs (RAD51B, RAD51C, RAD5 ID, XRCC2, XRCC3). These genes encode proteins that are important for the repair of doublestrand DNA breaks by the HR pathway. When the gene for any such protein is, e.g., mutated or under-expressed, the change can lead to errors in DNA repair that can eventually cause cancer. Other actors of the HR pathway include FANCA, FANCB, FANCC, FANCD2, FANCE, FANCG, FANCI, FANCL, FANCM, FAN1, SLX4 / FANCP or ERCC1.

[0060] As used herein the term “inactivation”, when referring to a gene, can mean any type of deficiency of said gene. It includes but is not limited to germline mutations in the coding sequence, somatic mutations in the coding sequence, mutations in the promoter and methylation of the promoter. Examples of highly deleterious mutations include frameshift mutations, stop codon mutations, and mutations that lead to altered RNA splicing. Deficient status in a gene in the HR pathway may result in deficient or reduced HR activity in cells (e.g., cancer cells).

[0061] In a specific embodiment, said tumors with HRD has a high large-scale state transition (LST) status. LST are chromosomal breakage that generates 10 Mb or larger fragments. The number of LSTs in the tumor genome can be estimated for each chromosome arm independently as described in Popova T, et al. Cancer Res. 2012;72:5454-62. A high number of LST in a tumor indicates that the tumor is HR deficient and a low number of LST in a tumor indicates that the tumor is not HR deficient. The cutoff for discriminating LST status into high and low number of LST (high and low LST status) can be evaluated based upon comparative measurements between patients having a tumor with and without HR deficiency, preferably as described in Popova T, et al. Cancer Res. 2012;72:5454-62. Typically, the optimal sensitivity and specificity (and so the threshold value) can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data. Typically, as described in Popova et al. the cutoff of the number of LSTs to segregate LST into high and low LST status can be between 15 to 20 LSTs per genome in near-diploid and near tetrapioid cases, respectively.

[0062] The present disclosure relates to a method for identifying a patient having a tumor with homologous recombination deficiency (HRD) (i.e., BRCAness patient), preferably with a high LST status, by determining the gene expression level of said biomarkers as described above in a patient sample, in particular by determining the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes, preferably at least 1, 2, 3, 4, 5, 6, 7 or 8 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, and MSN 6 genes, preferably at least 1, 2, 3 or 4 genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUM02, preferably the gene expression level of EFTUD1 or all combined of genes : EFTUD1 and FANCI, more preferably EFTUD1 , FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUM02, again more preferably: EFTUD1, FANCI, TKI, SUMO 2 and GMNN, again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN and PRC1, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC I and POLG, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC I, POLG and MSH6, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6 and HDDC3, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3 and EKIF23, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23 and MRPS11, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11 and RCCD1, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1 and MCM3, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3 and MRPL46, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46 and MEF2A or again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR in a patient sample, wherein a higher gene expression level of said gene(s) in said patient sample as compared to a control value is indicative that said patient has a tumor with HR deficiency, preferably with a high LST status.

[0063] As used herein, the term “control value “ may refer to the gene as described above in biological sample obtained from a general population or from a selected population of subjects. For example, the general population may comprise apparently healthy subjects, such as individuals who have not previously had any sign or symptoms indicating the presence of cancer. The term “healthy subjects” as used herein refers to a population of subjects who do not suffer from any known condition, and in particular, who are not affected with any cancer. In another embodiment, the control value refers to the gene expression level of each gene in a biological sample obtained from cancer patients such as breast or ovarian cancer patient known to not have a tumor with HR deficiency.

[0064] In another particular embodiment, said control value may be a “threshold value” or “cut-off value” determined experimentally, empirically, or theoretically. The threshold value may be established based upon comparative measurements between patients having a tumor with and without HR deficiency. Typically, the optimal sensitivity and specificity (and so the threshold value) can be determined using a Receiver Operating Characteristic (ROC) curve based on experimental data. For example, after determining the gene expression level in a group of reference, one can use algorithmic analysis for the statistic treatment of the measured values in samples to be tested, and thus obtain a classification standard having significance for sample classification. In a particular embodiment, Receiver operating characteristic (ROC) analysis was performed to calculate the gene expression level cut-off value of each gene using tumor DNA samples with HR deficiency and / or without HR deficiency. The gene expression level values offering the highest sensitivity and specificity were selected as cut-off points. This algorithmic method is preferably done with a computer. Existing software or systems in the art may be used for the drawing of the ROC curve, such as: MedCalc 9.2.0.1 medical statistical software, SPSS 9.0, ROCPOWER.SAS, DESIGNROC.FOR, MULTIREADER POWER.SAS, CREATE-ROC.SAS, GB STAT VIO.O (Dynamic Microsystems, Inc. Silver Spring, Md., USA), R software (CRAN project) etc.

[0065] According to the present disclosure, the threshold value can be determined for at least 1, 2, 3, 4, 5,

[0066] 6, 7, 8, 9, 10, 11, 12, 13, 14 or 15 genes or for each gene selected from the group consisting of: EFTUD1, FANCI, TK1, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR.

[0067] Typically, the gene expression level of said biomarkers in a patient sample is deemed to be higher than the control value if the log2 Fold change of the gene expression level of at least 1, 2, 3, 4, 5, 6,

[0068] 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes of set of genes as described above in said patient sample to that of said control value is higher than at least 0.1, preferably 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9, more preferably 1, 2, 3, 4 again more preferably 5.

[0069] According to the present disclosure, the gene expression level of said biomarkers can be determined by measuring the relative amount of product genes expressed in patient sample, and preferably by performing a single sample GSEA (ssGSEA) in GSVA algorithm, by calculating a gene set enrichment score per sample as the normalized difference in empirical cumulative distribution functions of gene expression ranks inside and outside the gene set.

[0070] Method for determining the therapeutic response of a tumor to DNA damaging agent treatment

[0071] The method for determining whether a patient has HR deficient tumor according to the present disclosure also indicates which treatment should be administered to said patient. Indeed, patients with HRD tumor may benefit from certain treatments that exploit their DNA repair vulnerability, such as DNA damaging agents like alkylating agents, platinum-based drugs, topoisomerase inhibitors, PARP inhibitors, ATM inhibitors or ATR inhibitors.

[0072] A DNA damaging agent is an agent that causes damage to the DNA of a cell. The damage may be caused by direct interaction with the DNA or by indirect mechanisms such as generation of reactive oxygen species (ROS). The damage may include, but is not limited to, single-strand breaks (SSBs), double-strand breaks (DSBs), base modifications, interstrand crosslinks (ICLs), intrastrand crosslinks, and DNA-protein crosslinks. The damage may affect one or both strands of the DNA. The damage may be reversible or irreversible. The damage may be repaired by the cell or may lead to cell death or senescence. A DNA damaging agent may act on any type of DNA, such as nuclear DNA, mitochondrial DNA, or viral DNA. A DNA damaging agent may be selective or non-selective for a particular type of cell, tissue, or organism. A DNA damaging agent may be natural or synthetic. A DNA damaging agent may be administered alone or in combination with other agents.

[0073] DNA damaging agents can be selected as non-limiting example from the group consisting of: alkylating agents, platinum-based drugs, topoisomerase inhibitors, PARP inhibitors, ATM inhibitors and ATR inhibitors.

[0074] As used herein, the term “alkylating agent” or “alkylating antineoplastic agent” has its general meaning in the art. It refers to compounds which attach an alkyl group to DNA. Typically, the alkylating agent according to the disclosure can be selected from platinium complexes such as cisplatin, carboplatin and oxaliplatin, chlormethine, chlorambucil, melphalan, cyclophosphamide, ifosfamide, estramustine, carmustine, lomustine, fotemustine, streptozocin, busulfan, pipobroman, procarbazine, dacarabazine, thiotepa and temozolomide.

[0075] As used herein the term “PARP inhibitor” or “PARPi” has its general meaning in the art. It refers to a compound which is capable of inhibiting the activity of the enzyme polyADP ribose polymerase (PARP), a protein that is important for repairing single-strand breaks (‘nicks’ in the DNA). If such nicks persist unrepaired until DNA is replicated (which must precede cell division), then the replication itself will cause double strand breaks to form. Drugs that inhibit PARP cause multiple double strand breaks to form in this way, and in tumors with BRCA1, BRCA2 or PALB2 mutations these double strand breaks cannot be efficiently repaired, leading to the death of the cells.

[0076] Typically, the PARP inhibitor according to the disclosure can be selected from the group consisting of iniparib, olaparib, rucaparib, 4,5,6,7-Tetrahydro-ll-methoxy-2-((4-methyl-l- piperazinyl)methyl)-lH-cyclopenta(a)pyrrolo(3,4-C)carbazole-I,3(2H)-dione (CEP 9722), Nirapib (MK 4827), Talazoparib (BMN-673), 3 -aminobenzamide, veliparib, 2-(4-(6-chloro-7- methylpyrazolo [ 1 ,5 -a]pyrimidin-3 -yloxy)phenyl)-N-(3 -fluoro-6-( 1 -methylpiperidin-4-yl)pyridin-2- yl)acetamide (AZD5305), pamiparib, NU1025 (CAS 90417-38-2), 1,5 -Isoquinolinediol (CAS 5154- 02-9), stenoparib (E7449), EB-47 (CAS 1190332-25-2), GP-L PARP inhibitor (8-fhioro-2-{[3- (piperidin-l-yl)propane]sulfonyl}-lH,2H,3H,4H,5H,6H-benzo[c] l,6-naphthyridin-6-one), GLXC- 26301, DR2313 (CAS 284028-90-6), PARP inhibitor XII (CAS 489457-67-2), BYK204165 (CAS No. : 1104546-89-5), INH2BP (CAS 137881-27-7), and PJ34 (2-(dimethylamino)-N-(6-oxo-5,6- dihydrophenanthridin-2-yl)acetamide hydrochloride) .

[0077] As used herein “topoisomerase inhibitor” has its general meaning in the art. It refers to a drug that blocks the action of an enzyme called topoisomerase such as topoisomerase I or II which is involved in DNA replication and transcription. Topoisomerase inhibitors can prevent cancer cells from dividing and growing by causing DNA damage and cell death.

[0078] Typically, the topoisomerase inhibitor according to the disclosure can be selected from the group consisting of camptothecins, anthracyclines, epipodophyllotoxins, and quinolones.

[0079] As used herein “platinum-based drugs” has its general meaning in the art. It refers to chemotherapeutic agents used to treat cancer. Their active moieties are coordination complexes of platinum. Typically, the platinum -based drugs according to the disclosure can be selected from the group consisting of cisplatin, oxaliplatin and carboplatin.

[0080] As used herein “ATR inhibitor” has its general meaning in the art. It refers to a compound that inhibits the activity of ataxia telangiectasia and Rad3 -related protein kinase (ATR). An ATR inhibitor may bind to the ATP -binding site or to an allosteric site of the ATR kinase domain. An ATR inhibitor may inhibit the phosphorylation and activation of downstream substrates of ATR, such as CHK1, p53, RPA32, and H2AX. An ATR inhibitor may enhance the cytotoxicity of DNA damaging agents, such as radiation, chemotherapy, or PARP inhibitors.

[0081] Typically, the ATR inhibitor according to the disclosure can be selected from the group consisting of pyrazine derivatives, pyrimidine derivatives, pyrrolopyrimidine derivatives, and macrocyclic compounds, preferably can be selected as non-limiting examples from the group consisting of: 4-(4- (l-((S(R))-S-methylsulfonimidoyl)cyclopropyl)-6-((3R)-3-methyl-4-morpholinyl)-2-pyrimidinyl)- lH-pyrrolo(2,3-b)pyridine (ceralasertib, AZD6738), 2-(3-Methyl-4-morpholinyl)-4-(l-methyl-lH- pyrazol-5-yl)-8-(lH-pyrazol-5-yl)-l,7-naphthyridin (BAY 1895344), 2-Pyrazinamine, 3-[3-[4- [(methylamino)methyl]phenyl]-5-isoxazolyl]-5-[4-[(l-methylethyl)sulfonyl]phenyl] (beszosertib, M6620, VX-970), (lR,5S)-3-[6-[(3R)-3-methyhnorpholin-4-yl]-l-(lH-pyrazol-5-yl)pyrazolo[3,4- b]pyridin-4-yl] -8-oxabicyclo [3.2.1] octan-3 -ol (RP-3500), 2-methyl-2-(4-(2-oxo-9-(quinolin-3 -yl)- 2H-[l,3]oxazino[5,4-c]quinolin-l(4H)-yl)phenyl)propanenitrile (ETP-46464) and 2-amino-6- fluoro-N-(5 -fluoro-4-(4-(4-(oxetan-3 -yl)piperazine- 1 -carbonyl)piperidin- 1 -yl)pyridin-3 - yl)pyrazolo [ 1 ,5 -a]pyrimidine-3 -carboxamide (M4344) .

[0082] As used herein “ATM inhibitor” has its general meaning in the art. It refers to a drug that blocks the activity of the ATM kinase, a member of the phosphatidylinositol-3 kinase-like (PIKK) family of serine / threonine protein kinases that is involved in the DNA damage response and cell cycle regulation. Typically, the ATM inhibitor according to the disclosure can be selected from the group consisting of: 8-(6-(3-(dimethylamino)propoxy)pyridin-3-yl)-3-methyl-l-(tetrahydro-2H-pyran-4- yl)-lH-imidazo[4,5-c]quinolin-2(3H)-one (AZD0156), N-Benzyl-N-methyl-l-phenylmethanamine (M3541 ), 8-( 1 ,3 -dimethylpyrazol-4-yl)- 1 -(3 -fluoro-5 -methoxypyridin-4-yl)-7 -methoxy-3 - methylimidazo[4,5-c]quinolin-2-one (laetesertib) (M4076), 2-(4-Morpholinyl)-6-(l-thianthrenyl) (KU-55933), 4-((S)-l-(tetrahydro-2H-pyran-4-yl)ethylamino)-6-(6-(methoxymethyl)pyridin-3- yl)quinoline-3 -carboxamide (AZ31), and 7-fluoro-l,3-dihydro-3-methyl-l-(l-methylethyl)-8-[6-[3- ( 1 -piperidinyl)propoxy] -3 -pyridinyl] -2H-imidazo [4,5 -c] quinolin-2-one (AZD 1390).

[0083] Patients having a tumor with HR deficiency, can therefore be classified as being likely to respond to a particular cancer treatment regimen that includes the use of a DNA damaging agent. Thus, according to a particular embodiment, the method according to the present disclosure allows to determine the therapeutic response of a tumor to a DNA damaging agent treatment in a patient.

[0084] The term "responder”, or “responsive to a treatment” refers to a subject in whom the onset of at least one of the symptoms of the condition to be treated is delayed or prevented, upon or after treatment, or whose symptoms or at least one of the symptoms stabilize, diminish or disappear.

[0085] “Therapeutic response” refers to the consequence of a medical treatment in a patient, the results of which are judged to be useful or favorable. For instance, a therapeutic response may be the delay or the prevention of at least one of the symptoms, upon or after treatment, or may be that the symptoms or at least one of the symptoms in patient stabilize, diminish or disappear.

[0086] According to the present disclosure, the terms “ therapeutic response of a tumor to a DNA damaging agent (e.g. PARP inhibitor) treatment in a patient” refers to an ability to assess whether the DNA damaging agent treatment (e.g., PARP inhibitor) is effective in (e.g., providing a measurable benefit or positive medical response to) the tumor of the patient before and / or after some time of administration of the treatment. In another terms, according to the present disclosure, determining the response to DNA damaging agent treatment refers to an ability to assess whether a tumor is responsive to DNA damaging agent treatment and for example whether following the DNA damaging agent treatment the number of cancer cells or the size of a tumor is reduced, the progression of a cancer to a more aggressive form (i.e. maintaining the cancer in a form that is susceptible to a therapeutic agent) is reduced, the proliferation of cancer cells or of the speed of tumor growth are reduced, cancer cells are killed or the likelihood of recurrence of a cancer is reduced in a subject.

[0087] A higher gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes of set of genes described above in a patient sample in comparison to a control value is indicative that the patient is likely responsive to a DNA damaging agent treatment, and preferably said patient can be treated with a DNA damaging agent. A lower gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes of set of genes as described above in a patient sample in comparison to a control value is indicative that the patient is likely non-responsive to said DNA damaging agent treatment and preferably said patient will not be treated with a DNA damaging agent.

[0088] The therapeutic response can be evaluated according to the present method, before DNA damaging agent treatment or throughout the course of said treatment for monitoring the therapeutic response over time.

[0089] Therefore, the present disclosure concerns a method for determining the therapeutic response of a tumor to DNA damaging agent treatment in a patient, said method comprising determining the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes, preferably at least 1, 2, 3, 4, 5, 6, 7 or 8 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, and MSH6 genes, preferably at least 1, 2, 3 or 4 genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUM02, preferably the gene expression level of EFTUD1 gene or all combined of genes : EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUM02, again more preferably: EFTUD1, FANCI, TKI, SUMO 2 and GMNN, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN and PRC1, again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC I and POLG, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG and MSH6, again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6 and HDDC3, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3 and EKIF23, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23 and MRPS11, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11 and RCCD1, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23,MRPS11, RCCD1 and MCM3. again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3 and MRPL46, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46 and MEF2A or again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRCI, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR in a patient sample as described above, wherein a higher gene expression level of the gene(s) in comparison to a control value is indicative that said tumor in a patient is likely responsive to said treatment.

[0090] According to a specific embodiment, the tumor is selected from ovarian cancer, breast cancer, fallopian tube cancer, peritoneal cancer, lung cancer, pancreatic cancer, head and neck cancer, prostate cancer, stomach or esophagus cancer, colorectal cancer, uterine cancer, cervical cancer, thyroid cancer, brain cancer, liver cancer, kidney cancer and bladder cancer, preferably ovarian or breast cancer. According to a preferred embodiment, the tumor is a breast cancer or an ovarian cancer, such as advanced ovarian cancer.

[0091] Therapeutic uses

[0092] In another particular embodiment, the present disclosure relates to a DNA damaging agent as described above for use in the treatment of a cancer in a patient in need thereof wherein said DNA damaging agent is administered in a patient previously identified as having a tumor with HRD using the methods as previously described.

[0093] The present invention relates also to a method for treating a cancer in a patient in need thereof comprising: i) determining the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD1, FANCI, TK1, SUM02, GMNN, PRCI, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes, preferably at least 1, 2, 3, 4, 5, 6, 7 or 8 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, and MSH6 genes, preferably at least 1, 2, 3 or 4 genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUM02, preferably the gene expression level of EFTUD1 gene or all combined of genes : EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUMO 2, again more preferably: EFTUD1, FANCI, TKI, SUMO 2 and GMNN, again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN wiAPRCl , again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN, PRCI and POLG, again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN, PRCI, POLG and MSH6, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRCI, POLG, MSH6 and HDDC3, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRCI, POLG, MSH6, HDDC3 and EKIF23, again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN, PRCI, POLG, MSH6, HDDC3, EKIF23 and MRPS11, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11 and RCCD1, again more preferably: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1 and MCM3, again more preferably: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3 and MRPL46, again more preferably: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23,MRPS11, RCCD1, MCM3, MRPL46wAMEF2A or again more preferably: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23,MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR in a patient sample, wherein a higher gene expression level of the gene(s) in comparison to a control value is indicative that the patient has a tumor with homologous recombination deficiency or is likely responsive to the DNA damaging agent treatment. ii) administering a therapeutically effective amount of said DNA damaging agent to said patient previously identified as having a tumor with homologous recombination deficiency or likely responsive to a DNA damaging agent treatment.

[0094] In the context of the present disclosure, the term "treating" or "treatment", as used herein, means reversing, alleviating, inhibiting the progress of, or preventing the disorder or condition to which such term applies, or reversing, alleviating, inhibiting the progress of, or preventing one or more symptoms of the disorder or condition to which such term applies.

[0095] Such treatment aims at improving the clinical status of the animal or human patient, by eliminating or lowering the symptoms associated with cancers, in particular metastatic colorectal cancer.

[0096] As used herein, a "therapeutically effective amount" or an "effective amount" means the amount of a composition that, when administered to a subject for treating a state, disorder or condition is sufficient to effect a treatment. The therapeutically effective amount will vary depending on the composition, the disease and its severity and the age, weight, physical condition and responsiveness of the subject to be treated.

[0097] The present disclosure also relates to the use of DNA damaging agent in the manufacture of a medicament for the treatment of a cancer in a patient in need thereof previously identified as having a tumor with homologous recombination deficiency or responsive to a DNA damaging agent treatment in the methods as described above.

[0098] According to the present disclosure, said DNA damaging agent is selected from the group consisting of: alkylating agents, platinum-based drugs, topoisomerase inhibitors, PARP inhibitors, ATM inhibitors and ATR inhibitors. In a preferred embodiment, said DNA damaging agent is a PARP inhibitor such as iniparib, olaparib, rocaparib, CEP 9722, MK 4827, BMN-673, 3 -aminobenzamide, veliparib, pamiparib, NU1025, 5154-02-9, E7449, EB-47, GP-L PARP inhibitor, GLXC-26301, DR2313, 489457-67-2, BYK204165, INH2BP, and PJ34.

[0099] In the present application, the inventors showed high synergies when a PARP inhibitor administered in combination with an ATM or ATR inhibitor, preferably ATM inhibitor.

[0100] Therefore, in a more preferred embodiment, said PARP inhibitor is administered in combination with an ATR inhibitor and / or an ATM inhibitor, preferably with an ATM inhibitor.

[0101] The present disclosure also relates to a pharmaceutical composition comprising a DNA damaging agent as described above for use in the treatment of a cancer in a patient in need thereof, preferably wherein said pharmaceutical composition is administered in a patient previously identified as having a tumor with HRD using the methods as described previously.

[0102] Said pharmaceutical composition may comprise a DNA damaging agent selected from the group consisting of: alkylating agents, platinum-based drugs, topoisomerase inhibitors, PARP inhibitors, ATM inhibitors and ATR inhibitors or a combination thereof such as PARP inhibitor and ATM and / or ATR inhibitor.

[0103] Said pharmaceutical composition can comprise one or more pharmaceutical acceptable excipient, diluent or carrier. As used herein, the term "pharmaceutically acceptable" means approved by a regulatory agency or recognized pharmacopeia such as European Pharmacopeia, for use in animals and / or humans. The term "excipient" refers to a diluent, adjuvant, carrier, or vehicle with which the therapeutic agent is administered.

[0104] Any suitable pharmaceutically acceptable carrier, diluent or excipient can be used in the preparation of a pharmaceutical composition (See e.g., Remington: The Science and Practice of Pharmacy, Alfonso R. Gennaro (Editor) Mack Publishing Company, April 1997). Pharmaceutical compositions are typically sterile and stable under the conditions of manufacture and storage. Pharmaceutical compositions may be formulated as solutions (e.g. saline, dextrose solution, or buffered solution, or other pharmaceutically acceptable sterile fluids), microemulsions, liposomes, or other ordered structure suitable to accommodate a high product concentration (e.g. microparticles or nanoparticles). The carrier may be a solvent or dispersion medium containing, for example, water, ethanol, polyol (for example, glycerol, propylene glycol, and liquid polyethylene glycol, and the like), and suitable mixtures thereof. The proper fluidity can be maintained, for example, by the use of a coating such as lecithin, by the maintenance of the required particle size in the case of dispersion and by the use of surfactants. In many cases, it will be preferable to include isotonic agents, for example, sugars, polyalcohols such as mannitol, sorbitol, or sodium chloride in the composition.

[0105] The composition may be administered by any means known to those skilled in the art, including, without limitation, intravenously, orally, intra-tumoral, intra-lesional, intradermal, topical, intraperitoneal, intramuscular, parenteral, subcutaneous and topical administration. Thus, the composition may be formulated as an injectable, topical, or ingestible formulation. Administration of the composition to a subject in accordance with the present disclosure may exhibit beneficial effects in a dose-dependent manner. Thus, within broad limits, administration of larger quantities of the composition is expected to achieve increased beneficial biological effects than administration of a smaller amount. Moreover, efficacy is also contemplated at dosages below the level at which toxicity is seen.

[0106] It will be appreciated that the specific dosage of an administered in any given case will be adjusted in accordance with the composition being administered, the volume of the composition that can be effectively delivered to the site of administration, the disease to be treated or inhibited, the condition of the subject, and other relevant medical factors that may modify the activity of the compositions or the response of the subject, as is well known by those skilled in the art.

[0107] For example, the specific dose of composition for a particular subject depends on age, body weight, general state of health, diet, the timing and mode of administration, the rate of excretion, medicaments used in combination and the severity of the particular disorder to which the therapy is applied. Dosages for a given patient can be determined using conventional considerations, e.g., by customary comparison of the differential activities of the immunotherapy and pharmaceutical compositions described herein and of a known agent, such as by means of an appropriate conventional pharmacological protocol. The composition can be given in a single dose schedule, or in a multiple dose schedule.

[0108] Suitable dosage ranges for composition may be of the order of several hundred micrograms of the agent with a range from about 0.001 to 10 mg / kg, preferably with the range from about 0.01 to 1 mg / kg, more preferably from about 1 to 10 mg / kg, again more preferably 10 mg / kg.

[0109] Kit

[0110] In another aspect, the present disclosure relates to a kit, preferably for use in an in vitro method for identifying a patient having a tumor with HRD or responsive to DNA damaging treatment comprising or consisting of a set of reagents that specifically detects the gene expression level of at least of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes, preferably at least 1, 2, 3, 4, 5, 6, 7 or 8 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, and MSH6 genes, preferably at least 1, 2, 3 or 4 genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUM02, preferably the gene expression level of EFTUD 1 gene or all combined of genes : EFTUD1 and FANCI, more preferably EFTUD 7, FANCI and TKI, again more preferably: EFTUD 7, FANCI, TKI and SUM02, again more preferably: EFTUD 7, FANCI, TKI, SUMO 2 and GMNN, again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN and PRC1, again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN, PRC I and POLG, again more preferably: EFTUD 1, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG and MSH6, again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6 and HDDC3, again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3 and EKIF23, again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23 and MRPS11, again more preferably: EFTUD 1, FANCI, TKI, SUMO 2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11 and RCCD1, again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1 and MCM3, again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3 and MRPL46, again more preferably: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46 and MEF2A or again more preferably: EFTUD 1, FANCI, TKI, SUM02, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR.

[0111] Preferably, the kit comprises containers each comprising one or more compounds at a concentration or in an amount that facilitates the reconstitution and / or the use of a set of reagents that specifically detects the gene expression level of at least of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD 1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes, preferably at least 1, 2, 3, 4, 5, 6, 7 or 8 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSN 6 genes, preferably at least 1, 2, 3 or 4 genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUMO2, preferably the gene expression level of EFTUD 1 gene or all combined of genes : EFTUD 1 and FANCI, more preferably EFTUD 1, FANCI and TKI, again more preferably: EFTUD 1, FANCI, TKI and SUMO2, again more preferably: EFTUD 1, FANCI, TKI, SUMO 2 and GMNN, again more preferably: EFTUD 1, FANCI, TKI, SUMO2, GMNN and PRC1, again more preferably: EFTUD 1, FANCI, TKI, SUMO2, GMNN, PRC I and POLG, again more preferably: EFTUD 1, FANCI, TKI, SUMO2, GMNN, PRC I, POLG and MSH6, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6 and HDDC3, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3 and EKIF23, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23 and MRPS11, again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11 and RCCD1, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1 and MCM3, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3 and MRPL46, again more preferably: EFTUD1, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46 and MEF2A or again more preferably: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR.

[0112] In particular, the kit contains primer pair and or probes specific of at least of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR genes, preferably at least 1, 2, 3, 4, 5, 6, 7 or 8 genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSH6 genes, preferably at least 1, 2, 3 or 4 genes selected from the group consisting of: EFTUDI, FANCI, TKI, and SUMO 2, preferably the gene expression level of EFTUDI gene or all combined of genes : EFTUDI and FANCI, more preferably EFTUDI, FANCI and TKI, again more preferably: EFTUDI, FANCI, TKI and SUMO 2, again more preferably: EFTUDI, FANCI, TKI, SUMO 2 and GMNN, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN and PRC1, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC I and POLG, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC1, POLG and MSH6, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6 and HDDC3, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC I, POLG, MSH6, HDDC3 and EKIF23, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23 and MRPS11, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11 and RCCD1, again more preferably: EFTUDI, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1 and MCM3, again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23,MRPS11, RCCD1, MCM3 and MRPL46, again more preferably: EFTUDI, FANCI, TKI, SUMO 2, GMNN, PRC I, POLG, MSH6, HDDC3, EKIF23, MRPS11, RCCD1, MCM3, MRPL46 and MEF2A or again more preferably: EFTUDI, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, EKIF23,MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR. The kit may also comprise instructions indicating the methods for preparing and / or using the reagents to determine the expression level of said genes according to the methods of the disclosure.

[0113] The present invention also relates to the use of the kit for a method according to the present disclosure.

[0114] The invention will now be exemplified with the following examples, which are not limitative, with reference to the attached Figures.

[0115] LEGEND FIGURES

[0116] Figure 1: A: Differential Expression in LST-high and LST-low Triple-Negative Breast Cancer (TNBC) Tumors. This figure represents the differential gene expression profiles between LST high and low tumors in a cohort of 92 triple-negative breast cancer (TNBC) patients from The Cancer Genome Atlas (TCGA) with gene expression data obtained from chips (64 genes identified as differentially expressed). B: Interaction Network of Differentially Expressed Genes. This figure represents a confidence view interaction network from the STRING database, visualizing the predicted functional associations between the 64 differentially expressed genes identified in TNBC. The varying thickness of the lines indicates the strength of data support for each interaction.

[0117] Figure 2: RNASeq Expression Profile of TNBC 64-Gene Signature by LST Status. The expression of the 64-gene signature by RNASeq data is displayed in the training (upper facet) and in an independent validation set (lower facet) of TNBCs samples from TCGA. Genes in Cluster 1 and 2 exhibit elevated expression in LST-high (49%) versus LST-low (51%) tumors across 88 patient samples in the 2 datasets, while genes in Cluster 3 lacked significant differential expression in the validation set. Statistical significance is denoted by asterisks above the box plots.

[0118] Figure 3: Expression levels of genes of the signature across independent cohorts. The expression data of selected genes is scaled and depicted for three cohorts: 330 TNBC samples from METABRIC, 364 ovarian cancer samples from TCGA, and 85 ovarian cancer samples from Institut Curie. The LST status is represented by color, with high in blue and low in salmon. Of the final genes in the signature, 8 are located on chromosome 15q, indicative of their potential role in cancer pathology. Statistical significance is denoted by asterisks above the box plots.

[0119] Figure 4: Validation and Expression Analysis of the 16-Gene Signature in TNBC and ovarian cancers. Expression levels of the 16 selected genes across three datasets of TNBC samples (METABRIC dataset) and ovarian cancers (The Cancer Genome Atlas (TCGA) dataset; and Curie ovarian cancer dataset), segregated according to the large-scale state transition (LST) status. Metagene analysis of the average expression of the 16 genes showing significantly higher levels in samples with high LST compared to low LST.

[0120] Figure 5: Prospective validation of the 16-gene signature in an in-house validation cohort of TNBC samples. Gene expression assessed by qPCR for each gene of the 16-gene signature in an independent in-house cohort of 97 TNBC cases. Metagene based on the average expression of the 16 genes compared in the LST high and LST-low group.

[0121] Figure 6: Performance evaluation of the 16-Gene signature in predicting LST status. This figure presents the validation of a predictive model based on a 16-gene signature across six independent datasets. The model's performance, measured by the Area Under the Receiver Operating Characteristic (AUC), ranged from 0.67 to 0.84. The predictive accuracy varied, with overall accuracy between 0.62 and 0.7. Sensitivity (true positive rate) spanned from 0.66 to 0.89 and specificity (true negative rate) from 0.58 to 0.68. The Fl-score, indicating the harmonic mean of precision and recall, was determined to be between 0.62 and 0.72. Confusion matrices for each dataset are provided to visualize the distribution of true positive, true negative, false positive, and false negative predictions.

[0122] Figure 7: Synergistic effects of PARP inhibitors and various DNA damage response inhibitors in BC Cell Lines. Heatmaps illustrating the synergy between olaparib, a PARP inhibitor, and various DNA damage response inhibitors in breast cancer cell lines SUM149-PT and MDAMB436. Strong synergistic effects are shown with ATM inhibitors (M4076, AZD1390) and moderate effects with ATR inhibitors (M4344, ceralasertib / AZD6738). There is no synergy observed with the UBE2T inhibitor (M435-1279), indicating that ATM and ATR inhibitors may enhance the therapeutic effect of olaparib in BRCAness tumors.

[0123] EXAMPLES

[0124] 1. Materials and methods

[0125] 1.1 Study populations

[0126] Cohort of TNBC from TCGA (training and validation set)

[0127] The inventors identified breast cancer samples from TCGA (BRCA) and downloaded preprocessed gene expression data (TCGA level 3) assessed by Agilent chips (n =520) and HTSeq gene expression data (n=1085). The definition of breast cancer (BC) subtype was based on the gene expression of ESRI, PR, ERBB2 assessed by gene expression and was determined using a bimodal mixture of two Gaussian distributions for ESRI, PGR, and ERBB2 gene expression. Triple negative breast cancer (TNBC) was defined as the combined expression of the lowest groups for ESRI, PGR and ERBB2 respectively. The group of patients with TNBCs and gene expression data assessed by Agilent chips served as training set, and the group of patients with RNASeq gene expression data served as validation set. In samples with both chips and RNASeq data, concordance between the two metrics was analysed with a pearson correlation coefficient.

[0128] Independent cohort TNBCs from METABRIC

[0129] The inventors used the METABRIC — Molecular Taxonomy of Breast Cancer International Consortium — dataset published by Curtis et al. (Curtis C, Shah SP, Chin S-F, Turashvili G, Rueda OM, Dunning MJ, et al. The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups. Nature. 2012;486:346-52), which was established for analysis of the prognosis of various molecular subtypes of breast cancer. The inventors normalized the 1992 samples together, using scripts and Rdata provided by the authors. The inventors fitted a linear model (limma R package (R Core Team (2020). R: A Language and Environment for Statistical Computing)) to remove the batch effect and probes were filtered according to three criteria: probe quality (Barbosa- Morais, N.L., et al. (2010). Nucleic Acids Res. 38, el7), GC content and presence in more than 5% of the samples, as described previously(5) (Hamy, A.-S., et al. (2016). PLOS ONE 11, e0167397).

[0130] Cohort of ovarian cancers from TCGA

[0131] Two cohorts of ovarian cancer were used for validation. The first cohort from TCGA has been previously described (Cancer Genome Atlas Research Network, (2011), Nature. 474:609-15). HTSeq gene expression data were downloaded from the GDC portal (https: / / portal.gdc.cancer.gov / ) using the data transfer tool gdc-client on April 6th 2018. The second cohort was a cohort of in-house ovarian cancers (Goundiam O, et al. (2015), Int J Cancer. 2015; 137: 1890-900).

[0132] In-house cohort of TNBCs

[0133] Samples from 323 unilateral invasive triple-negative primary breast tumors excised from women managed at Institut Curie (Paris and Saint-Cloud, France) between 1980 and 2015 were analyzed. Most patients (67%) were diagnosed and treated after 2000. All patients admitted to our institution before 2007 were informed that their tumor samples might be used for scientific purposes and were given the opportunity to refuse such use. Since 2007, patients admitted to our institution also give express consent for the use of their samples for research purposes, by signing an informed consent form. Patients (mean age, 56 years; range, 28-91 years) met the following criteria: primary unilateral non-metastatic TNBC, with full clinical, histological, and biological data and full follow-up at Institut Curie.

[0134] Determination ofLST (large-scale state transitions) status for the cohorts.

[0135] LST status was determined on all the internal and external datasets as previously described (Popova, T, et al. (2012). Cancer Res. 72, 5454-5462).

[0136] 1.2 Establishment and refinement of the homologous repair deficienty (HRD)-signature

[0137] Differential expression analyzes was performed using the limma package (Law CW, et al. Genome biology. 2014;15:R29) on the training set. The inventors performed hierarchical clustering on the samples using the Pearson correlation as the distance metric. This measures the linear correlation between the gene expression levels of different samples. The Ward's minimum variance method is used for clustering, which minimizes the total within-cluster variance. The inventors represented data on a heatmap. The inventors performed gene enrichment analyses using the website GSEA available at http: / / software.broadinstitute.org / gsea / msigdb / compute_overlaps.jsp, and using the MSigDB (Molecular signatures database v7.0). Briefly, the Molecular Signatures Database (MSigDB) is a collection of annotated gene sets for use with GSEA software. The MSigDB gene sets are divided into 8 major collections (H: hallmark gene sets ; Cl: positional gene sets ; C2: curated gene sets ;C3: motif gene sets ; C4: computational gene sets;C5: GO gene sets ;C6: oncogenic signatures ; C7: immunologic signatures). The inventors then identified known biological networks, for each gene cluster separately, using String database software version 11.5 available at the following URL https: / / string-db.org / . Final gene selection process was based on both external reproducibility criteria and biological relevance. Genes were kept in the signature if they (i) were found differentially expressed in at least two fully independent datasets; (ii) and if they met at least one out of the following criteria : biological relevance ; location on the 15q ; reproducibility in more than 3 independent datasets. In addition, genes were discarded from the signature if discrepancies were seen between different datasets, i.e. in the cases where they were upregulated in a LST condition in a given dataset, and down regulated in an independent dataset in the same condition. Genes of unknown significance (Corf) were also be discarded if they did not meet any of the criteria mentioned above.

[0138] 1.3 Performance Assessment of Identified Genes in Predicting LST Status

[0139] To assess the predictive performance of the 16 identified genes for LST status, the inventors build a Random Forrest classification model and used as a training dataset the TCGA BRCA Chip dataset. Six independent external cohorts, with breast or ovarian cancer patients, served to validate and evaluate the model's performance: TCGA BRCA RNASeq, METABRIC Breast Illumina, TCGA Ovary RNASeq, Ovary Curie, Tumor Bieche Stem, TCGA Ovary Chip. The expression levels of the 16 genes of interest were used as predictors in the Random Forest classification model to predict the LST status. The Random Forest model was implemented using the caret package in R. The model's hyperparameters, including the number of trees and the number of variables to consider at each split, were optimized using 10-fold cross-validation on the training data to prevent overfitting. The inventors fixed the number of tree at 500 and the mtry parameter at three. The evaluation of the feature importance was assessed based on Gini Importance. In case of missing values in the gene expression data, the median expression levels of each gene, according to LST status, were calculated on the training dataset. These values were then used to fill the missing gene expression levels in the three external validation cohorts with missing values, maintaining the distribution and potential relationship between each gene's expression and the LST status. The model's performance was evaluated using several metrics, including Area Under the Receiver Operating Characteristic (AUC), Accuracy, Sensitivity, Specificity, Precision and Fl -score.

[0140] Copy number data

[0141] The inventors obtained copy number alterations (CNA) data from the ASCAT (Martincorena, et al. (2017). Cell 171, 1029-1041.e21) complete results on TCGA data partly reported on the COSMIC database (Forbes, S.A., et al. (2017). Nucleic Acids Res. 45, D777-D783).

[0142] Copy number data were downloaded from the CBIO portal (Cerami, et al. (2012). Cancer Discov. 2, 401-404; Gao, J., et al. (2013). Sci. Signal. 6, pll) (included in http: / / download.cbioportal.org / brca_metabric.tar.gz) on March 25th 2020. Data consists in the report of status (heterozygous or homozygous deletion, neutral, gain or amplification) for each gene for each METABRIC sample.

[0143] 1.4 Experimental assays

[0144] RT-qPCR in TNBCs

[0145] Total RNA was extracted from breast specimens by using the acid-phenol guanidium method. The quality of the RNA samples was determined by electrophoresis through agarose gels and staining with ethidium bromide, and the 18S and 28S RNA bands were visualized under UV light.

[0146] Total RNA extraction and RT-qPCR (Real Time-qPCR) have been described elsewhere (Bieche et al, Cancer Res, 2001). The TBP gene (GenBank accession no. NM_003194) encoding the TATA boxbinding protein (a component of the DNA-binding protein complex TFIID) was quantified as an endogenous RNA control, and each sample was normalized on the basis of its TBP content (Mermel CH et al, Genome Biol., 2011). N-fold differences in target gene expression relative to the TBP gene (“Ntarget”), were determined as Ntarget = 2ACtsample, where the ACt value of the sample was obtained by subtracting the mean Ct value of the target gene from that of the TBP gene (Bieche et al; Clin Chem., 1999). The inventors analyzed the expression of the 16 genes from the signature in TNBC samples. All of the PCR reactions were performed using an ABI Prism 7700 Sequence Detection system (Perkin-Elmer Applied Biosystems). PCR was performed using either the TaqMan PCR Core Reagents kit or the SYBR Green PCR Core Reagents kit (Perkin-Elmer Applied Biosystems). The thermal cycling conditions comprised an initial denaturation step at 95 °C for 10 min and 50 cycles at 95°C for 15 s and 65°C for 1 min. Experiments were performed with duplicates for each data point.

[0147] Cell linesTwo cell lines were selected based on their BRCAness status, on their sensibility to PARP inhibitor olarapib and on their response to combinations between siRNA targeting our genes of interest and PARP inhibitors. Cells were seeded in 96-well plates at day 0 (5 000 cells / well for SUM149-PT, 9 000 cells / well for MDAMB436). At day 2, drugs were added. Serial 1:3 dilutions were prepared starting from the maximal concentration. Cell viability was assessed after 3 doubling time using CellTiter-Glo (Promega). Three technical replicates were performed for each treatment and for each cell line. Combenefit* software was used to determine the combination synergistic potential with Bliss model. A positive score represented synergism, while a negative score represented antagonism.

[0148] 2. Results

[0149] 2.1 LST gene expression-based signature establishment

[0150] Training set: cohort of TNBC from TCGA

[0151] The inventors selected triple-negative breast cancer (BC) with gene expression data assessed by chips and LST status available as previously published (Popova T, et al. Cancer Res. 2012;72:5454-62). Among 92 patients, LST status was high in 47% (n=43) and low in 53% (n=49). After performing differential expression analysis, the inventors found that 64 genes were differentially expressed. The inventors performed gene enrichment analyses using GSEA and using MSigDB (Molecular signatures database v7.0). Positional gene sets Cl showed a marked enrichment in genes located on the 15q chromosome. Twenty-three genes out of 64 genes (36%) that were overexpressed in LST high tumors when compared to LST low tumors were located on the 15q chromosome (locus 26, n=ll; locus 25, n=9, locus 24, n=2; locus 21,n=l) (Figure 1A).

[0152] Based on the analyses of the GSEA computational method, the inventors found that the 64-genes signature was enriched in genes of different ontologies (mitotic_cell_cycle n=l 1; ccll_cyclc_proccss. n=17; protein_synthesis, n=15; DNA_replication, n=6; cell_cycle_integrity, n=8). Tumors and genes clustering split the cohort into 3 subgroups: a cluster of tumors containing most of the LST-high tumors, associated with an upregulation of genes from cluster 1 (located on the 15q chromosome), and genes from cluster 2 (containing most of the genes from the mitotic cell cycle, cell cycle process and integrity, protein synthesis and DNA replication). The second group contained most of the LST- low tumors and was enriched in genes from cluster 3, displaying no specific ontology. The signature was explored according to previous knowledge in the literature using String database (https : / / string- db.org / ) and revealed 2 main clusters of genes, and a majority of genes without known previous connection (Figure IB).

[0153] Validation set: second independent cohort ofTNBCs from TCGA

[0154] The inventors next aimed at validating the signature on an independent dataset. The inventors first analyzed the concordance between the gene expression assessed by chips and the gene expression assessed by RNASeq. Out of 92 samples from training set, 90 had both chips RNASeq gene expression data available. Fifty five out of 64 genes from the 64-genes signature were found in RNASeq gene expression data, and the expression by chips and RNASeq were compared in 90 common samples. Overall, the correlation was high (median ro=0.81, range [0.5-0.98]), indicating a high reproducibility between former (chips) and next generation sequencing technologies such as RNASeq. The inventors applied the 64-genes signatures to an independent dataset from TCGA. Of 88 patients with TNBC samples, 43 tumors were LST-high (49%), while 45 were LST-low (51%). Most genes from cluster 1 and 2 were significantly higher in LST-high tumors when compared with LST-low tumors. Such results were not found reproducible regarding genes from cluster 3, that were discarded from the signature for subsequent analyses (Figure 2).

[0155] 2.2 Signature refinement on external datasets

[0156] To refine the gene signature and increase robustness, the inventors next analyzed the gene signature in 3 external independent cohorts. The cohorts included 330 TNBC from the METABRIC consortium(2) (LST-high: n=152 (46%), LST-low, n=178 (54%)), and two ovarian cancer datasets from Institut curie (LST-high: n=43 (51%), LST-low, n=42 (49%)), and from TCGA(3) (LST-high: n=181 (50%), LST-low, n=183 (50%)) (Figure 3).

[0157] The inventors selected genes differentially expressed throughout the 3 datasets; and / or differentially expressed in 2 validation datasets and with a biological role as defined by the presence in the gene knowledge network. After gene selection, 16 genes remained in the final signature, including 8 located on the 15q chromosome. After averaging the gene expression of the 16 genes selected, the resulting metagenes were significantly higher in LSThigh than in LST low tumors (Figure 4). 2.3 Prospective validation on an in-house dataset of TNBCs

[0158] The inventors performed a prospective validation of the 16 genes using qpCR analysis in an in-house cohort of TNBC (n=97 TNBC, LST high n=69; LST low n=28). The 16-gene signature was significantly higher in LST-high than in LST-low tumors (Figure 5).

[0159] 2.4 Assessment of the performance of the 16-genes signature in predicting LST status

[0160] A Random Forest model was trained using the TCGA BRCA Chip dataset, yielding predictive performance across six independent external cohorts. The model yielded an Area Under the Receiver Operating Characteristic (AUC) between 0.67 and 0.84, indicating a discriminative ability in differentiating between patients of varying LST statuses. The accuracy of the model was established between a range of 0.62 to 0.7. Sensitivity and specificity measurements, indicators of the model's capability to correctly identify cases, ranged from 0.66 to 0.89 and 0.58 to 0.68 respectively, while the Fl -score, assessing the balance between precision and recall, was determined between 0.62 and 0.72. The evaluation of feature importance showed that the two main genes contributing to the model’s predictive power were EFTUD1 and FANCI (Figure 6). Conversely, the TICRR gene appeared to have the least influence on the model's predictive performance. Despite the diverse nature of the cohorts and the presence of missing gene expression data, the model maintained a degree of consistency in its performance.

[0161] 2.5 Copy number changes

[0162] The inventors performed copy number analyses on the 4 datasets with copy number data available. The genes from the signatures located on the 15q chromosome were associated in significant copy number gains of segments the 15q chromosome, suggesting that copy number gains on 15q could explain at least partially the highest expression of the genes of the 16-genes signature in LST-high tumors versus LST-low.

[0163] 2.6 Experimental tests on BC cell lines

[0164] Given the reproducible upregulation of the 16 genes including DNA repair, replication genes, ribosomal proteins or cytokinesis genes throughout the datasets, the inventors investigated if the addition of agents targeting pathways involved of the signature could potentiate synergy with PARP inhibitors. The inventors selected 5 drugs acting on the complex of Fanconi anemia / and or in MCM phosphorylation: - ATM inhibitors: M4076, AZD1390 - ATR inhibitors: M4344, ceralasertib (AZD6738) (ATRi) - UBE2T inhibitor: M435-1279. Combinations were assessed for synergy based on cell viability and according to the Bliss model. In the SUM149-PT cell line, high synergies were found between olaparib and ATM inhibitors, and to a lesser extent, between olaparib and ATR inhibitor (Figure 7). Similar trends though less marked were seen in the MDAMB436 cell line. No synergy was found between olaparib and UBE2T inhibitor in any cell line. Alltogether, these results suggest that targeting ATR and ATM pathways in combination with PARP inhibitor could provoke synthetic lethality in BRCAness tumors.

Claims

CLAIMS1. An in vitro method for identifying a patient having a tumor with a homologous recombination deficiency (HRD), preferably with a high large-scale transition (LST) status, said method comprising: determining the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 of the genes selected from the group consisting of: EFTUD1, FANCI, TK1, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR, preferably at least 1, 2, 3, 4, 5, 6, 7, or 8 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSH6, more preferably at least 1, 2, 3, or 4, of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUMO2, in a patient sample, wherein a higher gene expression level of the gene(s) in comparison to a control value in a patient sample is indicative that the tumor has homologous recombination deficiency.

2. An in vitro method for determining the therapeutic response of a tumor to DNA damaging agent treatment in a patient, said method comprising: determining the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, MSH6, HDDC3, KIF23, MRPS11, RCCD1, MCM3, MRPL46, MEF2A and TICRR, preferably at least 1, 2, 3, 4, 5, 6, 7, or 8 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUMO2, GMNN, PRC1, POLG, and MSH6, more preferably at least 1, 2, 3, or 4, of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUMO2, in a patient sample, wherein a higher gene expression level of the gene(s) in comparison to a control value in a patient sample is indicative that said tumor is likely responsive to said treatment.

3. The method according to claim 2, wherein the therapeutic response is determined before DNA damaging agent treatment or throughout the course of said treatment for monitoring the therapeutic response over time.

4. The method according to claim 2 or 3 wherein said DNA damaging agent is selected from the group consisting of: an alkylating agent, a platinum-based drug, a topoisomeraseinhibitor, a PARP inhibitor, an ATM inhibitor and an ATR inhibitor, preferably a PARP inhibitor.

5. The method according to any one of claims 1 to 4 comprising determining the gene expression level of: EFTUD1, preferably of each of the following genes: EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUM02.

6. The method according to any one of claims 1 to 5 wherein said cancer is selected from the group consisting of: ovarian cancer, breast cancer, fallopian tube cancer, peritoneal cancer, lung cancer, pancreatic cancer, head and neck cancer, prostate cancer, stomach or esophagus cancer, colorectal cancer, uterine cancer, cervical cancer, thyroid cancer, brain cancer, liver cancer, kidney cancer and bladder cancer, preferably ovarian or breast cancer.

7. The method according to any one of claims 1 to 6 wherein said patient sample is a tumor tissue sample or a blood sample.

8. The method according to any one of claims 1 to 7 wherein gene expression level is determined by detecting the mRNA expression of said genes, preferably by RT-qPCR or RNA seq.

9. A DNA damaging agent for use in the treatment of a cancer in a patient in need thereof wherein said DNA damaging agent is administered in a patient previously identified as having a tumor with HRD using the method according to any one of claims 1, 5 to 8.

10. A DNA damaging agent for use in the treatment of a cancer in a patient in need thereof wherein said DNA damaging agent is administered in a patient previously identified as having a tumor likely responsive to said treatment using the method according to any one of claims 2 to 8.

11. The DNA damaging agent for use of claim 9 or 10 wherein said DNA damaging agent is selected from the group consisting of: alkylating agents, platinum-based drugs, topoisomerase inhibitors, PARP inhibitors, ATM inhibitors and ATR inhibitors, preferably PARP inhibitor.

12. The PARP inhibitor for use of claim 11 wherein said PARP inhibitor is selected from the group consisting of: iniparib, olaparib, rucaparib, CEP 9722, niraparib, talazoparib, and 3- aminobenzamide, veliparib, pamiparib, NU1025, 5154-02-9, E7449, EB-47, GP-L PARP inhibitor, GLXC-26301, DR2313, 489457-67-2, BYK204165, INH2BP, PJ34.

13. A PARP inhibitor for use of claim 11 or 12 wherein said PARP inhibitor is administered in combination with ATR or ATM inhibitor, preferably ATM inhibitor.

14. A kit for identifying a patient having a tumor with a homologous recombination deficiency (HRD) comprising a set of reagents that specifically detects the gene expression level of at least 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15 or 16 of the genes selected from the group consisting of: EFL1, ETUD1, FANCI, GMNN, HDDC3, KIF23, MCM3, MEF2A, MRPL46, MRPS11, MSH6, POLG, PRC1, RCCD1, SUMO 2, TICRR and TK1, preferably at least 1, 2, 3, 4, 5, 6, 7, or 8 of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, SUM02, GMNN, PRC1, POLG, and MSH6, preferably at least 1, 2, 3, or 4, of the genes selected from the group consisting of: EFTUD1, FANCI, TKI, and SUM02, again more preferably wherein said reagents are primer pairs and / or probes specific of each gene.

15. The kit of claim 14 comprising a set of reagents that specifically detects the gene expression level of: EFTUD1, preferably each of the following genes: EFTUD1 and FANCI, more preferably EFTUD1, FANCI and TKI, again more preferably: EFTUD1, FANCI, TKI and SUM02.

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