Biomarkers for sacituzumabugovitecan therapy

Abstract

Provision of biomarkers for sacituzumab govitecan therapy. [Solution] The present invention relates to a biomarker used to treat Trop-2 expressing cancer using an anti-Trop-2 ADC containing an anti-Trop-2 antibody conjugated to a topoisomerase I inhibitor, preferably SN-38 or DxD. The anti-Trop-2 ADC may be administered as monotherapy or in combination with one or more anticancer agents such as DDR inhibitors. Treatment with ADC alone or in combination with other anticancer agents can reduce the size of solid tumors, reduce or eliminate metastases, and is effective in treating cancers resistant to standard therapy. Preferably, the combination therapy has an additive effect in inhibiting tumor growth. Most preferably, the combination therapy has a synergistic effect in inhibiting tumor growth.

Description

[Technical Field]

[0001] (Cross-reference of related applications) This application asserts the interests of U.S. Provisional Patent Application No. 62 / 992,728, filed on 20 March 2020, under § 119(e) of the U.S. Patent Act, which is incorporated herein by reference in its entirety for all purposes.

[0002] (Sequence Listing) This application includes a sequence listing submitted in ASCII format via EFS-Web, which is incorporated herein by reference in its entirety. The ASCII copy, created on March 17, 2021, is named IMM376-WO-PCT-SL.txt and is 1,667 bytes in size.

[0003] This patent application includes a long table section. Copies of the table have been submitted electronically in ASCII format and are incorporated herein by reference and may be used in the practice of the methods provided herein. The ASCII table, created on 3 December 2019, is as follows: (1) IMM376-WO-PCT Appendix 1.txt, 10,198 bytes; (2) IMM376-WO-PCT Appendix 2-Part A.txt, 3,491 bytes; (3) IMM376-WO-PCT Appendix 2-Part B.txt, 96,588 bytes; and (4) IMM376-WO-PCT Appendix 2-Part C.txt, 1,169 bytes.

[0004] (Field of invention) This disclosure relates to the use of anti-Trop-2 antibody-drug conjugates (ADCs), such as sacituzumab govitecan (IMMU-132), for the treatment of cancers expressing Trop-2. In certain embodiments, the ADC is used in conjunction with one or more diagnostic assays, e.g., genomic assays for detecting mutations or genetic variations, or functional assays, e.g., anti-Trop-2 Trop-2 expression levels can be used to predict cancer sensitivity to ADCs, either alone or in combination with one or more other therapeutic agents, such as DDR (DNA Damage Response) inhibitors. In specific embodiments, a single gene or physiological marker (collectively, “biomarker”), or a combination of two or more such biomarkers, may be useful in predicting cancer sensitivity to a particular combination of ADCs and other therapeutic agents. In preferred embodiments, the anti-Trop-2 antibody may be an hRS7 antibody, as described below. More preferably, the anti-Trop-2 antibody may be conjugated to the chemotherapeutic agent using a cleavable linker, such as a CL2A linker. Most preferably, the drug is SN-38 and the ADC is sacituzumab govitecan (also known as IMMU-132 or hRS7-CL2A-SN-38). However, other known anti-Trop-2 ADCs, such as DS-1062, may also be utilized. This disclosure is not limited to the range of drug combinations used in cancer therapy, but may include, but is not limited to, treatment with ADCs in combination with any other known cancer therapies, such as PARP inhibitors, ATM inhibitors, ATR inhibitors, CHK1 inhibitors, CHK2 inhibitors, Rad51 inhibitors, WEE1 inhibitors, CDK4 / 6 inhibitors, and / or platinum-based chemotherapeutic agents. In certain embodiments, combination therapy may comprise an anti-Trop-2 ADC and one or more of the anticancer agents listed above. Preferably, combination therapy with or without biomarker analysis is effective in treating resistant / recurrent cancers that are poorly responding to standard anticancer therapy or that show resistance to ADC monotherapy. Those skilled in the art will know that the biomarkers of interest can be useful for a variety of purposes, including improving diagnostic accuracy, personalizing patient treatment (precision medicine), confirming prognosis, predicting treatment outcomes and recurrence, monitoring disease progression, and / or identifying early recurrence from cancer therapy.In specific embodiments, the biomarker may be selected from gene markers in DDR or apoptotic genes, such as BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, or DDB2. Most preferably, one or more of the biomarkers may be used to distinguish between responders and non-responders to anti-Trop-2 ADCs such as sacituzumab govitecan or D-1062. [Background technology]

[0005] Sacituzumab govitecan is an anti-Trop-2 antibody-drug conjugate (ADC) that has demonstrated efficacy against a wide range of Trop-2 expressing epithelial cancers, including but not limited to breast cancer, triple-negative breast cancer (TNBC), HR+ / HER2-metastatic breast cancer, urothelial carcinoma, small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), colorectal cancer, gastric cancer, bladder cancer, kidney cancer, ovarian cancer, uterine cancer, endometrial cancer, prostate cancer, esophageal cancer, and head and neck cancers (Ocean et al., 2017, Cancer 123:3843-54; Starodub et al., 2015, Clin Cancer Res 21:3870-78; Bardia et al., 2018, J Clin Oncol 36(15_suppl):1004).

[0006] Unlike most other existing ADCs, sacituzumab govitecan (SG) is not conjugated to an extremely toxic drug, i.e., a toxin (Cardillo et al., 2015, Bioconj Chem 26:919-31). Rather, SG is conjugated via a CL2A linker (US Patent No. 7,999,083) to the active metabolite (SN38) of irinotecan, a topoisomerase I inhibitor, thus acting as an anti-Trop-2 inhibitor. This includes hRS7 antibodies (e.g., U.S. Patent No. 7,238,785, U.S. Patent No. 8,574,575). Perhaps due to the use of less toxic conjugate drugs, as well as the targeting effect of anti-Trop-2 antibodies, sacituzumab govitecan exhibits only moderate systemic toxicity, primarily neutropenia (Bardia et al., 2019, N Engl J Med). It has a very favorable therapeutic concentration range (380:741-51), and possesses a very favorable therapeutic concentration range (Ocean et al., 2017, Cancer 123:3843-54, Cardillo et al., 2011, Clin Cancer Res 17:3157-69).

[0007] Sacituzumab govitecan is effective as a second-line or subsequent treatment for a variety of tumors due to its activity in patients who have relapsed / refractory to standard chemotherapy and / or checkpoint inhibitors (Bardia et al., 2019, N Engl J Med 380:741-51, Faltas et al., 2016, Clin Genitourin Cancer 14:e75-9). For example, in the second-line or subsequent setting, a Phase I / II clinical trial of SG reported a 33.3% response rate, a 45.5% clinical benefit rate, a median progression-free survival (PFS) of 5.5 months, and an overall survival (OS) of 13.0 months in metastatic TNBC (Bardia et al., 2019, N Engl J Med 380:741-51). Patients treated with SG had previously been unsuccessful with other standard therapies, including taxanes, anthracyclines, and checkpoint inhibitor antibodies (Bardia et al., 2019, N Engl J Med 380:741-51). Interim results from a phase II open-label trial of sacituzumab govitecan in patients with metastatic urothelial carcinoma (mUC) have been published (Tagawa et al., 2019, Ann Oncol 30(suppl_5):v851-934, mdz394). In 35 mUC patients treated with 10 mg / kg sacituzumab govitecan (SG), the objective response rate (ORR) was 29%, with 2 complete responses (CR), 6 confirmed partial responses (PR), and 2 PRs pending. 74 percent of treated patients showed tumor size reduction. The ORR in patients with liver metastases was 25%. SG demonstrated a manageable, predictable, and consistent safety profile with no grade 3 or higher neuropathy, no interstitial lung disease, no treatment-related deaths, and good tolerability. These data are based on initial data from the first first-in-human trial of sacituzumab govitecan (IMMU-132-01), in which an ORR of 31% was reported in 45 patients with urothelial carcinoma treated with the recommended phase 2 dose of sacituzumab govitecan.

[0008] Clinical outcomes for SG have also been obtained in patients with non-small cell lung cancer (NSCLC) (Heist et al., 2017, J Clin Oncol 35:2790-97). In 47 evaluable patients who had received a median of three prior therapies (including checkpoint inhibitors), the ORR was 19% and the clinical benefit rate was 43%. The median PFS was 5.2 months and the median OS was 9.5 months. Similar results were obtained in metastatic SCLC (Gray et al., 2017, Clin Cancer Res 23:5711-19). In 53 mSCLC patients treated with SC, the ORR was 14%, the median duration of response was 5.7 months, the median PFS was 3.7 months, and the median OS was 7.5 months. 60 percent of patients showed tumor shrinkage from baseline. Based on the results described above, it was concluded that SG is safe and effective for use in the treatment of a wide variety of Trop-2+ cancers. Despite these favorable responses to treatment with anti-Trop-2 ADCs, a significant proportion of patients still do not respond to, or develop resistance to, monotherapy with ADCs. There is a need for diagnostic assays or combinations of assays that can identify patients with tumors that are more susceptible to treatment with anti-Trop-2 ADCs such as sacituzumab govitecan, or to the effects of combination therapy of ADCs with one or more other known anti-cancer treatments. There is a further need for biomarkers that can identify patients with residual disease, and / or patients at high risk of recurrence, for whom treatment with the ADC alone, or in combination with other agents, may be effective.

Prior Art Documents

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[0011] In one embodiment, the foregoing provides a method for treating Trop-2-expressing cancer in a patient with anti-Trop-2 ADC, either alone or in combination with at least one other known anticancer therapy. In some embodiments, the method provided herein involves the use of one or more biomarkers and assays prior to administering anti-Trop-2 ADC to a patient having Trop-2-expressing cancer. In some embodiments, the method involves the use of one or more biomarkers for selecting patients to be treated with anti-Trop-2 ADC. In certain embodiments, the method provided herein involves the use of one or more diagnostic assays to predict and / or indicate the need for treatment of Trop-2-expressing cancer with anti-Trop-2 ADC, either alone or in combination with at least one other known anticancer therapy. Such assays may detect the presence or absence of DNA or RNA biomarkers such as mutations, promoter methylation, chromosomal rearrangement, gene amplification, and / or RNA splice variants. Alternatively, such assays may detect overexpression of mRNA and / or protein products of major genes such as Trop-2.The target genes used as biomarkers or for diagnostic assays include 53BP1, AKT1, AKT2, AKT3, APE1, ATM, ATR, BARD1, BAP1, BLM, BRAF, BRCA1, BRCA2, BRIP1 (FANCJ), CCND1, CCNE1, CCDKN1, CDK12, CHEK1, CHEK2, CK-19, CSA, CSB, DCLRE1C, DNA2, DSS1, EEPD1, EFHD1, EpCAM, ERCC1, ESR1, EXO1, FAAP24, FANC1, FANCA, FANCC, FANCD1, FANCD2, FANCE, FANCF, FANCM, HER2, HMBS, HR23B, KRT19, KU70, KU80, hMAM, MAGEA1, MAGEA3, and MA Possible but not limited to PK, MGP, MLH1, MRE11, MRN, MSH2, MSH3, MSH6, MUC16, NBM, NBS1, NER, NF-κB, P53, PALB2, PARP1, PARP2, PIK3CA, PMS2, PTEN, RAD23B, RAD50, RAD51, RAD51AP1, RAD51C, RAD51D, RAD52, RAD54, RAF, K-ras, H-ras, N-ras, RBBP8, c-myc, RIF1, RPA1, SCGB2A2, SLFN11, SLX1, SLX4, TMPRSS4, TP53, TROP-2, USP11, VEGF, WEE1, WRN, XAB2, XLF, XPA, XPC, XPD, XPF, XPG, XRCC4, and XRCC7. (For example, Kwan et al.,2018,Cancer Discov 8:1286-99, Vardakis et al.,2010,Clin Cancer Res,17:165-73, Lianidou & Markou,2011,Clin Chem 57:1242-55, Xing et al.,2019,Breast Cancer Res 21:78, Banno et al. al., 2017, Int J Oncol 50:2049-58, Yaganeh et al., 2017, Genes Cancer 8:784-98, Kitazano et al., Cancer. Sci,Jul 30,2019(Epub ahead of print), Allegra et al.,2016,J Clin Oncol 34:179-85, Shaw et al.,2017,Clin Cancer Res 23:88-96, Jin et al.,2017,Cancer Biol Ther 18:369-78, Williamson et al.,2016,Nature Commun 7:13837, McCabe et al., 2006, Cancer Res. See 66:8109-15, Srivastava & Raghavan, 2015, Chem Biol 22:17-29). In more specific embodiments, the target gene may be selected from BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2.

[0012] Different forms of biomolecules can be detected, purified, and / or analyzed. In certain embodiments, cancer biomarkers can be detected by direct sampling (biopsy) of a suspected tumor, for example, using immunohistochemistry, Western blotting, RT-PCR, or other known techniques. Preferably, biomarkers can be detected in blood, lymph, serum, plasma, urine, or other fluids (liquid cytology). Biomarkers in liquid cytology samples may appear in various forms such as proteins, cfDNA (cell-free DNA), ctDNA (circulating tumor DNA), and CTCs (circulating tumor cells), each of which can be detected using specific advanced detection techniques discussed in detail below. The methods and compositions disclosed herein are generally useful for the detection, identification, characterization, and / or prognosis of cancer, but in more specific embodiments, they may be applied to tumors expressing specific tumor-associated antigens (TAAs), such as Trop-2. In such embodiments, the expression level or copy number of a TAA (e.g., Trop-2) may have predictive values, independently of or in combination with other cancer biomarkers. Such predictive biomarkers may be useful in predicting sensitivity or resistance to ADC monotherapy or ADC combination therapy with other anticancer agents, or in predicting the toxicity of treatment or the need for treatment. Such biomarkers may also be useful in confirming the presence or absence of a particular tumor type, or in predicting the course of disease in patients exhibiting a particular biomarker or combination of biomarkers. Other uses of biomarkers include improving diagnostic accuracy, personalizing patient treatment (precision medicine), monitoring disease progression, and / or detecting early recurrence from cancer therapy.

[0013] In certain embodiments, circulating tumor cells (CTCs) can be isolated from blood, serum, or plasma. The presence of CTCs in a patient's blood, plasma, or serum may predict metastatic cancer after previous anticancer treatment or indicate residual cancer cells. In addition to the diagnostic value of the presence of CTCs themselves, isolated CTCs can also be tested for the presence of one or more biomarkers (e.g., Shaw et al., 2017, Clin Cancer Res 23:88-96; Tellez-Gabriel et al., 2019, Theranostics 9:4580-94; Kwan et al., 2018, Cancer Discov 8:1286-99). For example, a method for isolating CTCs from serum or plasma using the CELLSEARCH® system is discussed in more detail below. Trop-2+ or EpCAM+ CTCs can be isolated by using anti-Trop-2, anti-EpCAM, or other known antibodies as capture antibodies. Alternatively, combinations of capture antibodies known for use in CTC detection or isolation may be used.

[0014] In preferred embodiments, the present invention includes combination therapy using an anti-Trop-2 ADC in combination with one or more known anticancer agents. Such agents may include, but are not limited to, PARP inhibitors, ATM inhibitors, ATR inhibitors, CHK1 inhibitors, CHK2 inhibitors, Rad51 inhibitors, WEE1 inhibitors, PI3K inhibitors, AKT inhibitors, CDK4 / 6 inhibitors, and / or platinum-based chemotherapeutic agents.Specific drugs useful in combination therapy will be discussed in more detail below, but include olaparib, rucaparib, talazoparib, veliparib, niraparib, acalabrutinib, temozolomide, atezolizumab, pembrolizumab, nivolumab, ipilimumab, pizilizumab, durvalumab, BMS-936559, BMN-673, tremelimumab, idelalisib, and Matinib, ibrutinib, eribulin mesylate, abemaciclib, palbociclib, ribociclib, trilaciclib, beruzocertib, ipatasertib, uprosertib, afrecertib, trisirivine, ceraracertib, dinacyclib, flavopyridol, roscovitine, G1T38, SHR6390, copanlisib, temsirolimus, everolimus, KU 60019, KU 55933, KU 59403, AZ20, AZD0156, AZD1390, AZD1775, AZD2281, AZD5363, AZD6738, AZD7762, AZD8055, AZD9150, BAY-937, BAY1895344, BEZ235, CCT241533, CCT244747, CGK 733, CID44640177, CID1434724, CID46245505, CHIR-124, EPT46464, FTC, VE- 821, VRX0466617, VX-970, LY294002, LY2603618, M1216, M3814, M4344, M6620 , MK-2206, NSC19630, NSC109555, NSC130813, NSC205171, NU6027, NU7026, Prexasertib (LY2606368), PD0166285, PD407824, PV1019, SCH900776, SRA737, BMN May contain 673, CYT-0851, mirin, Torin-2, fluoroquinoline 2, fumitremorgin C, curcumin, Kol43, GF120918, YHO-13351, YHO-13177, XL9844, woltmannin, lapatinib, sorafenib, sunitinib, nilotinib, gemcitabine, bortezomib, trichostatin A, paclitaxel, cytarabine, cisplatin, oxaliplatin and / or carboplatin.

[0015] More preferably, combination therapy is more effective than ADC alone, anticancer drug alone, or the combined effects of ADC and anticancer drug. Most preferably, combination therapy exhibits a synergistic effect in the treatment of diseases such as cancer in human subjects. In alternative embodiments, ADC or combination therapy may be used as neoadjuvant or adjuvant therapy in conjunction with surgery, radiotherapy, chemotherapy, immunotherapy, radioimmunotherapy, immunomodulators, vaccines, and other standard cancer treatments.

[0016] In embodiments utilizing an anti-Trop-2 ADC, the anti-Trop-2 antibody moiety is preferably an hRS7 antibody comprising the light chain CDR sequences CDR1(KASQDVSIAVA, SEQ ID NO: 1), CDR2(SASYRYT, SEQ ID NO: 2), and CDR3(QQHYITPLT, SEQ ID NO: 3), and the heavy chain CDR sequences CDR1(NYGMN, SEQ ID NO: 4), CDR2(WINTYTGEPTYTDDFKG, SEQ ID NO: 5), and CDR3(GGFGSSYWYFDV, SEQ ID NO: 6). In more preferred embodiments, the anti-Trop-2 ADC is sacituzumab govitecan (hRS7-CL2A-SN-38). However, in alternative embodiments, other known anti-Trop-2 ADCs may be used, as discussed below.

[0017] In preferred embodiments, the drug moiety conjugated to the target antibody for forming the ADC is an active metabolite of a topoisomerase I inhibitor, such as SN-38 (Moon et al., 2008, J Med Chem 51:6916-26) or DxD (Ogitani et al., 2016 Clin Cancer Res 22:5097-108, Ogitani et al., 2016 Bioorg Med Chem). (Lett 26:5069-72). However, other drug parts that may be used include taxanes (e.g., baccatin III, taxol), auristatin (e.g., MMAE), calcaremycin, epothilon, anthracyclines (e.g., doxorubicin (DOX), epirubicin, morpholinodoxorubicin, cyanomorpholinodoxorubicin, 2-pyrrolinodoxorubicin), topotecan, etoposide, cisplatin, oxaliplatin, or carboplatin (see, for example, Priebe W (ed.), 1995, ACS symposium series 574, published by American Chemical Society, Washington DC, (332 pp), Nagy et al., 1996, Proc. Natl. Acad. Sci. USA 93:2464-2469). In general, any anti-cancer cytotoxic agent, more preferably a drug that causes DNA damage, can be used. Preferably, the antibody or fragment thereof is bound to at least one chemotherapeutic drug moiety, preferably 1 to 5 drug moieties, more preferably 6 to 12 drug moieties, and most preferably about 6 to about 8 drug moieties.

[0018] Various embodiments may involve the use of the methods and compositions of interest for treating cancers including, but not limited to, cancers of the oral cavity, esophagus, gastrointestinal tract, lungs, stomach, colon, rectum, breast, ovaries, prostate, pancreas, uterus, endometrium, cervix, bladder, bone, brain, connective tissue, thyroid gland, liver, gallbladder, urothelial cells, kidneys, skin, central nervous system, and testes. Preferably, the cancer may be metastatic triple-negative breast cancer (TNBC), metastatic HR+ / HER2- breast cancer, metastatic non-small cell lung cancer, metastatic small cell lung cancer, metastatic endometrial cancer, metastatic urothelial carcinoma, metastatic pancreatic cancer, metastatic prostate cancer, or metastatic colorectal cancer. The cancer to be treated may be metastatic or non-metastatic, and the treatments of interest may be used as first-line, second-line, third-line, or late-stage cancers, and in neoadjuvant, adjuvant, metastatic, or maintenance conditions. In some embodiments, the cancer is urothelial carcinoma. In some embodiments, the cancer is metastatic urothelial carcinoma. In some embodiments, the cancer is treatment-resistant urothelial carcinoma. In some embodiments, the cancer is resistant to treatment with platinum-based and / or checkpoint inhibitor (CPI) therapies (e.g., anti-PD1 antibody or anti-PD-L1 antibody). In some embodiments, the cancer is metastatic TNBC.

[0019] The preferred optimal dose of ADC may include a dose of 4-16 mg / kg, preferably 6-12 mg / kg, more preferably 8-10 mg / kg, administered once weekly, twice weekly, every two weeks, or every three weeks. The optimal administration schedule may include treatment cycles of 2 consecutive weeks of treatment followed by a 1-week, 2-week, 3-week, or 4-week rest period, or treatment and rest every other week, or 1 week of treatment followed by a 2-week, 3-week, or 4-week rest period, or 3 weeks of treatment followed by a 1-week, 2-week, 3-week, or 4-week rest period, or 5 weeks of treatment followed by a 1-week, 2-week, 3-week, 4-week, or 5-week rest period, or administration once every two weeks, once every three weeks, or once every month. Treatment may be extended by any number of cycles. Exemplary doses may include 1 mg / kg, 2 mg / kg, 3 mg / kg, 4 mg / kg, 5 mg / kg, 6 mg / kg, 7 mg / kg, 8 mg / kg, 9 mg / kg, 10 mg / kg, 11 mg / kg, 12 mg / kg, 13 mg / kg, 14 mg / kg, 15 mg / kg, 16 mg / kg, 17 mg / kg, or 18 mg / kg. Those skilled in the art will understand that various factors such as age, overall health, function of specific organs, or body weight, as well as the effects of prior treatment on specific organ systems (e.g., bone marrow), and the treatment objective (curative or palliative), may be considered when selecting the optimal dose and schedule of ADC, and that the dose and / or frequency may be increased or decreased during the course of treatment. Dosage may be repeated as needed based on evidence of tumor shrinkage observed after approximately 4 to 8 doses. The use of combination therapy may allow for lower doses of each therapeutic agent in such combinations, thus potentially reducing certain serious side effects and shortening the required course of treatment. If there is no or minimal overlapping toxicity, sufficient amounts of each substance may also be administered.

[0020] The claimed method provides a reduction in the size of a solid tumor by 15% or more, preferably 20% or more, preferably 30% or more, and more preferably 40% or more (measured by summing the longest diameters of the target lesion according to RECIST or RECIST 1.1). Those skilled in the art will understand that tumor size can be measured by a variety of different methods, such as total tumor volume, maximum tumor size in any dimension, or a combination of size measurements in several dimensions. This may be by standard radiological examinations such as computed tomography, magnetic resonance imaging, ultrasound, and / or positron emission tomography. The means of sizing is less important than observing the trend of tumor size reduction, preferably the result of tumor elimination, with antibody or immune complex therapy. However, in accordance with RECIST guidelines, serial CT or MRI with contrast is preferred and should be repeated to confirm the measurement. In the case of hematological malignancies, imaging as described above, as well as other standard measures of cancer response such as cell counts of different cell populations, detection and / or levels of circulating tumor cells, immunohistochemical examination, cytological examination, or fluorescence microscopy, and similar techniques may be utilized.

[0021] The optimized doses and schedules of administration disclosed herein, with or without biomarker analysis, demonstrate unexpectedly superior efficacy and reduced toxicity in human subjects, which were not predicted from animal model studies. Remarkably, the superior efficacy enables the treatment of tumors previously found to be resistant to one or more standard anticancer agents, including several tumors that were unsuccessful with irinotecan, the parent compound of SN-38. The present invention provides, for example, the following items: (Item 1) A method for treating Trop-2 expressing cancer, a) Assaying human samples with Trop-2 expressing cancer for the presence of one or more cancer biomarkers, b) To detect one or more biomarkers related to sensitivity to anti-Trop-2 antibody-drug conjugates (ADCs), c) A method comprising treating the subject with an anti-Trop-2 ADC containing an anti-Trop-2 antibody conjugated to a topoisomerase I inhibitor. (Item 2) d) To detect one or more biomarkers related to sensitivity to combination therapy with anti-Trop-2 ADCs and DDR inhibitors, e) The method according to item 1, further comprising treating the subject with a combination of an anti-Trop-2 ADC and a DDR (DNA damage repair) inhibitor. (Item 3) A method for selecting patients to be treated with anti-Trop-2 antibody-drug conjugates (ADCs), a) Analyze samples derived from human cancer patients for the presence of one or more cancer biomarkers, b) Detecting one or more biomarkers related to susceptibility or toxicity to anti-Trop-2 ADCs, c) Selecting patients to be treated with anti-Trop-2 ADC based on the presence of one or more of the biomarkers, d) A method comprising treating the selected patient with an anti-Trop-2 ADC. (Item 4) e) Selecting patients to be treated with combination therapy based on the presence of one or more biomarkers, f) The method according to item 3, further comprising treating the patient with a combination of an anti-Trop-2 ADC and a DDR inhibitor. (Item 5) The method according to item 3 or 4, wherein the anti-Trop-2 ADC is administered to the patient as neoadjuvant therapy prior to the administration of at least one other anticancer therapy. (Item 6) e) Monitoring the patient for the presence of one or more biomarkers f) The method according to any one of items 3 to 5, further comprising determining the cancer's response to the treatment. (Item 7) The method according to item 6, further comprising monitoring for residual disease or recurrence in the patient based on biomarker analysis. (Item 8) The method according to any one of items 3 to 7, further comprising determining the outcome or prognosis of disease progression based on biomarker analysis. (Item 9) The method according to any one of items 3 to 8, further comprising selecting an optimized individualized therapy for the patient based on biomarker analysis. (Item 10) The method according to any one of items 3 to 9, further comprising staging the cancer based on biomarker analysis. (Item 11) The method according to any one of items 3 to 10, further comprising stratifying the patient population for initial treatment based on biomarker analysis. (Item 12) The method described in any one of items 3 to 11, further including recommending supportive therapies to improve side effects of ADC treatment based on biomarker analysis. (Item 13) The method according to any one of items 1 to 12, wherein the sample is a biopsy sample derived from a solid tumor. (Item 14) The method according to any one of items 1 to 13, wherein the sample is a liquid cytology sample. (Item 15) The method according to any one of items 1 to 14, wherein the sample comprises cfDNA, ctDNA, or circulating tumor cells (CTCs). (Item 16) The method according to any one of items 1 to 15, wherein the sample contains CTCs, and the CTCs are analyzed for the presence of one or more cancer biomarkers. (Item 17) The method according to any one of items 1 to 16, wherein the biomarker is a gene marker in a DNA damage repair (DDR) gene or an apoptosis gene. (Item 18) The method according to any one of items 1 to 17, wherein the gene is selected from the group consisting of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2. (Item 19) The method according to any one of items 1 to 17, wherein the biomarker includes or consists of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2. (Item 20) The method according to any one of items 1 to 17, wherein the biomarker includes or consists of AEN, MSH2, MYBBP1A, SART1, SIRT1, USP28, CDKN1A, ABL1, TP53, BAG6, BRCA1, BRCA2, BRSK2, CHEK2, ERN1, FHIT, HIPK2, HRAS, LGALS12, MSH6, ZNF385B, and ZNF622. (Item 21) The method according to any one of items 1 to 17, wherein the biomarker includes or consists of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, and USP28. (Item 22) The method according to any one of items 1 to 17, wherein the biomarker includes or consists of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A. (Item 23) The method according to any one of items 1 to 17, wherein the biomarker includes or consists of GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A. (Item 24) The method according to any one of items 1 to 17, wherein the biomarker includes or consists of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A. (Item 25) The method according to any one of items 1 to 17, wherein the gene is selected from the group consisting of BRCA1, BRCA2, PTEN, ERCC1, and ATM. (Item 26) The method according to any one of items 1 to 17, wherein the biomarker includes or consists of BRCA1, BRCA2, PTEN, ERCC1, and ATM. (Item 27) The aforementioned biomarkers are single nucleotide polymorphisms, and include E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, and TP53. * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * The method described in any one of items 1 to 17, which results in a substitutional mutation selected from the group consisting of I987L in USP28, R370Q in ZNF385B, and A437E in ZNF622. (Item 28) The aforementioned biomarker is a single nucleotide polymorphism, and includes E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, and TP53. * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * The method described in any one of items 1 to 17, which results in substitutions including or consisting of I987L in USP28, R370Q in ZNF385B, and A437E in ZNF622. (Item 29) The aforementioned biomarker is a single nucleotide polymorphism, and includes V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, N127S in MSH2, S625F in MSH6, R373Q in SART1, and TP53. * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * The method described in any one of items 1 to 17, which results in a substitution including or comprising I987L in USP28. (Item 30) The method according to any one of items 1 to 17, wherein the biomarker is a frameshift mutation selected from the group consisting of K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A. (Item 31) The method according to any one of items 1 to 17, wherein the biomarker is a combination of multiple frameshift mutations including K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A. (Item 32) The method according to any one of items 1 to 17, wherein the biomarker is an increase or decrease in gene expression in the cancer of a gene selected from the group consisting of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue. (Item 33) The method according to any one of items 1 to 17, wherein the biomarker is a plurality of increases or decreases in gene expression in the cancer, including or comprising POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue. (Item 34) The method according to any one of items 1 to 33, wherein the biomarker is selected from the group consisting of mutation, insertion, deletion, chromosomal rearrangement, SNP (single nucleotide polymorphism), DNA methylation, gene amplification, RNA splice variant, miRNA, increased gene expression, decreased gene expression, protein phosphorylation, and protein dephosphorylation. (Item 35) The method according to any one of items 1 to 34, wherein the assay of the sample includes next-generation sequencing of DNA or RNA. (Item 36) The method according to any one of items 1 to 35, wherein the topoisomerase I inhibitor is SN-38 or DxD. (Item 37) The method according to any one of items 1 to 36, wherein the anti-Trop-2 ADC is selected from the group consisting of sacituzumab govitecan and DS-1062. (Item 38) The aforementioned DDR inhibitors include 53BP1, APE1, Artemis, ATM, ATR, ATRIP, BAP1, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDC2, CDC25A, CDC25C, CDK1, CDK12, CHK1, CHK2, CSA, CSB, CtIP, Cyclin B, Dna2, DNA-PK, EEPD1, EME1, ERCC1, ERCC2, ERCC3, ERCC4, Exo1, FAAP24, FANC1, FANCM, FAND2, HR23B, HUS1, KU70, KU80, Lig The method according to any one of items 2 to 37, wherein the inhibitor is of III, ligase IV, Mdm2, MLH1, MRE11, MSH2, MSH3, MSH6, MUS81, MutSα, MutSβ, NBS1, NER, p21, p53, PALB2, PARP, PMS2, Polμ, Polβ, Polδ, Polε, Polκ, Polλ, PTEN, RAD1, RAD17, RAD23B, RAD50, RAD51, RAD51C, RAD52, RAD54, RAD9, RFC2, RFC3, RFC4, RFC5, RIF1, RPA, SLX1, SLX4, TopBP1, USP11, WEE1, WRN, XAB2, XLF, XPA, XPC, XPD, XPF, XPG, XRCC1, or XRCC4. (Item 39) The method according to any one of items 2 to 38, wherein the DDR inhibitor is an inhibitor of PARP, CDK12, ATR, ATM, CHK1, CHK2, CDK12, RAD51, RAD52, or WEE1. (Item 40) The method according to item 33, wherein the PARP inhibitor is selected from the group consisting of olaparib, talazoparib (BMN-673), lucaparib, veliparib, niraparib, CEP 9722, MK 4827, BGB-290 (pamiparib), ABT-888, AG014699, BSI-201, CEP-8983, E7016, and 3-aminobenzamide. (Item 41) The method according to item 33, wherein the CDK12 inhibitor is selected from the group consisting of dinacyclib, flavopridol, roscovitine, THZ1, and THZ531. (Item 42) The method according to item 33, wherein the RAD51 inhibitor is selected from the group consisting of B02((E)-3-benzyl-2(2-(pyridine-3-yl)vinyl)quinazoline-4(3H)-one), RI-1(3-chloro-1-(3,4-dichlorophenyl)-4-(4-morpholinyl)-1H-pyrrole-2,5-dione), DIDS(4,4'-diisothiocyanostilbene-2,2'-disulfonic acid), halenaquinone, CYT-0851, IBR2, and imatinib. (Item 43) The method according to item 33, wherein the ATM inhibitor is selected from the group consisting of Waltmannin, CP-466722, KU-55933, KU-60019, KU-59403, AZD0156, AZD1390, CGK733, NVP-BEZ 235, Torin-2, Fluoroquinoline 2, and SJ573017. (Item 44) The method according to item 33, wherein the ATR inhibitor is selected from the group consisting of cisandrin B, NU6027, BEZ235, ETP46464, Torin 2, VE-821, VE-822, AZ20, AZD6738 (ceraracertib), M4344, BAY1895344, BAY-937, AZD6738, BEZ235 (dactricib), CGK 733, and VX-970. (Item 45) The method according to item 33, wherein the CHK1 inhibitor is selected from the group consisting of XL9844, UCN-01, CHIR-124, AZD7762, AZD1775, XL844, LY2603618, LY2606368 (prexasertib), GDC-0425, PD-321852, PF-477736, CBP501, CCT-244747, CEP-3891, SAR-020106, Arry-575, SRA737, V158411, and SCH 900776 (MK-8776). (Item 46) The method according to item 33, wherein the CHK2 inhibitor is selected from the group consisting of NSC205171, PV1019, CI2, CI3, 2-arylbenzimidazole, NSC109555, VRX0466617, and CCT241533. (Item 47) The method according to item 33, wherein the WEE1 inhibitor is selected from the group consisting of AZD1775 (MK1775), PD0166285, and PD407824. (Item 48) The method according to any one of items 2 to 47, wherein the DDR inhibitor is selected from the group consisting of mirin, M1216, NSC19630, NSC130813, LY294002, and NU7026. (Item 49) The method according to any one of items 2 to 48, wherein the DDR inhibitor is not an inhibitor of PARP or RAD51. (Item 50) The method according to any one of items 1 to 49, wherein the anti-Trop-2 ADC comprises an hRS7 antibody comprising the light chain CDR sequences CDR1(KASQDVSIAVA, SEQ ID NO: 1), CDR2(SASYRYT, SEQ ID NO: 2), and CDR3(QQHYITPLT, SEQ ID NO: 3), and the heavy chain CDR sequences CDR1(NYGMN, SEQ ID NO: 4), CDR2(WINTYTGEPTYTDDFKG, SEQ ID NO: 5), and CDR3(GGFGSSYWYFDV, SEQ ID NO: 6). (Item 51) Olaparib, Lucaparib, Talazoparib, Veliparib, Niraparib, Acalabrutinib, Temozolomide, Atezolizumab, Pembrolizumab, Nivolumab, Ipilimumab, Pizilizumab, Durvalumab, BMS-936559, BMN-673, Tremelimumab, Idelalisib, Imatinib, Ibrutinib, Eribulin Mesylate, Abemaciclib, Palbociclib, Ribociclib, Trilaciclib, Belzocertib, Ipatasertib, Uprosertib, Afrecertib, Tricilibine, Ceraracertib, Dinacyclib, Flavopyridol, Roscovitine, G1T38, SHR6390, Copanlisib, Temsirolimus, Everolimus, KU 60019, KU 55933,KU 59403, AZ20, AZD0156, AZD1390, AZD1775, AZD2281, AZD5363, AZD6738, AZD7762, AZD8055, AZD9150, BAY-937, BAY1895344, BEZ235, CCT241533, CCT244747, CGK 733, CID44640177, CID1434724, CID46245505, CHIR-124, EPT46464, FTC, VE- 821, VRX0466617, VX-970, LY294002, LY2603618, M1216, M3814, M4344, M6620 , MK-2206, NSC19630, NSC109555, NSC130813, NSC205171, NU6027, NU7026, Prexasertib (LY2606368), PD0166285, PD407824, PV1019, SCH900776, SRA737, BMN The method according to any one of items 1 to 50, further comprising treating the subject with an anticancer agent selected from the group consisting of 673, CYT-0851, mirin, Torin-2, fluoroquinoline 2, fumitremorgin C, curcumin, Kol43, GF120918, YHO-13351, YHO-13177, XL9844, woltmannin, lapatinib, sorafenib, sunitinib, nilotinib, gemcitabine, bortezomib, trichostatin A, paclitaxel, cytarabine, cisplatin, oxaliplatin, and carboplatin. (Item 52) The method according to any one of items 1 to 51, wherein the cancer is selected from the group consisting of breast cancer, triple-negative breast cancer (TNBC), HR+ / HER2- metastatic breast cancer, urothelial carcinoma, small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), colorectal cancer, gastric cancer, bladder cancer, kidney cancer, ovarian cancer, uterine cancer, endometrial cancer, cervical cancer, prostate cancer, esophageal cancer, pancreatic cancer, brain cancer, liver cancer, and head and neck cancer. (Item 53) The method according to any one of items 1 to 52, wherein the cancer is urothelial carcinoma. (Item 54) The method according to any one of items 1 to 53, wherein the cancer is metastatic urothelial carcinoma. (Item 55) The method according to any one of items 1 to 54, wherein the cancer is treatment-resistant urothelial carcinoma. (Item 56) The method according to any one of items 1 to 55, wherein the cancer is resistant to treatment with platinum-based and / or checkpoint inhibitor (CPI) (e.g., anti-PD1 antibody or anti-PD-L1 antibody) therapies. (Item 57) The method according to any one of items 1 to 52, wherein the cancer is metastatic TNBC. (Item 58) A method for predicting clinical outcomes in subjects with Trop-2 expressing cancer after treatment with an anti-Trop-2 ADC, comprising assaying a sample derived from a human subject with Trop-2 expressing cancer for the presence of one or more cancer biomarkers, wherein the presence or absence of the one or more cancer biomarkers predicts the clinical outcome in the subject. (Item 59) The method according to item 58, wherein the presence or absence of one or more cancer biomarkers predicts the effectiveness of treatment with an anti-Trop-2 ADC, and the ADC comprises a topoisomerase I inhibitor. (Item 60) The method according to item 58 or 59, wherein the presence or absence of one or more cancer biomarkers predicts the efficacy or safety of combination therapy with an anti-Trop-2 ADC and a DDR inhibitor. (Item 61) The method according to any one of items 58-60, wherein the presence or absence of one or more cancer biomarkers predicts the efficacy or safety of combination therapy with anti-Trop-2 ADC and standard anticancer therapy. (Item 62) The method according to any one of items 58 to 61, wherein the biomarker is selected from the group consisting of mutation, insertion, deletion, chromosomal rearrangement, SNP (single nucleotide polymorphism), DNA methylation, gene amplification, RNA splice variant, miRNA, increased gene expression, decreased gene expression, protein phosphorylation, and protein dephosphorylation. (Item 63) The method according to any one of items 58 to 62, wherein the biomarker is a gene marker in a DNA damage repair (DDR) gene or an apoptotic gene. (Item 64) The method according to item 63, wherein the gene is selected from the group consisting of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2. (Item 65) The method according to any one of items 58 to 63, wherein the biomarker includes or consists of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2. (Item 66) The method according to any one of items 58 to 63, wherein the biomarker includes or consists of AEN, MSH2, MYBBP1A, SART1, SIRT1, USP28, CDKN1A, ABL1, TP53, BAG6, BRCA1, BRCA2, BRSK2, CHEK2, ERN1, FHIT, HIPK2, HRAS, LGALS12, MSH6, ZNF385B, and ZNF622. (Item 67) The method according to any one of items 58 to 63, wherein the biomarker includes or consists of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, and USP28. (Item 68) The method according to any one of items 58 to 63, wherein the biomarker includes or consists of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A. (Item 69) The method according to any one of items 58 to 63, wherein the biomarker includes or consists of GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A. (Item 70) The method according to any one of items 58 to 63, wherein the biomarker includes or consists of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A. (Item 71) The method according to any one of items 58 to 63, wherein the gene is selected from the group consisting of BRCA1, BRCA2, PTEN, ERCC1, and ATM. (Item 72) The method according to any one of items 58 to 63, wherein the biomarker includes or consists of BRCA1, BRCA2, PTEN, ERCC1, and ATM. (Item 73) where the biomarker is a single nucleotide polymorphism, E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, * 394S in TP53, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 * in TP53, I987L in USP28, R370Q in ZNF385B, and A437E in ZNF622, and the method according to any one of items 58 to 63, which results in a substitution mutation and is selected from the group consisting of (Item 74) where the biomarker is a plurality of single nucleotide polymorphisms, E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, * 394S in TP53, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 * in TP53, I987L in USP28, R370Q in ZNF385B, and A437E in ZNF622, and the method according to any one of items 58 to 63, which results in a substitution and includes or consists of these (Item 75) The aforementioned biomarker is a single nucleotide polymorphism, and includes V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, N127S in MSH2, S625F in MSH6, R373Q in SART1, and TP53. * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * The method described in any one of items 58 to 63, which results in a substitution including or comprising I987L in USP28. (Item 76) The method according to any one of items 58 to 63, wherein the biomarker is a frameshift mutation selected from the group consisting of K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A. (Item 77) The method according to any one of items 58 to 63, wherein the biomarker is a plurality of frameshift mutations including K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A. (Item 78) The method according to any one of items 58 to 63, wherein the biomarker is an increase or decrease in gene expression in the cancer of a gene selected from the group consisting of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue. (Item 79) The method according to any one of items 58 to 63, wherein the biomarker is an increase or decrease in gene expression in the cancer, comprising or including POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue. (Item 80) The method according to any one of items 58 to 79, further comprising measuring an increase or decrease in gene expression of two or more genes in the said cancer. (Item 81) The method according to any one of items 58 to 80, wherein the anti-Trop-2 ADC is selected from the group consisting of sacituzumab govitecan and DS-1062. (Item 82) The method according to any one of items 58 to 81, wherein the presence or absence of one or more cancer biomarkers is used to determine the stage of the cancer. (Item 83) The method according to any one of items 58 to 82, wherein the presence or absence of one or more cancer biomarkers is used to quantify the risk of cancer recurrence after anti-cancer treatment. (Item 84) The method according to any one of items 58 to 83, wherein the cancer is selected from the group consisting of breast cancer, triple-negative breast cancer (TNBC), HR+ / HER2- metastatic breast cancer, urothelial carcinoma, small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), colorectal cancer, gastric cancer, bladder cancer, kidney cancer, ovarian cancer, uterine cancer, endometrial cancer, cervical cancer, prostate cancer, esophageal cancer, pancreatic cancer, brain cancer, liver cancer, and head and neck cancer. (Item 85) The method according to any one of items 58 to 84, wherein the cancer is urothelial carcinoma. (Item 86) The method according to any one of items 58 to 85, wherein the cancer is metastatic urothelial carcinoma. (Item 87) The method according to any one of items 58 to 86, wherein the cancer is treatment-resistant urothelial carcinoma. (Item 88) The method according to any one of items 58 to 87, wherein the cancer is resistant to treatment with platinum-based and / or checkpoint inhibitor (CPI) (e.g., anti-PD1 antibody or anti-PD-L1 antibody) therapies. (Item 89) The method according to any one of items 58 to 88, wherein the cancer is metastatic TNBC. (Item 90) The method according to any one of items 58 to 89, further comprising predicting relapse-free survival, overall survival, disease-free survival, or distant relapse-free survival after treatment with an anti-Trop-2 ADC. [Brief explanation of the drawing]

[0022] [Figure 1A] Treatment response in patients with metastatic urothelial carcinoma treated with sacituzumab govitecan. Waterfall plot showing the best percentage change from baseline in the total diameter of target lesions* in 40 patients (excluding 5 patients with no post-baseline evaluation). Abbreviations: CR, complete response; PR, partial response; SD, stable; PD, progressive disease. *Total diameter of target lesions (longest for non-narrow lesions, short axis for nodular lesions), †0% change, which is the best overall response for PD, ‡Classified as SD because target lesions have contracted by more than 30% but this is unconfirmed, §CR due to target lesions in lymph nodes shrinking to less than 10 mm, **Classified as PR because target lesions have decreased by 100%, but non-target lesions remain stably persistent. [Figure 1B] Treatment response in patients with metastatic urothelial carcinoma treated with sacituzumab govitecan. Swimmer plots of patients (n=14) who achieved an objective response from the start of treatment to disease progression. Black squares indicate the start of the response, and arrows indicate the continued response at the data cutoff point. Black circles indicate patients whose response duration was censored due to two missed or discontinued tumor assessments. At the time of analysis, three patients were continuing treatment with a sustained response (>17 months, >19 months, and >29 months). [Figure 2A] Median progression-free survival (PFS) for patients with metastatic urothelial carcinoma treated with sacituzumab govitecan. [Figure 2B] Median overall survival (OS) in patients with metastatic urothelial carcinoma (mUC) treated with sacituzumab govitecan. [Figure 3A]Molecular characteristics associated with the response to sacituzumab govitecan. Oncoprint showing the frequency of mutations in DNA damage repair (DDR) and apoptosis genes in the GO:0097193 signaling pathway in 14 mUC patients treated with sacituzumab govitecan (responders n=6, non-responders n=8). [Figure 3B] Molecular characteristics associated with the response to sacituzumab govitecan in mUC patients. RNA-seq heatmap showing differentially expressed genes between responders and non-responders (false detection rate [FDR] < 0.001; upregulatory genes: logarithmic change [LFC] > 2, n=374; downregulatory genes: LFC < -2, n=380). [Figure 3C] Molecular characteristics associated with the response to sacituzumab govitecan in mUC patients. Differences in single-sample GSEA (ssGSEA) enrichment scores indicating apoptosis and P53 pathway enrichment between responders and non-responders. Mann-Whitney U test p-values ​​are reported. [Figure 4A] Response and treatment analysis in TNBC. Waterfall plot showing the best percentage change from baseline in the sum of target lesion diameters (longest diameter for non-narrow lesions, short axis for nodular lesions). Asterisks indicate three patients with a best percentage change of zero percent (2 SD, 1 PD). Dashed lines at 20% and -30% indicate progressive disease and partial response, respectively, according to RECIST. [Figure 4B] Swimmer plot of objective response (RECIST, version 1.1) in TNBC patients from treatment initiation to disease progression, as determined by site evaluation. At the time of analysis, six patients had a sustained response. The dashed vertical lines show the response at 6 and 12 months. [Figure 5A]Graphs of antitumor response and duration in mSCLC patients with evaluable response. Description of best percentage change in the sum of diameters of selected target lesions and best overall response according to RECIST 1.1 criteria. Patients are identified by the starting dose of sacituzumab govitecan and whether they are sensitive to or resistant to previous first-line therapy. Patients with unconfirmed partial response were unable to maintain at least 30% tumor reduction at the next CT assessment 4–6 weeks after the first observed objective response. The best overall response for these patients according to RECIST 1.0 is stable. [Figure 5B] Graphs showing antitumor response and duration in mSCLC patients with evaluable response. Duration of response from the start of treatment for patients achieving partial or complete response. The timing of tumor shrinkage of 30% or more is shown, along with the starting dose of sacituzumab govitecan and sensitivity to first-line therapy. [Figure 5C] Graphs showing antitumor response and duration in mSCLC patients with evaluable response rates. The graphs show the response trends for patients who achieved stable or better condition. Two patients with confirmed partial responses and continued treatment are shown with dashed lines. [Figure 6A] Kaplan-Meier progression-free survival curves for all 53 mSCLC patients enrolled in the sustuzumab govibibican trial. [Figure 6B] Kaplan-Meier overall survival curves for all 53 mSCLC patients enrolled in the sustuzumab govibibican trial. [Modes for carrying out the invention]

[0023] definition In the following description, several terms are used to facilitate understanding of the claimed subject matter, and their definitions are provided below. Terms not expressly defined herein are used according to their simple, ordinary meanings.

[0024] Unless otherwise specified, "a" or "an" means "one or more."

[0025] In this specification, the term “approximately” is used to mean ±10 percent (10%) of a value. For example, “approximately 100” refers to any number between 90 and 110.

[0026] As used herein, “antibody” refers to a full-length (i.e., naturally occurring or formed by a normal immunoglobulin gene fragment recombination process) immunoglobulin molecule (e.g., an IgG antibody). Antibodies may be conjugated or otherwise derivatized within the scope of the claimed subject matter. Such antibodies include, but are not limited to, IgG1, IgG2, IgG3, IgG4 (and IgG4 subforms), and IgA isotypes. As used herein, the abbreviation “MAb” may be used interchangeably to refer to an antibody, antibody fragment, monoclonal antibody, or multispecific antibody.

[0027] Antibody fragments are parts of antibodies, such as F(ab')2, F(ab)2, Fab', Fab, Fv, scFv (single-chain Fv), and single-domain antibodies (DAB or VHH), and contain half of IgG4 (van der Neut Kolfschoten et al. (Science, 2007;317:1554-1557)). Regardless of structure, the antibody fragment used binds to the same antigen recognized by the complete antibody. The term “antibody fragment” also includes synthetic or genetically engineered proteins that act like antibodies by binding to a specific antigen and forming a complex. For example, antibody fragments include isolated fragments consisting of variable regions, such as “Fv” fragments consisting of heavy and light chain variable regions, and recombinant single-chain polypeptide molecules ("scFv proteins") in which the light and heavy chain variable regions are linked by a peptide linker. Fragments can be constructed in different ways to result in multivalent and / or multispecific binding forms.

[0028] A therapeutic agent is an atom, molecule, or compound useful for treating a disease. Examples of therapeutic agents include, but are not limited to, antibodies, antibody fragments, immune complexes, checkpoint inhibitors, drugs, cytotoxic agents, apoptosis promoters, toxins, nucleases (including DNAse and RNAse), hormones, immunomodulators, chelating agents, photoactivators or dyes, radionuclides, oligonucleotides, interfering RNA, siRNA, RNAi, anti-angiogenic agents, chemotherapeutic agents, cytokines, chemokines, prodrugs, enzymes, binding proteins or peptides, or combinations thereof.

[0029] As used herein, when referring to an increase or decrease in the expression of a particular gene, this term refers to an increase or decrease in cancer cells compared to normal, benign, and / or wild-type cells. Antibodies and antibody-drug conjugates (ADCs)

[0030] Specific embodiments relate to the use of anti-cancer antibodies in a non-conjugated form or as an immune complex (e.g., ADC) conjugated to one or more therapeutic agents. Preferably, the conjugated agents induce DNA strand breaks, more preferably by inhibiting topoisomerase I. Exemplary topoisomerase I inhibitors include SN-38 and DxD. However, other topoisomerase I inhibitors are known in the art, and any such known topoisomerase I inhibitor can be used in anti-Trop-2 ADCs. Examples of topoisomerase I inhibitors include camptothecins such as irinotecan, topotecan, SN-38, diflomotecan, S39625, siratecan, berotecan, namithecan, jaimatecan, berotecan, or camptothecin, as well as noncamptothecins such as indolocarbazole, phenanthidine, indenoisoquinoline, and their derivatives, e.g., NSC314622, NSC725776, NSC724998, ARC-111, isoindro[2,1-a]quinoxaline, indothecan, indimitecan, CRLX101, rebeccamycin, edotecarin, or becatecarin. [See, for example, Hevener et al., 2018, Acta Pharm Sin B 8:844-61]

[0031] In alternative embodiments, topoisomerase II inhibitors, such as anthracyclines, doxorubicin, epirubicin, barurubicin, daunorubicin, idarubicin, aldoxorubicin, anthracendione, mitoxantrone, pixantrone, amsacrin, dexrazoxane, epipodophyllotoxin, ciprofloxacin, vosaroxin, teniposide, or etoposide may be used. [See, for example, Hevener et al., 2018, Acta Pharm Sin B 8:844-61]

[0032] While topoisomerase inhibitors are preferred for antibody conjugation, other agents that induce DNA damage and / or strand breaks are known and may be used in alternative embodiments. Such known anticancer agents include, but are not limited to, nitrogen mustard, folate analogs such as aminopterin or methotrexate, alkylating agents such as cyclophosphamide, chlorambucil, mitomycin C, streptozotocin, or melphalan, nitrosourea such as carmustine, lomustine, or semustine, triazenes such as dacarbazine or temozolomide, or platinum-based inhibitors such as cisplatin, carboplatin, picoplatin, or oxaliplatin. [See, for example, Ong et al., 2013, Chem Biol 20:648-59]

[0033] In preferred embodiments, an immune complex comprising an antibody or an anti-Trop-2 antibody such as an hRS7 antibody may be used to treat cancers of the esophagus, pancreas, lung, stomach, colon, rectum, bladder, urothelium, breast, ovary, cervix, endometrium, uterus, kidney, head and neck, brain, and prostate, as disclosed in U.S. Patents 7,238,785, 7,999,083, 8,758,752, 9,028,833, 9,745,380, and 9,770,517, the respective examples of which are incorporated herein by reference. The hRS7 antibody is a humanized antibody comprising the light chain complementarity-determining region (CDR) sequences CDR1 (KASQDVSIAVA, SEQ ID NO: 1), CDR2 (SASYRYT, SEQ ID NO: 2), and CDR3 (QQHYITPLT, SEQ ID NO: 3), as well as the heavy chain CDR sequences CDR1 (NYGMN, SEQ ID NO: 4), CDR2 (WINTYTGEPTYTDDFKG, SEQ ID NO: 5), and CDR3 (GGFGSSYWYFDV, SEQ ID NO: 6). However, in alternative embodiments, other anti-Trop-2 antibodies are known and may be used in anti-Trop-2 ADCs. Exemplary anti-Trop-2 antibodies include, but are not limited to, catumakisomab, VB4-845, IGN-101, adecatumumab, ING-1, EMD273066, or hTINA1 (see U.S. Patent No. 9,850,312). Anti-Trop-2 antibodies are commercially available from several suppliers, including LS-C126418, LS-C178765, LS-C126416, LS-C126417 (LifeSpan BioSciences, Inc., Seattle, Wash.), 10428-MM01, 10428-MM02, 10428-R001, 10428-R030 (Sino Biological Inc., Beijing, China), MR54 (eBioscience, San Diego, Calif.), sc-376181, sc-376746, Santa Cruz Biotechnology (Santa Cruz, Calif.), and MM0588-49D6 (Novus). Examples include Biologicals (Littleton, Colo.), ab79976, and ab89928 (ABCAM.RTM., Cambridge, Mass.).

[0034] Other anti-Trop-2 antibodies are disclosed in the patent literature. For example, U.S. Patent Application Publication No. 2013 / 0089872 discloses anti-Trop-2 antibodies K5-70 (accession number FERM BP-11251), K5-107 (accession number FERM BP-11252), K5-116-2-1 (accession number FERM BP-11253), T6-16 (accession number FERM BP-11346), and T5-86 (accession number FERM BP-11254), which are deposited with the International Patent Organism Depositary (Tsukuba, Japan). U.S. Patent No. 5,840,854 discloses the anti-Trop-2 monoclonal antibody BR110 (ATCC number HB11698). U.S. Patent No. 7,420,040 discloses an anti-Trop-2 antibody produced by the hybridoma cell line AR47A6.4.2, deposited with IDAC (International Depository Authority of Canada, Winnipeg, Canada) under receipt number 141205-05. U.S. Patent No. 7,420,041 discloses an anti-Trop-2 antibody produced by the hybridoma cell line AR52A301.5, deposited with IDAC under receipt number 141205-03. U.S. Patent Publication No. 2013 / 0122020 discloses anti-Trop-2 antibodies 3E9, 6G11, 7E6, 15E2, and 18B1. The hybridoma encoding the representative antibodies is American Type Culture. The antibodies are deposited with Collection (ATCC) under receipt numbers PTA-12871 and PTA-12872. U.S. Patent No. 8,715,662 discloses hybridoma-produced anti-Trop-2 antibodies deposited with AID-ICLC (Genoa, Italy) under receipt numbers PD08019, PD08020, and PD08021. U.S. Patent Publication No. 20120237518 discloses anti-Trop-2 antibodies 77220, KM4097, and KM4590. U.S. Patent No. 8,309,094 (Wyeth) discloses antibodies A1 and A3, which are identified by sequence listing. U.S. Patent No. 9,850,312 discloses anti-Trop-2 antibodies TINA1, cTINA1, and hTINA1. In this paragraph, the examples of each patent or patent application cited above are incorporated herein by reference. Lipinski et al. (1981, Proc Natl. Acad Sci USA, 78:5147-50), a non-patent document, discloses anti-Trop-2 antibodies 162-25.3 and 162-46.2.

[0035] In preferred embodiments, the antibodies used to treat human diseases are human or humanized (CDR-grafted) antibodies, but mouse and chimeric antibodies can also be used. IgG molecules of the same species as the delivery agent are preferred in most cases to minimize the immune response. This is particularly important when considering repeated treatment. In humans, human or humanized IgG antibodies are less likely to elicit an anti-IgG immune response from the patient. ADC formulation and administration

[0036] Antibodies or immune complexes (e.g., ADCs) can be formulated according to known methods for preparing pharmaceutically useful compositions, thereby combining the antibody or immune complex with a pharmaceutically suitable excipient in a mixture. Sterile phosphate-buffered saline is an example of a pharmaceutically suitable excipient. Other suitable excipients are well known to those skilled in the art. For example, Ansel et al. See also al., PHARMACEUTICAL DOSAGE FORMS AND DRUG DELIVERY SYSTEMS, 5th Edition (Lea & Febiger 1990), and Gennaro (ed.), REMINGTON'S PHARMACEUTICAL SCIENCES, 18th Edition (Mack Publishing Company 1990), and their revised editions.

[0037] In preferred embodiments, the antibody or immune complex is formulated in Good's biological buffer (pH 6-7) using a buffer selected from the group consisting of N-(2-acetamide)-2-aminoethanesulfonic acid (ACES), N-(2-acetamide)iminodiacetic acid (ADA), N,N-bis(2-hydroxyethyl)-2-aminoethanesulfonic acid (BES), 4-(2-hydroxyethyl)piperazine-1-ethanesulfonic acid (HEPES), 2-(N-morpholino)ethanesulfonic acid (MES), 3-(N-morpholino)propanesulfonic acid (MOPS), 3-(N-morpholinyl)-2-hydroxypropanesulfonic acid (MOPSO), and piperazine-N,N'-bis(2-ethanesulfonic acid) [Pipes]. A more preferred buffer is preferably in the concentration range of 20-100 mM, more preferably about 25 mM of MES or MOPS. The most preferred solution is 25 mM MES, pH 6.5. The formulation may further contain 25 mM trehalose and 0.01% v / v polysorbate 80 as excipients, and as a result of the added excipients, the final buffer concentration is changed to 22.25 mM. The preferred storage method is a temperature range of -20°C to 2°C, most preferably 2°C to 8°C, for the lyophilized formulation of the complex.

[0038] Antibodies or immune complexes can be formulated for intravenous administration, for example, by bolus injection, slow infusion, or continuous infusion. Preferably, the antibodies of the present invention are infused over a period of less than about 4 hours, more preferably less than about 3 hours. For example, the first 25-50 mg may be infused within 30 minutes, preferably within 15 minutes, and the remainder infused over the next 2-3 hours. The injectable formulations, along with added preservatives, may be present in unit dosage forms, such as ampoules, or multi-dose containers. The compositions may take the form of suspensions, solutions, or emulsions in oily or aqueous media and may contain formulations such as suspending agents, stabilizers, and / or dispersants. Alternatively, the active ingredient may be in powder form for use with a suitable vehicle, such as pyrogenically decontaminated distilled water.

[0039] Generally, the dosage of antibodies or immune complexes administered to humans will vary depending on factors such as the patient's age, weight, height, sex, overall medical condition, and medical history. While it may be desirable to provide recipients with a single intravenous infusion of immune complexes ranging from approximately 1 mg / kg to 24 mg / kg, lower or higher doses may be administered depending on the situation. The dosage can be repeated as needed, for example, once a week for 4 to 10 weeks, once a week for 8 weeks, or once a week for 4 weeks. In maintenance therapy, the frequency may be reduced as needed, for example, every few months, or monthly or quarterly for several months. Preferred dosages may include, but are not limited to, 1 mg / kg, 2 mg / kg, 3 mg / kg, 4 mg / kg, 5 mg / kg, 6 mg / kg, 7 mg / kg, 8 mg / kg, 9 mg / kg, 10 mg / kg, 11 mg / kg, 12 mg / kg, 13 mg / kg, 14 mg / kg, 15 mg / kg, 16 mg / kg, 17 mg / kg, and 18 mg / kg. The dosage is preferably administered multiple times, once or twice a week, or once every three or four weeks. A minimum administration schedule of four weeks, more preferably eight weeks, and more preferably sixteen weeks or more can be used. The administration schedule may include once or twice weekly doses in cycles selected from the group consisting of (i) weekly, (ii) every other week, (iii) 1 week of treatment followed by 2, 3, or 4 weeks of rest, (iv) 2 weeks of treatment followed by 1, 2, 3, or 4 weeks of rest, (v) 3 weeks of treatment followed by 1, 2, 3, 4, or 5 weeks of rest, (vi) 4 weeks of treatment followed by 1, 2, 3, 4, or 5 weeks of rest, (vii) 5 weeks of treatment followed by 1, 2, 3, 4, or 5 weeks of rest, (viii) monthly, and (ix) every 3 weeks. The cycle may be repeated 2, 4, 6, 8, 10, 12, 16, or 20 or more times.

[0040] Alternatively, the antibody or immune complex may be administered once every two or three weeks, repeated at least three times in total. Or, twice a week for four to six weeks, with a dose of approximately 200-300 mg / m². 2If the dose can be reduced to (340 mg for a patient weighing 1.7 m, or 4.9 mg / kg for a patient weighing 70 kg), it may be administered once or even twice a week for 4 to 10 weeks. Alternatively, the dosage schedule may be shortened, i.e., every 2 or 3 weeks for 2 to 3 months. However, it has been determined that higher doses, such as 12 mg / kg once a week or once every 2 to 3 weeks, may be administered by slow intravenous infusion in repeated dosing cycles. The dosing schedule may be repeated at other intervals at the discretion of the administration, and the dose may be administered by various parenteral routes, with appropriate adjustments to the dose and schedule. DNA damage and repair pathways

[0041] The use of anti-cancer ADCs containing drug moieties that target topoisomerase can lead to the accumulation of single-strand or double-strand breaks in cancer cell DNA. Resistance to the anticancer effects of topoisomerase I inhibitors or other anticancer agents that damage DNA, or recurrence, may result from the presence of DNA repair mechanisms such as the DNA damage response (DDR). DDR is a complex combination of pathways involved in repairing DNA damage in normal and tumor cells. Inhibitors targeting the DDR pathway can be used in combination with anti-Trop-2 ADCs to provide an increased anticancer effect in tumors that have relapsed from or are resistant to anti-Trop-2 ADC monotherapy. Alternatively, combination therapy can be used as first-line therapy if the combination is substantially superior to monotherapy with the ADC or other therapeutic agent alone. In addition, the presence of mutations in the genes encoding the DDR component, other genetic defects or changes in gene expression levels, can predict the effectiveness of anti-Trop-2 ADCs and / or combination therapy with anti-Trop-2 ADCs and one or more other anticancer agents.

[0042] In a preferred embodiment, the target ADC may be used in combination with one or more known anticancer agents that inhibit various steps in the DDR pathway. There are many pathways involved in cellular DNA repair that have partial overlap in the protein effectors of different pathways. The use of topoisomerase inhibitory ADCs in combination with other inhibitors of different steps in the DNA damage repair pathway may exhibit synthetic lethality, leading to cell death when function is lost simultaneously in two different genes, but not when function is lost in only one gene (e.g., Cardillo et al., 2017, Clin Cancer Res 23:3405-15). This concept can also be applied to cancer therapy, where cancer cells with a mutation in one gene can be targeted by chemotherapeutic agents that inhibit the function of a second gene used by the cell to overcome the initial mutation (Cardillo et al., 2017, Clin Cancer Res 23:3405-15). This concept has been applied, for example, to the use of PARP inhibitors in cells with BRCA gene mutations (Benafif & Hall, 2015, Onco Targets Ther 8:519-28). In principle, synthetic lethality can be applied, in or out of the presence of latent cancer cell mutations, by using, for example, combination therapy with two or more inhibitors targeting different aspects of the DDR pathway, or in combination with DNA damage inducers.

[0043] Double-stranded DNA breaks (DSBs) are repaired by two main pathways: homologous recombination (HR) and non-homologous end joining (NHEJ). [See, for example, Srivastava & Raghavan, 2015, Chem Biol 22:17-29]. These each include subpathways (classical or alternative subpathways of NHEJ (cNHEJ and aNHEJ, respectively) and single-strand annealing (SSA) of the HR pathway). HR requires broad homology for DSB repair and is most active in the S and G2 phases of the cell cycle, while NHEJ can utilize limited homology for end joining, or not utilize homology at all, and can act throughout the cell cycle (Srivastava & Raghavan, 2015, Chem Biol 22:17-29).

[0044] Activation of the DDR pathway by DSBs includes checkpoint arrests mediated by ATM, ATR, and DNA-PKcs (Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059). ATM is required for DSB repair by HR and induces DSB end excision by stimulating the lysis activity of CtIP and MREll, resulting in 3'-ssDNA overhang and subsequent RPA loading and RAD51 nucleofilament formation (Bakr et al., 2015, Nucleic Acids Res 43:3154). ATR responds to broader DNA damage, including DSBs and ssDNA (Marechal et al., 2013, Cold Spring Harb Perspect Biol 5:a012716). However, the functions of ATR and ATM are not mutually exclusive, and both are required for DSB-induced checkpoint response and DSB repair (Marechal et al., 2013, Cold Spring Harb Perspect Biol 5:a012716). The localization of the ATR-ATRIP complex to the DNA damage site depends on the presence of long-stretch RPA-coated ssDNA, which can be generated by excision as discussed below (Marechal et al., 2013, Cold Spring Harb Perspect Biol 5:a012716). DNA-PKcs are catalytic subunits of DNA-PK and are mainly involved in the NHEJ pathway (Marechal et al., 2013, Cold Spring Harb Perspect Biol 5:a012716).

[0045] The determination of which DSB repair pathway is utilized is partially mediated by the amount of 5' end resection at the DSB, which is inhibited by 53BP1 / RIF1 and promoted by BRCA1 / CtIP. Increased resection favors the HR repair pathway, while decreased resection promotes the NHEJ pathway (Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059). At the initiation of the HR pathway, MRE11 (part of the MRN complex together with RAD50 and NBS1) initiates limited end resection, followed by Exo1 / EEPD1 and Dna2 for extensive resection (Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059). In the NHEJ pathway, 53BP1 / RIF1 and KU70 / 80 inhibit resection and promote classical NHEJ, while PARP1 competes with KU protein and promotes limited terminal resection of alternative NHEJ (Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059). Polθ is also involved in aNHEJ.

[0046] Further steps in the HR pathway are facilitated by RPA, BRCA2, RAD51, RAD52, RAD54, and Polδ (Nickoloff et al., 2017, J RAD52 is also involved in SSA along with ERCC1, ERCC2, ERCC3, and ERCC4 (Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059). Other proteins involved in HR include RAD50, NBS1, BLM, XPF, FANCM, FAAP24, FANC1, FAND2, MSH3, SLX4, MUS81, EME1, SLX1, PALB2, BRIP1, BARD1, BAP1, PTEN, RAD51C, USP11, WRN, and NER. [Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059, Srivastava & Raghavan, 2015, Chem [Biol 22:17-29]Other proteins involved in NHEJ include Artemis, Polμ, Polλ, ligase IV, XRCC4, and XLF. [Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059, Srivastava & Raghavan, 2015, Chem Biol 22:17-29] Further details on the roles of these various DDR proteins and their respective inhibitors are provided below.

[0047] Repair of single-stranded DNA lesions can also occur via multiple pathways (base excision repair (BER), nucleotide excision repair (NER), and mismatch repair (MMR)). The BER pathway is facilitated by APE1, PARP1, Polβ, Lig III, and XRCC1. NER is facilitated by XPC, RAD23B, HR23B, XPF, ERCC1, XPG, XPA, RPA, XPD, CSA, CSB, XAB2, and Polδ / κ / ε. MMR is facilitated by MutSα / β, MLH1, PMS2, Exo1, PARP1, MSH2, MSH6, and Polδ / κ / ε (Nickoloff et al.). (Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059). Mutations in MSH2 make cancer more responsive to methotrexate and psoralen (Nickoloff et al., 2017, J Natl Cancer (Inst 109:djx059). NER deficiency, such as decreased ERCC1 expression, makes the cells more responsive to cisplatin and crosslinking agents such as PARP1 or ATR inhibitors (Nickoloff et al., 2017, J Natl Cancer Inst 109:djx059).

[0048] As will be discussed below, various inhibitors of these DDR proteins are known, and such known inhibitors can be used in combination with the target ADC. In a more preferred embodiment, the presence of mutations in BRCA1 and / or BRCA2 can predict the effectiveness of either ADC monotherapy or combination therapy with ADC and a DSB repair inhibitor. Combination therapy with ADCs and DNA damage repair inhibitors

[0049] As described above, a key objective of combination therapy with anti-Trop-2 ADCs and one or more inhibitors of the DDR pathway is to induce synthetic lethality (as opposed to genetic lethality), and the combination of a drug that causes DNA damage (e.g., a topoisomerase I inhibitor) and a drug that inhibits a step in the DDR damage repair pathway is effective in killing cancer cells that are resistant to either type of drug alone. DDR inhibitors of particular interest in combination therapy are those against PARP, ATR, ATM, CHK1, CHK2, CDK12, RAD51, RAD52, and WEE1. In alternative embodiments, the DDR inhibitor of interest may be a DDR inhibitor other than a PARP inhibitor or a RAD51 inhibitor. PARP inhibitors

[0050] Poly(ADP-ribose) polymerase (PARP) plays a crucial role in the DNA damage response, directly or indirectly influencing numerous DDR pathways, including BER, HR, NER, NHEJ, and MMR (Gavande et al., 2016, Pharmacol Ther 160:65-83). Several PARP inhibitors, such as olaparib, talazoparib (BMN-673), lucaparib, veliparib, niraparib, CEP9722, MK4827, BGB-290 (pamiparib), ABT-888, AG014699, BSI-201, CEP-8983, E7016, and 3-aminobenzamide, are known in the art (see, for example, Rouleau et al., 2010, Nat Rev Cancer 10:293-301, and Bao et al., 2015, Oncotarget [Epub ahead of print, September 22, 2015]). PARP inhibitors are known to exhibit synthetic lethality, for example, in tumors with BRCA1 / 2 mutations. Olaparib is FDA approved for the treatment of ovarian cancer patients with BRCA1 or BRCA2 mutations. In addition to olaparib, other FDA-approved PARP inhibitors for ovarian cancer include niraparib and lucaparib. Rib was recently approved for the treatment of breast cancer with germline BRCA mutations and is in Phase III trials for hematological malignancies and solid tumors, with efficacy reported in SCLC, ovarian cancer, breast cancer, and prostate cancer (Bitler et al., 2017, Gynecol Oncol 147:695-704). Veliparib is in Phase III trials for advanced ovarian cancer, TNBC, and NSCLC (see Wikipedia's "PARP_inhibitor" entry). All PARP inhibitors are BRCA mutation-independent, and niraparib is approved for maintenance therapy of recurrent platinum-sensitive ovarian, fallopian tube, or primary peritoneal cancer, regardless of BRCA status (Bitler et al., 2017, Gynecol Oncol 147:695-704).

[0051] Any known PARP inhibitor can be used in combination with anti-Trop-2 ADCs such as sacituzumab govitecan or DS-1062. Synthetic lethality and synergistic inhibition of tumor growth have been demonstrated with sacituzumab govitecan in combination with olaparib, rucaparib, and talazoparib in nude mice with TNBC xenografts (Cardillo et al., 2017, Clin Cancer Res 23:3405-15). The beneficial effects of combination therapy were observed independently of BRCA1 / 2 mutation status (Cardillo et al., 2017, Clin Cancer Res 23:3405-15). CDK12 inhibitors

[0052] Cyclin-dependent kinase 12 (CDK12) is a cell cycle regulator that has been reported to act in coordination with PARP inhibitors, and knockdown of CDK12 activity has been observed to enhance sensitivity to olaparib (Bitler et al., 2017, Gynecol Oncol 147:695-704). CDK12 appears to act at least partially by regulating the expression of the DDR gene (Krajewska et al., 2019, Nature Commun 10:1757). Various CDK12 inhibitors are known, including dinacyclib, flavopridol, roscovitine, THZ1, or THZ531 (Bitler et al., 2017, Gynecol Oncol 147:695-704, Krajewska et al., 2019, Nature Commun 10:1757, Paculova & Kohoutek, 2017, Cell Div 12:7). Combination therapy with a PARP inhibitor and dinaciclib reverses resistance to the PARP inhibitor (Bitler et al., 2017, Gynecol Oncol 147:695-704). In the target area, combination therapy with an anti-Trop-2 ADC and a combination of a PARP inhibitor and a CDK12 inhibitor may be useful. RAD51 inhibitors

[0053] BRCA1 and BRCA2 encode proteins essential for the HR DNA repair pathway, and mutations in these genes require increased reliance on the NHEJ pathway for tumor survival. PARP is a key protein for NHEJ-mediated DNA repair, and the use of PARP inhibitors (PARPi) in BRCA-mutated tumors (e.g., ovarian cancer, TNBC) results in synthetic lethality. However, not all BRCA-mutated tumors are sensitive to PARPi, and many that initially respond will develop resistance.

[0054] RAD51 is another central protein in the HR pathway and is often overexpressed in cancer cells (see Wikipedia's "RAD51" entry). Increased RAD51 expression can partially counteract BRCA mutations and reduce sensitivity to PARP inhibitors. Sacituzumab govitecan, an anti-Trop-2 ADC containing a topoisomerase I inhibitor, has been shown to at least partially counteract RAD51 overexpression (see U.S. Patent Application No. 15 / 926,537). Therefore, there is a rationale for combination therapy using an ADC that inhibits topoisomerase I and a RAD51 inhibitor, with or without a PARP inhibitor.

[0055] Combination therapy with ADCs includes B02((E)-3-benzyl-2(2-(pyridine-3-yl)vinyl)quinazoline-4(3H)-one) (Huang & Mazin, 2014, PLoS ONE 9(6):e100993), RI-1(3-chloro-1-(3,4-dichlorophenyl)-4-(4-morpholinyl)-1H-pyrrole-2,5-dione) (Budke et al., 2012, Nucl Acids Res 40:7347-57), DIDS(4,4'-diisothiocyanostilbene-2,2'-disulfonic acid) (Ishida et al., 2009, Nucl Acids Res 37:3367-76), and halenaquinone (Takaku et al., 2011, Genes Cells). Examples include, but are not limited to, any Rad51 inhibitor known in the art, such as 16:427-36), CYT-0851 (Cyteir Therapeutics, Inc.), IBR2 (Ferguson et al., 2018, J Pharm Exp Ther 364:46-54), or imatinib (Choudhury et al., 2009, Mol Cancer Ther 8:203-13). Many of these are available from commercial sources (e.g., B02, Calbiomech; RI-1, Calbiomech; DIDS, Tocris Bioscience, Halenaquinone, Angene International Ltd., Hong Kong; Imatinib (GLEEVAC®), Novartis).

[0056] As discussed above, combination therapy with ADCs and both RAD51 inhibitors and PARP inhibitors can be used to treat cancer. ATM inhibitor

[0057] ATM and ATR are important mediators of DDR, inducing cell cycle arrest and promoting DNA repair through their downstream targets (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Many malignancies show functional loss or de-regulation of key proteins involved in DDR and cell cycle regulation, such as p53, ATM, MRE11, BRCA1 / 2, or SMC1 (Weber). (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). As mentioned above, deficiencies in specific DDR pathways such as HRD may increase cancer cells' dependence on alternative DDR pathways, thus providing targets for selective inhibition of cancer cells with such DDR mutations (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). In addition to the effect of BRCA1 / 2 mutations on sensitivity to PARP inhibitors, other functional changes in DDR proteins that may enhance sensitivity to DNA-damaging anticancer drug therapies include DNA-PKcs (Zhao et al., 2006, Cancer Res 66:5354-62) and ATM (Golding et al., 2012, Cell Cycle 11:1167-73), ATR (Fokas et al., 2012, Cell Death Dis 3:e441), CHK1 and CHK2 (Mathews et al., 2007, Cell Cycle 6:104-10, Riesterer et al., 2011, Invest Changes can be cited as described in New Drugs 29:514-22). In principle, the effects of such susceptibility mutations can be reproduced by combination therapy using inhibitors of the relevant DDR protein.

[0058] ATM and ATR are members of the phosphatidylinositol 2-kinase-related kinase (PIKK) family, which also includes DNA-PKcs / PRKDC, MTOR / FRAP, and SMG1 (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Due to the high degree of sequence homology among various PIKK proteins, cross-reactivity can be observed between inhibitors of different PIKK proteins, potentially leading to undesirable toxicity. It is preferable to use inhibitors that have a higher affinity for ATM or ATR compared to other PIKK proteins.

[0059] ATM attaches to the DSB site by binding to the MRN complex (MRE11-RAD50-NBS1) (Weber & Ryan, 2015, Pharmacol). (Ther 149:124-38). Binding to MRNs activates ATM kinase, promoting phosphorylation of its downstream targets (p53, CHK2, and Mdm2), which in turn activates cell cycle checkpoint activity (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Other downstream effectors of ATM include BRCA1, H2AX, and p21 (Ronco et al., 2017, Med Chem Commun 8:295-319). Both the ATM and ATR pathways inhibit the activity of CDC25C and CDK1 (Ronco et al., 2017, Med Chem Commun 8:295-319).

[0060] Various inhibitors of ATM are known in the art. Caffeine inhibits both ATM and ATR, making cells more susceptible to ionizing radiation (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Waltmannin is a relatively nonspecific inhibitor of PIKK and has activity against ATM, PI3K, and DNA-PKcs (Weber & Ryan, 2015, Pharmacol (Ther 149:124-38). CP-466722, KU-55933, KU-60019, and KU-59403 are all relatively selective for ATM, and it has been reported that cells become more susceptible to ionizing radiation (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). KU-59403 also increased the antitumor effects of etoposide and irinotecan, while KU-55933 increased cancer sensitivity to doxorubicin and etoposide (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). The effect of KU-60019 was substantially enhanced in p53-mutated cancer cells, suggesting that p53 mutations may be a biomarker for ATM inhibitor use. The ATM inhibitor AZD1056 is used in combination with the PARP inhibitor olaparib (Cruz et al., 2018, Ann Oncol 29:1203-10). AZD0156, used in combination with the WEE1 inhibitor AZD1775, showed a synergistic antitumor effect in prostate cancer xenografts (Jin et al., Cancer Res Treat [Epub ahead of print June 25, 2019]). Other reported ATM inhibitors include CGK733, NVP-BEZ235, Torin-2, fluoroquinoline 2, and SJ573017 (Ronco et al., 2017, Med Chem Commun 8:295-319). Significant antitumor effects have been reported with combination therapy with fluoroquinoline 2 and irinotecan (Ronco et al., 2017, Med Chem Commun 8:295-319).

[0061] While none of these have yet received FDA approval, AZD1390 (AstraZeneca), Ku-60019 (AstraZeneca), and AZD0156 (AstraZeneca) are among the ATM inhibitors currently undergoing clinical trials. ATR inhibitors

[0062] ATR is another major kinase involved in regulating DDR. In contrast to ATM, ATR is activated by single-stranded DNA structures (ssDNA), which can occur in excised DSBs or stuck replication forks (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). ATR binds to ATRIP (ATR-interacting protein) and controls the localization of ATR to DNA damage sites (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). ssDNA binds to RPA, which can then bind to ATR / ATRIP and even RAD17 / RFC2-5, and subsequently promotes the binding of RAD9-HUS1-RAD1 (9-1-1 complex) to the DNA ends (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). The 9-1-1 complex recruits TopBP1 and activates ATR (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Subsequently, ATR activates CHK1, promoting DNA repair, stabilization, and transient cell cycle arrest (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Other downstream effectors of ATR function include Cdc25A, Cdc25C, WEE1, cyclin B, and cdc2 (Ronco et al., 2017, Med Chem Commun 8:295-319). The ATM and ATR pathways partially overlap, and inhibition of one pathway may be partially compensated for by activation of the other pathway. In certain embodiments, combination therapy with ATM and ATR inhibitors, or the use of inhibitors active against both ATM and ATR, may be preferred. In other embodiments, ATR inhibitors may be shown in relation to cancer therapies in which mutations or other inactivating changes inhibit ATM function in cancer cells.

[0063] Several ATR-selective inhibitors have been developed. Schisandrin B is said to be selective for ATR (Nischida et al., 2009, Nucleic Acids Res 73:5678-89), but has low toxicity. More potent inhibitors such as NU6027, BEZ235, ETP46464, and Torin 2 have shown cross-reactivity with other PIKK proteins (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). More potent selective ATR inhibitors such as VE-821 and VE-822 (also known as VX-970, M6620, belzocertib, Merck) are being developed by Vertex Pharmaceuticals. Other ATR inhibitors include AZ20 (AstraZeneca), AZD6738 (ceraraceltib), M4344 (Merck) (Weber & Ryan, 2015, Pharmacol Ther 149:124-38), and EPT-46464 (Brandsma et al., 2017, Expert Opin Investig Drugs 26:1341-55). BAY1895344 (Bayer), BAY-937 (Bayer), AZD6738 (AstraZeneca), BEZ235 (dactricib), CGK733, and VX-970 (M6620) are currently in clinical trials for cancer therapy. AZD6738 has been reported to be synthetically lethal due to p53 and ATM deficiencies (Ronco et al., 2017, Med Chem Commun 8:295-319).

[0064] Combination therapy with VE-821 has been shown to enhance sensitivity to cisplatin and gemcitabine in vivo, while AZD6738 significantly increased sensitivity to carboplatin (Weber & Ryan, 2015, Pharmacol Ther). VX970 (M6620) increased sensitivity to various DNA-damaging agents such as cisplatin, oxaliplatin, gemcitabine, etoposide, and SN-38 (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Chemosensitization was more pronounced in cancer cells with p53 deficiency (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). A phase I trial of M6620 in combination with topotecan showed improved efficacy in platinum-resistant SCLC that did not respond to topotecan alone (Thomas et al. 2018, J Clin Oncol 36:1594-1602). AZD6738 enhanced sensitivity to carboplatin (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Various cancer chemotherapy agents have been reported to have additive and / or synergistic effects with ATR inhibitors. These include, but are not limited to, gemcitabine, cytarabine, 5-fluorouracil, camptothecin, SN-38, cisplatin, carboplatin, and oxaliplatin. [See, for example, Wagner and Kaufmann, 2010, Pharmaceuticals 3:1311-34]. Such agents can be used to further enhance combination therapy with anti-Trop-2 ADCs and ATR inhibitors. CHK1 inhibitors

[0065] CHK1 is a phosphorylation target of ATR kinase and a downstream mediator of ATR activity. ATR-mediated phosphorylation of CHK1 activates CHK1 activity, which then phosphorylates Cdc25A and Cdc25C, thereby regulating the ATR-dependent DNA repair mechanism (Wagner and Kaufmann, 2010, Pharmaceuticals 3:1311-34).

[0066] Various CHK1 inhibitors are known in the art and include several that are currently undergoing clinical trials for cancer treatment. Any known CHK1 inhibitor can be used in combination with an anti-Trop-2 ADC, including XL9844 (Exelixis, Inc.), UCN-01, CHIR-124, AZD7762 (AstraZeneca), AZD1775 (Astrazeneca), XL844, LY2603618 (Eli Lilly), LY2606368 (Prexasertib, Eli Lilly), GDC-0425 (Genentech), PD-321852, PF-477736 (Pfizer), CBP501, CCT-244747 (Sareum), CEP-3891 (Cephalon), SAR-020106 (Sareum), Arry-575 (Array), SRA737 (Sareum), V158411, and SCH 900776 (also known as MK-8776, Merck) is an example, but is not limited to these. [Wagner and See Kaufmann, 2010, Pharmaceuticals 3:1311-34, Thompson and Eastman, 2013, Br J Clin Pharmacol 76:3, and Ronco et al., 2017, Med Chem Commun 8:295-319. CHIR-124 has been reported to enhance the activity of topoisomerase I inhibitors in mouse xenografts (Ronco et al., 2017, Med Chem Commun 8:295-319). CCT244747 showed antitumor activity when used in combination with gemcitabine and irinotecan (Ronco et al., 2017, Med Chem Commun 8:295-319). Clinical trials have been conducted using LY2603618 and SCH900776 (Ronco et al., 2017, Med Chem Commun 8:295-319). CHK2 inhibitors

[0067] Several CHK2 inhibitors are known and can be used in combination with ADCs and / or other DDR inhibitors or anticancer agents. Such known CHK2 inhibitors include, but are not limited to, NSC205171, PV1019, CI2, CI3 (Gokare et al., 2016, Oncotarget 7:29520-30), 2-arylbenzimidazole (ABI, Johnson & Johnson), NSC109555, VRX0466617, and CCT241533 (Ronco et al., 2017, Med Chem Commun 8:295-319). PV1019 showed enhanced activity when used in combination with topotecan or camptothecin (Ronco et al., 2017, Med Chem Commun 8:295-319). However, the required doses were too high for therapeutic use (Ronco et al., 2017, Med Chem Commun 8:295-319). Ronco et al. concluded that the anticancer activity of CHK2 inhibitors developed to date was significantly lower than that of CHK1, ATM, or ATR inhibitors (Ronco et al., 2017, Med Chem Commun 8:295-319). WEE1 inhibitor

[0068] WEE1 is overexpressed in many forms of cancer, including breast cancer, glioma, glioblastoma, nasopharyngeal cancer, and drug-resistant cancer (Ronco et al., 2017, Med Chem Commun 8:295-319). WEE1 is a major mediator in the ATR pathway and is activated by CHK1 (Ronco et al., 2017, Med Chem Commun 8:295-319). WEE1 exerts inhibitory effects on cyclin B / cdc2 and CDK1, subsequently regulating cell cycle arrest (Ronco et al., 2017, Med Chem Commun 8:295-319). Compared to other components of DDR, there are relatively few WEE1 inhibitors available.

[0069] The WEE1 inhibitor AZD1775 (MK1775) is being used in clinical trials in combination with DNA damaging agents such as fludarabine, cisplatin, carboplatin, paclitaxel, gemcitabine, docetaxel, irinotecan, or cytarabine (Matheson). (See also clinicaltrials.gov, et al., 2016, Trends Pharm Sci 37:P872-81). Combination therapy with WEE1 and CHK1 / 2 inhibitors has been reported to produce synergistic effects in cancer xenografts (Ronco et al., 2017, Med Chem Commun 8:295-319). Therefore, combination therapy with anti-Trop-2 ADCs, WEE1 inhibitors, and one or more CHK1 / 2 inhibitors may be used. Other known WEE1 inhibitors include PD0166285 and PD407824. However, these appear to have significantly lower clinical utility than MK-1775 (Ronco et al., 2017, Med Chem Commun 8:295-319). Other DDR inhibitors

[0070] In addition to the major regulatory points mentioned above, various inhibitors of other proteins in the DDR pathway have been discovered (Srivastava & Raghavan, 2015, Chem Biol 22:17-29). Due to nonspecific interactions and high homology between various kinases in DDR, some of these inhibitors exhibit cross-reactivity with other DDR proteins.

[0071] Mirin is an HR inhibitor that targets MRE11 (Srivastava & Raghavan, 2015, Chem Biol 22:17-29). Ml216 and NSC19630 inhibit the RecQ helicases BLM and WRN, respectively (Srivastava & Raghavan, 2015, Chem Biol 22:17-29). NSC130813 was developed as an ERCC1 inhibitor and shows synergistic activity with cisplatin and mitomycin C (Srivastava & Raghavan, 2015, Chem Biol 22:17-29). Among NHEJ proteins, DNA-PKcs are inhibited by woltmannin, LY294002, MSC2490484A (M3814), VX-984 (M9831), and NU7026 (Srivastava & Raghavan, 2015, Chem Biol 22:17-29; Brandsma et al., 2017, Expert Opin Investig Drugs 26:1341-55). These and other known DDR inhibitors may be used in combination therapy with anti-Trop-2 ADCs in the methods and compositions of interest. Combination therapy with ADCs and other anticancer drugs PI3K / AKT inhibitors

[0072] The phosphatidylinositol-3-kinase (PI3K) / AKT pathway is genetically targeted in more tumor types than any other growth factor signaling pathway and is often activated as a cancer driver (Guo et al., 2015, J Genet Genomics 42:343-53). There is considerable sequence homology between PI3K and PI3K-related kinases (PIKKs) ATM, ATR, and DNA-PK, and there is frequent cross-reactivity between inhibitors of different kinases. Inhibitors of PI3K, AKT, and PIKK are being actively investigated for cancer therapy (Guo et al., 2015, J Genet Genomics 42:343-53).

[0073] In certain embodiments, inhibitors of PI3K and / or various AKT isoforms (AKT1, AKT2, AKT3) may be used alone or in combination with other DDR inhibitors in combination therapy with anti-Trop-2 ADCs. Examples include: Idelalisib, Woltmannin, Demethoxypyridine, Perifosin, PX-866, IPI-145 (Duvelisib), BAY 80-6946, BEZ235, RP6530, TGR1202, SF1126, INK1117, GDC-0941, GDC-0980, BKM120, XL147, XL765, Palomid. Various PI3K inhibitors are known, including 529, GSK1059615, ZSTK474, PWT33597, IC87114, TG100-115, CAL263, PI-103, GNE477, CUDC-907, AEZS-136, NVP-BYL719, NVP-BEZ235, SAR260301, TGR1202, or LY294002. BEZ235, a pan-PI3K inhibitor, has been reported to potently kill B-cell lymphomas and human cell lines with IG-cMYC translocations (Shortt et al., 2013, Blood 121:2964-74).

[0074] AKT is a downstream mediator of PI3K activity. In mammals, AKT consists of three isoforms: AKT1, AKT2, and AKT3 (Guo et al., 2015, J Genet Genomics 42:343-53). Different isoforms have different functions. AKT1 appears to regulate oncogenic initiation, while AKT2 primarily promotes tumor metastasis (Guo et al., 2015, J Genet Genomics 42:343-53). Following PI3K activation, AKT phosphorylates several downstream effectors that have broad effects on cell survival, growth, metabolism, tumorigenesis, and metastasis (Guo et al., 2015, J Genet Genomics 42:343-53).

[0075] Examples of AKT inhibitors include MK2206, GDC0068 (ipatasertib), AZD5663, ARQ092, BAY1125976, TAS-117, AZD5363, GSK2141795 (uprosertib), GSK690693, GSK2110183 (afresertib), CCT128930, A-674563, A-443654, AT867, AT13148, trisirivine, and MSC2363318A (Guo et al., 2015, J Genet Genomics 42:343-53, Xing et al., 2019, Breast Cancer Res 21:78, Nitulescu et al., 2016, Int J Oncol 48:869-85). Any known AKT inhibitor may be used in combination therapy with anti-Trop-2 ADCs and / or DDR inhibitors. MK-2206 monotherapy showed limited clinical activity in patients with advanced breast cancer exhibiting mutations in PIK3CA, AKT1, or PTEN and / or PTEN loss (Xing et al., 2019, Breast Cancer Res 21:78). MK-2206 appeared to be more effective when used in combination with paclitaxel for the treatment of breast cancer (Xing et al., 2019, Breast Cancer Res 21:78).

[0076] mTOR is a major downstream target of AKT and has an overall effect on cellular metabolism. Examples of mTOR inhibitors being developed for cancer therapy include temsirolimus, everolimus, AZD8055, MLN0128, and OSI-027 (Guo et al.). (al., 2015, J Genet Genomics 42:343-53). Such mTOR inhibitors may also be used in combination therapy with ADCs and / or DRR inhibitors.

[0077] Guo et al. (2015, J Genet Genomics 42:343-53) analyzed genetic alterations in 20 components of the PI3K / AKT pathway, including GNB2LI, EGFR, PIK3CA, PIK3R1, PIK3R2, PTEN, PDPKI, AKT1, AKT2, AKT3, FOXO1, FOXO3, MTOR, RICTOR, TSC1, TSC2, RHEB, AKT1SI, RPTOR, and MLST8. Genetic alterations were observed in all components of the PI3K / AKT pathway in different cancer cells. Genetic alterations were identified in all forms of cancer examined, ranging from 6% in thyroid cancer to 95% in endometrial cancer (Guo et al., 2015, J Genet Genomics). 42:343-53). The PIK3CA gene, which encodes the p110α subunit of PI3K, has been found to be the most frequently altered oncogene in general cancer (Guo et al., 2015, J Genet Genomics 42:343-53). Mutations in PTEN are also common, with RHEB overexpression (Guo et al., 2015, J Genet Genomics 42:343-53). Although not a common mutation, amplification of AKT has been frequently observed in ovarian, uterine, breast, liver, and bladder cancers (Guo et al., 2015, J Genet Genomics 42:343-53). However, AKT3 expression has been reported to be downregulated in high-grade serous ovarian cancer (Yeganeh et al., 2017, Genes & Cancer 8:784-98).

[0078] CDK4 is a downstream effector of PI3K in the protein kinase C-mediated pathway. CDK4 / 6 inhibitors interfere with cell cycle progression and include abemaciclib, palbociclib, and ribociclib (Schettini et al., 2018, Front Oncol 12:608). Other anticancer drugs

[0079] While the combination of DDR inhibitors with anti-Trop-2 ADCs is of importance in this application, the methods and compositions of interest may include the use of one or more other known anticancer agents. Any such anticancer agent may be used with the ADC of interest, with or without the presence of a DDR inhibitor. Various anticancer agents may be administered simultaneously or sequentially. Such agents may include, for example, drugs, toxins, oligonucleotides, immunomodulators, hormones, hormone antagonists, enzymes, enzyme inhibitors, radionuclides, and angiogenesis inhibitors. Exemplary anticancer agents include, but are not limited to, cytotoxic drugs, e.g., vinca alkaloids, anthracyclines, e.g., doxorubicin, gemcitabine, epipodophyllotoxin, taxanes, antimetabolites, alkylating agents, antibiotics, SN-38, COX-2 inhibitors, mitotic inhibitors, anti-angiogenic and apoptosis-promoting agents, platinum-based agents, taxol, camptothecin, proteosome inhibitors, mTOR inhibitors, HDAC inhibitors, and tyrosine kinase inhibitors. Other useful anti-cancer cytotoxic drugs include nitrogen mustard, alkyl sulfonates, nitrosoureas, triazenes, folic acid analogs, COX-2 inhibitors, antimetabolites, pyrimidine analogs, purine analogs, platinum-coordinated complexes, mTOR inhibitors, tyrosine kinase inhibitors, proteosome inhibitors, HDAC inhibitors, camptothecin, and hormones. Preferred cytotoxic drugs are listed in REMINGTON'S PHARMACEUTICAL SCIENCES, 19th Ed. (Mack Publishing Co., 1995), and GOODMAN AND GILMAN'S THE PHARMACOLOGICAL BASIS OF THERAPEUTICS, 7th Ed. (MacMillan Publishing Co., 1985), as well as revised editions of these publications.

[0080] Specific drugs used in combination therapy include 5-fluorouracil, afatinib, apridin, azalibine, anastrozole, anthracyclines, axitinib, AVL-101, AVL-291, bendamustine, bleomycin, bortezomib, bosutinib, bryostatin-1, busulfan, calitiamycin, camptothecin, carboplatin, 10-hydroxycamptothecin, carmustine, celecoxib, chlorambucil, cisplatin, COX-2 inhibitors, irinotecan (CPT-11), SN-38, carboplatin, cladribine, crizotinib, cyclophosphamide, and cyanophosphate. Tarabine, dacarbazine, dasatinib, dinacicrib, docetaxel, dactinomycin, daunorubicin, DM1, DM3, DM4, doxorubicin, 2-pyrrolinodoxorubicin (2-PDox), cyanomorpholinodoxorubicin, doxorubicin clonide, endostatin, epirubicin clonide, erlotinib, estramustine, epipodophyllotoxin, erlotinib, entinostat, estrogen receptor binder, etoposide (VP16), etoposide glucuronide, etoposide phosphate, exemestane, fingolimod, phloxuridine (FUdR), 3',5'-O-Dioleoyl-FudR (FUdR-dO), fludarabine, flutamide, farnesyl-protein transferase inhibitor, flavopyridol, fostamatinib, ganetespib, GDC-0834, GS-1101, gefitinib, gemcitabine, hydroxyurea, ibrutinib, idarubicin, idelalisib, ifosfamide, imatinib, lapatinib, lenalidomide, leucovorin, LFM-A13, lomustine, mechloretamine, melphalan, mercaptopurine, 6-mercaptopurine, methotrexate, mitoxantrone, mithramycin, mitomycin, mitotane, monomethyl auristatin F (MMAF), Examples include monomethyl auristatin D (MMAD), monomethyl auristatin E (MMAE), navelbine, neratinib, nilotinib, nitrosourea, olaparib, plicamycin, procarbazine, paclitaxel, PCI-32765, pentostatin, PSI-341, raloxifene, semustine, SN-38, sorafenib, streptozocin, SU11248, sunitinib, tamoxifen, temozolomide, transplatin, thalidomide, thioguanine, thiotepa, teniposide, topotecan, uracil mustard, batalanib, vinorelbine, vinblastine, vincristine, vinca alkaloids, and ZD1839.

[0081] Examples of immunomodulatory agents used in combination therapy include cytokines, lymphokines, monokines, stem cell growth factors, lymphotoxins, hematopoietic factors, colony-stimulating factors (CSF), interferon (IFN), parathyroid hormone, thyroxine, insulin, proinsulin, relaxin, prorelaxin, follicle-stimulating hormone (FSH), thyroid-stimulating hormone (TSH), progesterone (LH), hepatic growth factors, prostaglandins, fibroblast growth factors, prolactin, placental lactogens, OB protein, transforming growth factor (TGF), TGF-α, TGF-β, insulin-like growth factor (ILGF), erythropoietin, thrombopoietin, tumor necrosis factor (TNF), TNF-α, TNF-β, Müllerian inhibitor, and mouse hormone. Examples include nadotropin-related peptides, inhibin, activin, vascular endothelial growth factor, integrins, interleukins (IL), granulocyte colony-stimulating factor (G-CSF), granulocyte-macrophage colony-stimulating factor (GM-CSF), interferon-α, interferon-β, interferon-γ, interferon-λ, S1 factor, IL-1, IL-1cc, IL-2, IL-3, IL-4, IL-5, IL-6, IL-7, IL-8, IL-9, IL-10, IL-11, IL-12, IL-13, IL-14, IL-15, IL-16, IL-17, IL-18, IL-21, and IL-25, LIF, kit-ligands, FLT-3, angiostatins, thrombospondin, endostatins, and lymphotoxins.

[0082] These and other known anticancer drugs may be used in combination with ADC and / or DDR inhibitors to treat cancer. Biomarker detection

[0083] Various biomarkers have been described above in relation to inhibitors of specific classes of DDR proteins. For example, BRCA mutations are well known to be used to predict sensitivity to PARP inhibitors. The use of these and other cancer biomarkers will be discussed in more detail below. Such biomarkers may be used to detect or diagnose various forms of cancer, or to predict the efficacy and / or toxicity of ADC monotherapy and / or combination therapy with ADCs and one or more other anticancer agents such as DDR inhibitors or alternative anticancer agents.

[0084] As used herein, cancer biomarkers are molecular markers associated with malignant cells. Protein biomarkers of cancer have been known and detected since the mid-19th century. For example, Bence Jones protein was first identified in 1846 in the urine of multiple myeloma patients, while prostatic acid phosphatase was detected as early as 1933 in the serum of prostate cancer patients (Virji et al., 1988, CA Cancer J). Clin 38:104-26). Carbonic anhydrase IX, CCL19, CCL21, CSAp, HER-2 / neu, CD1, CD1a, CD5, CD14, CD15, CD19, CD20, CD21, CD22, CD23, CD29, CD30, CD32b, CD33, CD37, CD38, CD40, CD40L, CD44, CD45, CD46, CD52, CD54, CD55, CD59, CD67, CD70, CD74, CD79a, CD83, CD95, CD126, CD133, CD138, CD147, CEACAM5, CEACAM6, α-fetoprotein (AFP), VEGF, ED-B fibronectin, EGP-1 (Trop-2), EGP-2, EGF receptor (ErbB1), ErbB2, ErbB3, H factor, Fl Examples of tumor-associated antigens (TAAs) include t-3, HMGB-1, hypoxia-inducible factor (HIF), insulin-like growth factor (ILGF), IL-13R, IL-2, IL-6, IL-8, IL-17, IL-18, IP-10, IGF-1R, HCG, HLA-DR, CD66a-d, MAGE, MCP-1, MIP-1A, MUC5ac, PSA (prostate-specific antigen), PSMA, NCA-95, Ep-CAM, Le(y), mesoserine, tenascin, Tn antigen, Thomas-Friedenreich antigen, TNF-α, TRAIL receptor R1, TRAIL receptor R2, VEGFR, RANTES, and various oncogene proteins, but are not limited to these; many other tumor-associated antigens (TAAs) have been detected in various forms of cancer.

[0085] Such protein biomarkers have historically been detected in solid tumor biopsy specimens or in bodily fluids such as blood or urine (liquid cytology). Many methods for protein detection, such as ELISA, Western blotting, immunohistochemistry, HPLC, mass spectrometry, protein microarrays, fluorescence microscopy, and similar techniques, are well known in the art and can be used to detect protein biomarkers. Many protein-based assays rely on specific protein / antibody interactions for detection. Such assays are standard in clinical cancer diagnosis and are available in the methods and compositions of interest, while the following discussion deals more with the detection of nucleic acid biomarkers for cancer. Preferably, such nucleic acid biomarkers are detected in the patient's liquid samples (blood, plasma, serum, lymph, urine, cerebrospinal fluid, etc.). This is a rapidly developing field, and highly sensitive and specific tests for detecting nucleic acid biomarkers are still under development. Generally, the following discussion of liquid cytology nucleic acid biomarkers focuses on the analysis of cell-free DNA (cfDNA), circulating tumor DNA (ctDNA), or circulating tumor cells (CTCs). cfDNA analysis

[0086] cfDNA (cell-free DNA) refers to extracellular DNA that occurs in blood or other bodily fluids. cfDNA primarily exists in the form of short nucleic acid fragments, approximately 150–180 bp in length, released from normal or tumor cells by apoptosis and necrosis, or detached from cells through the formation of exosomes or microvesicles (Huang et al., 2019, Cancers 11:E805, Kubiritova et al., 2019, Int J Mol Sci 20:3662). Longer cfDNA fragments can also exist, reaching sizes up to 10,000 bp in cancer patients (Bronkhorst et al., 2019, Biomol Detect Quantif 18:100087). cfDNA levels are typically elevated in cancer patients (Pos (Stroun et al., 1989, Oncology 46:318-22) The fraction of cfDNA in the plasma of cancer patients originates from cancer cells. (Stroun et al., 2018, J Immunol 26:937-45)

[0087] cfDNA has been proposed to have broad applications in cancer treatment, including disease staging and prognosis assessment, tumor localization, initial treatment stratification, monitoring of treatment response, monitoring of residual disease, and identification of recurrence mechanisms and drug resistance acquisition mechanisms (Bronkhorst et al., 2019, Biomol Detect Quantif 18:100087). The usefulness of cfDNA in clinical practice has been validated by the FDA approval of the cobas® EGFR Mutation Test v2, aimed at identifying lung cancer patients suitable for treatment with erlotinib or osimertinib, and Epi proColon®, a colorectal cancer screening test based on the methylation status of the SEPT9 promoter (Bronkhorst et al., 2019, Biomol Detection Quantif 18:100087).

[0088] Analysis of cfDNA derived from liquid samples may involve preanalytic separation, concentration, and purification. While these can be performed manually, several automated systems or kits for extracting cfDNA from liquid samples are available and preferably used. These include the NUCLEOMAG® DNA Plasma kit (Takara), the MAGMAX® Cell-Free DNA Isolation Kit (ThermoFisher) for use with KINGFISHER® instruments, the Omega Bio-tek automated system for use with the Hamilton MICROLAB® STAR® platform, the MAXWELL® RSC(MR) cfDNA Plasma Kit, and many others. Such methods and apparatus for isolating cfDNA from liquid samples are well known in the art, and such known methods or apparatus may be used in the practice of the method in question.

[0089] Once isolated, cfDNA can be analyzed for the presence or absence of biomarkers. Traditional methods such as Sangerdideoxysequencing (manual or Applied Biosystems workstation), RT-PCR, fluorescence microscopy, SNP hybridization, GENECHIP®, and other known techniques have been used to detect DNA mutations, insertions, deletions, recombinations, or other biomarkers. If a specific mutant “hotspot” is known and well-characterized, PCR-based analysis can be used for biomarker detection. For example, Qiagen sells the PI3K Mutation Test Kit for detecting four mutations (H1047R, E542K, E545D, E545K) in exons 9 and 20 of the PI3K oncogene using ARMS® and SCORPION® technologies. It is possible to detect 1% of mutant sequences in the background of wild-type genomic DNA. BRCANALYSISCDX® (Myriad) is another PCR-based test for detecting BRCA1 or BRCA2 mutations. Other tests designed to detect biomarkers in specific genes or sets of genes are commercially available.

[0090] These methods are sufficient to detect a limited number of nucleic acid biomarkers that are well-characterized and known to be associated with specific types of cancer. However, a more comprehensive approach to detecting a range of biomarkers that can occur in multiple locations, are heterogeneous, or are not well-characterized requires the use of more advanced DNA analysis techniques, such as next-generation sequencing, which are discussed below (Kubiritova et al., 2019, Int J Mol Sci 20:3662). NGS techniques used with liquid cytology samples are being re-evaluated (e.g., Chen & Zhao, 2019, Human Genomics 13:34).

[0091] Next-generation sequencing (NGS) can be performed for the coding regions of DNA (whole exome sequencing) or for both coding and non-coding regions (whole genome sequencing). Analysis of cancer biomarkers generally concerns coding region variations and regulatory sequences such as promoters. Specific target gene panels can also be optimized for NGS (Johnson). et al., 2013, Blood 122:3268-75). There are many variations in the NGS technologies and equipment used. The following discussion is a generalization of some common characteristics of NGS.

[0092] For example, after obtaining a cfDNA sample, the first step in NGS is to cleave the genomic DNA or cDNA into short fragments of several hundred base pairs, which is the average size of cfDNA. If longer DNA sequences are present, they may need to be fragmented to an appropriate size. Short oligonucleotide linkers (adapters) may be added to the DNA fragments. When analyzing multiple samples simultaneously, the linkers may be labeled with a unique fluorescence or other detectable probe (molecular barcode) to allow for sequence assignment to different individuals or different genes. The linkers also enable PCR amplification if the source DNA is limited to signal detection. Barcoding techniques may also be used to identify specific nucleic acid sequences against a background of numerous other nucleic acid species, as discussed below.

[0093] Short DNA fragments are converted to single-stranded DNA and hybridize to complementary oligonucleotides located within a channel on a slide or another type of microfluidic chip device, although other types of solid surfaces can be used. The location of the hybridized fragment can be detected, for example, by fluorescence microscopy (Johnson et al., 2013, Blood 122:3268-75). Since the location and sequence of the complementary oligonucleotide are known, the corresponding sequence of the hybridized DNA fragment can be identified. In various embodiments, the complementary oligonucleotide can function as a primer for further extension by DNA polymerase activity to generate additional sequence data.

[0094] In the Illumina NGS system, complementary DNA bound to primers on the surface of the flow cell is replicated to form small clusters of identical DNA sequences for signal amplification. Unlabeled dNTPs and DNA polymerase are added to extend and junction the DNA binding strands, creating "crosslinks" of dsDNA between primers on the flow cell. The dsDNA is then degraded into ssDNA. Primers specific to each of the four nucleotides and fluorescently labeled terminators are added. Once the nucleotides are incorporated into the growth strand, further elongation is inhibited until the terminators are removed. A fluorescence microscope is used to identify which nucleotides have been incorporated at each location in the flow cell. The terminators are removed, and the next polymerization round proceeds. Individual short (approximately 150 bp) sequences can be combined into larger exons or non-coding genomic sequences.

[0095] The Illumina platform is illustrative only, and many other NGS systems are available, each using several variations of the techniques, chemicals, and protocols used to obtain nucleic acid sequences (see, e.g., Besser et al., 2018, Clin Microbiol Infect. 24:335-41). Other common detection platforms may include pyrosequencing (based on pyrophosphate release) (see, e.g., Jouini et al., 2019, Heliyon 19:e01330) or ION TORRENT® NGS (based on hydrogen ion release when DNTPs are taken up) (see, e.g., Fan et al., 2019, Oncol Rep 42:1580-88). ctDNA analysis

[0096] ctDNA is cell-free DNA derived from tumor cells. Typically, ctDNA is present in very small amounts of cfDNA, potentially less than 0.1% of cfDNA in individuals with early-stage cancer (Huang et al., 2019, Cancers 11:E805), although estimates of ctDNA occurrence as high as 90% of cfDNA have been reported (Volik et al., 2016, Mol Cancer Res 14:898-908). Due to its slightly different size range, ctDNA can be partially enriched from cfDNA by polyacrylamide gel electrophoresis followed by appropriate size range excision and elution (Huang et al., 2019, Cancers 11:E805). However, while such techniques may enrich ctDNA, the majority of cfDNA, at least in early-stage cancer, still originates from normal cells, resulting in a high signal-to-noise background. Analysis of ctDNA is also complicated by tumor heterogeneity. Droplet digital PCR (ddPCR) and molecular index-based next-generation sequencing (Volik et al., 2016, Mol Cancer Res 14:898-908, Wood-Bouwens et al., 2017, J Mol Methods have been developed to address low ctDNA expression rates, such as those described in Diagn 19:697-710.

[0097] Early studies of ctDNA relied on real-time allele-specific PCR to detect target mutations (Yi et al., 2017, Int J Cancer 140:2642-47). This technique was designed to detect mutations present only in cancer cells. However, the sensitivity and specificity of this method limited its use, mainly to individuals with high tumor burden. Digital PCR offers increased sensitivity and specificity by limiting the dilution of DNA samples, resulting in individual DNA molecules being present in water-oil emulsion droplets or chambers (Yi et al., 2017, Int J Cancer 140:2642-47). Primers and probes designed to distinguish between variants and normal alleles of specific genes can be used to amplify and quantify the frequency of mutant alleles. However, such techniques require prior information on the nucleic acid biomarkers being detected.

[0098] Next-generation sequencing, particularly large-scale parallel sequencing, has been applied to ctDNA and cfDNA. These methods and systems are discussed in detail in the previous section. As mentioned above, due to the size overlap between cfDNA and ctDNA in normal cells, separating ctDNA from much higher concentrations of cfDNA is technically difficult. Therefore, ctDNA analysis frequently attempts to detect tumor-specific nucleic acid biomarkers against a high background of cfDNA using the same analytical techniques described above.

[0099] An interesting variation of this method utilizes capture-based next-generation sequencing to detect ALK (anaplastic lymphoma kinase) rearrangement in NSCLC (Wang et al.). (al., 2016, Oncotarget 7:65208-17). A capture-based sequencing panel (Burning Rock Biotech Ltd (Guangzhou China)) was used, targeting 168 genes and spanning 160kb of human genomic DNA sequences. cfDNA was hybridized with capture probes, separated by magnetic bead binding, and then amplified by PCR. The amplified samples were sequenced using a NextSeq 500 system (Illumina). Given the difficulty of size-based separation techniques, the use of capture techniques may be superior for separating ctDNA from cfDNA. However, this requires targeted analysis of specific gene sets or prior information on nucleic acid sequence variants present in tumor cells.

[0100] An increasing number of studies are investigating cancer biomarkers based on ctDNA analysis. Angus et al. (Mol Oncol 2019 13:2361-74) analyzed ctDNA from patients with metastatic colorectal cancer (mCRC) using NGS for mutations in RAS and BRAF. mCRC patients with RAS or BRAF mutations do not respond to anti-EGFR antibodies such as cetuximab and panitumumab (Angus et al., 2019 13:2361-74). Despite patient selection for anti-EGFR therapy based on RAS mutations, less than 50% of patients with wild-type mCRC demonstrate clinical benefit (Angus et al., 2019 13:2361-74). ctDNA analysis of plasma samples revealed heterogeneity in RAS and BRAF mutations in patients identified as having wild-type RAS by tumor biopsy. Compared to patients without mutations, those with RAS / BRAF mutations had shorter progression-free survival (1.8 vs. 4.9 months) and overall survival (3.1 vs. 9.4 months) (Angus et al., 2019 13:2361-74). We concluded that RAS and BRAF mutations in cfDNA / ctDNA predict the outcome of cetuximab monotherapy (Angus et al., 2019 13:2361-74).

[0101] Galbiati et al. (2019, Cells 8:769) used a combination of microarray probe hybridization with droplet digital PCR (ddPCR) to detect specific mutations in KRAS, NRAS, and BRAF and to determine the amount of mutant allele fractions in ctDNA of mCRC patients. The microarray capture probes were specific to KRAS (G12A, G12C, G12D, G12R, G12S, G12V, G13D, Q61H(A>C), Q61H(A>T), Q61K, Q61L, Q61R, A146T), NRAS (G12A, G12C, G12D, G12S, G12V, G13D, G13V), and BRAF (V600E), as well as wild-type sequences (Galbiati et al., 2019, Cells 8:769). After allele-specific hybridization, ssPCR-reporter hybrids were used for detection. Following microarray analysis, ddPCR was performed using the QX100™ DROPLET DIGITAL™ PCR system (Bio-Rad). When the microarray results were compared with the tissue biopsy analysis, a 95% overall agreement was observed, and two additional KRAS mutations not found in the tissue biopsy were detected (Galbiati et al., 2019, Cells). (8:769). We concluded that ctDNA analysis could be used for non-invasive biomarker detection to induce anti-EGFR antibody therapy in mCRC (Galbiati et al., 2019, Cells 8:769).

[0102] These and many other reported studies on cfDNA or ctDNA analysis demonstrate the usefulness of circulating nucleic acids for detection, prognosis, monitoring of disease response, and prediction of responsiveness to specific anticancer drugs and / or combination therapies. It should be noted that, generally, ctDNA studies do not isolate tumor-derived nucleic acids from normal cell cfDNA, while ctDNA analysis is based on the detection of tumor-specific or tumor-selective markers. Therefore, the distinction between cfDNA and ctDNA analysis in cancer diagnosis is inherently significant, and all the techniques, methods, and apparatus described in the previous section for cfDNA can also be used for ctDNA analysis. Analysis of circulating tumor cells (CTCs)

[0103] It has been suggested that cancer cells may be found in low concentrations in circulation during the early stages of tumor progression (see, for example, Krishnamurthy et al., 2013, Cancer Medicine 2:226-33; Alix-Panabieres & Pantel, 2013, Clin Chem 50:110-18; Wang et al., 2015, Int J Clin Oncol, 20:878-90). Because blood sampling is inherently relatively non-invasive, there is great interest in isolating and detecting cytoplasmic tumors (CTCs) to facilitate cancer diagnosis in the early stages of the disease as predictors of tumor progression, disease prognosis, and / or responsiveness to drug therapy (see, for example, Alix-Panabieres & Pantel, 2013, Clin Chem 50:110-18; Winer-Jones et al., 2014, PLoS One 9:e86717; U.S. Patent Application Publication No. 2014 / 0357659).

[0104] Various techniques and devices have been developed for isolating and / or detecting circulating tumor cells. Several reviews in this field have recently been published (see, e.g., Alix-Panabieres & Pantel, 2013, Clin Chem 50:110-18; Joosse et al., 2014, EMBO Mol Med 7:1-11; Truini et al., 2014, Fron Oncol 4:242). These techniques generally involve the enrichment and / or isolation of CTCs using capture antibodies against antigens expressed on tumor cells, as well as the use of magnetic nanoparticles, microfluidic devices, filtration, magnetic separation, centrifugation, flow cytometry and / or cell classification devices (e.g., Krishmanurthy et al., 2013, Cancer Medicine 2:226-33; Alix-Panabieres & Pantel, 2013, Clin Chem 50:110-18;Joosse et al.,2014,EMBO Mol Med 7:1-11;Truini et al.,2014,Fron Oncol 4:242;Powell et al.,2012,PLoS ONE 7:e33788;Winer-Jones et al.,2014,PLoS ONE 9:e86717; Gupta et al., 2012, Biomicrofluidics 6:24133; Saucedo-Zeni et al., 2012, Int J Oncol 41:1241-50; Harb et al., 2013, Transl Oncol 6:528-38). The enriched or isolated CTCs can then be analyzed using a variety of known methods, as will be discussed further below.

[0105] Systems or devices used for CTC isolation and detection include the CELLSEARCH® system (e.g., Truini et al., 2014, Front Oncol 4:242), the MagSweeper device (e.g., Powell et al., 2012, PLoS ONE 7:e33788), the LIQUIDBIOPSY® system (Winer-Jones et al., 2014, PLoS One 9:e86717), the APOSTREAM® system (e.g., Gupta et al., 2012, Biomicrofluidics 6:24133), the GILUPI CELLCOLLECTOR® system (e.g., Saucedo-Zeni et al., 2012, Int J Oncol 41:1241-50), and the ISOFLUX® system (Harb et al., 2013, Transl Oncol). 6:528-38) is one example.

[0106] To date, the only FDA-approved technology for CTC detection is the CELLSEARCH® platform (Veridex LLC (Raritan, NJ)), which utilizes anti-EpCAM antibodies bound to magnetic nanoparticles to capture CTCs. Detection of bound cells occurs with fluorescently labeled antibodies against cytokeratin (CK) and CD45. Fluorescently labeled cells bound to magnetic particles are separated using a strong magnetic field and counted by digital fluorescence microscopy. The CELLSEARCH® system is FDA-approved for the detection of metastatic breast cancer, prostate cancer, and colorectal cancer.

[0107] Most CTC detection systems emphasize the use of anti-EpCAM capture antibodies (see, for example, Truini et al., 2014, Front Oncol 4:242; Powell et al., 2012, PLoS ONE 7:e33788; Alix-Panabieres & Pantel, 2013, Clin Chem 50:110-18; Lin et al., 2013, Biosens Bioelectron 40:63-67; Magbunaa et al., 2015, Clin Cancer Res 21:1098-105; Harb et al., 2013, Transl Oncol 6:528-38). However, not all metastatic tumors express EpCAM (see, for example, Mikolajcyzyzek et al., 2011, J Oncol 2011:252361; Pecot et al., 2011, Cancer Discovery 1:580-86; Gupta et al., 2012, Biomicrofluidics 6:24133). Attempts have been made to utilize alternative schemes for isolating and detecting EpCAM-negative CTCs, such as the use of antibody combinations against TAA. In attempts to increase the recovery of metastatic circulating tumor cells, antibodies against 10 different TAAs have been used (see, for example, Mikolajcyzygek et al., 2011, J Oncol 2011:252361; Pecot et al., 2011, Cancer Discovery 1:580-86; Krishmansurthy et al., 2013, Cancer Medicine 2:226-33; Winer-Jones et al., 2014, PLoS ONE 9:e86717).

[0108] This method for CTC analysis can be used with or without an affinity-based enrichment step, such as MAINTRAC® (Pachmann et al. 2005, Breast Cancer Res, 7:R975). Methods using magnetic devices for affinity-based enrichment include the CELLSEARCH® system (Veridex), the LIQUIDBIOPSY® platform (Cynvenio Biosystems), and the MagSweeper device (Talasaz). Examples include the CTC chip (Stott et al. 2010, Sci Transl Med, 2:25ra23), the HB-chip (Stott et al. 2010, PNAS, 107:18392), the NanoVelcro chip (Lu et al., 2013, Methods, 64:144), the GEDI microdevice (Kirby et al., 2012, PLoS ONE, 7:e35976), and Biocept's OncoCEE® technology (Pecot et al. Examples of various manufactured microfluidic devices include those described in (al., 2011, Cancer Discov, 1:580).

[0109] The use of the FDA-approved CELLSEARCH® system for CTC detection in non-small cell and small cell lung cancer patients was discussed by Truini et al. (2014, Front Oncol 4:242). A 7.5 mL peripheral blood sample was mixed with magnetic iron nanoparticles coated with anti-EpCAM antibody. A strong magnetic field was used to separate EpCAM-positive cells from EpCAM-negative cells. Detection of bound CTCs was performed using fluorescently labeled anti-CK and anti-CD45 antibodies, along with DAPI (4',6'-diamidino-2-phenylindole) fluorescence labeling of the cell nucleus. CTCs were identified by fluorescence detection as CK-positive, CD45-negative, and DAPI-positive.

[0110] The VerIFAST® system was used for the diagnosis and pharmacodynamic analysis of circulating tumor cells (CTCs) in non-small cell lung cancer (NSCLC) (Casavant et al., 2013, Lab Chip 13:391-6; 2014, Lab Chip 14:99-105). The VerIFAST® platform utilizes the relative dominance of surface tension over gravity at the microscale to load non-miscible phases side by side. This pins aqueous and oil fields within adjacent chambers, creating a virtual filter between the two aqueous wells (Casavant et al., 2013, Lab Chip 13:391-6). Using paramagnetic particles (PMPs) with bound antibodies or other targeting moieties, specific cell populations can be targeted and isolated from the complex background by simply traversing the oil barrier. In the NSCLC example, streptavidin was conjugated to DYNABEADS® FLOWCOMP® PMP (Life Technologies, USA), and cells were captured using a biotinylated anti-EpCAM antibody. A small magnet was used to move PMP-bound CTCs between aqueous chambers. The recovered CTCs were released with PMP-releasing buffer (DYNABEADS®) and stained for EpCAM, EGFR, or transcription termination factor (TTF-1). The VerIFAST® platform integrates a microporous membrane into the aqueous chamber, enabling multiple fluid transfers without the need for cell transfer or centrifugation. With physical properties that enable high accuracy compared to macroscale technologies, such microfluidic technologies are well-suited for the capture and evaluation of CTCs with minimal sample loss. The VerIFAST® platform effectively captured CTCs from the blood of NSCLC patients (Casavant et al., 2013, Lab Chip 13:391-6; 2014, Lab Chip 14:99-105).

[0111] The GILUPI CELLCOLLECTOR (trademark) (Saucedo-Zeni et al., 2012, Int J Oncol 41:1241-50) is based on a functionalized medical Seldinger guidewire (FSMW) coated with a chimeric anti-EpCAM antibody. The guidewire was functionalized with a polycarboxylate hydrogel layer activated with EDC and NHS to enable covalent binding of the antibody. The antibody-coated FSMW was inserted into the cubital vein of breast cancer or NSCLC lung cancer patients through a standard intravenous cannula for 30 minutes. After cell binding to the guidewire, CTCs were identified by immunocytochemical staining and nuclear staining for EpCAM and / or cytokeratin. Fluorescent labeling was analyzed using an Axio Imager.A1m microscope (Zeiss (Jena, Germany)). The FSMW system was able to enrich EpCAM-positive CTCs in 22 out of 24 patients tested, including those with early-stage cancer that had not yet been diagnosed with distant metastasis. CTCs were not detected in healthy volunteers. An advantage of the FSMW system is that it is not limited by the volume of the ex vivo blood sample, which can be processed using alternative methods. The estimated blood volume in contact with the FSMW during 30 minutes of exposure was 1.5–3 liters.

[0112] Using these and other methods for CTC isolation, samples for biomarker analysis can be obtained. EpCAM is the most commonly used target for antibody capture, but various devices can also be used with different capture antibodies, such as anti-Trop-2 antibodies. Cancer types targeted by the ADC combination therapies disclosed herein generally have high Trop-2 expression, and such antibodies may be more efficient at capturing CTCs in such cancer patients. It is not ruled out that the same antibody (e.g., hRS7) can be used in the form of an ADC conjugated with a topoisomerase I inhibitor for both CTC capture and characterization, as well as treatment of the underlying tumor.

[0113] Once CTCs are isolated from circulation, they can be analyzed for the presence of biomarkers using standard methods disclosed elsewhere herein, such as PCR, RT-PCR, fluorescence microscopy, ELISA, Western blotting, immunohistochemistry, microfluidic chipping, SNP hybridization, molecular barcoding analysis, or next-generation sequencing. Kwan et al. (2018, Cancer Discov 8:1286-99) performed digital analysis of RNA derived from CTCs in breast cancer. Chemotherapy resistance was associated with ESR1 mutations (L536R, Y537C, Y537N, Y537S, D538G), and CTC scores and persistent CTC signaling were elevated after 4 weeks of treatment (Kwan et al., 2018, Cancer Discov 8:1286-99). Rapid tumor progression was associated with biomarkers for PIP, SERPINA3, AGR2, SCGB2A1, EFHD1, and WFDC2.

[0114] Shaw et al. (2017, Clin Cancer Res 23:88-96) performed an analysis of cfDNA and single cytotoxic tumor cells (CTCs) in patients with metastatic breast cancer. CTCs were obtained using a CellSearch® instrument with an anti-EpCAM antibody. The analysis was performed by next-generation sequencing of approximately 2200 mutations in 50 oncogenes. Heterogeneity of mutations among individual CTCs was observed in PIK3CA, TP53, ESR1, and KRAS (Shaw et al., 2017, Clin Cancer Res 23:88-96). cfDNA profiles correlated with those obtained from CTCs (Shaw et al., 2017, Clin Cancer Res 23:88-96). ESR1 and KRAS mutations observed in CTCs were not found in primary tumor samples, suggesting they either represent a subclonal population of cells or are acquired through disease progression (Shaw et al., 2017, Clin Cancer Res 23:88-96). Other methods for biomarker detection

[0115] The detection of nucleic acid biomarkers is not limited to any specific method or type of molecule or cell. In other embodiments, the biomarker may be, for example, RNA. RNA samples can be obtained from circulating blood, but are typically present at very low concentrations due to endogenous ribonuclease activity. Alternatively, mRNA can be extracted from solid biopsy samples using standard methods (e.g., Singh et al., 2018, J). (See Biol Methods 5:e95).

[0116] Automated systems for detecting RNA biomarkers are commercially available. One such system is the NanoString NCOUNTER® method. If sufficient RNA is present in the sample, solution-phase hybridization of mRNA occurs via a capture probe and a fluorescent barcode-labeled reporter probe. The reporter probe sequence is designed to hybridize to the specific nucleic acid biomarker of interest. After removal of unhybridized material, the hybridized probes are immobilized and aligned on the surface of a cartridge. The barcode-labeled mRNA is then identified by fluorescence detection of the localized barcode. The NCOUNTER® system allows for the simultaneous detection of up to 800 selected nucleic acid targets. Direct detection of circulating or solid biopsy RNA is preferred, but an RT-PCT step can be added if the sample size is insufficient. This inherently reduces the accuracy of the method due to amplification bias or other potential errors. Direct detection is preferred when reliable quantification is desired, such as determining the gene expression levels of various biomarker genes. The NanoString method can also be used to analyze cfDNA or ctDNA samples.

[0117] Souza et al. (2019, J Oncol 8393769) analyzed circulating cell-free microRNAs in the serum of breast cancer patients using the NanoString NCOUNTER® Human v3 miRNA Expression panel. Of the 800 microRNA probes analyzed, 42 showed the presence of significantly differentially expressed circulating microRNAs in breast cancer patients, further demonstrating differential expression across different subtypes of breast cancer (Souza et al., 2019, J Oncol 8393769). The biomarker miR-2503p showed the greatest correlation with TNBC. They concluded that liquid cytology of circulating microRNAs may be suitable for the early detection of breast cancer (Souza et al., 2019, J Oncol 8393769).

[0118] Another platform for detecting nucleic acid biomarkers is Affymetrix GENECHIP® is a registered trademark. This system can be used with various GENECHIP® microarrays that pre-load hybridization probes for RNA or DNA analysis. Probe sets may be custom-designed or selected from standard chips for SNP detection, and each chip may contain up to 1 million probes (Dalma-Weiszhausz et al., 2006, Methods Enzymol 410:3-28). Different chips are designed for genomic SNP detection, whole-genome expression profiling, whole-genome sequencing, differential splice variation, and numerous other applications. For example, the Affymetrix Genome-Wide Human SNP Array 6.0 contains 18 million genetic markers, including 906,600 SNPs and over 946,000 probes for detecting copy number variation. Agilent miRNA The Microarray Human Release 12.0 can assay for the presence of 866 miRNA species. The Affymetrix GENECHIP® Human Genome U133 Plus 2.0 Array can analyze the expression of over 47,000 transcripts, including 38,500 well-characterized genes.

[0119] DNA methylation can be assayed using standard techniques and equipment. For example, information on genome-wide DNA methylation can be found in The Cancer Genome Methylation can be obtained using the INFINIUM® HumanMethylation450 dataset from Atlas (TCGA). Methylation can be detected using the INFINIUM® MethylationEpic Beadchip Kit (Illumina) or the INFINIUM® 450K Methylation Array (Illumina). Alternatively, methylation can be detected using GOLDENGATE® Assay for Methylation and BEADARRAY® Technology. The Illumina INFINIUM® HD Beadchip can assay approximately 12 million genomic loci for genotyping and copy number variation. These and many other standard platforms or systems are well known in the art for detecting and identifying cancer biomarkers. Biomarkers related to anticancer effects and / or toxicity

[0120] Many cancer biomarkers are listed above, including mutations in NRAS, KRAS, BRCA1, BRCA2, p53, ATM, MRE11, SMC1, DNA-PKcs, PI3K, or BRAF. The genes (or proteins encoded by them) targeted for biomarker analysis include 53BP1, AKT1, AKT2, AKT3, APE1, ATM, ATR, BARD1, BAP1, BLM, BRAF, BRCA1, BRCA2, BRIP1 (FANCJ), CCND1, CCNE1, CDKN1, CDK12, CHEK1, CHEK2, CK-19, CSA, CSB, DCLRE1C, DNA2, DSS1, EEPD1, EFHD1, EpCAM, ERCC1, ESR1, EXO1, FAAP24, FANC1, FANCA, FANCC, FANCD1, FANCD2, FANCE, FANCF, FANCM, HER2, HMBS, HR23B, KRT19, KU70, KU80, hMAM, MAGEA1, and MAGE Examples include, but are not limited to, A3, MAPK, MGP, MLH1, MRE11, MRN, MSH2, MSH3, MSH6, MUC16, NBM, NBS1, NER, NF-κB, P53, PALB2, PARP1, PARP2, PIK3CA, PMS2, PTEN, RAD23B, RAD50, RAD51, RAD51AP1, RAD51C, RAD51D, RAD52, RAD54, RAF, K-ras, H-ras, N-ras, RBBP8, c-myc, RIF1, RPA1, SCGB2A2, SLFN11, SLX1, SLX4, TMPRSS4, TP53, TROP-2, USP11, VEGF, WEE1, WRN, XAB2, XLF, XPA, XPC, XPD, XPF, XPG, XRCC4, and XRCC7. As discussed in Example 1 below, in certain embodiments, the target genes for biomarker detection may include BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, or DDB2.

[0121] In some embodiments, the target genes for biomarker detection include BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2.

[0122] In some embodiments, the target genes for biomarker detection include BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2.

[0123] In some embodiments, the target genes for biomarker detection include AEN, MSH2, MYBBP1A, SART1, SIRT1, USP28, CDKN1A, ABL1, TP53, BAG6, BRCA1, BRCA2, BRSK2, CHEK2, ERN1, FHIT, HIPK2, HRAS, LGALS12, MSH6, ZNF385B, and ZNF622.

[0124] In some embodiments, the target genes for biomarker detection include AEN, MSH2, MYBBP1A, SART1, SIRT1, USP28, CDKN1A, ABL1, TP53, BAG6, BRCA1, BRCA2, BRSK2, CHEK2, ERN1, FHIT, HIPK2, HRAS, LGALS12, MSH6, ZNF385B, and ZNF622.

[0125] In some embodiments, the target genes for biomarker detection include BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, and USP28.

[0126] In some embodiments, the target genes for biomarker detection include BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, and USP28.

[0127] In some embodiments, the target genes for biomarker detection include POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A.

[0128] In some embodiments, the target genes for biomarker detection consist of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A.

[0129] In some embodiments, the target genes for biomarker detection include BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A.

[0130] In some embodiments, the target genes for biomarker detection include BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A.

[0131] In some embodiments, the biomarker is a plurality of single nucleotide polymorphisms, such as E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, and TP53 * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * This results in substitutions including R370Q in I987LZNF385B in USP28 and A437E in ZNF622.

[0132] In some embodiments, the biomarker is a plurality of single nucleotide polymorphisms, such as E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, and TP53 * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * This results in substitutions consisting of R370Q in I987LZNF385B in USP28 and A437E in ZNF622.

[0133] In some embodiments, the biomarker is a plurality of single nucleotide polymorphisms, such as V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, N127S in MSH2, S625F in MSH6, R373Q in SART1, and TP53. * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * This results in substitutions, including I987L in USP28.

[0134] In some embodiments, the biomarker is a plurality of single nucleotide polymorphisms, such as V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, N127S in MSH2, S625F in MSH6, R373Q in SART1, and TP53. * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * This results in a substitution consisting of I987L in USP28.

[0135] In some embodiments, the biomarker is a frameshift mutation selected from the group consisting of K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A.

[0136] In some embodiments, the biomarkers are multiple frameshift mutations, including K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A.

[0137] In some embodiments, the biomarker is a set of frameshift mutations consisting of K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A.

[0138] In some embodiments, the biomarker is an increase or decrease in gene expression in cancer of a gene selected from the group consisting of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue.

[0139] In some embodiments, the biomarkers are multiple increases or decreases in gene expression in cancer, including POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue.

[0140] In some embodiments, the biomarkers are multiple increases or decreases in gene expression in cancer, consisting of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue.

[0141] In some embodiments, the gene is selected from the group consisting of BRCA1, BRCA2, PTEN, ERCC1, and ATM.

[0142] In some embodiments, one or more biomarkers include or consist of BRCA1, BRCA2, PTEN, ERCC1, and ATM.

[0143] The biomarkers used may take various forms, including mutations, insertions, deletions, gene amplification, duplication or rearrangement, promoter methylation, RNA splice variants, SNPs, increased or decreased levels of specific mRNA or proteins, and any other forms of biomolecular mutations. Many cancer biomarkers have been identified in the literature, some of which are useful for predicting which monotherapy or combination therapy is likely to be effective in a given cancer. Any such known biomarker may be used in the methods of the study. The following sentences summarize various biomarkers that have been identified for use in cancer diagnosis. However, the methods of the study are not limited to the specific biomarkers disclosed herein, but may include any biomarkers known in the art. Biomarkers for the use of topoisomerase I inhibitors

[0144] Biomarkers for cancer cell sensitivity or toxicity to topoisomerase I inhibitors may correlate with sensitivity or toxicity to topoisomerase I inhibitory ADCs such as sacituzumab govitecan or DS-1062. Cecthin et al. (2009, J Clin Oncol 27:2457-65) investigated the predictive value of haplotypes in UGT1A1, UGT1A7, and UGT1A9 in patients with metastatic colorectal cancer (mCRC) treated with irinotecan, the parent compound of SN-38. * 28. UGT1A1 * 60, UGT1A1 * 93, UGT1A7 * 3 and UGT1A9 * 22 identified the genotype in 250 mCRC patients (Cectin et al., 2009, J Clin Oncol 27:2457-65). UGT1A7 * Haplotype 3 is the only biomarker for severe hematological and gastrointestinal toxicity after the first cycle of treatment and is associated with glucuronidation of SN-38, while UGT1A1 *28 was the only biomarker associated with progression-free survival (Cecthin et al., 2009, J Clin Oncol 27:2457-65). Other studies have shown that UGT1A1 * 6 and UGT1A1 * It has been concluded that 28 is significantly associated with irinotecan-induced toxicity (Yang et al., 2018, Asia Pac J). Clin Oncol, 14:e479-89). However, the results for these biomarkers are inconsistent (Yang et al., 2018, Asia Pac J). (Clin Oncol, 14:e479-89). UGT1A encodes UDP-glucuronosyltransferase, which inactivates SN-38 by glucuronidation. SN-38 conjugated with sacituzumab govitecan is protected from glucuronidation (Shargey et al., 2015, Clin Cancer). Res 21:5131-8), UGT1A1 biomarkers may not be associated with the toxicity of these ADCs. Ocean et al. (2017, Cancer 123:3843-54)'s trial of sacituzumab govitecan (SG) in the treatment of various epithelial cancers showed that UGT1A1 genotype (specifically UGT1A1) may not be associated with the toxicity of these ADCs. * 28 / UGT1A1 * 28) A very slight but clear correlation between them and the toxicity of SG was evident. In this study, UGT1A1 * 28 / UGT1A1 * Patient 28 did not exhibit dose-limiting toxicity from sacituzumab govitecan.

[0145] P38 is a downstream effector kinase of the DNA damage sensor system, which begins with the activation of ATM, ATR, and DNA-PK (Paillas et al., 2011, Cancer Res 71:1041-9). Elevated levels of activated (phosphorylated) MAPK p38 are associated with resistance to SN-38, and treatment of SN-38-resistant cells with the p38 inhibitor SB202190 enhances the cytotoxic effects of SN-38 (Paillas et al., 2011, Cancer Res 71:1041-9). Primary colon cancer in patients sensitive to irinotecan showed decreased levels of phosphorylated p38 (Paillas et al., 2011, Cancer Res 71:1041-9). The level of phosphorylated p38 may be a biomarker for the use of anti-Trop-2 ADCs, with low levels indicating sensitivity to ADCs and high levels indicating resistance (Paillas et al., 2011, Cancer Res 71:1041-9). Furthermore, p38 inhibitors may be useful in combination therapy with topoisomerase I inhibitory ADCs in resistant tumors.

[0146] Other DDR genes reported to be associated with sensitivity or resistance to topoisomerase I inhibitors include PARP, TDP1, XPF, APTX, MSH2, MLH1, and ERCC1 (Gilbert et al., 2012, Br J Cancer 106:18-24). The same biomarkers may be used to predict sensitivity or resistance to topoisomerase I inhibitory ADCs. Furthermore, inhibitors of each expressed protein may be useful in combination therapy with topoisomerase I inhibitory ADCs.

[0147] Hoskins et al. (2008, Clin Cancer Res 14:1788-96) investigated the effects of genetic variants in CDC45L, NFKB1, PARP1, TDP1, XRCC1, and TOP1 on irinotecan cytotoxicity. SNP markers were identified based on the haplotype composition of subjects from different ethnic groups. Haplotype-tagged SNPs (htSNPs) were used to determine the genotype of irinotecan-treated patients with advanced colorectal cancer (Hoskins et al., 2008, Clin Cancer Res 14:1788-96). htSNPs in the TOP1 gene were associated with grade 3 / 4 neutropenia, and in the TDP1 gene, they were associated with the response to irinotecan (Hoskins et al., 2008, Clin Cancer Res 14:1788-96). The htSNP in TOP1 was located at IVS4+61. The TDP1 SNP was located at IVS12+79 (Hoskins et al., 2008, Clin Cancer Res 14:1788-96). In TOP1 IVS4+61, the G / G genotype showed an incidence of grade 3 / 4 neutropenia at 8%, while the A / A genotype showed an incidence of 50% (small sample size). In TDP1 IVS12+79, the G / G genotype showed a response to irinotecan at 64%, while the T / T genotype showed a response at 25% (Hoskins et al., 2008, Clin Cancer Res 14:1788-96). No significant association was found between genotype and clinical response in XRCC1c.1196G>A.

[0148] Recently, Schlafen 11 (SLFN11) gene expression has been identified as a biomarker of sensitivity to DNA damage repair inhibitors, including topoisomerase I inhibitors (Thomas & Pommier, June 21, 2019, Clin Cancer Res [Epub ahead of print], Ballestrero). (Ballestrero et al., 2017, J Transl Med 15:199). SLFN11 is presumed to be a DNA / RNA helicase associated with resistance to topoisomerase I and II inhibitors, platinum compounds and other DNA damaging agents, as well as antiviral responses (Ballestrero et al., 2017, J Transl Med 15:199). Hypermethylation of SLFN11 (resulting in decreased expression) has been associated with poor prognosis in ovarian cancer and resistance to platinum compounds in lung cancer, while high expression of SLFN11 has been correlated with improved survival rates after chemotherapy in breast cancer (Ballestrero et al., 2017, J Transl Med 15:199). Therefore, the expression level and / or methylation status of SLFN11 in cancer cells can predict sensitivity to topoisomerase inhibitory ADCs alone or in combination with one or more DDR inhibitors.

[0149] A novel phosphorylation site at serine residue 506 in the topoisomerase I sequence has been identified as being absent in normal tissues but widely expressed in cancer, and is associated with increased sensitivity to camptothecin-type topoisomerase I inhibitors (Zhao & Gjerset, 2015, PLoS One 10:e0134929).

[0150] Increased c-Met expression was associated with poor clinical outcomes and resistance to topoisomerase II inhibitors in breast cancer (Jia et al., 2018, Med Sci Monit 24:8239-49). Increased APTX expression has also been reported to be associated with resistance to camptothecin (Gilbert et al., 2012, Br J Cancer 106:18-24).

[0151] These and other biomarkers can predict the toxicity and / or efficacy of topoisomerase I inhibitory ADCs. Biomarkers for sensitivity to PARP inhibitors

[0152] BRCA1 / 2 mutations are known to be sensitive to PARP inhibitors, and it is well known in the art that FDA-approved clinical use of PARP inhibitors such as olaparib in ovarian cancer is intended for the treatment of patients with germline BRCA mutations. The diagnostic and predictive use of BRCA mutations is not limited to ovarian cancer but can also be applied to other cancer types such as TNBC (see, for example, Cardillo et al., 2017, Clin Cancer Res 23:3405-15). Similar mutations have been suggested to exhibit "BRCAness," such as mutations in the CHEK2, NBN, PTEN, and ATM genes (Cardillo et al., 2017, Clin Cancer Res 23:3405-15, Turner et al. 2004, Nat Rev Cancer 4:814-19, Lips et al., 2011, Ann Oncol 22:870-76). Other gene mutations that predispose individuals to PARP1 sensitivity include those in PARB2, BRIP1, BARD1, CDK12, RAD51, and p53 (Bitler et al., 2017, Gynecol Oncol 147:695-704, Lui et al., J Clin Pathol 71:957-62, Weber & Ryan, 2015, Pharmacol Ther 149:124-38). BRCA methylation, which leads to epigenetic silencing, has also been suggested to predispose individuals to PARP inhibitor sensitivity (see, for example, Bitler et al., 2017, Gynecol Oncol 147:695-704). BRCA1 / 2 mutations and silencing occur in approximately 30% of high-grade serous ovarian cancers and often result in reduced HR pathway activity (Bitler et al.). (Cruz et al., 2017, Gynecol Oncol 147:695-704). Other biomarkers for PARPi resistance include FANCD2 overexpression, PARP1 loss, CHD4 loss, SLFN11 inactivation, or loss of 53BP1, REV7 / MAD2L2, PAXIPI / PTIP, or Artemis (Cruz et al., 2018, Ann Oncol 29:1203-10). Furthermore, secondary mutations can restore BRCA1 / 2 function and overcome PARP inhibition (Cruz et al., 2018, Ann Oncol 29:1203-10).

[0153] The impact of altered RAD51 function on PARP resistance has been investigated in BRCA-mutant breast cancer (Cruz et al., 2018, Ann Oncol 29:1203-10). RAD51 is frequently overexpressed in cancer (see, for example, "RAD51" on Wikipedia). As a key protein in the HR pathway, overexpression of RAD51 in gBRCA1 / 2 mutants may partially offset the loss of HR function and reduce sensitivity to PARPi (Cruz et al., 2018, Ann Oncol 29:1203-10). Cruz et al. investigated the mechanism of PARPi resistance in BRCA-mutant breast cancer using exome sequencing and immunostaining of DDR proteins. RAD51 nuclear foci, a surrogate marker of HR function, was the only common feature observed in PARPi-resistant tumors, while low RAD51 expression was associated with an increased response to PARPi (Cruz et al., 2018, Ann Oncol 29:1203-10). These results suggest that the use of PARP inhibitors (PARPi) may be contraindicated by the presence of RAD51 foci, but low RAD51 expression may be a positive biomarker of sensitivity to PARPi. Furthermore, RAD51 inhibitors can be used in combination with PARP inhibitors. No correlation was observed between RAD51 foci and sensitivity to platinum-based chemotherapeutic agents (Cruz et al., 2018, Ann Oncol 29:1203-10).

[0154] The above discussion concerns biomarkers of sensitivity to PARP inhibitors such as olaparib. Therefore, they may be relevant to combination therapy using anti-Trop-2 ADCs and PARP inhibitors. Furthermore, since biomarkers indicate the state of the DDR pathway and may be related to sensitivity to DNA damaging agents such as topoisomerase I inhibitors and corresponding ADCs, any such biomarker may be used to predict sensitivity to ADCs with topoI inhibitors such as SN-38 or DxD. Other biomarkers for sensitivity to anticancer drugs

[0155] p53 mutations, which are commonly found in cancer, have been suggested to make cancer cells more susceptible to inhibitors targeting ATM and / or ATR kinase (Weber & Ryan, 2015, Pharmacol Ther 149:124-38), as well as combination therapies with ATM and PARP inhibitors (Brandsma et al., 2017, Expert Opin Investig Drugs 26:1341-55).

[0156] Sensitivity to the ATR inhibitor AZD6738 was enhanced in ATM-deficient xenografts compared to tumors with ATM function, suggesting that synthetic lethality can be achieved by mutations or inhibitors that block both the ATM and ATR pathways (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). NSCLC tumors deficient in both ATM and p53 showed particular sensitivity to ATR inhibition (Weber & Ryan, 2015, Pharmacol Ther 149:124-38). Synthetic lethality has been observed between the ATM or ATR pathway and the functional loss of several components of DDR, such as the Fanconi anemia pathway, APE1 inhibitors, XRCC1, ERCC1, ERCC4 (XPF), or MRE11A (Weber & Ryan, 2015, Pharmacol Ther 149:124-38; Brandsma et al., 2017, Expert Opin Investig Drugs 26:1341-55). Other deficiencies that increase sensitivity to ATM and / or ATR inhibitors include FANCD2, RAD50, BRCA1, and ATM. These results are associated with combination therapy of DNA damage ADCs with ATM and / or ATR inhibitors. If both the ATM and ATR regulatory pathways are active, the use of anti-Trop-2 ADCs in combination with both ATM and ATR inhibitors may be indicated. If there are mutations in the ATM-regulated DNA repair pathway, combination therapy of ADCs and ATR inhibitors may be indicated. Similarly, mutations in the ATR-modulating pathway may be addressed by using an ADC in combination with an ATM inhibitor. Those skilled in the art will recognize that ATM and ATR catalyze the initial steps of pathways involving the multiple downstream effectors discussed in detail above, and that the use of an ATM or ATR inhibitor may be substituted by an inhibitor of a downstream effector in the same DDR pathway.

[0157] RNAi experiments suggest synthetic lethality for ATR, indicating silencing of ATRIP, RAD17, RAD9A, RAD1, HUS1, POLD1, ARID1A, and TOPBP1, and also sensitized cells to VE821 (Brandsma et al., 2017, Expert Opin Investig Drugs 26:1341-55). Loss of CDC25A function has been suggested to be associated with ATR inhibitor resistance (Brandsma et al., 2017, Expert Opin Investigative Drugs 26:1341-55).

[0158] Biomarkers for DNA-PK inhibitor sensitivity include defects in AKT1, CDK4, CDK9, CHK1, IGFR1, mTOR, VHL, RRM2, MYC, MSH3, BRCA1, BRCA2, ATM, and other HR-related genes (Brandsma et al., 2017, Expert Opin Investig Drugs 26:1341-55).

[0159] p53 mutations have been suggested to indicate increased sensitivity to WEE1 inhibitors or combination therapy with CHK1 inhibitors and DNA damaging agents (Ronco et al., 2017, Med Chem Commun 8:295-319). WEE1 inhibitors are also more effective in cells with low PKMYT1 expression, as well as in cells with mutations in FANCC, FANCG, and BRCA2 (Brandsma et al., 2017, Expert Opin Investig Drugs 26:1341-55).

[0160] Nadaraja et al. (Sep 3, 2019, Acta Oncol, [Epub ahead of print]) investigated changes in the transcriptome profile of patients with high-grade serous carcinoma (HGSC) receiving first-line platinum-based therapy. They detected mRNA changes using gene expression arrays, while simultaneously examining the protein expression of selected biomarkers by IHC (Nadaraja et al., Sep 3, 2019, Acta Oncol [Epub ahead of print]). ARAP1 (ankyrin repeat and PH domain 1) expression was significantly lower in early-stage patients compared to late-stage patients. ARAP1 expression was identified in 64.7% of early-stage patients, with a sensitivity of 78.6% (Nadaraja et al., Sep 3, 2019, Acta Oncol [Epub ahead of print]). These results suggest that ARAP1 expression indicates sensitivity to platinum-based anticancer drugs and can be used to predict sensitivity to other DNA damaging agents such as topoisomerase I inhibitory ADCs.

[0161] A similar study was conducted by Ilelis et al. (2018, Pathol Res Pract 214:187-94), which used ICH to examine the expression of GRIM-19, NF-κB, and IKK2 in HGSC patients treated with platinum-based chemotherapy. High IKK2 and NF-κB expression was associated with poor survival and resistance to platinum-based agents, while high GRIM-19 expression predicted longer disease-free survival and was not associated with relapse. GRIM-19 expression may be a useful biomarker for sensitivity to platinum-based therapies and potentially other DNA damage treatments such as topoisomerase I inhibitory ADCs.

[0162] Miao et al. (2019, Cell Mol biol 65:64-72) used quantitative PCR to determine cfDNA levels in breast cancer patients compared to benign and normal samples. Plasma CEA, CA125, and CA15-3 were also determined. cfDNA concentration and integrity were significantly higher in breast cancer patients than in the control group, and both biomarkers were significantly reduced after chemotherapy. (65:64-72). The sensitivity and specificity of cfDNA analysis were significantly higher than those of conventional tumor biomarkers (Miao et al., 2019, Cell Mol biol 65:64-72). Therefore, in addition to examining specific biomarkers in cfDNA, the level of total cfDNA in serum may serve as a biomarker for the presence of cancer and the effectiveness of anti-cancer therapy.

[0163] Faltas et al. (2016 Nat Genet 48:1490-99) reported that mutations in L1CAM (L1-cell adhesion molecule) are involved in chemotherapy resistance (e.g., cisplatin resistance) in metastatic urothelial carcinoma. The majority of these were missense mutations. The analysis was performed using whole exome sequencing, which analyzed 21,522 genes, including 250 target oncogenes.

[0164] These and other known biomarkers can be used to predict the sensitivity, resistance, or toxicity of ADCs used in cancer treatment, either alone or in combination with other anticancer agents. Those skilled in the art will know that such biomarkers may also have other applications, such as improving diagnostic accuracy, personalizing patient treatment (precision medicine), confirming prognosis, predicting treatment outcomes and recurrence, monitoring disease progression, and / or identifying early recurrence from cancer therapy. kit

[0165] Various embodiments may involve kits containing components suitable for treating a patient's affected tissue. An exemplary kit may contain at least one antibody or ADC described herein. The kit may also contain drugs such as DDR inhibitors or other known anticancer agents. If the composition containing the components for administration is not formulated for delivery via the gastrointestinal tract, for example by oral delivery, a device capable of delivering the kit components through several other routes may be included. One type of device for applications such as parenteral delivery is a syringe used to inject the composition into the body of the subject. Inhalation devices may also be used.

[0166] The kit components may be packaged together or separated into two or more containers. In some embodiments, the containers may be vials containing a sterile, lyophilized formulation of a composition suitable for redissolution. The kit may also contain one or more buffers suitable for redissolution and / or dilution of other drugs. Other containers that may be used include, but are not limited to, pouches, trays, boxes, and tubes. The kit components may be packaged and maintained in a sterile manner within the containers. Another component that may be included is an instruction manual for the person using the kit. Additional exemplary embodiments

[0167] In one embodiment, a method for treating Trop-2-expressing cancer is provided herein, comprising: a) assaying a sample derived from a human subject having Trop-2-expressing cancer for the presence of one or more cancer biomarkers; b) detecting one or more biomarkers associated with sensitivity to an anti-Trop-2 antibody-drug conjugate (ADC); and c) treating the subject with an anti-Trop-2 ADC comprising an anti-Trop-2 antibody conjugated to a topoisomerase I inhibitor. In some embodiments, the method further comprises: d) detecting one or more biomarkers associated with sensitivity to combination therapy of an anti-Trop-2 ADC and a DDR inhibitor; and e) treating the subject with a combination of an anti-Trop-2 ADC and a DDR (DRA damage repair) inhibitor.

[0168] In another aspect, a method of selecting a patient to be treated with an anti-Trop-2 antibody-drug conjugate (ADC) is provided herein, the method comprising: a) analyzing a sample from a human cancer patient for the presence of one or more cancer biomarkers; b) detecting one or more biomarkers associated with the sensitivity or toxicity of the anti-Trop-2 ADC; c) selecting a patient to be treated with the anti-Trop-2 ADC based on the presence of the one or more biomarkers; and d) treating the selected patient with the anti-Trop-2 ADC. In some embodiments, the method further comprises: e) selecting a patient to be treated with a combination therapy based on the presence of the one or more biomarkers; and f) treating the patient with a combination of the anti-Trop-2 ADC and a DDR inhibitor.

[0169] In some embodiments, the anti-Trop-2 ADC is administered to the patient as a neoadjuvant therapy prior to the administration of at least one other anti-cancer therapy.

[0170] In some embodiments, the method further comprises: e) monitoring the patient for the presence of the one or more biomarkers; and f) determining the cancer response to the treatment.

[0171] In some embodiments, the method further comprises monitoring the patient's residual disease or recurrence based on biomarker analysis.

[0172] In some embodiments, the method further comprises determining the prognosis of the disease outcome or progression based on biomarker analysis.

[0173] In some embodiments, the method further comprises selecting an optimized individualized therapy for the patient based on biomarker analysis.

[0174] In some embodiments, the method further comprises classifying the cancer stage based on biomarker analysis.

[0175] In some embodiments, the method further includes stratifying the patient population for initial treatment based on biomarker analysis.

[0176] In some embodiments, the method further includes recommending supportive therapies to improve side effects of ADC treatment based on biomarker analysis.

[0177] In some embodiments, the sample is a biopsy sample derived from a solid tumor.

[0178] In some embodiments, the sample is a liquid cytological sample.

[0179] In some embodiments, the sample includes cfDNA, ctDNA, or circulating tumor cells (CTCs).

[0180] In some embodiments, the sample contains cytotoxic cephalocarcinoma (CTC), which is analyzed for the presence of one or more cancer biomarkers.

[0181] In some embodiments, the biomarker is a genetic marker in a DNA damage repair (DDR) gene or an apoptotic gene.

[0182] In some embodiments, the gene is selected from the group consisting of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2.

[0183] In some embodiments, the biomarkers include or consist of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NDRG1, WEE1, PPP1R15A, MYBBP1A, SIRT1, ABL1, HRAS, ZNF385B, POLR2K, and DDB2.

[0184] In some embodiments, the biomarkers include or consist of AEN, MSH2, MYBBP1A, SART1, SIRT1, USP28, CDKN1A, ABL1, TP53, BAG6, BRCA1, BRCA2, BRSK2, CHEK2, ERN1, FHIT, HIPK2, HRAS, LGALS12, MSH6, ZNF385B, and ZNF622.

[0185] In some embodiments, the biomarkers include or consist of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, and USP28.

[0186] In some embodiments, the biomarkers include or consist of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A.

[0187] In some embodiments, the biomarkers include or consist of GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A.

[0188] In some embodiments, the biomarkers include or consist of BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A, BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28, GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A.

[0189] In some embodiments, the gene is selected from the group consisting of BRCA1, BRCA2, PTEN, ERCC1, and ATM.

[0190] In some embodiments, the biomarkers include or consist of BRCA1, BRCA2, PTEN, ERCC1, and ATM.

[0191] In some embodiments, the biomarker is a single nucleotide polymorphism, such as E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, and TP53 * 394S, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 in TP53 * This results in a substitution mutation selected from the group consisting of R370Q in I987LZNF385B within USP28 and A437E in ZNF622.

[0192] In some embodiments, the biomarker is a plurality of single nucleotide polymorphisms, including E155K in ABL1, G706S in ABL1, V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, G12V in HRAS, A278V in LGALS12, N127S in MSH2, S625F in MSH6, H680Y in MYBBP1A, R373Q in SART1, E113Q in SIRT1, * 394S in TP53, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 * in TP53, I987L in USP28, R370Q in ZNF385B, and A437E in ZNF622, which result in substitutions or consist of these.

[0193] In some embodiments, the biomarker is a plurality of single nucleotide polymorphisms, including V172L in AEN, R279Q in BAG6, P1020Q in BRCA1, E255K in BRCA1, L2518V in BRCA2, T656A in BRSK2, M1V in CDKN1A, A377D in CHECK2, G771S in ERN1, R46S in FHIT, E457Q in HIPK2, N127S in MSH2, S625F in MSH6, R373Q in SART1, * 394S in TP53, R282G in TP53, T377P in TP53, E271K in TP53, Y220C in TP53, E180 * in TP53, and I987L in USP28, which result in substitutions or consist of these.

[0194] In some embodiments, the biomarker is a frameshift mutation selected from the group consisting of K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A.

[0195] In some embodiments, the biomarker is a plurality of frameshift mutations including or consisting of K1110fs in BAG6, R32fs in CDKN1A, DC33fs in CDKN1A, and EG60fs in CDKN1A.

[0196] In some embodiments, the biomarker is an increase or decrease in gene expression in cancer of a gene selected from the group consisting of POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue.

[0197] In some embodiments, the biomarker is a combination of multiple increases or decreases in gene expression in cancer, including or comprising POLR2K, DDB2, GADD45B, WEE1, TGFB1, NDRG1, and PPP1R15A, compared to the corresponding normal tissue.

[0198] In some embodiments, the gene is selected from the group consisting of BRCA1, BRCA2, PTEN, ERCC1, and ATM.

[0199] In some embodiments, the biomarkers include or consist of BRCA1, BRCA2, PTEN, ERCC1, and ATM.

[0200] In some embodiments, the biomarker is selected from the group consisting of mutations, insertions, deletions, chromosomal rearrangements, SNPs (single nucleotide polymorphisms), DNA methylation, gene amplification, RNA splice variants, miRNAs, increased gene expression, decreased gene expression, protein phosphorylation, and protein dephosphorylation.

[0201] In some embodiments, the sample assay includes next-generation sequencing of DNA or RNA.

[0202] In some embodiments, the topoisomerase I inhibitor is SN-38 or DxD.

[0203] In some embodiments, the anti-Trop-2 ADC is selected from the group consisting of sacituzumab govitecan and DS-1062.

[0204] In some embodiments, the DDR inhibitors are 53BP1, APE1, Artemis, ATM, ATR, ATRIP, BAP1, BARD1, BLM, BRCA1, BRCA2, BRIP1, CDC2, CDC25A, CDC25C, CDK1, CDK12, CHK1, CHK2, CSA, CSB, CtIP, Cyclin B, Dna2, DNA-PK, EEPD1, EME1, ERCC1, ERCC2, ERCC3, ERCC4, Exo1, FAAP24, FANC1, FANCM, FAND2, HR23B, HUS1, KU70, KU80, Lig These are inhibitors of III, ligase IV, Mdm2, MLH1, MRE11, MSH2, MSH3, MSH6, MUS81, MutSα, MutSβ, NBS1, NER, p21, p53, PALB2, PARP, PMS2, Polμ, Polβ, Polδ, Polε, Polκ, Polλ, PTEN, RAD1, RAD17, RAD23B, RAD50, RAD51, RAD51C, RAD52, RAD54, RAD9, RFC2, RFC3, RFC4, RFC5, RIF1, RPA, SLX1, SLX4, TopBP1, USP11, WEE1, WRN, XAB2, XLF, XPA, XPC, XPD, XPF, XPG, XRCC1, or XRCC4.

[0205] In some embodiments, the DDR inhibitor is an inhibitor of PARP, CDK12, ATR, ATM, CHK1, CHK2, CDK12, RAD51, RAD52, or WEE1.

[0206] In some embodiments, the PARP inhibitor is selected from the group consisting of olaparib, talazoparib (BMN-673), lucaparib, veliparib, niraparib, CEP 9722, MK 4827, BGB-290 (pamiparib), ABT-888, AG014699, BSI-201, CEP-8983, E7016, and 3-aminobenzamide.

[0207] In some embodiments, the CDK12 inhibitor is selected from the group consisting of dinaciclib, flavopridol, roscovitine, THZ1, and THZ531.

[0208] In some embodiments, the RAD51 inhibitor is selected from the group consisting of B02((E)-3-benzyl-2(2-(pyridine-3-yl)vinyl)quinazoline-4(3H)-one), RI-1(3-chloro-1-(3,4-dichlorophenyl)-4-(4-morpholinyl)-1H-pyrrole-2,5-dione), DIDS(4,4'-diisothiocyanostilbene-2,2'-disulfonic acid), halenaquinone, CYT-0851, IBR2, and imatinib.

[0209] In some embodiments, the ATM inhibitor is selected from the group consisting of Waltmannin, CP-466722, KU-55933, KU-60019, KU-59403, AZD0156, AZD1390, CGK733, NVP-BEZ 235, Torin-2, Fluoroquinoline 2, and SJ573017.

[0210] In some embodiments, the ATR inhibitor is selected from the group consisting of cisandrin B, NU6027, BEZ235, ETP46464, Torin 2, VE-821, VE-822, AZ20, AZD6738 (ceraracertib), M4344, BAY1895344, BAY-937, AZD6738, BEZ235 (dactricib), CGK 733, and VX-970.

[0211] In some embodiments, the CHK1 inhibitor is selected from the group consisting of XL9844, UCN-01, CHIR-124, AZD7762, AZD1775, XL844, LY2603618, LY2606368 (prexacertib), GDC-0425, PD-321852, PF-477736, CBP501, CCT-244747, CEP-3891, SAR-020106, Arry-575, SRA737, V158411, and SCH 900776 (MK-8776).

[0212] In some embodiments, the CHK2 inhibitor is selected from the group consisting of NSC205171, PV1019, CI2, CI3, 2-arylbenzimidazole, NSC109555, VRX0466617, and CCT241533.

[0213] In some embodiments, the WEE1 inhibitor is selected from the group consisting of AZD1775 (MK1775), PD0166285, and PD407824.

[0214] In some embodiments, the DDR inhibitor is selected from the group consisting of mirin, M1216, NSC19630, NSC130813, LY294002, and NU7026.

[0215] In some embodiments, the DDR inhibitor is not an inhibitor of PARP or RAD51.

[0216] In some embodiments, the anti-Trop-2 antibody moiety comprises an hRS7 antibody containing the light chain CDR sequences CDR1(KASQDVSIAVA, SEQ ID NO: 1), CDR2(SASYRYT, SEQ ID NO: 2), and CDR3(QQHYITPLT, SEQ ID NO: 3), as well as the heavy chain CDR sequences CDR1(NYGMN, SEQ ID NO: 4), CDR2(WINTYTGEPTYTDDFKG, SEQ ID NO: 5), and CDR3(GGFGSSYWYFDV, SEQ ID NO: 6).

[0217] In some embodiments, the method involves olaparib, lucaparib, talazoparib, veliparib, niraparib, acalabrutinib, temozolomide, atezolizumab, pembrolizumab, nivolumab, ipilimumab, pizilizumab, durvalumab, BMS-936559, BMN-673, tremelimumab, idelalisib, imatinib, ibrutinib, eribulin mesylate, abemaciclib, palbociclib, ribociclib, trilaciclib, bezocertib, ipatasertib, uprosertib, afrecertib, trisilibine, ceraracertib, dinacyclib, flavopyritol, roscovitine, G1T38, SHR6390, copanlisib, temsirolimus, everolimus, KU 60019, KU 55933, KU 59403, AZ20, AZD0156, AZD1390, AZD1775, AZD2281, AZD5363, AZD6738, AZD7762, AZD8055, AZD9150, BAY-937, BAY1895344, BEZ235, CCT241533, CCT244747, CGK 733, CID44640177, CID1434724, CID46245505, CHIR-124, EPT46464, FTC, VE- 821, VRX0466617, VX-970, LY294002, LY2603618, M1216, M3814, M4344, M6620 , MK-2206, NSC19630, NSC109555, NSC130813, NSC205171, NU6027, NU7026, Prexasertib (LY2606368), PD0166285, PD407824, PV1019, SCH900776, SRA737, BMN The treatment further includes treating the subject with an anticancer agent selected from the group consisting of 673, CYT-0851, mirin, Torin-2, fluoroquinoline 2, fumitremorgin C, curcumin, Kol43, GF120918, YHO-13351, YHO-13177, XL9844, woltmannin, lapatinib, sorafenib, sunitinib, nilotinib, gemcitabine, bortezomib, trichostatin A, paclitaxel, cytarabine, cisplatin, oxaliplatin, and carboplatin.

[0218] In some embodiments, the cancer is selected from the group consisting of breast cancer, triple-negative breast cancer (TNBC), HR+ / HER2-metastatic breast cancer, urothelial carcinoma, small cell lung cancer (SCLC), non-small cell lung cancer (NSCLC), colorectal cancer, gastric cancer, bladder cancer, kidney cancer, ovarian cancer, uterine cancer, endometrial cancer, cervical cancer, prostate cancer, esophageal cancer, pancreatic cancer, brain cancer, liver cancer, and head and neck cancer. In some embodiments, the cancer is urothelial carcinoma. In some embodiments, the cancer is metastatic urothelial carcinoma. In some embodiments, the cancer is treatment-resistant urothelial carcinoma. In some embodiments, the cancer is resistant to treatment with platinum-based and checkpoint inhibitor (CPI) (e.g., anti-PD1 antibody or anti-PD-L1 antibody) therapies. In some embodiments, the cancer is metastatic TNBC.

[0219] In another embodiment, the present invention provides a method for predicting clinical outcomes in a subject with Trop-2-expressing cancer after treatment with an anti-Trop-2 ADC, comprising assaying a sample from a human subject having Trop-2-expressing cancer for the presence of one or more cancer biomarkers, wherein the presence or absence of one or more cancer biomarkers predicts the clinical outcome in the subject.

[0220] In some embodiments, the presence or absence of one or more cancer biomarkers predicts the efficacy of treatment with an anti-Trop-2 ADC, and the ADC includes a topoisomerase I inhibitor.

[0221] In some embodiments, the presence or absence of one or more cancer biomarkers predicts the efficacy or safety of combination therapy with anti-Trop-2 ADCs and DDR inhibitors.

[0222] In some embodiments, the presence or absence of one or more cancer biomarkers predicts the efficacy or safety of combination therapy with anti-Trop-2 ADCs and standard anticancer therapy.

[0223] In some embodiments, the method further includes predicting relapse-free survival, overall survival, disease-free survival, or long-term relapse-free survival after treatment with an anti-Trop-2 ADC. [Examples]

[0224] Various embodiments of the present invention are illustrated by the following examples, without limiting their scope. Example 1. Sacituzumab govitecan and biomarkers for sensitivity in treatment-resistant metastatic urothelial carcinoma (mUC). summary

[0225] Patients with metastatic urothelial carcinoma (mUC) that has progressed after platinum-based and checkpoint inhibitor (CPI) therapy have limited treatment options. Sacituzumab govitecan is an antibody-drug conjugate (ADC) containing a humanized monoclonal anti-Trop-2 antibody conjugated to the cytotoxic agent SN-38. A phase I / II single-arm, multicenter trial (NCT01631552) evaluated the safety and activity of sacituzumab govitecan in previously treated mUC that had progressed after one or more prior systemic therapies.

[0226] Patients received intravenous sacituzumab govitecan (10 mg / kg) on ​​days 1 and 8 of a 21-day cycle until disease progression or unacceptable toxicity occurred. Endpoints included safety, investigator-assessed objective response rate (ORR according to RECIST 1.1), clinical benefit rate, duration of response (DOR), progression-free survival (PFS), and overall survival (OS). Differentially mutated and expressed gene and pathway sequencing analysis was performed in subsets of responder and non-responder tumors.

[0227] Forty-five patients treated with the recommended phase 2 dose were enrolled (median age, 67 [range: 49-90] years; male, 91%; median number of prior treatments, 2 [range: 1-6]; ECOG PS score 1, 69%; visceral metastases, 73% [liver metastases, 33%]), and received one or more doses of sacituzumab govitecan. The overall response rate (ORR) was 31% (14 / 45; 2 complete responses, 12 partial responses). The median duration of treatment (DOR) was 12.9 months, progression-free survival (PFS) was 7.3 months, and overall survival (OS) was 16.3 months. The ORR was 33% (5 / 15) in patients with liver metastases, 24% (4 / 17) in patients with prior CPI treatment (median 3 prior treatments), and 27% (4 / 15) in patients with prior CPI and platinum therapy. The most frequent grade ≥3 adverse events were neutropenia (38%), anemia (13%), hypophosphatemia (11%), diarrhea (9%), fatigue (9%), and febrile neutropenia (7%). Tumor sequencing of responders showed enrichment of DNA repair and apoptotic pathway molecules.

[0228] Based on the results of the studies reported herein, it was concluded that sacituzumab govitecan exhibits significant clinical activity in resistant mUC, with manageable toxicity. Introduction

[0229] Patients with metastatic urothelial carcinoma (mUC) that have progressed after platinum-based chemotherapy and immune checkpoint inhibitor (CPI) therapy have a poor outcome and limited treatment options (Di Lorenzo et al., 2015, Medicine (Baltimory) 94:e2297, Vlachostergios et al., 2018, Bladder Cancer 4:247-59). The treatment landscape for mUC has recently expanded with the approval of several CPIs (checkpoint inhibitors) for chemotherapy-resistant mUC. However, only about 15% to 21% of patients respond to these drugs (Vlachostergios et al., 2018, Bladder Cancer 4:247-59, Bellmunt et al., 2017, N Eng J Med 37:1015-26, Patel et al.,2018, Lancet Oncol 19:51-64, Powles et al.,2017, JAMA Oncol 3:e172411, Rosenberg et al.,2016, Lancet 387:1909-20). Patients whose disease has progressed with CPI currently have no approved treatment options (Di Lorenzo et al., 2015, Medicine (Baltimore) 94:e2297, Bellmunt et al., 2017, N Eng J Med 37:1015-26). The development of effective regimens to address these patients remains an urgent and unmet need.

[0230] Sacituzumab govitecan is a novel antibody-drug conjugate (ADC) that targets trophoblast cell surface antigen 2 (Trop-2) (Goldenberg et al., 2015, Oncotarget 6:22496-512). Trop-2 is a transmembrane calcium signaling molecule that is highly expressed in most epithelial cancers (Trerotola). et al.,2013,Oncogene 32:222-33;Avellini et al.,2017,Oncotarget 8:58642-53;Shvartsur & Bonavida,2015,Genes Cancer 6:84-105;Stepan et al.,2011,J Histochem Cytochem 59:701-10;Goldenberg et al.,2018,Oncotarget 9:28989-29006). Elevated Trop-2 expression plays a crucial role in cell transformation and proliferation, associated with poor prognosis, and is expressed more highly in metastatic diseases than in early-stage diseases (Trerotola et al., 2013, Oncogene 32:222-33; Avellini et al., 2017, Oncotarget 8:58642-53; Shvartsur & Bonavida, 2015, Genes Cancer 6:84-105; Stepan et al., 2011, J Histochem Cytochem 59:701-10; Goldenberg et al., 2018, Oncotarget 9:28989-29006).

[0231] Sacituzumab govitecan consists of the anti-Trop-2 humanized monoclonal antibody hRS7 IgG1κ, conjugated to SN-38, the active metabolite of the topoisomerase 1 inhibitor irinotecan (Goldenberg et al., 2018, Oncotarget 9:28989-29006). This coupling is achieved using a unique hydrolyzable CL2A linker (Goldenberg et al., 2015, Oncotarget 6:22496-512; Goldenberg et al., 2018, Oncotarget 9:28989-29006; Cardillo et al., 2011, Clin Cancer Res 17:3157-69; Cardillo et al., 2015, Bioconjug Chem 26:919-31; Starodub et al., 2015, Clin Cancer Res 21:3870-78). Sacituzumab govitecan is a novel ADC with a much higher drug-to-antibody ratio than other ADCs (up to 8 molecules of SN-38 per antibody), which generally have a ratio of 2:1 to 4:1 (Goldenberg et al., 2018, Oncotarget 9:28-989-29006; Challitia et al., 2016, Cancer Res 76:3003-13). After binding to Trop-2, hRS7 (free or conjugated) is internalized to deliver SN-38 into tumor cells (Cardillo et al., 2011, Clin Cancer Res 17:3157-69). The unique hydrolytic linker of sacituzumab govitecan also allows for the release of SN-38 into the tumor microenvironment. This allows tumor cells bound to sacituzumab govitecan to be killed by the intracellular uptake of SN-38, and because SN-38 easily passes through the cell surface membrane of very close cells, adjacent tumor cells are killed by the extracellularly released SN-38 (Goldenberg et al., 2018, Oncotarget 9:28989-29006; Cardillo et al., 2015, Bioconjug Chem 26:919-31; Starodub et al., 2015, Clin Cancer Res 21:3870-78).

[0232] The safety and efficacy of sacituzumab govitecan were first evaluated in a phase I / II basket-design, open-label, single-arm, multicenter trial (IMMU-132-01, NCT01631552) in patients with advanced epithelial cancer who had received at least one prior treatment for metastatic disease (Starodub et al., 2015, Clin Cancer Res 21:3870-78, Ocean et al., 2017, Cancer 123:3843-54). This trial reported favorable clinical activity in four cancer types: triple-negative and hormone receptor-positive / HER2-negative breast cancer (Bardia et al., 2017, J Clin Oncol 35:2141-48, Bardia et al., 2019, N Engl J Med 380:741-51, Bardia et al., 2018, J Clin Oncol 36(suppl):1004), previously treated small cell lung cancer (Gray et al., 2017, Clin Cancer Res 23:5711-19), and non-small cell lung cancer (Heit et al., 2017, J Clin Oncol 35:2790-97). Furthermore, Faltas's team reported initial results from the Phase I part of the trial in mUC patients (Faltas et al., 2016, Clin Genitourin Cancer 14:e75-9). This specification reports on the safety and efficacy findings of sacituzumab govitecan in previously treated patients with mUC. Materials and methods

[0233] Patients enrolled were eligible patients aged 18 years or older with histologically confirmed mUC that had relapsed or been refractory after at least one previous standard treatment regimen. All patients had metastatic disease measurable by Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST 1.1) at enrollment. Patients were required to have an expected survival of 6 months or more, and an Eastern Cooperative Oncology Group (ECOG) performance status of 0-1 with adequate hepatic, renal, and hematological function. Patients had to have been at least 2 weeks post-treatment, including chemotherapy, high-dose systemic corticosteroids, or major surgery, and all acute toxicity (except alopecia) had to have recovered to grade 1 or lower. Patients with stable brain metastases may be included only if they had been at least 2 weeks post-treatment with high-dose steroids. Prior selection of patients based on tumor Trop-2 expression was not required.

[0234] Study Design – Based on data from the Phase I part of previously reported studies and the initial safety data from the Phase II part of this study, sacituzumab govitecan at a dose of 10 mg / kg was determined to be the maximum tolerated dose (Starodub et al., 2015, Clin Cancer Res 21:3870-8; Ocean et al., 2017, Cancer 123:3843-54). Sacituzumab govitecan was administered intravenously without premedication on days 1 and 8 of every 21 days of a 3-week treatment cycle, until unacceptable toxicity occurred or disease progression occurred. Hematopoietic growth factors or blood transfusions were permitted at the discretion of the principal investigator, but not before the first dose. Other supportive therapies (antiemetics, antidiarrheals, or bone stabilizers) were permitted as medically necessary.

[0235] The primary objectives of the Phase I and Phase II parts of the study were to determine the maximum tolerated dose of sacituzumab govitecan and to evaluate its safety and efficacy, respectively. Additional secondary objectives included pharmacokinetic and immunogenicity evaluations, as previously reported by the Ocean team (Ocean et al., 2017, Cancer 123:3843-54). Safety evaluations included adverse events (AEs), serious adverse events (SAEs), laboratory safety assessments, vital signs, physical examinations, and 12-lead electrocardiograms (ECGs; performed at baseline, after completion of infusion on day 1 of each even-numbered treatment cycle, at the end of treatment, and at the end of the study). AEs were assessed according to version 4.0 of the National Cancer Institute Common Terminology Criteria for Adverse Events.

[0236] CT / magnetic resonance imaging (MRI) scans for disease staging were performed at baseline and at 8-week intervals from the start of treatment until disease progression requiring discontinuation. Confirmatory CT / MRI scans were performed immediately 4 weeks after the first partial response (PR) or complete response (CR). Subsequent scans were performed at 8-week intervals after the confirmatory scan. Patients with clear clinical benefit were permitted to receive treatment after disease progression. Responses were assessed by the investigator using RECIST, version 1.1. Efficacy endpoints included objective response rate (ORR), time to response, duration of response (DOR), clinical benefit rate (CBR; defined as CR, PR, or stable for 6 months or more), progression-free survival (PFS), and overall survival (OS).

[0237] Biomarker Analysis – To gain a fundamental biological understanding of the response to sacituzumab govitecan, whole exome sequencing (WES) and RNA sequencing (RNAseq) were performed on available tumors of responders and non-responders under protocols with written informed consent separately approved by the Institutional Review Board. Differentially mutated and expressed genes and pathways were analyzed between responders and non-responders, focusing on molecular changes in pathways involved in mediating the cytotoxic effect of SN-38, the active portion of sacituzumab govitecan. Single-sample gene set enrichment analysis (GSEA) was performed on each tumor to determine the cellular processes mediating the response to sacituzumab govitecan.

[0238] Fresh, frozen, formalin-fixed, paraffin-embedded (FFPE) specimens were retrospectively collected from surplus preserved tissue of stored primary (TURBT, cystectomy) and metastatic (core biopsy) specimens from 14 patients with a diagnosis of urothelial carcinoma enrolled in the WCM-NYP study. All tumor specimens consisted of conventional UC. All pathological specimens were reviewed and reported by qualified urological pathologists in the WCM / NYP pathology department.

[0239] DNA Extraction and Whole Exome Sequencing - The whole exome sequencing (WES) protocol used in this study has been previously discussed (Di Lorenzo et al., 2015, Medicine (Baltimore) 94:e2297, Vlachostergios et al., 2018, Bladder Cancer 4:247-59). After macrodissection of the target lesion, tumor DNA was extracted from FFPE or core-supported OCT cryopreserved tumors using Promega Maxwell® 16 MDx (Promega (Madison, WI, USA)). Germline DNA was extracted from normal tissue adjacent to the tumor using the same method. The diagnosed and determined tumor contents were confirmed by a pathological review by one WCM / NYP pathologist. A minimum of 200 ng of DNA was used for WES. DNA quality was determined by TapeStation Instrument (Agilent Technologies (Santa Clara, CA)) and confirmed by real-time PCR before sequencing. Sequencing was performed using an Illumina HiSeq 2500 (2×100bp). A total of 21,522 genes were analyzed using Agilent HaloPlex Exome (Agilent Technologies (Santa Clara, CA)) with an average coverage of 85×.

[0240] Whole exome sequencing data processing pipeline - All sample data was processed using the computer analysis pipeline (IPM-Exome-pipeline) at the Institute for Precision Medicine, Weill Cornell, New York Presbyterian Hospital (Vlachostergios et al., 2018, Bladder Cancer 4:247-59). Raw read quality was assessed using FASTQC and aligned to the GRCh37 human reference genome (Vlachostergios et al., 2018, Bladder Cancer 4:247-59). Pipeline output includes segment DNA copy number data, somatic copy number anomalies (CNAs), and putative somatic single nucleotide variants (SNVs).

[0241] Single-nucleotide variants—To improve the accuracy of these calls, a consensus somatic cell SNV calling pipeline was developed. SNVs were identified in paired tumor-normal samples using MuTect2, Strelka, VarScan, and SomaticSniper, and only SNVs identified by at least two variant callers were retained. Indels (insertions or deletions) were identified using Strelka and VarScan, and only those identified by both tools were retained. Identified somatic variants were further screened using the following criteria: (a) read depth of ≥10 reads in both tumor and matched normal samples, (b) variant allele frequency (VAF) of ≥5% in tumor samples and more than 3 reads with a variant allele, (c) VAF of ≤1% or only 1 read with a variant allele in matched normal samples. Variants were annotated using Oncotator (version 1.9), and dbSNPs during variant calling were excluded unless they were also found in the COSMIC database. For IPM samples, random mutation calls pre-identified internally as Haloplex artifacts were also excluded from the final list of mutations. Fisher's direct test was applied to a matrix of mutation and wild-type phenotype gene counts in responders and non-responders for a given pathway to determine whether that pathway was enriched in either of the two patient response groups. Oncoprints were generated for selected mutations using the "ComplexHeatmap" Bioconductor R package.

[0242] RNA extraction, RNA sequencing, and data analysis - Promega Maxwell® 16 MDx instrument (Maxwell® 16 RNA was extracted from frozen material for RNA sequencing (RNA-seq) using the LEV simplyRNA Tissue Kit. Samples were prepared for RNA sequencing using the TruSeq RNA Library Preparation Kit v2 or riboZero®. RNA integrity was verified using Agilent Bioanalyzer 2100 (Agilent Technologies). cDNA was synthesized from total RNA using Superscript® III (Invitrogen). Sequencer was then performed using GAII, HiSeq2000, or HiSeq2500. All reads were independently aligned to the human genome sequence build GRCh37 downloaded via the UCSC Genome Browser using STAR_2.4.0fl (Bellmunt et al., 2017, N Eng J Med 37:1015-26) for sequence alignment, and SAMTOOLS v0.1.19 (Patel et al., 2018, Lancet Oncol 19:51-64) for read classification and indexing. The number of reads mapped to each transcript was quantified as counts using HTSeq-count software. The corrected transcript volume was quantified as fragments per exon kb (FPKM) per 1 million mapped fragments using Cufflinks (2.0.2) (Powles et al., 2017, JAMA Oncol 3:e172411) along with annotated GTF files from GENCODE v23 (Rosenberg et al., 2016, Lancet 387:1909-20). RStudio (1.0.136) with R (v3.3.2) and ggplot2 (2.2.1) was used for statistical analysis and figure generation.

[0243] Quantification, integration, and expression analysis of RNA-seq data: mRNA gene expression from 17 UC tumors was quantified as fragments per kilobase of transcript (FPKM) per million transcripts. FPKM values ​​were logarithmically transformed for further analysis. Differential gene expression (DGE) between responder and non-responder tumors was performed on counting data using the Bioconductor package DESeq2. Thresholds for selecting differentially regulated genes were determined by a multiplier change of >2 for upregulated genes and <-2 for downregulated genes, and results were considered significant with an adjusted p-value of 0.05 (Benjamini-Hochberg corrected).

[0244] Gene set enrichment analysis—differential gene expression (DGE) analysis—was performed on RNA-seq counts using the Bioconductor R package DESeq. Genes differentially expressed between responder and non-responder patient groups were identified (upward regulation in responders: log-fold change (LFC) > 2, downward regulation in responders: log-fold change <-2, adjusted p-value < 0.001) and visualized in a heatmap using the "pheatmap" package in R. Pre-ranked gene set enrichment analysis (GSEA) was applied to a ranking list of all genes, ranked by LFC values ​​obtained from DGE analysis. Molecular The gene set available through Gene Ontology Biological Pathways, collected in the Signature Database (Goldenberg et al., 2015, Oncotarget 6:22496-512), was used for GSEA analysis. Two key pathways from the GSEA analysis, namely HALLMARK_P53_PATHWAY and HALLMARK_APOPTOSIS (FDR<0.10), were further analyzed to obtain individual pathway enrichment scores for each sample using single-sample GSEA (ssGSEA), which were then implemented in RNAseq FPKM using the "gsva" R package. The p-value was obtained by Mann-Whitney U test applied between the responder and non-responder patient groups.

[0245] Statistical Analysis - The efficacy and safety analyses reported herein include all patients who received at least one dose of sacituzumab govitecan at a dose level of 10 mg / kg, regardless of enrollment in the Phase I or Phase II part of the trial, and include 45 patients enrolled between September 2014 and June 2017. The data cutoff date for this analysis was September 1, 2018. ORR and CBR were calculated using the Clopper-Pearson method (Clopper & The 95% confidence intervals were calculated along with those estimated by Pearson (1934, Biometrika 26:404-13). PFS, OS, and time to event were analyzed using the Kaplan-Meier method, and the median and corresponding 95% confidence intervals were determined using the Brookmeyer-Crowley method with log-log transformation. Descriptive statistical methods were used to characterize AEs. Fisher's exact test was applied to a matrix of mutations and wild-type phenotypic pathway-associated gene counts between responders and non-responders to identify pathways enriched in either of the two response groups. The p-values ​​for the difference in single-sample GSEA (ssGSEA) enrichment scores between responder and non-responder patients were obtained using the Mann-Whitney U test. result

[0246] Forty-five patients (median age 67 years, range 49–90 years) received at least one dose of sacituzumab govitecan at a dose level of 10 mg / kg and were included in the analysis. Of these patients, 17 had previously received CPI treatment, and 15 had previously received both CPI and platinum-based treatment. The demographic and baseline characteristics of the patients are shown in Table 1. Patients had a median of two prior treatments (range 1–6), including previous platinum-based chemotherapy (93.3%) and previous CPI (37.8%). The majority of patients (33 out of 45 [73%]) had visceral complications, mainly liver (n=15) and lung (n=27) metastases. Forty-four percent of patients had two to three Bellmunt risk factors (Table 1). [Table 1] * Categories are not mutually exclusive. † Bacillus Calmette-Guerin immunotherapy was not considered a prior therapy. ‡ Risk factors include ECOG PS > 0, presence of liver metastases, and hemoglobin < 10 g / dL.

[0247] The median follow-up period was 15.7 months (range, 1–39.6 months). Patients received a median of 8 cycles of sacituzumab govitecan (16 doses, range 1–90 doses), and the median treatment duration was 5.2 months (range, 0.03–32.3 months).

[0248] Dose reduction occurred in 40% of patients (18 out of 45) (12 of these patients experienced only one dose reduction). Nine patients received treatment for more than 12 months. 29 patients (87%) discontinued treatment, primarily due to disease progression (Table 2). Five patients were still receiving treatment at the data cutoff date in September 2018 (3 were responders, 1 was stable [SD], and 1 continued treatment after drug discontinuation and progressed after a pre-confirmed complete response). As of the data cutoff date, 28 deaths had been reported (17 during the follow-up period): 26 due to disease progression, 1 due to myocardial infarction after the end of the study, and 1 death of unknown cause. [Table 2] * Of the 29 patients, two discontinued treatment due to adverse events (AEs) unrelated to the investigational drug and associated with disease progression. † Two additional patients were discontinued due to adverse events (AEs) unrelated to the investigational drug and associated with disease progression.

[0249] Sacituzumab govitecan tolerability - The most common adverse events (AEs) were diarrhea, nausea, fatigue, and neutropenia. Grade ≥3 AEs observed in ≥5% of patients also included hypophosphatemia and febrile neutropenia (Table 3). Growth factor support agents were administered to 24.4% of patients (11 out of 45). No cases of grade 3 or higher peripheral neuropathy or cardiovascular AEs were reported. Eleven percent of patients (5 out of 45) discontinued treatment by the investigator due to AEs considered likely to be drug-related (grade 3 diarrhea, grade 2 cystitis, grade 2 pruritus / itchiness, grade 3 maculopapular rash / pruritus, and grade 3 hypertension). Of the 45 patients, 21 (46.7%) had one or more SAEs, including febrile neutropenia, diarrhea, and neutropenia (2 patients each), which occurred in two or more patients. No adverse events (AEs) resulting in death or treatment-related death were reported. [Table 3] *Includes neutropenia and decreased neutropenia.

[0250] Clinical activity of sacituzumab govitecan in the overall population and patient subgroups - Overall, 31.1% of patients (14 out of 45) achieved an objective response (95% CI, 18.2%–46.6%, Table 4). Responses included 2 complete responses (CR) (4.4%) and 12 partial responses (PR) (26.7%). SD was observed in 35.6% of patients (16 out of 45), and 22.2% of patients (10 out of 45) had progressive disease. The chronicity benefit (CBR), including CR, PR, and SD for 6 months or more, was 46.7% (21 out of 45 patients). The median time to objective response was 1.9 months (range, 1.7–7.4 months), and the median duration of response (DOR) was 12.9 months (Table 4). [Table 4]

[0251] Subgroup analysis of ORR showed an ORR of 33.3% (5 out of 15 patients) in patients with liver metastases and 27.3% (9 out of 33 patients) in patients with any visceral impairment (Table 4). The ORR for patients who had received prior treatment with CPI (17 out of 45 patients) and patients who had received prior treatment with both CPI and platinum therapy (15 out of 45 patients) was 23.5% (4 out of 17 patients) and 26.7% (4 out of 15 patients), respectively.

[0252] Target lesion reduction was achieved in 77.5% of patients (31 out of 40 patients had at least one post-baseline tumor assessment, Figure 1A). 50 percent of responders (7 out of 14 patients) had a response of more than 12 months. At the time of this analysis, three patients with a continuing response were still receiving treatment (Figure 1B), and five patients remained in treatment at the data cutoff. The median PFS and median OS were 7.3 months (95% CI, 5.0–10.7 months) and 16.3 months (95% CI, 9.0–31.0 months), respectively (Figure 2).

[0253] Genomic evaluation-WES and RNA-seq analysis revealed that mutations in the endogenous apoptosis signaling pathway (GO:0097193), including DNA damage repair and apoptosis genes, were enriched in responders compared to non-responders (unadjusted p=0.02). Several DNA damage response and repair genes (BRCA1, BRCA2, CHEK2, MSH2, MSH6, TP53, CDKN1A) and apoptosis genes (BAG6, BRSK2, ERN1, FHIT, HIPK2, LGALS12, ZNF622, AEN, SART1, USP28) in this pathway were differentially mutated between the two groups (Figure 3A). Analysis of RNA-seq data identified GADD45B, TGFB1, NRG1, WEE1, and PPP1R15A genes as top differentially regulated genes between responders and non-responders to sacituzumab govitecan (Figure 3B). These genes are functionally linked to the response of irinotecan or its metabolites to SN-38 (Miettinen et al., 2009, Anticancer Drugs 20:589-600; Bauer et al., 2012, PLoS One 7:e39381; Yang et al., 2017, Oncotarget 8:47709-24; Yin et al., 2018, Mol Med Rep 17:3344-49; Roh et al., 2016, J Cancer Res Clin Oncol 142:1705-14). Single-sample GSEA analysis revealed enrichment of differential changes in the apoptotic pathway (p=0.04) and the p53 pathway (p=0.006) in responders to sacituzumab govitecan (Figure 3C), consistent with the role of p53 signaling in mediating the downstream cytotoxic effects of SN-38. Poele & Joele, 1999, Br J Cancer 81:1285-93).

[0254] Specific data regarding genomic biomarkers, allele frequencies, and specific mutations or other genetic alterations are disclosed in Appendix 1 and Appendix 2. Appendix 1 identifies specific genomic biomarkers identified in mUC patient samples. Column 1 lists the gene from which the biomarker originated, the chromosome number, start and end locations of the gene variant, the type of variant, if applicable (e.g., SNP), the reference and tumor alleles, the resulting codon and protein sequence changes, and the tumor VAF (mutant allele frequency).

[0255] Part A of Appendix 2 separates the mutation frequencies of responders and non-responders for each mutated gene, with the gene identified in column 1, followed by the responder mutation frequency, the non-responder mutation frequency, and the presence or absence of samples from each patient. Specific types of genetic changes (SNPs or insertions / deletions) are also indicated. Part B of Appendix 2 lists the individual genes examined and the biomarkers observed in responders versus non-responders. Part C of Appendix 2 summarizes the P53 and GSEA scores for the apoptotic pathway for each sample, classified as either a responder or a non-responder to sacituzumab govitecan. Consideration

[0256] Patients with mUC whose disease progresses after chemotherapy and CPI have a poor outcome and there are no approved treatment options (Di Lorenzo et al., 2015, Medicine (Baltimore) 94:e2297; Vlachostergios et al., 2018, Bladder Cancer 4:247-59). Developing safe and effective treatments for these patients is important, and ADCs represent a promising treatment modality (Vlachostergios et al., 2018, Bladder Cancer 4:247-59; Starodub et al., 2015, Clin Cancer Res 21:3870-8; Rosenberg et al., 2019, J Clin Oncol 37(suppl 7S):377). Our trial demonstrated that sacituzumab govitecan had significant clinical activity in a multi-priority population of resistant / refractory mUC patients, achieving an objective response rate of 31%, including a 33% response rate in patients with liver metastases. Patients with prior CPI exposure had a 23.5% objective response rate, despite having an inadequate performance status and multiple prior therapies. Overall, patients achieved sustained clinical benefit, with a median duration of response (DOR) of 12.9 months, 50% of responders having a response duration of over 12 months, and the longest continuous response duration at data cutoff being 29.4 months. Despite having received a median of two prior therapies, the median progression-free survival (PFS) and overall survival (OS) observed with sacituzumab govitecan were 7.3 months and 16.3 months, respectively, and five patients were still receiving treatment at data cutoff.These initial results for sacituzumab govitecan in mUC report longer median OS than observed in other standard treatments or clinical trials (range: 4.3–13.8 months) in similar second-line settings for mUC patients (Bellmunt et al., 2017, N Eng J Med 37:1015-26; Patel et al., 2018, Lancet Oncol 19:51-64; Rosenberg et al., 2016, Lancet 387:1909-20; Rosenberg et al., 2019, J Clin Oncol 37(suppl 7S):377; Bellmunt et al., J Clin Oncol. 27:4454-61; Bellmunt et al., 2013, Ann Oncol 24:1466-72; Siefker-Radtke et al., 2018, J Clin Oncol 36:4503). In summary, these findings suggest that sacituzumab govitecan is effective in patients with resistant / refractory mUC.

[0257] AEs associated with sacituzumab govitecan were predictable and manageable, resulting in low discontinuation rates. The safety profile was consistent with those reported for sacituzumab govitecan in other cancers (Starodub et al., 2015, Clin Cancer Res 21:3870-8; Ocean et al., 2017, Cancer 123:3843-54; Bardia et al., 2019, N Engl J Med 380:741-51; Gray et al., 2017, Clin Cancer Res 23:5711-19; Heist et al., 2017, J Clin Oncol 35:2790-97). Severe diarrhea is a major concern with irinotecan (Rothenberg, 1997, Ann Oncol). In the study (8:837-55, Beer et al., 2008, Clin Genitourin Cancer 6:36-9, Camptosar [package insert] New York, NY, Pharmacia & Upjohn, 2016), 31% of patients with delayed diarrhea of ​​grade 3 or higher and 8% with early diarrhea of ​​grade 3 or higher were reported with irinotecan administered as monotherapy (Camptosar [package insert] New York, NY, Pharmacia & Upjohn, 2016). In particular, the incidence of grade 3 diarrhea observed with sacituzumab govitecan in this study was low (9%), there were no cases of diarrhea of ​​grade 4 or higher, and there was only one case of treatment discontinuation due to diarrhea. Despite the expression of Trop-2 in normal tissues (Trerotola et al., 2013, Oncogene 32:222-33, Goldenberg et al., 2018, Oncotarget 9:28989-29006), the toxicity of sacituzumab govitecan, including frequent myelosuppression, is manageable with modifications to the administration schedule and supportive care, ensuring a relative dose intensity of over 90% and a low discontinuation rate due to adverse events. Indeed, in our trial, there were no discontinuations due to neutropenia, and a high response rate was reported despite 40% of patients experiencing dose reduction, consistent with what has been reported in other populations treated with sacituzumab govitecan (Bardia et al., 2017, J Clin Oncol). 35:2141-48;Bardia et al.,2019,N Engl J Med 380:741-51;Bardia et al.,2018,J Clin (Oncol 36(suppl):1004; Gray et al., 2017, Clin Cancer Res 23:5711-19; Heist et al., 2017, J Clin Oncol 35:2790-97), there were no cases of grade 3 or higher neuropathy or cardiovascular AEs. Importantly, no treatment-related deaths were reported in our trial.

[0258] Integrated genomic and transcriptome analyses in a subset of patients in this study revealed distinctive patterns of differential somatic mutations and gene expression in the DNA damage response and apoptotic pathways between responders and non-responders to sacituzumab govitecan. This is consistent with the biological effects of SN-38 on the induction of DNA damage and the activation of p53-mediated apoptosis (Candeil et al., 2004, Int J Cancer 109:848-54; Tomicic et al., 2013, Biochim Biophys Acta 1835:11-27). It is noteworthy that the combination of sacituzumab govitecan with a poly-ADP-ribose polymerase (PARP) inhibitor in triple-negative breast cancer cell lines and mouse xenograft models resulted in enhanced antitumor activity regardless of BRCA1 / 2 mutation status (Cardillo et al., 2017, Clin Cancer Res 23:3405-15). In summary, our findings lay the foundation for a deeper understanding of the biological effects of sacituzumab govitecan and, if validated in prospective studies, could have significant implications for selecting patients most likely to benefit from treatment.

[0259] A major strength of this study is that at least 38% of this population received sacituzumab govitecan as a fourth-line or later treatment, including patients with disease progression after CPI treatment, allowing for evaluation of its activity in patients with a high degree of prior treatment. Furthermore, this population was evaluated in a way that is more representative of clinical practice. While the small number of patients in specific clinical subgroups limits the interpretation of data from subgroup analyses, the overall efficacy data support the use of sacituzumab govitecan for the treatment of metastatic urothelial carcinoma (mUC).

[0260] In summary, sacituzumab govitecan demonstrated clinically meaningful activity, including high response rates, long duration of response, and favorable survival rates, as well as a manageable safety profile, in patients with treatment-resistant / refractory mUC who had received prior treatment, including many prior treatments. An international, multicenter, open-label phase II trial (TROPHY-U-01, NCT03547973) is underway to further evaluate the efficacy and safety of sacituzumab govitecan in mUC patients who have failed platinum-based chemotherapy regimens or anti-PD-1 / PD-L1 immunotherapy. Example 2. Treatment of metastatic triple-negative breast cancer with the anti-Trop-2 ADC sacituzumab govitecan

[0261] Triple-negative breast cancer (TNBC) is characterized by the lack of expression of estrogen receptors, progesterone receptors, and HER2. TNBC accounts for approximately 20% of breast cancers and has been shown to have a more aggressive clinical course and a higher risk of recurrence and death. Due to the lack of hormone receptor targets, there is no suitable targeted therapy for TNBC (Jin et al., 2017, Cancer Biol Ther 18:369-78), however, atezolizumab in combination with Abraxane chemotherapy has recently been approved as a first-line therapy for TNBC. Currently, the main systemic treatment for TNBC is platinum-based chemotherapy, primarily with cisplatin and carboplatin (Jin et al., 2017, Cancer Biol Ther 18:369-78). However, resistance to these drugs or recurrence is common. Over 75% of BRCA1 / 2 mutant breast cancers exhibit the TNBC phenotype, and homologous recombination deficiency (HRD) resulting from loss of BRCA function due to mutation or methylation has been suggested to predict platinum efficacy (Jin et al., 2017, Cancer Biol Ther 18:369-78). This study reports the results of a Phase I / II clinical trial (NCT01631552) in patients with metastatic TNBC who had previously failed treatment with at least one standard anticancer drug. The results reported below demonstrate the safety and efficacy of sacituzumab govitecan, an anti-Trop-2 ADC, in a population of metastatic, relapsed / refractory TNBC patients who had received many prior treatments. Methods and materials

[0262] Patients with relapsed / refractory TNBC who had previously failed at least one prior treatment were enrolled in a single-arm, multicenter trial (Bardia et al., 2019, N Engl J Med). (380:741-51). This study reports on 108 patients who had failed at least two prior treatments (median three prior treatments) (Bardia et al., 2019, N Engl J Med 380:741-51). Patients were administered an initial dose of 10 mg / kg on days 1 and 8 of a 21-day cycle, and this was repeated until disease progression or an unacceptable adverse event occurred. In cases of severe treatment-related adverse events, the dose was reduced by 25% after the first occurrence, by 50% after the second occurrence, and discontinued after the third occurrence. Of the 108 patients, 107 were female and 1 was male, with a median age of 55 years. Prior treatments included taxanes (98%), anthracyclines (86%), platinum (69%), gemcitabine (55%), eribulin (45%), and checkpoint inhibitors (17%). Tumor staging was performed using computed tomography (CT) and MRI at baseline and then at 8-week intervals from the start of treatment until disease progression. result

[0263] The most common adverse events included nausea (67% of patients, 6% grade 3), diarrhea (62%, 8% grade 3), vomiting (49%, 6% grade 3), fatigue (55%, 8% grade 3), neutropenia (64%, 26% grade 3), and anemia (50%, 11% grade 3). The only grade 4 adverse events observed were neutropenia (16%), hyperglycemia (1%), and leukopenia (3%). Four patients died during the study. Each of these was attributed by the principal investigator to disease progression and not to the toxicity of sacituzumab govitecan (Bardia et al., 2019, N Engl J Med 380:741-51). Three patients discontinued treatment due to adverse events. At the data cutoff, the median follow-up period for the 108 patients was 9.7 months. Eight patients continued treatment, 100 discontinued treatment, but 86 discontinued treatment due to disease progression. Transient changes in safety laboratory values ​​included decreased blood cell counts and changes in biochemical values, which generally recovered after treatment completion.

[0264] Figure 4A shows a waterfall plot illustrating the range and depth of response based on site evaluation. The response rate (CR ± PR) was 33.3%, including 2.8% complete response (CR). The clinical benefit rate (including stability for at least 6 months) was 45.5%.

[0265] Figure 4B shows swimmer plots of response onset and duration in 36 patients who demonstrated objective response. The median time to response was 2.0 months, and the median duration of response was 7.7 months. The estimated probability of patients responding was 59.7% at 6 months and 27.0% at 12 months. At the data cutoff date, six patients had a long-term response of more than 12 months. No significant differences in response to sacituzumab govitecan were observed with respect to patient age, onset of metastatic disease, number of prior treatments, or presence of visceral metastases. The response rate was 44% in patients who had failed previous checkpoint inhibitor therapy. The median progression-free survival was 5.5 months, and the median overall survival was 13.0 months. Consideration

[0266] The majority of TNBC patients progress after receiving first-line therapy, and standard treatment options are limited to chemotherapy. Chemotherapy has been associated with low response rates (10–15%) and short PFS (2–3 months) in metastatic TNBC patients who have previously failed standard chemotherapy. Due to the lack of normal breast tissue receptors, there are no targeted therapy options for TNBC.

[0267] Sacituzumab govitecan (SG) is an anti-Trop-2 ADC containing a humanized RS7 antibody conjugated to SN-38 (a metabolite of irinotecan), a topoisomerase I inhibitor, via a CL2A linker. Trop-2 has been reported to be expressed in over 85% of breast cancer tumors (Bardia et al., 2019, N Engl J Med 380:741-51).

[0268] In this trial, treatment with the optimal dose of 10 mg / kg SG in a population of metastatic, resistant / refractory TNBC patients who had received many prior treatments resulted in a 33.3% response rate, with a median duration of response of 7.7 months, a median progression-free survival (PFS) of 5.5 months, and a median overall survival (OS) of 13.0 months. These figures are substantially better than the current standard of care for TNBC patients receiving second-line or later treatment, which is limited to systemic chemotherapy. Further use of targeted anti-Trop-2 ADCs, either alone or in combination with one or more other therapeutic modalities, and with or without diagnostic assays, to predict the likelihood of patients responding to monotherapy or combination therapy would further improve the efficacy of this treatment for this highly refractory and fatal form of cancer. Example 3. Treatment of mSCLC patients with anti-Trop-2 ADC

[0269] Topotecan, a topoisomerase I inhibitor, is approved as a second-line treatment for patients sensitive to first-line platinum-containing regimens, but only a few newer therapies are approved for the treatment of metastatic small cell lung cancer (mSCLC) (Gray et al., 2016, Clin Cancer Res 23:5711-9). In this study, we tested sacituzumab govitecan, a novel anti-Trop-2 ADC. Patients with a median of two prior therapies (range 1–7) received the ADC on days 1 and 8 of a 21-day cycle for a median of 10 doses (range 1–63). The primary grade ≥3 toxicities were manageable neutropenia, fatigue, and diarrhea. Despite up to 63 repeated doses, the ADC was not immunogenic.

[0270] In 49 percent of 43 evaluable patients, there was a reduction in tumor size from baseline, with an objective response rate (partial response) of 16%, and stabilization was achieved in 49 percent of patients. Median progression-free survival and median overall survival were 3.6 and 7.0 months, respectively, based on intention-to-treat analysis (N=53). This ADC was also active in patients who were chemotherapy-sensitive or resistant to first-line chemotherapy, and in patients who failed second-line topotecan therapy (Gray et al., 2016, Clin Cancer Res 23:5711-9). These data support the use of sacituzumab govitecan as a novel treatment for advanced mSCLC. method

[0271] Patients aged 18 years or older with mSCLC who had relapsed or were refractory to at least one prior standard treatment for stage IV metastatic disease and had a tumor measurable by CT were enrolled. Patients had to have an Eastern Cooperative Oncology Group (ECOG) performance status of 0 or 1, adequate bone marrow, liver, and kidney function, and other eligibility criteria described in the Phase I trial (Starodub et al., 2015, Clin Cancer Res 21:3870-8). Prior treatment had to be completed in the stomach at least 4 weeks prior to enrollment.

[0272] The overall objective of this part of a basket trial conducted across various cancers (ClinicalTrials.gov, NCT01631552) was to evaluate the safety and antitumor activity of sacituzumab govitecan in patients with mSCLC. Doses of 8 or 10 mg / kg were administered on days 1 and 8 of a 21-day cycle, with delays if necessary (up to 2 weeks). Toxicity was managed by supportive hematopoietic growth factor therapy in case of cytopenia, protocol-specified dose delays and / or modifications (e.g., 25% of the previous dose), or standard medical practice. Treatment continued until disease progression, initiation of alternative anticancer therapy, unacceptable toxicity, or withdrawal of consent.

[0273] Fifty-three mSCLC patients were enrolled (30 women, 23 men, median age 63 years (range, 44–82)). The median time from initial diagnosis to treatment with sacituzumab govitecan was 9.5 months (range, 3–53). Most patients had received many prior treatments, with a median of two (range, 1–7) prior treatments. All had received cisplatin or carboplatin and etoposide. Twenty-two patients (41%) had received one prior treatment, while 14 patients (26%) and 17 patients (32%) had received two and three or more prior chemotherapy regimens, respectively. In addition, 18 patients (33%) received topotecan and / or irinotecan, 9 patients (16%) received taxanes, and 5 patients (9%) received immune checkpoint inhibitor therapy, including nivolumab (N=4) or atezolizumab (N=1).

[0274] Based on the duration of response to the latest platinum-containing therapy (more than 3 months or less than 3 months), there were 27 chemotherapy-sensitive patients (51%) and 26 chemotherapy-resistant patients (49%), respectively. Most patients had extensive disease with metastases to multiple organs, including the lungs (66%), liver (59%), lymph nodes (76%), chest (34%), adrenal glands (25%), bones (23%), and pleura (6%). Other sites of disease included the pancreas (N=4), brain (N=2), skin (N=2), and esophageal wall, ovaries, and sinuses (1 each).

[0275] The primary endpoint was the proportion of patients with a confirmed objective response, assessed approximately every 8 weeks until disease progression by the radiology department of each institution or contracted local radiology service. Objective response was assessed using the Response Evaluation Criteria in Solid Tumors, version 1.1 (RECIST 1.1) (Eisenhauer et al., 2009, Eur J Cancer 45:228-47). Partial response (PR) or complete response (CR) required confirmation within 4–6 weeks after the initial response. Clinical benefit rate (CBR) was defined as patients with objective response + stable disease (SD) for 4 months or longer. Survival rates were monitored every 3 months until death or withdrawal of consent.

[0276] Safety assessments were performed during scheduled consultations or more frequently as needed. Blood counts and serological tests were checked before administration of sacituzumab govitecan and regularly when clinically indicated.

[0277] Statistical Analysis - Data included in the analysis were from patients registered between November 2013 and June 2016 and followed up until January 31, 2017. The frequency and severity of adverse events (AEs) were defined according to MedDRA Preferred Term and System Organ Class (SOC) version 10, and NCI-CTCAE The severity was assessed according to v4.03. All patients who received sacituzumab govitecan were evaluated for toxicity.

[0278] The protocol stipulated that the objective response rate (ORR) be determined for patients who received two or more doses (1 cycle) and had a CT evaluation during the initial 8 weeks. Duration of response was defined according to the RECIST 1.1 criteria and refers to objective response recorded from the time of initial evidence of response until progression, while stability time was recorded from the start of treatment until progression. Progression-free survival (PFS) and overall survival (OS) were defined as the time from the start of treatment until an objective assessment of progression was determined (PFS) or until death (OS). Duration of response, PFS, and OS were estimated using the Kaplan-Meier method with 95% confidence intervals (CI) using MedCalc Statistical Software, version 16.4.3 (Ostend (Belgium)).

[0279] Sacituzumab govitecan and its components were stained with IHC for tumor Trop-2 immunohistochemistry and immunogenicity-Trop-2 in preserved tumor specimens and interpreted as previously reported (Starodub et al., 2015, Clin Cancer Res 21:3870-8). Positivity required staining of at least 10% of tumor cells, and the intensity was scored as 1+ (weak), 2+ (moderate), and 3+ (strong). Antibody responses to sacituzumab govitecan, IgG antibody, and SN-38 were monitored in serum samples collected at baseline and before each subsequent even-numbered cycle by enzyme-linked immunosorbent assay performed by the sponsor (Starodub et al., 2015, Clin Cancer Res 21:3870-8). The assay sensitivity was 50 ng / mL for ADC and IgG, and 170 ng / mL for anti-SN-38 antibody. result

[0280] Patients – From November 2013 to June 2016, 53 patients with mSCLC were enrolled (30 women, 23 men, median age 63 years (range, 44–82)). The median time from initial diagnosis to treatment with sacituzumab govitecan was 9.5 months (range, 3–53). Most patients had received a median of two prior therapies (range, 1–7). All patients received cisplatin or carboplatin and etoposide. 22 patients (41%) had received one prior therapy, while 14 patients (26%) and 17 patients (32%) had received two and three or more prior chemotherapy regimens, respectively. In addition, 18 patients (33%) received topotecan and / or irinotecan, 9 patients (16%) received taxanes, and 5 patients (9%) received immune checkpoint inhibitor therapy, including nivolumab (N=4) or atezolizumab (N=1). Most patients had extensive disease with metastases to multiple organs, including the lungs (66%), liver (59%), lymph nodes (76%), chest (34%), adrenal glands (25%), bones (23%), and pleura (6%). Other sites of disease included the pancreas (N=4), brain (N=2), skin (N=2), and esophageal wall, ovaries, and sinuses (1 each).

[0281] Treatment exposure, safety, and tolerability - Of the 53 patients enrolled, the first two treated in May 2016 were continuing sacituzumab govitecan treatment as of the cutoff date of January 31, 2017. All other patients had discontinued treatment or were being monitored for survival. There were fewer than 590 doses (more than 295 cycles), and the median number of doses per patient was 10 (range, 1–63). No infusion-related reactions were reported.

[0282] In 15 patients, the initial dose was administered at a starting dose of 8 mg / kg. 10 mg / kg was the starting dose for the next 38 patients. Between the two treatment groups, 25 patients received ≥10 doses (≥5 cycles), and 2 patients received 62 and 63 doses (>30 cycles). The median treatment duration was 2.5 months (range, 1–23). Neutropenia (grade ≥2) was the only indicator of dose reduction and was recorded in 29% (11 / 38) of patients after a median of 2.5 doses (range, 1–9) at the 10 mg / kg dose level. Of the 15 patients (13%) treated with 8 mg / kg, two underwent dose reduction: one after 2 doses and the other after 41 doses (20 cycles). Once dose reduction occurred, further reductions were rare. No treatment-related deaths were observed.

[0283] In this trial, 10 patients dropped out before the initial response assessment; 4 received one dose, 5 received two doses, and the others after four doses. Three patients were ineligible for response assessment after one or two doses; one had mixed histological features of SCLC and NSCLC, and the other two were diagnosed with pre-trial brain and / or spinal metastases after the first dose of sacituzumab govitecan. Two patients who reported post-first-dose CTCAE grade 3 adverse events (neutropenia and fatigue) that had not resolved by the second dose were discontinued according to the protocol. Four patients withdrew from the trial after two doses; two withdrew consent, and two withdrew due to grade 2 fatigue. A further patient withdrew from the trial after four doses due to sudden death before the initial response assessment due to multiple comorbidities.

[0284] In 53 patients who received at least one dose of sacituzumab govitecan, the most frequently reported adverse events were nausea, diarrhea, fatigue, alopecia, neutropenia, vomiting, and anemia (data not shown). Grade 3 or 4 neutropenia occurred in 34% (18 / 53) of patients, with only one patient experiencing febrile neutropenia. Other grade 3 or 4 adverse events were rare and included fatigue (13%), diarrhea (9%), anemia (8%), elevated alkaline phosphatase (8%), and hyponatremia (8%). Fewer patients required dose reduction in the 8 mg / kg dose group (13% vs. 28% in 10 mg / kg), while the 10 mg / kg dose group was similarly well-tolerated, with several patients requiring dose adjustment and / or growth factor support.

[0285] Efficacy - As described, of the 53 mNSCLC patients enrolled, 10 discontinued before the first CT response assessment, and the remaining 43 had an objective assessment of the response as required by the protocol after receiving at least two doses of sacituzumab govitecan and at least one follow-up scan. Figure 5 provides a series of graphical representations of the response, including a waterfall plot of the best percentage change in the total diameter of the target lesions for the 43 patients (Figure 5A), a graph showing the duration of response for those achieving PR or SD status (Figure 5B), and a plot tracking the change in response over time for patients with PR and SD (Figure 5C).

[0286] Of the 43 CT-evaluable patients, 21 (49%) experienced tumor size reduction from baseline (Figure 5A). Confirmed partial response (≥30% reduction) occurred in 7 patients, resulting in an ORR of 16% (Table 5). The median time to response in these patients was 2.0 months (range, 1.8–3.6 months), and the median duration of response estimated by Kaplan-Meier was 5.7 months (95% CI: 3.6, 19.9). Of the 7 responders, 2 were in an ongoing response at the last follow-up (i.e., the patient was alive, disease progression-free, and had not initiated alternative anticancer therapy), one at 7.2+ months from the start of treatment, and the other at 8.7+ months. [Table 5]

[0287] Stability (SD) was determined in 21 patients (49%), including 6 patients (14%) who initially had >30% tumor reduction but this was not sustained at subsequent confirmatory CT (unconfirmed PR, or PRu), and 3 patients with ≥20% tumor reduction. It is important to note that 10 patients had SD for ≥4 months (Kaplan-Meier median = 5.6 months, 95% CI: 5.2, 9.7), and their median PFS (7.9 months, 95% CI: 7.6, 21.9; P=0.1620) and clinical benefit rate (CBR: PR+SD ≥4 months) of 40% (17 / 43) were not significantly different from those in the confirmed PR group. In fact, even the overall survival (OS) of these 10 SD patients was not significantly different from that of the 7 confirmed PR patients (8.3 months, 95% CI 7.5, 22.4 months vs. 9.2 months, 95% CI: 6.2, 20.9, P=0.5599, respectively). This suggests that maintaining SD for an appropriate period (≥4 months) should be the target endpoint. Under the intention to treat (ITT) criteria (N=53), the median progression-free survival (PFS) was 3.6 months (95% CI: 2.0, 4.3) (Figure 6A), while the median OS was 7.0 months (95% CI: 5.5, 8.3). Seventeen patients survived, and five were lost to follow-up (one at 1.8 months, one at 5 months, and three at 11.4–12.8 months) (Figure 6B).

[0288] Of the 43 patients with objective response evaluations, 13 were treated with 8 mg / kg, including one confirmed PR (8%), one unconfirmed PR, and three SDs. In the 10 mg / kg group (N=30), 6 patients had confirmed PR (20%), 12 had SD, and 5 showed a reduction of more than 30% (PRu) on a single CT scan. The CBR was 47% (14 / 30), suggesting that the starting dose of 10 mg / kg resulted in a better overall response.

[0289] Of the 24 patients with response assessments, those were classified as sensitive to first-line platinum-based chemotherapy. Four patients (17%) achieved confirmed partial response (PR), nine had stable disease (SD), and four had a single scan showing tumor reduction (PRu) of over 30%. Nineteen patients were resistant, with three (16%) achieving confirmed PR, six having SD, and two showing PRu. The median progression-free survival (PFS) for the chemotherapy-sensitive and chemotherapy-resistant groups was 3.8 months (95% CI: 2.8, 6.0) and 3.6 months (95% CI: 1.8, 3.8), respectively, and the median overall survival (OS) was 8.3 months (95% CI: 7.0, 13.2) and 6.2 months (95% CI: 4.0, 10.5), respectively (Table 5). There were no significant differences in PFS or OS between the chemotherapy-sensitive and chemotherapy-resistant groups (P=0.3981 and P=0.3100, respectively).

[0290] Of the 43 patients, 19 received sacituzumab govitecan as second-line treatment, with 3 / 19 (16%) achieving a partial response (PR) and 7 achieving stable disease (SD) as the best response (two of the latter had tumor shrinkage of >30% compared to one patient). The responses observed in these patients were the same as those seen in patients who received sacituzumab govitecan as third-line or later treatment (N=24), with 4 confirmed PRs (16%) and 8 SDs, including 4 SD patients with >30% tumor shrinkage on a single CT scan. There were no significant differences in the duration of progression-free survival (PFS) or overall survival (OS) (P=0.9538 and P=0.6853, respectively). The results of the response analysis are summarized in Table 5.

[0291] Among five patients who had previously received immune checkpoint inhibitor (CPI) therapy, one achieved an unconfirmed partial response (54% tumor shrinkage at the initial evaluation, with no further treatment or evaluation, and withdrawal of consent), two achieved stable disease (SD), one of whom had 17% tumor shrinkage lasting 8.7 months, another had no change in tumor size for 3.7 months, and one had progressive disease, while the fifth patient withdrew consent after one cycle of sacituzumab govitecan. All of the CPI-treated patients either did not respond to CPI or had disease progression before sacituzumab govitecan administration, indicating that patients can respond to sacituzumab govitecan after CPI treatment.

[0292] Of the 24 patients who received sacituzumab govitecan as a third-line or later treatment, 15 had previously received topotecan and / or irinotecan, while 9 had not. Objective responses were similar in these two groups, and there was no significant difference in PFS (3.8 vs. 3.7 months, P=0.7341). However, patients who had received prior topotecan treatment and were then treated with sacituzumab govitecan had a significantly longer overall survival (OS) than those who did not (8.8 months, 95% CI: 6.2, 20.9 vs. 5.5 months, 95% CI: 3.2, 8.3; P=0.0357). This longer OS in this group may reflect the known activity of topotecan in platinum-sensitive patients and thus may indicate better long-term outcomes.

[0293] Immunohistochemical (IHC) staining of tumor specimens - Preserved tumor specimens were collected from 29 patients, but 4 were insufficient for testing. Of the remaining 25 evaluable tumors, 92% were positive, including 2 (8%) with strong staining (3+) and 13 (52%) with moderate staining (2+). Of these patients, 23 had objective response evaluations. In this group, there were 5 confirmed PRs and 2 unconfirmed PRs, with 5 being 2+ stained and the other 2 being 1+ (not shown), suggesting that higher expression provided a better response. However, the evaluation of PFS and OS values ​​against IHC scores did not show a clear trend (not shown), and the Kaplan-Meier estimates for PFS and OS in patients with a total IHC score of 0 and 1+ (N=10) versus a total IHC score of 2+ and 3+ (N=13) did not show a significant difference based on IHC score (not shown) (PFS, P=0.2661; OS, P=0.7186).

[0294] Immunogenicity of ADC, SN-38, or hRS7 antibodies - Neutralizing antibodies against sacituzumab govitecan, hRS7 antibody, or SN-38 were not detected even in patients who maintained treatment for up to 22 months. Consideration

[0295] Relapses of SCLC in response to the latest chemotherapy are classified into two categories: resistant relapses that occur within 3 months of the initial platinum-based therapy, and susceptible relapses that occur at least 3 months after treatment (O'Brien et al., 2006, J Clin Oncol). 24:5441-7, Perez-Soler et al., 1996, J Clin Oncol 14:2785-90). Although there is still some ambiguity regarding the best management of relapsed SCLC, topotecan, a topoisomerase I inhibitor similar to SN-38 used in the ADCs tested herein, is the only product approved for chemotherapy-sensitive relapse, as supported by numerous trials (O'Brien et al., 2006, J Clin Oncol 24:5441-7, Horita). (Horita et al., 2015, Sci Rep 5:15437). However, the efficacy and adverse events of topotecan have changed significantly in previous trials, as demonstrated by a meta-analysis of over 1,000 patients reported in 14 studies, where the objective response rate to topotecan was 5% in chemotherapy-resistant, previously treated patients and 17% in chemotherapy-sensitive patients (Horita et al., 2015, Sci Rep 5:15437). Grade ≥3 neutropenia, thrombocytopenia, and anemia occurred in 69%, 1%, and 24% of patients, respectively, and approximately 2% of patients died from this chemotherapy (Horita et al., 2015, Sci Rep 5:15437). et al., 2015, Sci Rep 5:15437). Therefore, topotecan shows some efficacy as a second-line treatment in patients who have relapsed after showing sensitivity to platinum-based chemotherapy, but it has considerable hematological toxicity. However, even this conclusion was recently challenged by Lara et al. (2015, J Thorac Oncol 10:110-5), who argued that platinum sensitivity is not strongly associated with improvements in PFS and OS after treatment with topotecan, which is a currently approved indication.

[0296] In this context, the results of sacituzumab govitecan in patients with persistent progressive disease (stage IV) following prior treatment with a median of 2 (range, 1–7) prior treatments, as reported herein, are promising. Forty-nine percent of patients showed a reduction from baseline in tumor measurements, with an ORR of 16% and a median duration of response of 5.7 months (95% CI: 3.6, 19.9) according to RECIST 1.1. Stability was observed in 35% of patients, and 14% of these SD patients had >30% tumor shrinkage as the best response, but this was not maintained at a second scan. The clinical benefit rate after 4 months was 40%. Median PFS and OS were 3.6 and 7.0 months, respectively. Interestingly, the median OS for the 10 patients with SD was 8.3 months (95% CI: 7.5, 22.4), which is not statistically different from the median OS of 9.2 months (95% CI: 6.2, 20.9) for patients with PR (P=0.5599). In the group administered 10 mg / kg as the starting dose (N=30), there were 6 patients (20%) with confirmed objective response, and an additional 5 patients had a single CT showing ≥30% tumor reduction (PRu). Furthermore, the clinical benefit rate at the 10 mg / kg dose in this group was 47%, which supports the preferred dose of 10 mg / kg. It is also noteworthy that there was no required patient selection based on immunohistochemical staining of tumor Trop-2, although stronger staining was suggested to correlate with a better response, but no significant difference in PFS or OS was observed with respect to IHC scores.

[0297] As described above, there was no substantial difference in PFS and OS between patients with SD or PR lasting more than 4 months. Patients with unconfirmed PR (i.e., >30% tumor reduction on a single CT) or SD are not considered in most ORR assessments. However, the results herein indicate no difference in duration of response between patients with confirmed PR or SD lasting more than 4 months. In fact, dynamic tracking of individual patient responses of PR or SD (particularly when SD lasts more than 4 months, which is a similar timeframe for confirming PR) suggests clinical utility for both groups by remaining smaller than baseline tumor size for several months. While PFS tended to be longer in patients with confirmed PR than in patients with SD lasting more than 4 months (P=0.1620), the difference in OS between these two groups was not significant (P=0.5599). Therefore, although the number of patients in this initial analysis is relatively small, these data suggest that more investigation should be given to disease stabilization as an important indicator of clinical activity when adequate duration is achieved, as well as in the follow-up of patients receiving immune checkpoint inhibitors.

[0298] When patients were evaluated based on their previous chemotherapy sensitivity (N=24) or chemotherapy resistance (N=19), there was no difference in response to sacituzumab govitecan treatment (Table 5). PFS and OS results were 3.8 months and 8.3 months for patients who were chemotherapy-sensitive to first-line treatment, compared to 3.6 months and 6.2 months, respectively, for the chemotherapy-resistant group. In the absence of statistical differences, sacituzumab govitecan appears to be administered to patients as a second-line or later treatment regardless of whether they are chemotherapy-sensitive or chemoresistant to first-line chemotherapy. This differs from topotecan, which is indicated only for SCLC patients who have shown a response of 3 months or more to first-line cisplatin and etoposide chemotherapy (O'Brien et al., 2006, J Clin Oncol 24:5441-7, Perez-Soler et al., 1996, J Clin Oncol 14:2785-90). Perez-Solid et al. (1996, J Of the 28 patients tested by Clin Oncol 14:2785-90, 11% had a partial response (PR), with a median survival time of 5 months and a 1-year survival rate of 3.5%.

[0299] Both topotecan and SN-38 are inhibitors of the DNA topoisomerase I enzyme, which is involved in the relaxation of supercoiled DNA helices during DNA synthesis by stabilizing DNA complexes, leading to the accumulation of single-strand DNA breaks (Takimoto & Arbuck, 1966, Camptothecins. In: Chabner & Long (Eds.). Cancer Chemotherapy and Biotherapy. Second ed. Philadelphia: Lippincott-Raven; pp. 463-84), sacituzumab govitecan showed activity in patients who relapsed after topotecan therapy. Therefore, topotecan resistance or relapse may not be a contraindication to sacituzumab govitecan administration, and since it is similarly active in patients who were resistant to cisplatin and etoposide, it may be particularly valuable as a second-line treatment in metastatic SCLC patients regardless of chemotherapy sensitivity status.

[0300] In the 20 years since the approval of topotecan as a second-line treatment, no new drugs have been approved for the therapy of metastatic SCLC in treatments beyond the second line. However, there has recently been progress with inhibitors of T cell checkpoint receptor programmed cell death protein (PD-1) and cytotoxic T lymphocyte-associated protein 4 (CTLA-4) (Antonia et al.). (Antonia et al., 2016, Lancet Oncol 17:883-95). These authors conducted a phase I-II trial of nivolumab with and without the CTLA-4 antibody ipilimumab in patients with relapsed SCLC. Nivolumab monotherapy achieved a response rate of 10%, while combination therapy yielded a response rate of 19-23% and a disease control rate of 32% (Antonia et al., 2016, Lancet Oncol 17:883-95). However, recent trials of ipilimumab with and without chemotherapy in SCLC have not been able to confirm these results (Reck et al., 2016, J Clin Oncol). 34:3740-48). Sacituzumab govitecan has been observed to be active in patients who have failed treatment with immune checkpoint inhibitors, and this is being further investigated, particularly by evidence of such responses after treatment with immune checkpoint inhibitors in patients with other cancer types (Bardia et al., 2017, J Clin Oncol 35:2141-48; Faltas et al., 2016, Clin Genitourin Cancer 14:e75-9; Gray et al., 2017, Clin Cancer Res 23:5711-19; Heist et al., 2017, J Clin Oncol 35:2790-97; Tagawa et al., 2017, J Clin Oncol 35:abstract 327; Han et al., 2018, Gynecol Oncol Rep 25:37-40).

[0301] Despite recent advances in immunotherapy and the identification of other novel targets for SCLC (Rudin et al., 2017, Lancet Oncol 18:42-51), it remains a fatal disease, particularly in populations that are chemoresistant to first-line therapy. Current outcomes of sacituzumab govitecan in multiple prior-treatment patients with advanced or relapsed stage IV SCLC suggest that anti-Trop-2 ADCs may be useful in treating both chemotherapy-sensitive and chemotherapy-resistant SCLC patients, both before and after topotecan. Example 4. Clinical trials of sacituzumab govitecan in various epithelial cancers

[0302] This example reports the results of a Phase I clinical trial and ongoing Phase II diastolic trial of sacituzumab govitecan (mean drug-antibody ratio = 7.6), an endogenous, humanized, hRS7 anti-Trop-2 antibody ADC conjugated to SN-38 by a pH-sensitive linker. Trop-2 is present in high density (~1 × 10⁻¹⁶) in many human cancers. 5 It is a type I transmembrane calcium transdextrinsing protein that is expressed with frequency and specificity, and whose expression is limited in normal tissues. Preclinical studies in nude mice with Capan-1 human pancreatic tumor xenografts revealed that sacituzumab govitecan could deliver 120 times more SN-38 than tumors derived from maximum tolerable doses of irinotecan therapy.

[0303] This example reports the initial Phase I of 25 patients who had failed multiple prior therapies (including several topoisomerase-I / II inhibitors), and the ongoing Phase II diastolic stage, which has been reported for 69 patients to date. These patients have cancers including colorectal cancer (CRC), small cell and non-small cell lung cancer (SCLC and NSCLC, respectively), triple-negative breast cancer (TNBC), pancreatic cancer (PDC), esophageal cancer, gastric cancer, prostate cancer, ovarian cancer, kidney cancer, bladder cancer, head and neck cancer, and hepatocellular carcinoma. The patients were refractory / recurrent after standard treatment regimens for metastatic cancer.

[0304] As will be discussed in detail below, Trop-2 was not detected in serum, but was strongly expressed in the most conserved tumors (≧2 +In a 3+3 study design, sacituzumab govitecan was administered on days 1 and 8 of repeated 21-day cycles, starting at 8 mg / kg / dose, then dose-restricted to 12 and 18 mg / kg until neutropenia occurred. To optimize cumulative treatment with minimal delay, Phase II focused on 8 and 10 mg / kg (n=30 and 14, respectively). Of the 49 patients who reported relevant AEs at this point, ≥G3 neutropenia occurred in 28% (4% G4). The most common initial non-hematological toxicities in these patients were fatigue (55%, ≥G3=9%), nausea (53%, ≥G3=0%), diarrhea (47%, ≥G3=9%), alopecia (40%), and vomiting (32%, ≥G3=2%). Homozygous UGT1A1 * 28 / * Twenty-eight patients were observed, with two of them having more severe hematological and GI toxicity. In Phase I and Diastolic, there are currently 48 patients (excluding PDCs) whose best response is evaluable by RECIST / CT. Seven patients (15%) had a partial response (PR), including patients with CRC (N=1), TNBC (N=2), SCLC (N=2), NSCLC (N=1), and esophageal cancer (N=1), and another 27 patients (56%) had stable disease (SD). A total of 38 patients (79%) had a disease response. Of the 13 PDC patients eligible for CT assay, eight (62%) had SD and had a median progression-free survival (TTP) of 12.7 weeks compared to 8.0 weeks with the most recent prior treatment. The TTP for the remaining 48 patients was 12.6+ weeks (range, 6.0–51.4 weeks). Plasma CEA and CA19-9 correlated with the response. Anti-hRS7 or anti-SN-38 antibodies were not detected despite several months of administration. The complex was removed from serum within 3 days, consistent with in vivo animal studies where 50% of SN-38 was released daily, and over 95% of serum SN-38 was bound to IgG in a non-glucuronidized form at concentrations 100-fold higher than SN-38 reported in patients treated with irinotecan. These results indicate that anti-Trop-2 ADCs are therapeutically active in numerous metastatic solid tumors and have manageable diarrhea and neutropenia. Pharmacokinetics

[0305] Two ELISA methods were used to measure IgG clearance (captured with anti-hRS7 idiotype antibody) and intact complex (captured with anti-SN-38 IgG / probe containing anti-hRS7 idiotype antibody). SN-38 was measured by HPLC. The total sacituzumab govitecan fraction (intact complex) was effluxed more rapidly than IgG (not shown), reflecting the known gradual release of SN-38 from the complex. HPLC measurements of SN-38 (unbound and total) showed that over 95% of SN-38 in serum was bound to IgG. Low concentrations of SN-38G suggest that SN-38 bound to IgG is protected from glucuronidation. A comparison of ELISA for complex and SN-38 HPLC revealed overlap between the two, suggesting that ELISA is an alternative for monitoring SN-38 clearance. Status of clinical trials

[0306] A total of 69 patients with diverse metastatic cancers (including 25 patients in Phase I) with a median of three prior treatments were reported. Eight patients experienced clinical progression and discontinued treatment before CT evaluation. Thirteen patients with CT-evaluable pancreatic cancer were reported separately. The median TTP (progression-free survival) in PDC patients was 11.9 weeks (range, 2–21.4 weeks) compared to the median TTP of 8 weeks for the preceding treatment.

[0307] A total of 48 patients with diverse cancers had at least one CT evaluation in which the best response and time to progression (TTP) were determined. Summarizing the best response data, among 8 evaluable patients with TNBC (triple-negative breast cancer), 2 achieved PR (partial response), 4 achieved SD (stable disease), and 2 achieved PD (progressive disease), with a total response [PR+SD] of 6 / 8 (75%). In SCLC (small cell lung cancer), among 4 evaluable patients, 2 achieved PR, 0 achieved SD, and 2 achieved PD, with a total response of 2 / 4 (50%). In CRC (colorectal cancer), among 18 evaluable patients, 1 achieved PR, 11 achieved SD, and 6 achieved PD, with a total response of 12 / 18 (67%). In esophageal cancer, among 4 evaluable patients, 1 achieved PR, 2 achieved SD, and 1 achieved PD, with a total response of 3 / 4 (75%). In the case of NSCLC (non-small cell lung cancer), among 5 evaluable patients, 1 showed a partial response (PR), 3 showed stable disease (SD), and 1 showed progressive disease (PD), with a total response rate of 4 / 5 (80%). In all treated patients, among 48 evaluable patients, 7 showed a PR, 27 showed SD, and 14 showed PD, with a total response rate of 34 / 48 (71%). These results indicate that anti-TROP-2 ADC (hRS7-SN-38) demonstrated significant clinical efficacy against a wide range of solid tumors in human patients.

[0308] The reported adverse events associated with the treatment are summarized in Table 6. As is evident from the data in Table 6, the therapeutic efficacy of sacituzumab govitecan was achieved at ADC doses that produced tolerably low levels of adverse side effects. [Table 6]

[0309] An exemplary partial response to anti-Trop-2 ADC was confirmed by CT data (not shown). As an exemplary PR in CRC, a 62-year-old woman initially diagnosed with CRC underwent primary hemicolectomy. Four months later, she underwent hepatectomy due to liver metastases and received 7 months of FOLFOX and 1 month of 5FU treatment. Presenting multiple lesions primarily in the liver (3+Trop-2 by immunohistochemistry), she entered a clinical trial of sacituzumab govitecan at an initial dose of 8 mg / kg one year after initial diagnosis. A PR was achieved on the first CT evaluation, with a 37% reduction in target lesions (not shown). The patient continued treatment and achieved a maximum reduction of 65% at 10 months of treatment, with a decrease in CEA from 781 ng / mL to 26.5 ng / mL (not shown), before progressing 3 months later.

[0310] A 65-year-old male diagnosed with stage IIIB NSCLC (squamous cell carcinoma) is presented as an example of a partial response (PR) in NSCLC. Initial treatment with carboplatin / etoposide (3 months) accompanied by 7000 cGy of XRT resulted in a persistent response for 10 months. Subsequently, erlotinib maintenance therapy was initiated and continued until a trial of sacituzumab govitecan was considered, in addition to undergoing lumbar laminectomy. This patient received the first dose of sacituzumab govitecan after 5 months of erlotinib, at which point he had a 5.6 cm lesion in the right lung with massive pleural effusion. Two months later, immediately after completion of the sixth dose, the initial CT showed a reduction of the initial target lesion to 3.2 cm (not shown).

[0311] A 65-year-old woman diagnosed with poorly differentiated SCLC is presented as an example of a partial response (PR) in SCLC patients. She received carboplatin / etoposide (a Topo-II inhibitor), but discontinued treatment after 2 months due to lack of response. She then continued with topotecan (a Topo-I inhibitor), which was also discontinued after 2 months due to lack of response. She received local XRT (3000 cGy) and discontinued treatment after 1 month. However, disease progression continued until the following month. The patient initiated sacituzumab govitecan the following month (12 mg / kg, reduced to 6.8 mg / kg, Trop-2 expression 3+), and two months after starting sacituzumab govitecan, a 38% reduction in target lesions occurred, including a substantial reduction in major lung lesions (not shown). The patient progressed 3 months after receiving 12 doses.

[0312] These results are significant because they demonstrate that anti-Trop-2 ADCs were effective even in patients who had failed multiple prior treatments or whose condition had subsequently progressed.

[0313] In conclusion, at the dose used, the primary toxicity was manageable neutropenia, accompanied by minor grade 3 toxicity. Sacituzumab govitecan demonstrated evidence of activity (PR and persistent SD) in relapsed / refractory patients with triple-negative breast cancer, small cell lung cancer, non-small cell lung cancer, colorectal cancer, and esophageal cancer, including patients with a history of relapse to topoisomerase-I inhibitor therapy. These results demonstrate the efficacy of anti-Trop-2 ADCs in a broad range of cancers resistant to existing therapies. Example 5. Recovery and analysis of circulating tumor cells (CTCs) and cfDNA

[0314] CTC cells are collected from the blood of patients with metastatic TNBC. A 7.5 mL whole blood sample is collected in a CELLSAVE® preservative tube for CTC capture using the CELLSEARCH® CTC system (Janssen Diagnostics). A 20 mL whole blood sample is collected in an EDTA tube and the plasma is treated for cfDNA as disclosed in Page et al. (2013, PLoS One 8:e77963). The cfDNA is circulated using QIAAMP® according to the manufacturer's instructions. CTCs are isolated from 3 mL of plasma using the Nucleic Acid Kit (Qiagen). Single CTCs are isolated using the DEPARRAY® system, and the CTC nucleic acids undergo AMPLI1® whole-genome amplification.

[0315] Custom AMPLISEQ® panels (Fisher) are for the following genes: 53BP1, AKT1, AKT2, AKT3, APE1, ATM, ATR, BARD1, BAP1, BLM, BRAF, BRCA1, BRCA2, BRIP1 (FANCJ), CCND1, CCNE1, CEACAM5, CDKN1, CDK12, CHEK1, CHEK2, CK-19, CSA, CSB, DCLRE1C, DNA2, DSS1, EEPD1, EFHD1, EpCAM, ERCC1, ESR1, EXO1, FAAP24, FANC1, FANCA, FANCC, FANCD1, FANCD2, FANCE, FANCF, FANCM, HER2, HMBS, HR23B, KRT19, KU70, KU80, hMAM, MAGEA1, MAG EA3, MAPK, MGP, MLH1, MRE11, MRN, MSH2, MSH3, MSH6, MUC16, NBM, NBS1, NER, NF-κB, P53, PALB2, PARP1 , PARP2, PIK3CA, PMS2, PTEN, RAD23B, RAD50, RAD51, RAD51AP1, RAD51C, RAD51D, RAD52, RAD54, RAF, K- It is designed to screen for mutations in ras, H-ras, N-ras, RBBP8, c-myc, RIF1, RPA1, SCGB2A2, SLFN11, SLX1, SLX4, TMPRSS4, TP53, TROP-2, USP11, VEGF, WEE1, WRN, XAB2, XLF, XPA, XPC, XPD, XPF, XPG, XRCC4, and XRCC7. The AMPLISEQ® reaction is set up using 10 ng of WGA DNA or 8 ng of cfDNA. Next-generation sequencing is performed on an Ion 316® chip (ThermoFisher) using an ION PERSONAL GENOME MACHINE® (ThermoFisher) as described by Guttery et al. (2015, Clin Chem 61:974-82). The selected mutations are validated by droplet digital PCR using the Bio-Rad QX200® droplet digital PCR system, as described by Hindson et al. (2011, Anal Chem 83:8604-10).The expression level of Trop-2 in CTCs is determined by ELISA using the RS7 anti-Trop-2 antibody.

[0316] Patients are treated with a combination therapy of olaparib (200-300 mg twice daily for 21 days, depending on the patient's calculated creatinine clearance) and sacituzumab govitecan (10 mg / kg IV, on days 1 and 8 of each 21-day cycle).

[0317] Patients are divided into responders (CR+PR+SD>6 months) and non-responders to combination therapy. Correlations between susceptibility to combination therapy and biomarker data of CTC and cfDNA, as well as Trop-2 expression, indicate that susceptibility to olaparib and SG combination therapy is positively correlated with Trop-2 expression and mutations in BRCA1, BRCA2, PTEN, ERCC1, and ATM. These biomarkers will be used as positive indicators for future treatment with combination therapy of a PARP inhibitor and sacituzumab govitecan. Example 6. Treatment of recurrent metastatic ovarian cancer using sacituzumab govitecan + CHK1 inhibitor prexasertib (LY2606368)

[0318] A 66-year-old woman with FIGO stage IV ovarian cancer positive for BRCA1 mutation underwent primary surgery followed by postoperative paclitaxel and carboplatin (TC). After a 20-month platinum-free period, elevated CA125 levels and peritoneal recurrence were confirmed by CT. Following retreatment with TC, a hypersensitivity reaction to carboplatin occurred, and the treatment was changed to nedaplatin. Complete response was confirmed by CT. Eight months after PFI, elevated serum CA125 levels and recurrence in the peritoneum and liver were confirmed.

[0319] Subsequently, combination therapy with an anti-Trop-2 ADC (sacituzumab govitecan) and the CHK1 inhibitor prexasertib is administered. Sacituzumab govitecan is administered at 10 mg / kg on days 1 and 8 of a 28-day cycle, and prexasertib is administered at 105 mg / m² every 14 days of a 28-day cycle. 2It is administered intravenously. Aside from transient grade 2 neutropenia and some early diarrhea, the treatment is well tolerated, and another course is repeated after a 2-month break. Radiographic examination shows a 45% reduction in the total diameter of the indicator lesions, indicating a partial response according to RECIST criteria. The patient's general condition also improves, and their activity level returns to almost the same level as before the illness. Example 7. Cell surface expression of Trop-2 in normal versus cancerous tissue.

[0320] The expression and localization of Trop-2 were determined by immunohistochemistry (IHC) in a series of normal tissue samples and corresponding cancer tissues. Trop-2 was typically expressed in a lower proportion of normal tissue samples and showed weaker IHC staining intensity compared to corresponding cancer tissues (Table 7). In tumor cells, Trop-2 overexpression was mostly vesicular. However, in the relevant normal tissues, vesicular Trop-2 expression was typically weak or not observed. [Table 7] 1.Bignotti E,et al.Eur J Cancer.2010;46:944-953.2.Ohmachi T,et al.Clin Cancer Res.2006;12:3057-3063.3.Muhlmann G,et al.J Clin Pathol.2009;62:152-158.4.Fong D,et al.Mod Pathol.2008;21:186-191.5.Fong D, et al.Br J Cancer.2008;99:1290-1295. * * *

[0321] From the above description, it will be readily apparent to those skilled in the art that the essential features of the present invention can be modified and adapted in various ways to suit various uses and conditions without departing from its spirit and scope and without excessive experimentation. All patents, patent applications, and publications cited herein are incorporated by reference. [ka]

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Claims

[Claim 1] The invention as shown in the drawings.

Images