Novel and Highly Potent ATR Inhibitor M4344 Kills Cancer Cells With Replication Stress, and Enhances the Chemotherapeutic Activity of Widely Used DNA Damaging Agents

Ukhyun Jo, Ilya S Senatorov, Astrid Zimmermann, Liton Kumar Saha, Yasuhisa Murai, Se Hyun Kim, Vinodh N Rajapakse, Fathi Elloumi, Nobuyuki Takahashi, Christopher W Schultz, Anish Thomas, Frank T Zenke, Yves Pommier, Ukhyun Jo, Ilya S Senatorov, Astrid Zimmermann, Liton Kumar Saha, Yasuhisa Murai, Se Hyun Kim, Vinodh N Rajapakse, Fathi Elloumi, Nobuyuki Takahashi, Christopher W Schultz, Anish Thomas, Frank T Zenke, Yves Pommier

Abstract

Although several ATR inhibitors are in development, there are unresolved questions regarding their differential potency, molecular signatures of patients with cancer for predicting activity, and most effective therapeutic combinations. Here, we elucidate how to improve ATR-based chemotherapy with the newly developed ATR inhibitor, M4344 using in vitro and in vivo models. The potency of M4344 was compared with the clinically developed ATR inhibitors BAY1895344, berzosertib, and ceralasertib. The anticancer activity of M4344 was investigated as monotherapy and combination with clinical DNA damaging agents in multiple cancer cell lines, patient-derived tumor organoids, and mouse xenograft models. We also elucidated the anticancer mechanisms and potential biomarkers for M4344. We demonstrate that M4344 is highly potent among the clinically developed ATR inhibitors. Replication stress (RepStress) and neuroendocrine (NE) gene expression signatures are significantly associated with a response to M4344 treatment. M4344 kills cancer cells by inducing cellular catastrophe and DNA damage. M4344 is highly synergistic with a broad range of DNA-targeting anticancer agents. It significantly synergizes with topotecan and irinotecan in patient-derived tumor organoids and xenograft models. Taken together, M4344 is a promising and highly potent ATR inhibitor. It enhances the activity of clinical DNA damaging agents commonly used in cancer treatment including topoisomerase inhibitors, gemcitabine, cisplatin, and talazoparib. RepStress and NE gene expression signatures can be exploited as predictive markers for M4344.

Trial registration: ClinicalTrials.gov NCT02278250 NCT04149145.

©2021 The Authors; Published by the American Association for Cancer Research.

Figures

Figure 1.
Figure 1.
Comparison between M4344 and other clinical ATR inhibitors. A, Chemical structures of ATR inhibitors. B, Comparative analysis of cell viability between clinical ATR inhibitors. DU145 cells were treated as indicated for 72 hours. Cell viability was accessed by CellTiter-Glo assay. CF, Synergistic effects between ATR inhibitors and camptothecin (CPT). Cells were co-incubated with CPT (100 nmol/L) and M4344 (C), BAY1895344 (D), berzosertib (E), and ceralasertib (F) as indicated concentrations for 72 hours. Cell viability was accessed by CellTiter-Glo assay. G, Comparison of combination index values obtained for combination treatments of CPT (6.3 and 12.5 nmol/L) with the indicated ATR inhibitors. H, Inactivation of ATR-mediated CHK1 phosphorylation by ATR inhibitors. DU145 cells were pretreated with the indicated concentrations of ATR inhibitors for 1 hour and then incubated with CPT (100 nmol/L) and the ATR inhibitors for three additional hours. Protein levels were examined by Western blotting (see Supplementary Fig. S1 for effects of M4344 in H82 and U2OS cells).
Figure 2.
Figure 2.
M4344 kills cancer cells under replication stress (RepStress) and with NE genomic signatures by replication-mediated DNA damage. A, Cytotoxicity of M4344 as monotherapy in 16 cancer cell lines from different histology. Following incubation with the indicated concentrations of M4344 for 72 hours, cell viability was accessed by CellTiter-Glo assay. B, Correlations between protein levels related to DNA damage response pathways and M4344 sensitivity. Protein levels were mined from the CCLE cell line database. Correlation heatmap between protein levels and IC50 values of M4344 in A were generated by CellMinerCDB (http://discover.nci.nih.gov/cellminercdb). C, Correlation of RepStress signature scores in the GDSC databases with M4344 activity obtained in A. Plots were generated with CellMinerCDB. D, Correlation of NE signature scores in the GDSC databases with M4344 activity in A. Plots were generated by CellMinerCDB. E and F, Gene dependency of M4344 response. Dependency scores of ARID1A and BRG1were mined from the Project Achilles from CCLE. Plots were generated with CellMinerCDB. P values indicate Pearson correlation coefficients. G, Biphasic effect of M4344 on DNA synthesis. H82 cells treated as indicated were pulse-labeled with EdU (10 μmol/L) 30 minutes prior to harvest. Edu incorporation per cell was analyzed by FACS. Numbers indicate percentage of cells in the areas. H, Induction of DNA damage detected by γH2AX Western blotting. Cells were incubated with the indicated concentrations of M4344 for 24 hours.
Figure 3.
Figure 3.
M4344 synergizes clinical TOP1 inhibitors. AD, H82 cells were co-incubated with M4344 (25 nmol/L) and the indicated concentrations of exatecan (A), SN-38 (B), topotecan (C), and indotecan (LMP400; D) for 72 hours. E and F, Conversely, H82 cells were co-incubated with the indicated concentrations of M4344 and exatecan (E, 0.25 nmol/L), SN-38 (F, 1 nmol/L), topotecan (G, 10 nmol/L), and indotecan (LMP400; H, 10 nmol/L) for 72 hours. IL, Synergy of M4344 with topotecan in four additional cell lines: SK-OV-3 (I), DMS114 (J), U2OS (K), and A549 (L). Cells were cotreated with M4344 (25 nmol/L) and the indicated concentrations of topotecan for 72 hours. Cell viability was accessed by CellTiter-Glo assay. Synergy plots are presented in Supplementary Fig. S3.
Figure 4.
Figure 4.
M4344 shows synergy with etoposide, gemcitabine, cisplatin, and talazoparib. AD, H82 cells were co-incubated with a nontoxic concentration of M4344 (25 nmol/L) and the indicated concentrations of etoposide (A), gemcitabine (B), cisplatin (C), and talazoparib (D) for 72 hours. EH, H82 cells were coincubated with the indicated concentrations of M4344 and etoposide (E, 1 μmol/L), gemcitabine (F, 1 nmol/L), cisplatin (G, 0.5 μmol/L), and talazoparib (H, 5 nmol/L) for 72 hours. Cell viability was accessed by CellTiter-Glo assay. Synergy plots are presented in Supplementary Fig. S4.
Figure 5.
Figure 5.
M4344 synergizes with topotecan in patient derived prostate tumor organoids. AD, LuCaP 145.2 (A), LuCaP 173.1 (B), MB155 (C), and MB44 (D) organoids were incubated with a noncytotoxic concentration of M4344 (25 nmol/L) and the indicated concentrations of topotecan for 72 hours. Cell viability was quantified using CellTiter-Glo 3D. Data shown are the mean ± SEM (N = 4 for each group). P values indicate statistical difference between groups (topotecan vs. combination; *, P values < 0.0001). E, Bar graph representing normalized AUC values calculated by measuring changes in cell viability of organoids treated as indicated. Data shown are the mean ± SEM (N = 4 for each group; *, P values < 0.0001).
Figure 6.
Figure 6.
Efficacy of the combination of M4344 with irinotecan in human small-cell lung cancer tumor xenografts and schematic flow chart summarizing this study. AD, The in vivo efficacy of M4344 was evaluated in mice transplanted with H82 (A) and H446 (B) cells. Mice received subcutaneous injections in the right flank with cancer cells (in PBS/Matrigel). Mice received M4344 at an oral dose of 10 mg/kg, irinotecan at an intraperitoneal dose of 50 mg/kg or the combination thereof. Both compounds were applied once weekly, the treatment duration was 2 weeks for the H82 and 5 weeks for the H446. For the combination M4344 was applied 24 hours after Irinotecan. Tumor volumes are shown as mean ± SEM (N = 10 mice for each group). C and D, Benefits of progression-free survival by combination treatment, compared with control treatment and either monotherapy. E, M4344 inhibits activation of the ATR signaling pathway, thereby consequently blocking signal transduction from replicative DNA damage. After M43444 treatment, cells undergo replication catastrophe with DNA damage and mitotic defects, leading to cell death. Gene expression signatures including replication stress (RepStress), NE signature, and SWI/SNF inactivation are candidate predictive markers for M4344 in cancer therapy.

References

    1. Jackson SP, Bartek J. The DNA-damage response in human biology and disease. Nature 2009;461:1071–8.
    1. Roos WP, Thomas AD, Kaina B. DNA damage and the balance between survival and death in cancer biology. Nat Rev Cancer 2016;16:20–33.
    1. Ma J, Setton J, Lee NY, Riaz N, Powell SN. The therapeutic significance of mutational signatures from DNA repair deficiency in cancer. Nat Commun 2018;9:3292.
    1. Kantidze OL, Velichko AK, Luzhin AV, Petrova NV, Razin SV. Synthetically lethal interactions of ATM, ATR, and DNA-PKcs. Trends Cancer 2018;4:755–68.
    1. O'Connor MJ. Targeting the DNA damage response in cancer. Mol Cell 2015;60:547–60.
    1. Ubhi T, Brown GW. Exploiting DNA replication stress for cancer treatment. Cancer Res 2019;79:1730–9.
    1. Blackford AN, Jackson SP. ATM, ATR, and DNA-PK: the trinity at the heart of the DNA damage response. Mol Cell 2017;66:801–17.
    1. Saldivar JC, Cortez D, Cimprich KA. The essential kinase ATR: ensuring faithful duplication of a challenging genome. Nat Rev Mol Cell Biol 2017;18:622–36.
    1. Karnitz LM, Zou L. Molecular pathways: targeting ATR in cancer therapy. Clin Cancer Res 2015;21:4780–5.
    1. Lecona E, Fernandez-Capetillo O. Targeting ATR in cancer. Nat Rev Cancer 2018;18:586–95.
    1. Gorecki L, Andrs M, Rezacova M, Korabecny J. Discovery of ATR kinase inhibitor berzosertib (VX-970, M6620): clinical candidate for cancer therapy. Pharmacol Ther 2020;210:107518.
    1. Bradbury A, Hall S, Curtin N, Drew Y. Targeting ATR as cancer therapy: a new era for synthetic lethality and synergistic combinations? Pharmacol Ther 2020;207:107450.
    1. Wengner AM, Siemeister G, Lucking U, Lefranc J, Wortmann L, Lienau P, et al. . The novel ATR inhibitor BAY 1895344 is efficacious as monotherapy and combined with DNA damage-inducing or repair-compromising therapies in preclinical cancer models. Mol Cancer Ther 2020;19:26–38.
    1. Thomas A, Redon CE, Sciuto L, Padiernos E, Ji J, Lee MJ, et al. . Phase I study of ATR inhibitor M6620 in combination with topotecan in patients with advanced solid tumors. J Clin Oncol 2018;36:1594–602.
    1. Yap TA, O'Carrigan B, Penney MS, Lim JS, Brown JS, de Miguel Luken MJ, et al. . Phase I trial of first-in-class ATR inhibitor M6620 (VX-970) as monotherapy or in combination with carboplatin in patients with advanced solid tumors. J Clin Oncol 2020;38:3195–204.
    1. Dillon MT, Boylan Z, Smith D, Guevara J, Mohammed K, Peckitt C, et al. . PATRIOT: a phase I study to assess the tolerability, safety and biological effects of a specific ataxia telangiectasia and Rad3-related (ATR) inhibitor (AZD6738) as a single agent and in combination with palliative radiation therapy in patients with solid tumours. Clin Transl Radiat Oncol 2018;12:16–20.
    1. Rawlinson R, Massey AJ. gammaH2AX and Chk1 phosphorylation as predictive pharmacodynamic biomarkers of Chk1 inhibitor-chemotherapy combination treatments. BMC Cancer 2014;14:483.
    1. Williamson CT, Miller R, Pemberton HN, Jones SE, Campbell J, Konde A, et al. . ATR inhibitors as a synthetic lethal therapy for tumours deficient in ARID1A. Nat Commun 2016;7:13837.
    1. Wang C, Wang G, Feng X, Shepherd P, Zhang J, Tang M, et al. . Genome-wide CRISPR screens reveal synthetic lethality of RNASEH2 deficiency and ATR inhibition. Oncogene 2019;38:2451–63.
    1. Qiu Z, Fa P, Liu T, Prasad CB, Ma S, Hong Z, et al. . A genome-wide pooled shRNA screen identifies PPP2R2A as a predictive biomarker for the response to ATR and CHK1 inhibitors. Cancer Res 2020;80:3305–18.
    1. Dunlop CR, Wallez Y, Johnson TI, de Quirós Fernández SB, Durant ST, Cadogan EB, et al. . Complete loss of ATM function augments replication catastrophe induced by ATR inhibition and gemcitabine in pancreatic cancer models. Br J Cancer 2020;123:1424–36.
    1. Tan MSY, Sandanaraj E, Chong YK, Lim SW, Koh LWH, Ng WH, et al. . A STAT3-based gene signature stratifies glioma patients for targeted therapy. Nat Commun 2019;10:3601.
    1. Nishiwada S, Sho M, Cui Y, Yamamura K, Akahori T, Nakagawa K, et al. . A gene expression signature for predicting response to neoadjuvant chemoradiotherapy in pancreatic ductal adenocarcinoma. Int J Cancer 2021;148:769–79.
    1. Mazo C, Barron S, Mooney C, Gallagher WM. Multi-gene prognostic signatures and prediction of pathological complete response to neoadjuvant chemotherapy in ER-positive, HER2-negative breast cancer patients. Cancers 2020;12:1133.
    1. de Klein A, Muijtjens M, van Os R, Verhoeven Y, Smit B, Carr AM, et al. . Targeted disruption of the cell-cycle checkpoint gene ATR leads to early embryonic lethality in mice. Curr Biol 2000;10:479–82.
    1. Zhang N, Fu JN, Chou TC. Synergistic combination of microtubule targeting anticancer fludelone with cytoprotective panaxytriol derived from panax ginseng against MX-1 cells in vitro: experimental design and data analysis using the combination index method. Am J Cancer Res 2016;6:97–104.
    1. Tlemsani C, Pongor L, Elloumi F, Girard L, Huffman KE, Roper N, et al. . SCLC-CellMiner: a resource for small cell lung cancer cell line genomics and pharmacology based on genomic signatures. Cell Rep 2020;33:108296.
    1. Zhang W, Girard L, Zhang YA, Haruki T, Papari-Zareei M, Stastny V, et al. . Small cell lung cancer tumors and preclinical models display heterogeneity of neuroendocrine phenotypes. Transl Lung Cancer Res 2018;7:32–49.
    1. Rajapakse VN, Luna A, Yamade M, Loman L, Varma S, Sunshine M, et al. . CellMinerCDB for integrative cross-database genomics and pharmacogenomics analyses of cancer cell lines. iScience 2018;10:247–64.
    1. Tsherniak A, Vazquez F, Montgomery PG, Weir BA, Kryukov G, Cowley GS, et al. . Defining a cancer dependency map. Cell 2017;170:564–76.
    1. Beshiri ML, Tice CM, Tran C, Nguyen HM, Sowalsky AG, Agarwal S, et al. . A PDX/Organoid biobank of advanced prostate cancers captures genomic and phenotypic heterogeneity for disease modeling and therapeutic screening. Clin Cancer Res 2018;24:4332–45.
    1. Drost J, Karthaus WR, Gao D, Driehuis E, Sawyers CL, Chen Y, et al. . Organoid culture systems for prostate epithelial and cancer tissue. Nat Protoc 2016;11:347–58.
    1. Therasse P, Arbuck SG, Eisenhauer EA, Wanders J, Kaplan RS, Rubinstein L, et al. . New guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst 2000;92:205–16.
    1. Zenke FT, Zimmermann A, Dahmen H, Elenbaas B, Pollard J, Reaper P, et al. . Antitumor activity of M4344, a potent and selective ATR inhibitor, in monotherapy and combination therapy. Cancer Res 2019;79:p.369.
    1. Josse R, Martin SE, Guha R, Ormanoglu P, Pfister TD, Reaper PM, et al. . ATR inhibitors VE-821 and VX-970 sensitize cancer cells to topoisomerase i inhibitors by disabling DNA replication initiation and fork elongation responses. Cancer Res 2014;74:6968–79.
    1. Thomas A, Pommier Y. Targeting topoisomerase I in the era of precision medicine. Clin Cancer Res 2019;25:6581–9.
    1. Thomas A, Pommier Y. Small cell lung cancer: time to revisit DNA-damaging chemotherapy. Sci Transl Med 2016;8:346fs12.
    1. Gupta M, Concepcion CP, Fahey CG, Keshishian H, Bhutkar A, Brainson CF, et al. . BRG1 loss predisposes lung cancers to replicative stress and ATR dependency. Cancer Res 2020;80:3841–54.
    1. Shao RG, Cao CX, Zhang H, Kohn KW, Wold MS, Pommier Y. Replication-mediated DNA damage by camptothecin induces phosphorylation of RPA by DNA-dependent protein kinase and dissociates RPA:DNA-PK complexes. EMBO J 1999;18:1397–406.
    1. Toledo LI, Altmeyer M, Rask MB, Lukas C, Larsen DH, Povlsen LK, et al. . ATR prohibits replication catastrophe by preventing global exhaustion of RPA. Cell 2013;155:1088–103.
    1. Coussy F, El-Botty R, Chateau-Joubert S, Dahmani A, Montaudon E, Leboucher S, et al. . BRCAness, SLFN11, and RB1 loss predict response to topoisomerase I inhibitors in triple-negative breast cancers. Sci Transl Med 2020;12:eaax2625.
    1. Murai J, Thomas A, Miettinen M, Pommier Y. Schlafen 11 (SLFN11), a restriction factor for replicative stress induced by DNA-targeting anti-cancer therapies. Pharmacol Ther 2019;201:94–102.
    1. Pommier Y, O'Connor MJ, de Bono J. Laying a trap to kill cancer cells: PARP inhibitors and their mechanisms of action. Sci Transl Med 2016;8:362ps17.
    1. Conteduca V, Oromendia C, Eng KW, Bareja R, Sigouros M, Molina A, et al. . Clinical features of neuroendocrine prostate cancer. Eur J Cancer 2019;121:7–18.
    1. Balanis NG, Sheu KM, Esedebe FN, Patel SJ, Smith BA, Park JW, et al. . Pan-cancer convergence to a small-cell neuroendocrine phenotype that shares susceptibilities with hematological malignancies. Cancer Cell 2019;36:17–34.
    1. Murai J, Feng Y, Yu GK, Ru Y, Tang SW, Shen Y, et al. . Resistance to PARP inhibitors by SLFN11 inactivation can be overcome by ATR inhibition. Oncotarget 2016;7:76534–50.
    1. Jo U, Murai Y, Chakka S, Chen L, Cheng K, Murai J, et al. . SLFN11 promotes CDT1 degradation by CUL4 in DNA damage whilst its absence leads to synthetic lethality with ATR/CHK1 inhibitors. Proc Natl Acad Sci U S A 2021;118:e2015654118.

Source: PubMed

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