TOP1-DNA Trapping by Exatecan and Combination Therapy with ATR Inhibitor

TOP1-DNA 捕获及与 ATR 抑制剂联合治疗

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作者:Ukhyun Jo, Yasuhisa Murai, Keli K Agama, Yilun Sun, Liton Kumar Saha, Xi Yang, Yasuhiro Arakawa, Sophia Gayle, Kelli Jones, Vishwas Paralkar, Ranjini K Sundaram, Jinny Van Doorn, Juan C Vasquez, Ranjit S Bindra, Woo Suk Choi, Yves Pommier

Abstract

Exatecan and deruxtecan are antineoplastic camptothecin derivatives in development as tumor-targeted-delivery warheads in various formulations including peptides, liposomes, polyethylene glycol nanoparticles, and antibody-drug conjugates. Here, we report the molecular pharmacology of exatecan compared with the clinically approved topoisomerase I (TOP1) inhibitors and preclinical models for validating biomarkers and the combination of exatecan with ataxia telangiectasia and Rad3-related kinase (ATR) inhibitors. Modeling exatecan binding at the interface of a TOP1 cleavage complex suggests two novel molecular interactions with the flanking DNA base and the TOP1 residue N352, in addition to the three known interactions of camptothecins with the TOP1 residues R364, D533, and N722. Accordingly, exatecan showed much stronger TOP1 trapping, higher DNA damage, and apoptotic cell death than the classical TOP1 inhibitors used clinically. We demonstrate the value of SLFN11 expression and homologous recombination (HR) deficiency (HRD) as predictive biomarkers of response to exatecan. We also show that exatecan kills cancer cells synergistically with the clinical ATR inhibitor ceralasertib (AZD6738). To establish the translational potential of this combination, we tested CBX-12, a clinically developed pH-sensitive peptide-exatecan conjugate that selectively targets cancer cells and is currently in clinical trials. The combination of CBX-12 with ceralasertib significantly suppressed tumor growth in mouse xenografts. Collectively, our results demonstrate the potency of exatecan as a TOP1 inhibitor and its clinical potential in combination with ATR inhibitors, using SLFN11 and HRD as predictive biomarkers.

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