Abstract 2835: Temporal sequencing of anticancer drugs, ex vivo, optimizes therapeutic effect by targeting drug-induced glucose-6-phosphate dehydrogenase

Abstract

Abstract Background: Phenotypic cell state transitions are emerging as novel drivers of transient resistance to cancer chemotherapy. We recently demonstrated that non-cancer stem cells are able to undergo a phenotypic cell state transition that enables acquire a ‘reversible' drug tolerant state. Consequently, we made two key discoveries, drug tolerance 1) results in a cross-resistance to other classes of anticancer drugs 2) coincidental to a switch in the metabolic behavior. Further, evidences prompted to investigate if drug-induced metabolic reprogramming contributes to combination therapy resistance in a population of cancer cells that have gained tolerance to a primary therapy. Methods: We investigated the metabolic phenotype of drug tolerant cells using 3-D in-vitro models of breast cancer. A systems biology approach was used to identify key, interconnecting proteins involved in metabolic dysregulation, drawing inferences among signaling networks and events in a temporal context. Using an in-silico simulation we perturbed glucose metabolism, and tested how timing, combination and drug order impact the therapeutic effect of combination therapy and validated our findings using in-vivo experiments. Finally, to provide a direct clinical translation, we tested temporally-sequenced 3-drug combinations using CANscriptTM, a human explant tumor assay that captures the entire tumor ecosystem. Results: We report that conventional chemotherapies used to treat breast cancer, results in an adaptive cross-tolerance against an unrelated chemotherapeutic agent via induction of both glycolytic and oxidative pathways. These drug-tolerant cells switch to a CD44Hi phenotypic cell state, and rely on both the Akt pathway and HIF1α-Glut1 axis in a reactive oxygen species-dependent manner, which temporally cooperate to remodel a glucose shunt towards the pentose phosphate pathway. Mathematically modeling these pathways, we demonstrate how a sequentially-applied, 3-drug combination that includes G6PD metabolic inhibitors and cytotoxic agents can improve therapeutic effect. The use of CANscriptTM demonstrated that pharmacodynamics, biomarkers of resistance, and temporal ordering of drugs can influence the phenotypic response to therapy, reflecting in-vitro and in-vivo evidence, in a patient-specific manner. Conclusions: Timing, sequence and order of drugs is emerging as a critical component of combination therapy for cancer. Our results demonstrate that timing the order of G6PD inhibitors in exquisitely sequenced combination with chemotherapy can emerge as a new paradigm in the treatment of cancer. Ex-vivo, human tumor models that fully capture the tumor microenvironment can contribute to and potentially uncover the mechanisms of action, phenotypic effect, and pharmacodynamics of anticancer drug combinations in distinct temporal sequences. Citation Format: Baraneedharan Ulaganathan, Andrew Dhawan, Biswanath Majumder, Munisha Smalley, Saravanan Thiyagarajan, Gopinath S. Kodaganur, S Krishnamurthy, Mohammed Mamunur Rahman, Elizaveta Freinkman, Pradip Majumder, Mohammad Kohandel, Aaron Goldman. Temporal sequencing of anticancer drugs, ex vivo, optimizes therapeutic effect by targeting drug-induced glucose-6-phosphate dehydrogenase [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2835.