Abstract LB-149: Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy
Authors: Avinash Das, Joo Sang Lee, Gao Zhang, Zhiyong Wang, Arnaud Amzallag, Genevieve Boland, Sridhar Hannenhalli, Meenhard Herlyn, Cyril Benes, J. Silvio Gutkind, Keity Flaherty, Eytan Ruppin
Journal: Cancer Research (2019)

Abstract Background: Most patients with advanced cancer eventually acquire resistance to targeted therapies, spurring extensive efforts to identify molecular events mediating therapy resistance. Here we demonstrate that many of these molecular events involve synthetic rescue (SR) genetic interactions, where the reduction in cancer cell viability caused by targeted gene inactivation is rescued by an adaptive alteration of another gene (the rescuer). Methods: Analyzing recently published large scale in vitro functional screens we identify 100,000s candidate SR interactions that show evidence of rescue events in cancer cell lines. We then analyze tumor transcriptomic, genomic, and genetic profiles together with survival and clinical characteristics of 10,000 TCGA cancer patients to identify the few thousand SR interactions that have strong evidence that they are mediators of emerging resistance in patient tumors. Results: We identify the first rescue network, composed of SR interactions common to many cancer types. The identified SRs successfully match the resistance mediators identified in recently published clinical studies. We perform multiple in vitro analyses in head and neck and lung cancer, showing that targeting predicted rescuer genes successfully re-sensitizes resistant cancer cells, providing specific leads for targeting resistance proactively. We further demonstrate that SR-based combination therapy can improve the progression free survival in mouse xenografts models. Notably, we show that SR interactions successfully predict cancer patients' response in the TCGA compendium, showing performance superior to existing machine learning based predictive models. Finally, we show that SR analysis of melanoma patients successfully identifies known mediators of resistance to checkpoint immunotherapy (reported previously in mice) and suggests new combination therapies that counteract the resistance. Conclusions: This work presents a new paradigm identifying and harnessing synthetic rescue interactions to counteract resistance to both targeted- and immuno-therapies. Future implementations of this approach will have two broad implications in the precision oncology era: first for determining the most effective treatment regimen based on the molecular characteristics of individual patient’s tumor; second for identifying conjunct drugs to counteract resistance to existing primary therapies, for both targeted and immune checkpoint therapies. Citation Format: Avinash Das, Joo Sang Lee, Gao Zhang, Zhiyong Wang, Arnaud Amzallag, Genevieve Boland, Sridhar Hannenhalli, Meenhard Herlyn, Cyril Benes, J. Silvio Gutkind, Keity Flaherty, Eytan Ruppin. Genome-wide prediction of synthetic rescue mediators of resistance to targeted and immunotherapy [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr LB-149.