Abstract PR013: Detecting pairwise and higher-order antagonistic epistatic effects among somatic cancer genotypes to discover synthetic lethality

Abstract The mutual exclusivity of somatic variants in cancer suggests that current somatic variants can exert antagonistic epistatic effects on the selection of new mutations, contributing to a complex landscape of evolutionary trajectories. However, quantifying pairwise and higher-order epistatic effects—which are essential to estimation of the trajectory of likely cancer genotypes—has been a challenge. We have developed a continuous-time Markov chain model that enables the estimation of mutation origination and fixation, dependent on somatic cancer genotype. We coupled the continuous-time Markov chain model with an approach that deconvolutes the underlying mutation rates and selection intensities across trajectories of oncogenesis. By elucidating the routes of variant evolution and the strengths of selective forces at play, our approach lays the groundwork for quantifying antagonistic epistatic effects of specific somatic genotypes. We applied our approach to report the variant mutation rates, selection intensities, and consequent substitution rates for lung adenocarcinoma, comparing smoker and nonsmoker tumor cohorts. We describe the distinct influences of smoking on underlying mutation rates and on physiology affecting the selective regime of lung tissue. Inference of the most likely routes of site-specific variant evolution, as well as estimation of the selection strength operating on each step along the route represents a key component for prioritization, development, and implementation of personalized cancer therapies that target synthetic lethality. Citation Format: Jorge A. Alfaro-Murillo, Krishna Dasari, Jeffrey P. Townsend. Detecting pairwise and higher-order antagonistic epistatic effects among somatic cancer genotypes to discover synthetic lethality abstract. In: Proceedings of the AACR Special Conference in Cancer Research: Expanding and Translating Cancer Synthetic Vulnerabilities; 2024 Jun 10-13; Montreal, Quebec, Canada. Philadelphia (PA): AACR; Mol Cancer Ther 2024;23(6 Suppl):Abstract nr PR013.