Abstract IA014: Detecting epistatic effects among somatic cancer mutations across oncogenesis

Abstract

Abstract The somatic evolution of cancer depends on the rate at which new mutations are acquired, as well as the selective pressure acting on them. Further, mutual exclusivity or co-occurrence of somatic variants suggests that current somatic variants can exert antagonistic or synergistic epistatic effects on the selection of new mutations, contributing to a complex landscape of evolutionary trajectories. However, quantifying these epistatic effects—which are essential to estimation of the trajectory of likely cancer genotoypes—has been a challenge, especially for higher-order epistatic effects. To estimate these epistatic effects, we have developed a continuous-time Markov chain model that enables the estimation of mutation origination and fixation, dependent on somatic cancer genotype. Coupling the continuous-time Markov chain model with a mutation-rate deconvolution approach, we have estimated the underlying mutation rates and selection intensities across trajectories of oncogenesis. Specifically, we report the mutation rates, selection intensities, and consequent variant fluxes for lung adenocarcinoma, informed by a compilation of samples from multiple data sets including The Cancer Genome Atlas and the AACR Project GENIE. Furthermore, we compare smoker and nonsmoker tumor cohorts describing the distinct evolutionary trajectories jointly, influenced by differential mutation and also by the differential physiological effects that smoking can have on the selective regime of lung tissue. Our approach enables 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—a key component of what we need to know to prioritize, develop, and implement personalized cancer therapies. Citation Format: Jorge A. Alfaro-Murillo, Krishna Dasari, Jeffrey P. Townsend. Detecting epistatic effects among somatic cancer mutations across oncogenesis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Translating Cancer Evolution and Data Science: The Next Frontier; 2023 Dec 3-6; Boston, Massachusetts. Philadelphia (PA): AACR; Cancer Res 2024;84(3 Suppl_2):Abstract nr IA014.