Abstract B010: Ecological epistasis can drastically alter evolutionary trajectories on genotypic fitness landscapes, maintaining, masking or mimicking genetic selection in evolutionary simulations

Abstract

Abstract The evolution of drug resistance is broadly understood in terms of the evolution and survival of the genotype that is "fittest" under treatment. There are many computational evolutionary models built upon the assumption that under treatment, cancer cells with the fittest genotype persist and ultimately prevail. Many of these models lack sufficient complexity to predict tumor evolution in the clinic. In particular, the standard Wright-Fisher approach taken from population genetics neither considers nor accurately predicts the heterogeneity that we see in patients and cell-cell interactions are not included. To combat this we develop a model of evolution that incorporates average cell-cell interactions by adding game theoretic interactions to a Wright-Fisher model with mutation and use this to explore and model cases of interest. In our agent-based model we start with N wildtype cells and represent the genotype of each cell with a binary string of n alleles. We represent mutations to the genotype as transitions from 0 to 1 and vice-versa in an allele and each unique genotype is a cell type. Each cell in the non-spatial, well-mixed agent-based model can be selected to reproduce with probability p proportional to the fitness of its genotype and each daughter cell can undergo mutation with probability μ. At each new time step we modify the fitness of each cell type, using the multiplication of the payoff matrix with the cell type frequency vector to reflect the average fitness benefits and costs of cell-cell interactions. We vary the payoff matrices for up to 4 alleles (16 possible genotypes) and show how the addition of these ecological game interactions between different cell populations can modify evolutionary trajectories. We find, for example, that with certain strengths of game interactions, the evolution on an initially selective genotypic landscape can mimic neutral landscapes and vice versa. We term this addition of ecological game interactions to genotypic landscapes "ecological epistasis". We derive mathematical expressions for the equilibrium population distribution in the single allele (two genotype) with arbitrary games case. We also derive expressions for the payoff matrices required to mimic selective games and to make selective landscapes neutral. Furthermore we derive an expression for the curvature of the resultant population distribution, producing a "game signature” with which to probe temporal evolutionary data for the presence of games. This model emphasizes that the emergence of a dominant cell-type can be caused by both ecological and genotypic factors and conversely that the genotypic landscape does not need to be neutral for heterogeneity to persist. Due to the multiclonal and heterogeneous nature of tumors and their microenvironment, these results are of key importance in considering treatment approaches and interpreting existing patient data. We highlight how game interactions may explain heterogeneous patient outcomes and contradicting results on the fitness of cancer genotypes in the literature. Citation Format: Steph J. Owen, Michael Hinczewski, Jacob G. Scott. Ecological epistasis can drastically alter evolutionary trajectories on genotypic fitness landscapes, maintaining, masking or mimicking genetic selection in evolutionary simulations [abstract]. In: Proceedings of the AACR Special Conference on the Evolutionary Dynamics in Carcinogenesis and Response to Therapy; 2022 Mar 14-17. Philadelphia (PA): AACR; Cancer Res 2022;82(10 Suppl):Abstract nr B010.