Abstract IA04: Game theory and personalized cancer treatment

Abstract

Abstract The presence of driver mutations and subsequent clonal expansion by Darwinian evolution does not explain dormancy and re-emergence of cancer from a community of cancer and host cells (including stromal and immune cells). Dormancy appears to be a slow-driven, interaction-dominated, threshold system which is poorly prognosed. At the simplest level, we view cancer cells interacting with host cells via complex, non-linear population dynamics, which can lead to very non-intuitive but perhaps deterministic and understandable progression dynamics of cancer. We explore here the dynamics of host-cancer cell populations in the presence of (1) payoffs gradients and (2) perturbation due to cell migration to determine to what extent the time-dependence of the populations can be quantitatively understood in spite of the underlying complexity of the individual agents. The population dynamics presented here provide a model system for the clinic to map the payoffs matrices and suggest new avenues to predict drug dosages. Citation Format: Robert H. Austin. Game theory and personalized cancer treatment. [abstract]. In: Proceedings of the AACR Special Conference on Engineering and Physical Sciences in Oncology; 2016 Jun 25-28; Boston, MA. Philadelphia (PA): AACR; Cancer Res 2017;77(2 Suppl):Abstract nr IA04.