Modeling the strategies of interactions between melanoma tumor and CD8+ immune cells using game theory

Abstract

The cooperation between biologists and mathematicians made the new field of research which is called biological modeling. In this study, we employed an agent-based model for modeling tumor-immune interactions. The parameters of the agent-based model are optimized so that the results of the model can follow the experimental data from the animal assay. The probabilities of the tumor-immune interactions are formulated from this model and used to design a mixed game between tumor and immune system. The payoffs and the values of this game are calculated for every time step. The results of the game are compatible with the steady state of the system in the scenario of tumor escaping the immune system. Specifically, evaluating the game value during the simulation time enables us to find the exact moment of changing strategies in favor of tumor to win this game. This game can be used to study the dynamics of the model and how tumor and immune cells select their behavioral strategies during the time and help to get a better understanding of tumor-immune system interactions.