A Predictive Approach for the Tumor-Immune System Interactions Based on an Agent Based Modeling

The goal of this study is introducing a quantified feature for investigating the quality manner and interaction between the immune system and tumor cell. For this purpose, we introduced an agent based model which uses two agents, consists tumor cell and CD8 cells and the environment which consists IL-2 and TGF-β cytokines. This model works using a variety of ratios. The most important ratio of this model is the tumor’s proliferation ratio. We investigated this ratio in three states of tumor-immune system interaction consist elimination, equilibrium and escape using a raw model, then this ratio investigated using models which optimized by experimental data. The results showed that, if model be leaning to the elimination state, this ratio falls faster and if be leaning to the escape state, this ratio will reduce slowly. This result proved by models which used experimental data for optimizing. Therefore, using this ratio we can compare the different manner of tumor-immune system interactions.