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Mathematical models of tumor-immune interactions in the context of chemotherapy

Quantitative Biology Colloquium

Mathematical models of tumor-immune interactions in the context of chemotherapy
Series: Quantitative Biology Colloquium
Location: MATH 402
Presenter: Victoria Gershuny, Program in Applied Mathematics, University of Arizona

In recent years, advances in cancer research have shown that the body’s immune response to tumor cells plays a significant role in fighting cancer growth. Although the immune system is intrinsically capable of destroying tumor cells, tumors and their microenvironment have an ability to suppress the immune response. This talk develops a series of systems of deterministic and stochastic ordinary equations that capture the relationship between tumor cells, the immune system, and chemotherapy to determine the role of different immune cells and molecules in the tumor growth and treatment with the therapeutic cocktail FOLFOX. This model captures the complex interplay between CD4+ and CD8+ T cells, regulatory T cells, NK cells, dendritic cells, MDSCs, and both immunostimulatory (IL-2, IFN-gamma) and immunosuppressive (IL-10, TGF-beta) cytokines or factors, the primary tumor, circulating tumor cells, and tumor metastases. All parameters are estimated from experimental data. The model shows that for a single tumor nodule, NK cells play a negligleable role compared to cytolytic T cells, although this result depends heavily on the tumor antigen expression. For tumors with high antigen expression on their surface, T cells play the primary role in preventing metastasis formation, however circulating tumor cells with low antigen expression are eradicated mostly by NK cells. With this model, it is possible to replicate experimental data of tumor growth and treatment under depletion of NK cells and CD8+ T cells. The extension of this model to give individualized predictions to patients on combinations of chemotherapy and immunotherapy will be discussed.