| Abstract | A mathematical model of tumor-immune interactions is presented. The model accounts for tumor-induced immunosuppessive effects, such as increases in TGF-beta and the population of regulatory T cells. In the phase immediately following cytoreductive treatment, the initial state of the immune system is primed for a larger tumor; cytokine concentrations and immune cell populations then undergo a transient decay to equilibrate with the new, lower tumor burden. The dynamic interplay between immunoresponsive and immunosuppressive forces during this transient period is simulated numerically, both for single and multiple cycles of chemotherapy. The model is used to probe the optimization of treatments to maximize immune system efficacy, and to shed light on which suppressive effects are important at different phases of tumor growth and treatment. |
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