Dynamics of the anti-cancer immune response

With the expanding options for cancer therapy and vast possibilities for drug scheduling, we need quantitative models of the response dynamics to rationally design combination strategies. Our previous research integrated a branching model and ODE models to simulate the dynamics of ovarian cancer clinical course and predict optimal combinations of surgery and chemotherapy for this disease. We also used clonal tracing of cancer cells to characterize the dynamics and heterogeneity of response to immune checkpoint blockade therapy. We aim to further integrate experimental/clinical data and mathematical modeling to quantify the dynamics of the anti-cancer immune response, which can help us gain mechanistic insights into this biological process and optimize combination therapy strategies.