Speaker
Description
The immune system can eradicate cancer, but various immunosuppressive mechanisms active within a tumor curb this beneficial response. Unraveling the effects of multimodal interactions between tumor and immune cells and their contributions to tumor control using an experimental approach alone is time- and resource-intensive. To identify key immunological features associated with tumor control and escape, we built a mathematical model of the interactions between CD8+ T cells, Tregs, DCs, and tumor cells. A distinguishing feature of our model is that it captures Treg accrual occurring after checkpoint blockade immunotherapy. After fitting the model to data from an immunogenic melanoma mouse model showing resistance to αPD-1, we generated hundreds of parameter sets, each representing a unique ‘virtual mouse’ to capture individual variability. Our model indicates that the initial tumor and immune conditions instruct cancer control or progression. Increasing the initial number of CD8+ T cells alone does not always yield better outcomes; instead, the model implies there exist optimal initial immune cell ratios that result in improved tumor control. The model also predicts Treg influx as a key determinant of αPD-1 resistance. All predictions were experimentally validated. Overall, this integrated approach of modeling and experimental validation identified key determinants of resistance to immunotherapy and can be used to guide the development of more effective therapeutic strategies.
