Evolutionary dynamics of cancer on complex stress landscapes

Understanding the evolutionary dynamics of cancer progression requires explicit consideration of both spatial and environmental heterogeneities. We have recently developed a purely diffusion-based cancer-on-chip microfluidic platform, enabling the quantitative study of various cell types on chemotherapeutic gradients on long time scales. In a co-culture of bone-metastatic prostate cancer cells (PC3-EPI) with bone marrow stromal cells (HS5), we found a marked transition in population dominance across a docetaxel gradient. To interpret these results, we employ evolutionary game theory (EGT) as a predictive framework for cancer-stroma dynamics. We generate a spatial interacting-agent EGT model comprised of interconnected habitats in various network topologies. Informed by our experimental findings, we explore distinct strategies utilized by populations under stress by considering system parameters as a function of both space and time as well as by modulating migrational probabilities. This model will be adapted to probe interactions between drug-resistant cancer subpopulations, stromal cells, and immune cells, providing clinical implications for therapeutic approaches.