Agent-based models can reveal cancer as a complex, evolving ecosystem shaped by interactions between tumor cells, normal tissue, and the microenvironment. Using prostate cancer and lung cancer examples, Sandy Anderson shows how modeling can uncover the roles of stromal regulation, signaling heterogeneity, and tissue context in tumor evolution and therapy response. Overall, the talk highlights how integrating biological data with computational models can generate hypotheses, improve patient stratification, and deepen understanding of cancer dynamics.