Salón de Grados, ETSII, 10:00h.

Dr. Simon Syga

 

Cancer is a complex ecosystem where genetic and phenotypic diversity drive tumor evolution, progression, and treatment resistance. Understanding how microscopic cellular processes, such as mutation, proliferation, and migration, shape macroscopic tumor dynamics remains a challenge. In this talk, I present a mathematical modeling framework to study tumor heterogeneity. By linking discrete stochastic models to population genetics and evolutionary game theory, I explore the role of the distribution of fitness effects (DFE) and the evolution of phenotypic plasticity in tumor growth. The findings highlight how spatial dynamics influence cancer evolution and how tumor heterogeneity can predict treatment outcomes. This work provides new insights into cancer progression and potential strategies for therapeutic intervention.