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Issue 304: Tumor heterogeneity is a major obstacle to effective cancer treatment. Multiple factors, including irreversible mutations and reversible phenotypic changes, cause it. But how can we model the interplay between both processes and what's their effect on cancer treatment? Our new study sheds light on this interplay, focusing on the phenotypic switch between migration and proliferation, essential in glioblastoma, the most deadly brain tumor. We study this hypothesis using a novel, spatially explicit model that tracks individual cells’ phenotypic and genetic states. When a new cancer cell is born, a mutation can change its genotype and, thereby, its regulation of the phenotypic switch. We observe that cells at the tumor edge evolve to favor migration over proliferation and vice versa in the tumor bulk. The evolutionary process results in a heterogeneous tumor with a dense tumor core of fast-growing cells (teal) and a diffuse rim of invasive cells (brown). Notably, different genetic configurations, i.e., different regulations of the phenotypic switch, can result in this pattern of phenotypic heterogeneity. We investigate implications for cancer treatment and discover that phenotypic, rather than genetic, heterogeneity predicts tumor recurrence after therapy. This offers new insights into the significant variability in glioblastoma recurrence times post-treatment. Based on the paper: Evolution of phenotypic plasticity leads to tumor heterogeneity with implications for therapy published in PLOS Computational Biology.