ABSTRACT Targeted cancer therapy, in the form of tyrosine kinase inhibitors, has been a game changer for patients with cancers driven by activating mutations in genes encoding these proteins. Yet, while we are seeing overall survival benefits unlike with any new agents in over a decade, cures remain elusive, or non-existent, as resistance to these agents reliably emerges. The process driving this resistance is the same process that drives invasive pests' resistance to pesticides, pathogens' resistance to antibiotics and many other phenomena in life: Darwinian evolution. While this is being increasingly recognized, it has yet to change the paradigm in cancer research where most projects are centered on a hunt for actionable mutations conferring resistance. While these secondary mutations are often druggable themselves, we submit that this is a never-ending race that evolution will always win. We hypothesize that an approach centered instead on studying the evolutionary process itself can help break this cycle. While there is a robust theoretical literature modeling cancer evolution with mathematics, there is a relative paucity of research connecting this theory to empirical biology or clinical medicine. To address this shortcoming, we have worked for the past three years to develop a first-in-class evolutionary game assay to directly measure the eco-evolutionary interactions driving the emergence of resistance in vitro. This assay allows us to directly parameterize an evolutionary game theoretic model with empiric studies in any system. Here, we propose to extend our initial observations revealing a vast heterogeneity in evolutionary dynamics under different agents in vitro to allow for clinical translation by extend ouring assay to an in vivo system. We posit that the new methods and understanding we will gain during this proposal will benefit the cancer research community as a whole, as well as provide novel opportunities for therapeutic interventions aimed at disrupting and altering the evolutionary mechanisms driving resistance.

NARRATIVE Darwinian evolution drives the emergence of resistance to targeted therapy in cancer. We propose to use results from our in vitro evolutionary game assay to parameterize a computer model to allow us to predict 3-dimensional dynamics on clinically relevant timescales. Further, we will extend our assay to function in vivo, allowing the community to test mathematically derived evolutionary therapy hypotheses in preclinical models.