Funded in Collaboration With Stand Up To Cancer (SU2C)
One of the foremost challenges to cancer treatment is the emergence of drug resistance. Adding complexity to this problem is the realization that both the initial as well as the emergent drug-resistant cancer population can be in highly heterogeneous epigenetic and genetic states and from populations of very different sizes. This heterogeneity makes it difficult to predict which cells will survive drug treatment and which drug-resistance mechanism will emerge, repopulate the cancer cell population and ultimately cause relapse. Our goal is to better understand which cellular subpopulations are predisposed to initially survive targeted therapy, how diverse these subpopulations are from one another, and combination therapies would best target these subpopulations. To accomplish this, we will make use of novel high-throughput assays for drug treatment, genomic and image analysis and mathematical analysis of cellular heterogenity and evolution. These studies will address questions that are central to the fields of cancer biology, modeling, and cancer therapeutics, and allow us to test novel therapeutic approaches that can then be rapidly translated to the clinical context.