Short Talk: Quantitative experimental platforms to measure the evolutionary dynamics of drug resistance in vitro

Shannon Mumenthaler (September 17, 2014)

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Tumor growth and therapeutic response involve a complex evolutionary process driven in part by a heterogeneous microenvironment. Spatial and temporal gradients of nutrients, oxygen, and drug can create physical niches that drive cellular adaptation and force tumor cells to adopt various strategies to survive. As a result, the tumor microenvironment affects the fitness of cancer cells and influences the overall composition of the tumor. The ability to experimentally capture the heterogeneity of the microenvironment and resulting cellular behavior is imperative for achieving a full understanding of the evolutionary dynamics of a tumor. Mathematical models can have great utility in predicting clinical endpoints when tightly integrated with experimental measurements. Utilizing assays that deliver reproducible, quantitative, and dynamic measurements on physiologically relevant biological model systems can be extremely valuable for calibrating and validating mathematical models. Therefore, we have developed a high-throughput imaging platform that captures detailed information on the behavior of hundreds of thousands of cells in 2D, where we can assess the effects of systematically varying individual environmental parameters, and in 3D, where gradients of environmental factors co-exist. One application of this imaging approach has been to inform a stochastic compartment-based tumor model of pre-existing drug resistance in non-small cell lung cancer. Each compartment represents a specific tumor environmental niche and this integrative modeling framework is then used to predict rebound growth kinetics and tumor composition (i.e. % resistance). In particular, we provide insight into the magnitude by which the microenvironment influences these results and how one might utilize drugs that target the interface between the microenvironment and tumor cells (e.g. TH-302, a hypoxia activated pro-drug) to achieve a better clinical outcome. Identifying, measuring, and targeting tumor heterogeneity is important for the successful treatment of cancer.