Abstract Tumor populations are in constant flux as a result of dynamic pressures of their surrounding microenvironment. Measuring the phenotypic response of multiple cell types exposed to physiological relevant tumor conditions has been a challenge due to the heterogenous nature of the tumor microenvironment. Further, traditional cell biology assays for assessing cell viability do not allow for additional downstream analyses and use surrogate measures for cell number, which may fail to provide a complete picture of cellular events. Here, we present a method to utilize high-content screening to generate quantitative, robust data sets characterizing cellular phenotypic responses (i.e. birth, death, morphology) of tumor cells to co-occurring perturbations of drug, oxygen, glucose, ECM stiffness, and stromal cell co-culture. Using an Operetta high-content imaging platform, we are able to perform multiple analyses on the same experimental setup to quantitatively assess the evolutionary dynamics of heterogenous cell populations under multiple environmental perturbations. We are able to differentiate between the effect of microenvironmental conditions on a decrease in cell birth versus increase in cell death, which has significant implications for predicting tumor growth kinetics and drug treatment response. We applied this platform to analyze isogenic lung tumor cells that are either sensitive or resistant to erlotinib, a commonly used tyrosine receptor kinase inhibitor in the treatment of lung cancer. We identified specific microenvironmental contexts where the resistant populations have a fitness advantage over the sensitive population, irrespective of the resistance mechanism. Furthermore, our experimental workflow allows us to capture and quantify cell morphology, an additional measure for overall cell health. We observed significant shifts in specific cell morphological parameters in response to alterations in tumor microenviromental conditions such as low oxygen and increased drug concentration. This novel application of a high-content screening platform allows for the quantification of multiple cellular phenotypes in response to over a hundred different microenvironmental contexts, thus providing deeper insight into the effect of tumor microenvironmental heterogeneity on evolving tumor cell populations. Citation Format: Colleen M. Garvey, Oscar Chen, Jasmine Foo, Shannon M. Mumenthaler. High-content screening to capture tumor dynamics in response to microenvironmental perturbations. [abstract]. In: Proceedings of the AACR Special Conference: Function of Tumor Microenvironment in Cancer Progression; 2016 Jan 7–10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2016;76(15 Suppl):Abstract nr C39.
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