![]() ATP levels or DNA content) and the data is expressed as relative events rather than as absolute cell counts. These assays frequently depend on surrogate measurements of cell number (e.g. In particular, they tend to overlook alterations in additional cellular phenotypes, are not amenable to co-culturing different cell types and are prone to missing absolute changes in cell population composition. Although these assays are robust and easy to perform, they often fail to provide a complete picture of cellular events 7. MTS, alamar blue, Annexin V-FITC flow cytometry assay) are widely employed. To determine cellular response to a perturbation, traditional biology assays for cell viability (e.g. Ignoring contextual influences when exploring these areas of research can be misleading. In preclinical studies, it has become increasingly important to capture the heterogeneity of tumors at the cellular and microenvironmental level in order to recapitulate a more realistic environmental context to study tumor progression and therapeutic response 4, 5, 6. Tumors are dynamic, evolving systems whose multi-layered complexity stems from a number of microenvironmental features including oxygen and nutrient gradients and interactions among diverse cell types (host and tumor, different molecular subtypes) 1, 2, 3. Our image-based approach provides a deeper insight into the cellular dynamics and heterogeneity of tumors (or other complex systems), with reduced reagents and time, offering advantages over traditional biological assays. These important features can directly influence tumor evolution and clinical outcome. The platform has been applied to both 2D and 3D culture systems and readily distinguishes between (1) cytotoxic versus cytostatic cellular responses and (2) changes in morphological features over time and in response to perturbation. The speed of this platform enables a thorough investigation of the impacts of diverse selective pressures including genetic alterations, therapeutic interventions, heterocellular components and microenvironmental factors. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. ![]() Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. Existing approaches to characterize this interplay suffer from an inability to distinguish between multiple cell types, often lack environmental context and are unable to perform multiplex phenotypic profiling of cell populations. ![]() Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. ![]()
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