Disruption of the cellular pathway modulating endogenous 24-hour rhythms, referred to as 'the circadian clock', has been recently proven to be associated with cancer risk, development and progression. This pathway operates through a complex network of transcription-translation feedback loops generated by a set of interplaying proteins. The expression of core circadian clock genes is frequently dysregulated in human tumors; however, the specific effects and underlying mechanisms seem to vary depending on the cancer types and are not fully understood. Additionally, specific oncogenes may differentially induce the dysregulation of the circadian clock in tumors. Pharmacological modulation of clock components has been shown to result in specific lethality in certain types of cancer cells, and thus holds great promise as a novel anti-cancer therapeutic approach. Here we present an overview of the rationale and current evidence for targeting the clock in cancer treatment.
Tumor progression results from a complex interplay between cellular heterogeneity, treatment response, microenvironment and heterocellular interactions. 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. Here we present a high-throughput platform for characterizing, with single-cell resolution, the dynamic phenotypic responses (i.e. morphology changes, proliferation, apoptosis) of heterogeneous cell populations both during standard growth and in response to multiple, co-occurring selective pressures. 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. 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. These important features can directly influence tumor evolution and clinical outcome. 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.
A human colorectal cancer chip recapitulates aspects of CRC biology On-chip imaging and metabolomic effluent analyses offer insight into progression Organ-on-chip conditions induce phenotypic heterogeneity compared to 2D cultures Stromal cell cross talk and mechanical forces increase tumor cell intravasation
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