SUMMARY
Crosstalk and complexity within signaling pathways, and their perturbation by oncogenes, limits component-by-component approaches to understanding human disease. Network analysis of how normal and oncogenic signaling can be re-wired by drugs may provide opportunities to target tumors with high specificity and efficacy. Using targeted inhibition of oncogenic signaling pathways combined with DNA damaging chemotherapy, we report that time-staggered EGFR inhibition, but not simultaneous co-administration, dramatically sensitizes a subset of triple-negative breast cancer cells to genotoxic drugs. Systems-level analysis—using high-density time-dependent measurements of signaling networks, gene expression profiles, and cell phenotypic responses in combination with mathematical modeling— revealed an approach for altering the intrinsic state of the cell through dynamic re-wiring of oncogenic signaling pathways. This process converts these cells to a less tumorigenic state that is more susceptible to DNA damage-induced cell death by re-activation of an extrinsic apoptotic pathway whose function is suppressed in the oncogene-addicted state.
14-3-3 proteins play critical roles in the regulation of cell fate through phospho-dependent binding to a large number of intracellular proteins that are targeted by various classes of protein kinases. 14-3-3 proteins play particularly important roles in coordinating progression of cells through the cell cycle, regulating their response to DNA damage, and influencing life-death decisions following internal injury or external cytokine-mediated cues. This review focuses on 14-3-3-dependent pathways that control cell cycle arrest and recovery, and the influence of 14-3-3 on the apoptotic machinery at multiple levels of regulation. Recognition of 14-3-3 proteins as signaling integrators that connect protein kinase signaling pathways to resulting cellular phenotypes, and their exquisite control through feedforward and feedback loops, identifies new drug targets for human disease, and highlights the emerging importance of using systems-based approaches to understand signal transduction events at the network biology level.
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