6 research outputs found
Basal-Subtype and MEK-Pl3K Feedback Signaling Determine Susceptibility of Breast Cancer Cells to MEK Inhibition
Specific inhibitors of MEK have been developed that efficiently inhibit the oncogenic RAF-MEK-ERK pathway. We employed a systems-based approach to identify breast cancer subtypes particularly susceptible to MEK inhibitors and to understand molecular mechanisms conferring resistance to such compounds. Basal-type breast cancer cells were found to be particularly susceptible to growth-inhibition by small-molecule MEK inhibitors. Activation of the PI3 kinase pathway in response to MEK inhibition through a negative MEK-EGFR-PI3 kinase feedback loop was found to limit efficacy. Interruption of this feedback mechanism by targeting MEK and PI3 kinase produced synergistic effects, including induction of apoptosis and, in some cell lines, cell cycle arrest and protection from apoptosis induced by proapoptotic agents. These findings enhance our understanding of the interconnectivity of oncogenic signal transduction circuits and have implications for the design of future clinical trials of MEK inhibitors in breast cancer by guiding patient selection and suggesting rational combination therapies
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Bayesian Network Inference Modeling Identifies TRIB1 as a Novel Regulator of Cell-Cycle Progression and Survival in Cancer Cells
Molecular networks governing responses to targeted therapies in cancer cells are complex dynamic systems that demonstrate nonintuitive behaviors. We applied a novel computational strategy to infer probabilistic causal relationships between network components based on gene expression. We constructed a model comprised of an ensemble of networks using multidimensional data from cell line models of cell-cycle arrest caused by inhibition of MEK1/2. Through simulation of a reverse-engineered Bayesian network model, we generated predictions of G1-S transition. The model identified known components of the cell-cycle machinery, such as CCND1, CCNE2, and CDC25A, as well as revealed novel regulators of G1-S transition, IER2, TRIB1, TRIM27. Experimental validation of model predictions confirmed 10 of 12 predicted genes to have a role in G1-S progression. Further analysis showed that TRIB1 regulated the cyclin D1 promoter via NFκB and AP-1 sites and sensitized cells to TRAIL-induced apoptosis. In clinical specimens of breast cancer, TRIB1 levels correlated with expression of NFκB and its target genes (IL8, CSF2), and TRIB1 copy number and expression were predictive of clinical outcome. Together, our results establish a critical role of TRIB1 in cell cycle and survival that is mediated via the modulation of NFκB signaling. Cancer Res; 77(7); 1575-85. ©2017 AACR