4.6 Article

Inhibition of RPS6K reveals context-dependent Akt activity in luminal breast cancer cells

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PLOS COMPUTATIONAL BIOLOGY
卷 17, 期 6, 页码 -

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PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pcbi.1009125

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  1. NIH [P30 CA047904, U01CA204826, 1UL1TR001857]

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Insulin and insulin-like growth factor I (IGF1) receptors play a crucial role in the risk and advancement of various cancer types by activating cell survival cascades. A dual receptor computational model identified the role of ribosomal protein S6 kinase in regulating MAPK and Akt activation levels in response to Ins and IGF1 stimulation. The study suggests potential new targets for anti-IGF1R cancer therapy.
Aberrant signaling through insulin (Ins) and insulin-like growth factor I (IGF1) receptors contribute to the risk and advancement of many cancer types by activating cell survival cascades. Similarities between these pathways have thus far prevented the development of pharmacological interventions that specifically target either Ins or IGF1 signaling. To identify differences in early Ins and IGF1 signaling mechanisms, we developed a dual receptor (IGF1R & InsR) computational response model. The model suggested that ribosomal protein S6 kinase (RPS6K) plays a critical role in regulating MAPK and Akt activation levels in response to Ins and IGF1 stimulation. As predicted, perturbing RPS6K kinase activity led to an increased Akt activation with Ins stimulation compared to IGF1 stimulation. Being able to discern differential downstream signaling, we can explore improved anti-IGF1R cancer therapies by eliminating the emergence of compensation mechanisms without disrupting InsR signaling. Author summary The activity of the type I insulin-like growth factor receptor (IGF1R) has been linked to aggressive cancer growth and spreading, and inhibiting IGF1R activity has slowed cancer growth in laboratory models. Unfortunately, molecules that are known to bind to IGF1R also bind to the closely related insulin receptor (InsR) and can disrupt metabolism in a fashion similar to diabetes. To alter the activity of IGF1R without affecting that of InsR, one must identify differences in how the two receptors affect other proteins. Here we build a computational model of the biochemical signaling pathways initiated by the two receptors. By fitting the model to data, we identify potential differences in IGF1R and InsR signaling-specifically, our model predicts that feedback from the ribosomal protein S6 kinase (RPS6K) to the insulin receptor substrate (IRS) protein is sensitive to whether IGF1R or InsR is activated. We experimentally validate our model's predictions in three breast cancer cell lines, leading to possible new targets for IGF1R-associated cancer therapy.

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