Computational response modeling reveals context dependent Akt activity in luminal breast cancer cells

Abstract

Aberrant signaling through insulin (Ins) and insulin-like growth factor I (IGF1) receptors contributes to the risk and advancement of many cancer types by activating cell survival cascades. Mechanistic computational modeling of such pathways provides insights into each components role in the cell response. In previous computational models, the two receptors were treated as indistinguishable, missing the opportunity to delineate their distinct roles in cancer progression. Here, a dual receptor (IGF1R & InsR) computational model elucidated new experimental hypotheses on how differential early responses emerge. Complementary to our previous findings, the model suggested that the regulation of insulin receptor substrate (IRS) is critical in inducing differential MAPK and Akt activation. As predicted, perturbing ribosomal protein S6 kinase (RPS6K) kinase activity led to an increased Akt activation with insulin stimulation compared to IGF1 stimulation. Being able to discern differential downstream signaling, we can explore improved anti-IGF1R cancer therapies by eliminating emergence of compensation mechanisms, without disrupting InsR signaling. ImplicationsThe study shows, both experimentally and through computational models, that IGF1 and insulin receptor signaling pathways respond differently to RPS6K inhibition.