TY - JOUR T1 - An Integrated Mechanistic Model of Pan-Cancer Driver Pathways Predicts Stochastic Proliferation and Death JF - bioRxiv DO - 10.1101/128801 SP - 128801 AU - Mehdi Bouhaddou AU - Anne Marie Barrette AU - Rick J. Koch AU - Matthew S. DiStefano AU - Eric A. Riesel AU - Alan D. Stern AU - Luis C. Santos AU - Annie Tan AU - Alex Mertz AU - Marc R. Birtwistle Y1 - 2017/01/01 UR - http://biorxiv.org/content/early/2017/04/19/128801.abstract N2 - Most cancer cells harbor multiple drivers whose epistasis and interactions with expression context clouds drug sensitivity prediction. We constructed a mechanistic computational model that is context-tailored by omics data to capture regulation of stochastic proliferation and death by pan-cancer driver pathways. Simulations and experiments explore how the coordinated dynamics of RAF/MEK/ERK and PI-3K/AKT kinase activities in response to synergistic mitogen or drug combinations control cell fate in a specific cellular context. In this context, synergistic ERK and AKT inhibitor-induced death is likely mediated by BIM rather than BAD. AKT dynamics explain S-phase entry synergy between EGF and insulin, but stochastic ERK dynamics seem to drive cell-to-cell proliferation variability, which in simulations are predictable from pre-stimulus fluctuations in C-Raf/B-Raf levels. Simulations predict MEK alteration negligibly influences transformation, consistent with clinical data. Our model mechanistically interprets context-specific landscapes between driver pathways and cell fates, moving towards more rational cancer combination therapy. ER -