RT Journal Article
SR Electronic
T1 An Integrated Mechanistic Model of Pan-Cancer Driver Pathways Predicts Stochastic Proliferation and Death
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 128801
DO 10.1101/128801
A1 Mehdi Bouhaddou
A1 Anne Marie Barrette
A1 Rick J. Koch
A1 Matthew S. DiStefano
A1 Eric A. Riesel
A1 Alan D. Stern
A1 Luis C. Santos
A1 Annie Tan
A1 Alex Mertz
A1 Marc R. Birtwistle
YR 2017
UL http://biorxiv.org/content/early/2017/04/19/128801.abstract
AB 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.