Boolean network model for cancer pathways: predicting carcinogenesis and targeted therapy outcomes.

ABSTRACT: A Boolean dynamical system integrating the main signaling pathways involved in cancer is constructed based on the currently known protein-protein interaction network. This system exhibits stationary protein activation patterns--attractors--dependent on the cell's microenvironment. These dynamical attractors were determined through simulations and their stabilities against mutations were tested. In a higher hierarchical level, it was possible to group the network attractors into distinct cell phenotypes and determine driver mutations that promote phenotypic transitions. We find that driver nodes are not necessarily central in the network topology, but at least they are direct regulators of central components towards which converge or through which crosstalk distinct cancer signaling pathway

SUBMITTER: Fumia HF 

PROVIDER: S-EPMC3724878 | biostudies-literature | 2013

REPOSITORIES: biostudies-literature