Automated oncogene detection in complex protein networks with applications to the MAPK signal transduction pathway

Abstract

Activation of the extracellular signal-regulated kinases (ERK1/2; p42/p44 mitogen-activated protein kinase (MAPK)) is one of the most extensively studied signaling pathways not least because it occurs downstream of oncogenic RAS. Here, we take advantage of the wealth of experimental data available on the canonical RAS/RAF/MEK/ERK pathway of Bhalla et al. to test the utility of a newly developed nonlinear analysis algorithm designed to predict likelihood of cellular transformation. By using ERK phosphorylation as an “output signal”, the method analyzes experimentally determined kinetic data and predicts putative oncogenes and tumor suppressor gene products impacting the RAS/MAPK module using a purely theoretical approach. This analysis identified several modifiers of ERK/MAPK activation described previously. In addition, several novel enzymes are identified which are not previously described to affect ERK/MAPK phosphorylation. Importantly, the nonlinear analysis enables a ranking of modifiers of MAPK activation predicting their relative importance in RAS-dependent oncogenesis. The results are compared with a linearized analysis based on sensitivity analysis about the steady state or metabolic control analysis (MCA). The results are favorable, pointing to the utility of first-order sensitivity analysis and MCA in the analysis of complex signaling networks for oncogenes.