Identifying driver genomic alterations in cancers by searching minimum-weight, mutually exclusive sets

An important goal of cancer genomic research is to identify the driving pathways underlying disease mechanisms. It is well known that somatic genome alterations (SGAs) affecting the genes that encode the proteins within a common signaling pathway exhibit mutual exclusivity, in which these SGAs usually do not co-occur in a tumor. With some success, this property has been utilized as an objective function to guide the search for driver mutations. However, the mutual exclusivity alone is not sufficient to indicate that genes affected by such SGAs are in common pathways. Here, we propose a novel, signal-oriented framework for identifying driver SGAs, such that our new method constrains the mutual exclusivity only on tumors that have SGAs to perturb a common signal (not on all tumors as previous methods used). We apply this framework to the OV and GBM data FROM TCGA, and perform systematic evaluations. Our results indicate that the signal-oriented approach enhances the ability to find informative sets of driver SGAs that likely constitute signaling pathways.