Algorithms for Detecting Significantly Mutated Pathways in Cancer

Abstract. Recent genome sequencing studies have shown that the somatic mutations that drive cancer development are distributed across a large number of genes. This mutational heterogeneity complicates efforts to distinguish functional mutations from sporadic, passenger mutations. Since cancer mutations are hypothesized to target a relatively small number of cellular signaling and regulatory pathways, a common approach is to assess whether known pathways are enriched for mutated genes. However, restricting attention to known pathways will not reveal novel cancer genes or pathways. An alterative strategy is to examine mutated genes in the context of genome-scale interaction networks that include both well characterized pathways and additional gene interactions measured through various approaches. We introduce a computational framework for de novo identification of subnetworks in a large gene interaction network that are mutated in a significant number of patients. This framework includes...

• Type: Conference
• Year: 2010
• Where: RECOMB
• Authors: Fabio Vandin, Eli Upfal, Benjamin J. Raphael
• Keywords: Computational Biology, Interaction Network, Mutated, Mutated Gene, RECOMB 2010