Molecular Concepts Analysis Links Tumors, Pathways, Mechanisms, and Drugs

Abstract

Global molecular profiling of cancers has shown broad utility in delineating pathways and processes underlying disease, in predicting prognosis and response to therapy, and in suggesting novel treatments. To gain further insights from such data, we have integrated and analyzed a comprehensive collection of “molecular concepts”" representing > 2500 cancer-related gene expression signatures from Oncomine and manual curation of the literature, drug treatment signatures from the Connectivity Map, target gene sets from genome-scale regulatory motif analyses, and reference gene sets from several gene and protein annotation databases. We computed pairwise association analysis on all 13,364 molecular concepts and identified > 290,000 significant associations, generating hypotheses that link cancer types and subtypes, pathways, mechanisms, and drugs. To navigate a network of associations, we developed an analysis platform, the Molecular Concepts Map. We demonstrate the utility of the approach by highlighting molecular concepts analyses of Myc pathway activation, breast cancer relapse, and retinoic acid treatment.

Keywords

• Cancer
• bioinformatics
• gene expression signature
• network
• oncomine