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Integrated analysis of recurrent properties of cancer genes to identify novel drivers

Matteo D'Antonio and Francesca D Ciccarelli*

Author affiliations

Department of Experimental Oncology, European Institute of Oncology, IFOM-IEO Campus, Via Adamello 16, 20139 Milan, Italy

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Citation and License

Genome Biology 2013, 14:R52  doi:10.1186/gb-2013-14-5-r52

Published: 29 May 2013

Abstract

The heterogeneity of cancer genomes in terms of acquired mutations complicates the identification of genes whose modification may exert a driver role in tumorigenesis. In this study, we present a novel method that integrates expression profiles, mutation effects, and systemic properties of mutated genes to identify novel cancer drivers. We applied our method to ovarian cancer samples and were able to identify putative drivers in the majority of carcinomas without mutations in known cancer genes, thus suggesting that it can be used as a complementary approach to find rare driver mutations that cannot be detected using frequency-based approaches.

Keywords:
Driver mutations; cancer genetic heterogeneity; interaction network; gene duplication; gene origin; gene expression