title: Detection of gene communities in multi-networks reveals cancer drivers.
abstract: We propose a new multi-network-based strategy to integrate different layers of genomic information and use them in a coordinate way to identify driving cancer genes. The multi-networks that we consider combine transcription factor co-targeting, microRNA co-targeting, protein-protein interaction and gene co-expression networks. The rationale behind this choice is that gene co-expression and protein-protein interactions require a tight coregulation of the partners and that such a fine tuned regulation can be obtained only combining both the transcriptional and post-transcriptional layers of regulation. To extract the relevant biological information from the multi-network we studied its partition into communities. To this end we applied a consensus clustering algorithm based on state of art community detection methods. Even if our procedure is valid in principle for any pathology in this work we concentrate on gastric, lung, pancreas and colorectal cancer and identified from the enrichment analysis of the multi-network communities a set of candidate driver cancer genes. Some of them were already known oncogenes while a few are new. The combination of the different layers of information allowed us to extract from the multi-network indications on the regulatory pattern and functional role of both the already known and the new candidate driver genes.
authors.affiliation: Università di Torino, Department of Oncology, Candiolo, Italy.|Politecnico di Torino, Department of Control and Computer Engineering, Torino, Italy.|Istituto Nazionale Biostrutture e Biosistemi - Consorzio Interuniversitario, Viale delle Medaglie d'Oro, 305 - 00136 Roma, Italy.
authors.forename: Laura
authors.initials: L
authors.lastname: Cantini
authors.affiliation: Università di Torino, Department of Oncology, Candiolo, Italy.|Candiolo Cancer Institute, FPO IRCCS, Candiolo, Italy.
authors.forename: Enzo
authors.initials: E
authors.lastname: Medico
authors.affiliation: Department of Computer Science, Aalto University School of Science, Aalto, Finland.
authors.forename: Santo
authors.initials: S
authors.lastname: Fortunato
authors.affiliation: Università di Torino, Department of Physics and INFN, Torino, Italy.
authors.forename: Michele
authors.initials: M
authors.lastname: Caselle
mesh_terms: D063646:Carcinogenesis / Q000235:genetics; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D009369:Neoplasms / Q000235:genetics*