title: Efficient exploration of pan-cancer networks by generalized covariance selection and interactive web content.
abstract: Statistical network modeling techniques are increasingly important tools to analyze cancer genomics data. However, current tools and resources are not designed to work across multiple diagnoses and technical platforms, thus limiting their applicability to comprehensive pan-cancer datasets such as The Cancer Genome Atlas (TCGA). To address this, we describe a new data driven modeling method, based on generalized Sparse Inverse Covariance Selection (SICS). The method integrates genetic, epigenetic and transcriptional data from multiple cancers, to define links that are present in multiple cancers, a subset of cancers, or a single cancer. It is shown to be statistically robust and effective at detecting direct pathway links in data from TCGA. To facilitate interpretation of the results, we introduce a publicly accessible tool (cancerlandscapes.org), in which the derived networks are explored as interactive web content, linked to several pathway and pharmacological databases. To evaluate the performance of the method, we constructed a model for eight TCGA cancers, using data from 3900 patients. The model rediscovered known mechanisms and contained interesting predictions. Possible applications include prediction of regulatory relationships, comparison of network modules across multiple forms of cancer and identification of drug targets.
authors.affiliation: Sahlgrenska Cancer Center and Dept of Molecular and Clinical Medicine, University of Gothenburg, Box 425, SE-405 30 Gothenburg, Sweden.
authors.forename: Teresia
authors.initials: T
authors.lastname: Kling
authors.affiliation: Department of Immunology, Genetics and Pathology (IGP) and Science for Life Laboratory, Uppsala University, Rudbecklaboratoriet, SE-751 85 Uppsala, Sweden.
authors.forename: Patrik
authors.initials: P
authors.lastname: Johansson
authors.affiliation: Mathematical Sciences, University of Gothenburg and Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.
authors.forename: José
authors.initials: J
authors.lastname: Sanchez
authors.affiliation: Department of Immunology, Genetics and Pathology (IGP) and Science for Life Laboratory, Uppsala University, Rudbecklaboratoriet, SE-751 85 Uppsala, Sweden.
authors.forename: Voichita D
authors.initials: VD
authors.lastname: Marinescu
authors.affiliation: Mathematical Sciences, University of Gothenburg and Chalmers University of Technology, SE-412 96 Gothenburg, Sweden.
authors.forename: Rebecka
authors.initials: R
authors.lastname: Jörnsten
authors.affiliation: Department of Immunology, Genetics and Pathology (IGP) and Science for Life Laboratory, Uppsala University, Rudbecklaboratoriet, SE-751 85 Uppsala, Sweden sven.nelander@igp.uu.se.
authors.forename: Sven
authors.initials: S
authors.lastname: Nelander
mesh_terms: D000970:Antineoplastic Agents / Q000494:pharmacology; D002872:Chromosome Deletion; D002880:Chromosomes, Human, Pair 11; D056915:DNA Copy Number Variations; D019175:DNA Methylation; D023281:Genomics / Q000379:methods; D005910:Glioma / Q000235:genetics; D006801:Humans; D020407:Internet; D007521:Isocitrate Dehydrogenase / Q000235:genetics; D053208:Kaplan-Meier Estimate; D035683:MicroRNAs / Q000378:metabolism; D008957:Models, Genetic; D015233:Models, Statistical; D009154:Mutation; D009369:Neoplasms / Q000235:genetics* / Q000401:mortality; D012333:RNA, Messenger / Q000378:metabolism; D012984:Software
chemical_list: D000970:Antineoplastic Agents; D035683:MicroRNAs; D012333:RNA, Messenger; D007521:Isocitrate Dehydrogenase; C543588:IDH1 protein, human