title: Network modeling of the transcriptional effects of copy number aberrations in glioblastoma.
abstract: DNA copy number aberrations (CNAs) are a hallmark of cancer genomes. However, little is known about how such changes affect global gene expression. We develop a modeling framework, EPoC (Endogenous Perturbation analysis of Cancer), to (1) detect disease-driving CNAs and their effect on target mRNA expression, and to (2) stratify cancer patients into long- and short-term survivors. Our method constructs causal network models of gene expression by combining genome-wide DNA- and RNA-level data. Prognostic scores are obtained from a singular value decomposition of the networks. By applying EPoC to glioblastoma data from The Cancer Genome Atlas consortium, we demonstrate that the resulting network models contain known disease-relevant hub genes, reveal interesting candidate hubs, and uncover predictors of patient survival. Targeted validations in four glioblastoma cell lines support selected predictions, and implicate the p53-interacting protein Necdin in suppressing glioblastoma cell growth. We conclude that large-scale network modeling of the effects of CNAs on gene expression may provide insights into the biology of human cancer. Free software in MATLAB and R is provided.
authors.affiliation: Mathematical Sciences, University of Gothenburg and Chalmers University of Technology, Gothenburg, Sweden.
authors.forename: Rebecka
authors.initials: R
authors.lastname: Jörnsten
authors.forename: Tobias
authors.initials: T
authors.lastname: Abenius
authors.forename: Teresia
authors.initials: T
authors.lastname: Kling
authors.forename: Linnéa
authors.initials: L
authors.lastname: Schmidt
authors.forename: Erik
authors.initials: E
authors.lastname: Johansson
authors.forename: Torbjörn E M
authors.initials: TE
authors.lastname: Nordling
authors.forename: Bodil
authors.initials: B
authors.lastname: Nordlander
authors.forename: Chris
authors.initials: C
authors.lastname: Sander
authors.forename: Peter
authors.initials: P
authors.lastname: Gennemark
authors.forename: Keiko
authors.initials: K
authors.lastname: Funa
authors.forename: Björn
authors.initials: B
authors.lastname: Nilsson
authors.forename: Linda
authors.initials: L
authors.lastname: Lindahl
authors.forename: Sven
authors.initials: S
authors.lastname: Nelander
mesh_terms: D045744:Cell Line, Tumor; D002869:Chromosome Aberrations; D016208:Databases, Factual; D018628:Gene Dosage; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D015894:Genome, Human; D055106:Genome-Wide Association Study; D005909:Glioblastoma / Q000235:genetics* / Q000378:metabolism / Q000401:mortality / Q000473:pathology; D006801:Humans; D008957:Models, Genetic; D009419:Nerve Tissue Proteins / Q000235:genetics / Q000378:metabolism*; D009423:Nervous System Neoplasms / Q000235:genetics* / Q000378:metabolism / Q000401:mortality / Q000473:pathology; D009687:Nuclear Proteins / Q000235:genetics / Q000378:metabolism*; D011379:Prognosis; D012984:Software; D015533:Transcriptional Activation / Q000235:genetics*; D016159:Tumor Suppressor Protein p53 / Q000235:genetics / Q000378:metabolism*
chemical_list: D009419:Nerve Tissue Proteins; D009687:Nuclear Proteins; D016159:Tumor Suppressor Protein p53; C069766:necdin