The gene regulatory network for breast cancer: integrated regulatory landscape of cancer hallmarks

In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of 351 patient samples. In order to elucidate the functional relevance of...

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Bibliographic Details
Published in:Frontiers in genetics 2014, Vol.5, p.15-15
Main Authors: Emmert-Streib, Frank, de Matos Simoes, Ricardo, Mullan, Paul, Haibe-Kains, Benjamin, Dehmer, Matthias
Format: Article
Language:English
Subjects:
breast cancer
Computational Biology
Computational genomics
Gene Regulatory Networks
Genetics
statistical inference
Systems Biology
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Summary:In this study, we infer the breast cancer gene regulatory network from gene expression data. This network is obtained from the application of the BC3Net inference algorithm to a large-scale gene expression data set consisting of 351 patient samples. In order to elucidate the functional relevance of the inferred network, we are performing a Gene Ontology (GO) analysis for its structural components. Our analysis reveals that most significant GO-terms we find for the breast cancer network represent functional modules of biological processes that are described by known cancer hallmarks, including translation, immune response, cell cycle, organelle fission, mitosis, cell adhesion, RNA processing, RNA splicing and response to wounding. Furthermore, by using a curated list of census cancer genes, we find an enrichment in these functional modules. Finally, we study cooperative effects of chromosomes based on information of interacting genes in the beast cancer network. We find that chromosome 21 is most coactive with other chromosomes. To our knowledge this is the first study investigating the genome-scale breast cancer network.
ISSN:1664-8021
1664-8021
DOI:10.3389/fgene.2014.00015