"Breast cancer is among the most common cancers with worldwide more than 1,300,000 cases each year (Cancer and Atlas, 2012). Among these cases, ductal carcinoma, a particular subtype of breast cancer, represents up to 25% of all newly diagnosed patients in the United States (Wickerham and Julian, 2013). In general, breast cancer is derived from epithelial cells that develop neoplasia in breast tissue. "
[Show abstract][Hide abstract] ABSTRACT: 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.
Frontiers in Genetics 02/2014; 5:15. DOI:10.3389/fgene.2014.00015
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