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

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,

SUBMITTER: Emmert-Streib F 

PROVIDER: S-EPMC3909882 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature