title: Identification of hub subnetwork based on topological features of genes in breast cancer.
abstract: The aim of this study was to provide functional insight into the identification of hub subnetworks by aggregating the behavior of genes connected in a protein-protein interaction (PPI) network. We applied a protein network-based approach to identify subnetworks which may provide new insight into the functions of pathways involved in breast cancer rather than individual genes. Five groups of breast cancer data were downloaded and analyzed from the Gene Expression Omnibus (GEO) database of high-throughput gene expression data to identify gene signatures using the genome-wide global significance (GWGS) method. A PPI network was constructed using Cytoscape and clusters that focused on highly connected nodes were obtained using the molecular complex detection (MCODE) clustering algorithm. Pathway analysis was performed to assess the functional relevance of selected gene signatures based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) database. Topological centrality was used to characterize the biological importance of gene signatures, pathways and clusters. The results revealed that, cluster1, as well as the cell cycle and oocyte meiosis pathways were significant subnetworks in the analysis of degree and other centralities, in which hub nodes mostly distributed. The most important hub nodes, with top ranked centrality, were also similar with the common genes from the above three subnetwork intersections, which was viewed as a hub subnetwork with more reproducible than individual critical genes selected without network information. This hub subnetwork attributed to the same biological process which was essential in the function of cell growth and death. This increased the accuracy of identifying gene interactions that took place within the same functional process and was potentially useful for the development of biomarkers and networks for breast cancer.
authors.affiliation: Department of Thyroid and Breast Surgery, Jinan Military General Hospital of Chinese PLA, Jinan, Shandong 250031, P.R. China.
authors.forename: Da-Yong
authors.initials: DY
authors.lastname: Zhuang
authors.affiliation: Department of Prevention and Health Care, Central Hospital of Zibo City, Zibo, Shandong 255036, P.R. China.
authors.forename: Li
authors.initials: L
authors.lastname: Jiang
authors.affiliation: Department of Thyroid and Breast Surgery, Jinan Military General Hospital of Chinese PLA, Jinan, Shandong 250031, P.R. China.
authors.forename: Qing-Qing
authors.initials: QQ
authors.lastname: He
authors.affiliation: Department of Thyroid and Breast Surgery, Jinan Military General Hospital of Chinese PLA, Jinan, Shandong 250031, P.R. China.
authors.forename: Peng
authors.initials: P
authors.lastname: Zhou
authors.affiliation: Department of Thyroid and Breast Surgery, Jinan Military General Hospital of Chinese PLA, Jinan, Shandong 250031, P.R. China.
authors.forename: Tao
authors.initials: T
authors.lastname: Yue
mesh_terms: D001943:Breast Neoplasms / Q000235:genetics* / Q000378:metabolism; D019295:Computational Biology; D030541:Databases, Genetic; D005260:Female; D020869:Gene Expression Profiling; D015972:Gene Expression Regulation, Neoplastic; D053263:Gene Regulatory Networks; D006801:Humans; D025941:Protein Interaction Mapping; D060066:Protein Interaction Maps; D015398:Signal Transduction; D059467:Transcriptome