Identification of hub subnetwork based on topological features of genes in breast cancer

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...

Full description

Bibliographic Details
Main Authors:	ZHUANG, DA-YONG, JIANG, LI, HE, QING-QING, ZHOU, PENG, YUE, TAO
Format:	Online
Language:	English
Published:	D.A. Spandidos 2015
Online Access:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314413/

id	pubmed-4314413
recordtype	oai_dc
spelling	pubmed-43144132015-02-06 Identification of hub subnetwork based on topological features of genes in breast cancer ZHUANG, DA-YONG JIANG, LI HE, QING-QING ZHOU, PENG YUE, TAO Articles 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. D.A. Spandidos 2015-03 2014-12-30 /pmc/articles/PMC4314413/ /pubmed/25573623 http://dx.doi.org/10.3892/ijmm.2014.2057 Text en Copyright © 2015, Spandidos Publications http://creativecommons.org/licenses/by/3.0 This is an open-access article licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License. The article may be redistributed, reproduced, and reused for non-commercial purposes, provided the original source is properly cited.
repository_type	Open Access Journal
institution_category	Foreign Institution
institution	US National Center for Biotechnology Information
building	NCBI PubMed
collection	Online Access
language	English
format	Online
author	ZHUANG, DA-YONG JIANG, LI HE, QING-QING ZHOU, PENG YUE, TAO
spellingShingle	ZHUANG, DA-YONG JIANG, LI HE, QING-QING ZHOU, PENG YUE, TAO Identification of hub subnetwork based on topological features of genes in breast cancer
author_facet	ZHUANG, DA-YONG JIANG, LI HE, QING-QING ZHOU, PENG YUE, TAO
author_sort	ZHUANG, DA-YONG
title	Identification of hub subnetwork based on topological features of genes in breast cancer
title_short	Identification of hub subnetwork based on topological features of genes in breast cancer
title_full	Identification of hub subnetwork based on topological features of genes in breast cancer
title_fullStr	Identification of hub subnetwork based on topological features of genes in breast cancer
title_full_unstemmed	Identification of hub subnetwork based on topological features of genes in breast cancer
title_sort	identification of hub subnetwork based on topological features of genes in breast cancer
description	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.
publisher	D.A. Spandidos
publishDate	2015
url	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4314413/
_version_	1613183371230314496

Identification of hub subnetwork based on topological features of genes in breast cancer

Similar Items