Identification of potential core genes in triple negative breast cancer using bioinformatics analysis
Authors Li MX, Jin LT, Wang TJ, Feng YJ, Pan CP, Zhao DM, Shao J
Received 25 February 2018
Accepted for publication 1 June 2018
Published 18 July 2018 Volume 2018:11 Pages 4105—4112
Checked for plagiarism Yes
Review by Single anonymous peer review
Peer reviewer comments 2
Editor who approved publication: Prof. Dr. Geoffrey Pietersz
Man-Xiu Li, Li-Ting Jin, Tie-Jun Wang, Yao-Jun Feng, Cui-Ping Pan, Dei-Mian Zhao, Jun Shao
Department of Breast Cancer, Hubei Cancer Hospital, Wuhan, People’s Republic of China
Background: Triple-negative breast cancer (TNBC) is a subtype of breast cancer with poor clinical outcome and limited treatment options. Lacking molecular targets, chemotherapy is the main adjuvant treatment for TNBC patients.
Materials and methods: To explore potential therapeutic targets for TNBC, we analyzed three microarray datasets (GSE38959, GSE45827, and GSE65194) derived from the Gene Expression Omnibus (GEO) database. The GEO2R tool was used to screen out differentially expressed genes (DEGs) between TNBC and normal tissue. Gene Ontology function and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis were performed using the Database for Annotation, Visualization and Integrated Discovery to identify the pathways and functional annotation of DEGs. Protein–protein interaction of these DEGs was analyzed based on the Search Tool for the Retrieval of Interacting Genes database and visualized by Cytoscape software. In addition, we used the online Kaplan–Meier plotter survival analysis tool to evaluate the prognostic value of hub genes expression in breast cancer patients.
Results: A total of 278 upregulated DEGs and 173 downregulated DEGs were identified. Among them, ten hub genes with a high degree of connectivity were picked out. Overexpression of these hub genes was associated with unfavorable prognosis of breast cancer, especially, CCNB1 overexpression was observed and indicated poor outcome of TNBC.
Conclusion: Our study suggests that CCNB1 was overexpressed in TNBC compared with normal breast tissue, and overexpression of CCNB1 was an unfavorable prognostic factor of TNBC patients. Further study is needed to explore the value of CCNB1 in the treatment of TNBC.
Keywords: triple-negative breast cancer, hub genes, expression profiling data, CCNB1
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