Identification of Key Genes and Pathways in Triple-Negative Breast Cancer by Integrated Bioinformatics Analysis. (2nd August 2018)

• Record Type: Journal Article
• Authors: Dong, Pengzhi; Yu, Bing; Pan, Lanlan; Tian, Xiaoxuan; Liu, Fangfang
• Other Names: Vierkant Robert A. Academic Editor.
• Is Part Of: BioMed research international. Volume 2018(2018)
• Publication Date: 2018-08-02
• Subjects: Medicine -- Periodicals; Biology -- Periodicals; Biotechnology -- Periodicals; Life sciences -- Periodicals; 610.5
• DOI: 10.1155/2018/2760918
• Languages: English
• ISSNs: 2314-6133

Abstract

Abstract : Purpose. Triple-negative breast cancer refers to breast cancer that does not express estrogen receptor (ER), progesterone receptor (PR), or human epidermal growth factor receptor 2 (Her2). This study aimed to identify the key pathways and genes and find the potential initiation and progression mechanism of triple-negative breast cancer (TNBC). Methods. We downloaded the gene expression profiles of GSE76275 from Gene Expression Omnibus (GEO) datasets. This microarray Super-Series sets are composed of gene expression data from 265 samples which included 67 non-TNBC and 198 TNBC. Next, all the differentially expressed genes (DEGs) with p<0.01 and fold change ≥1.5 or ≤-1.5 were identified. Result. 56 upregulated and 151 downregulated genes were listed and the gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes pathway (KEGG) enrichment analysis was performed. These significantly changed genes were mainly involved in the biological process termed prostate gland morphogenesis, inner ear morphogenesis, cell maturation, digestive tract morphogenesis, autonomic nervous system development, monovalent inorganic anion homeostasis, neural crest cell development, regulation of dendrite extension and glial cell proliferation, immune system process termed T cell differentiation, regulation of immune response, and macrophage activation. Genes are mainly involved in the KEGG pathway termed Oocyte meiosis. All DEGs underwent survival analysis using datasets from The Cancer Genome Atlas (TCGA) integrated by cBioPortal, of which amplification of SRY-related HMG-box 8 (SOX8), androgen receptor (AR), and Chromosome 9 Open Reading Frame 152 (C9orf152) were significantly negative while Nik Related Kinase (NRK) and RAS oncogene family 30 (RAB30) were positively correlated to the life expectancy (p<0.05). Conclusions. In conclusion, these pathways and genes identified could help understanding the mechanism of development of TNBC. Besides, SOX8, AR, C9orf152, NRK and RAB30, and other key genes and pathways might be promising targets for the TNBC treatment.