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Updated: Feb 23, 2026
Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Screening and identification of potential biomarkers in triple-negative breast cancer by integrated analysis
Jilong Guo1, Guohua Gong1, Bin Zhang1
1Medicinal Chemistry and Pharmacology Institute, Inner Mongolia University for Nationalities, Tongliao, Inner Mongolia 028000, P.R. China.
Abstract:
Triple-negative breast cancer (TNBC) has attracted great attention due to its unique biology, poor prognosis, and aggressiveness. TNBC patients are more likely to suffer from metastasis. We screened and identified the TNBC-specific genes as potential biomarkers. A total of 167 breast cancer samples (45 TNBC and 122 non-TNBC) were used in the integrated analysis. Gene expression microarrays were used to screen the differentially expressed genes. We identified 65 core DEGs. According to the GO and KEGG analysis, the gene function enrichment in TNBC was revealed, such as basal cell carcinoma, prostate cancer, oocyte meiosis and choline metabolism in cancer pathways. Moreover, the PPI network reconstruction would benefit the screening of hubs. A RFS analysis of TNBC-specific genes was also conducted. RT-PCR was used to validate the expression pattern of hubs in TNBC. Finally, nine genes were identified and all of them were novel, specific and higher dysregulation expressed genes in TNBC. Such that, these genes will serve as potential biomarkers in TNBC and benefit further research in TNBC.
