Bioinformatic analysis identifies QPRT, RAB26, and SRPRB as potential biomarkers for prognosis in triple-negative breast cancer, suggesting future therapeutic strategies.
To screen differentially expressed genes (DEGs) in triple-negative breast cancer (TNBC) by bioinformatic methods and explore their relationship between TNBC prognosis and related biological functions. Microarray dataset GSE65194 was downloaded from Gene Expression Omnibus (GEO) database. The whole TNBC-related datasets were downloaded from The Cancer Genome Atlas (TCGA) database. After screening DEGs in R software, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses were performed to predict the function of these DEGs. The survival curve examination of the DEGs was performed based on TCGA database and Kaplan-Meier plotter website. In addition, the gene-drug interaction network was explored using the Comparative Toxicogenomics Database (CTD). A total of 2,496 up-regulated and 142 down-regulated DEGs were revealed in GEO database and TCGA database simultaneously. The GO and KEGG analysis revealed enrichment in regulation of nucleobase, nucleoside, nucleic acid metabolism, DNA binding, and integrin family cell surface interactions. Furthermore, up-regulation of quinolinate phosphoribosyl transferase (QPRT), member RAS oncogene family (RAB26), and SRP receptor subunit beta (SRPRB) were significantly associated with survival in TNBC patients. QPRT, RAB26, and SRPRB may be three potential novel prognostic biomarkers for TNBC and will provide potential guidance value for future research on TNBC.
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Liu et al. (2025) studied this question.
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