Novel biomarkers identified in triple-negative breast cancer through RNA-sequencing

Background and aims: Triple-negative breast cancer (TNBC) is a subtype of breast cancer with a poor prognosis due to its aggressive biological behavior and lack of therapeutic targets. Here, we aimed to identify specific biomarkers for TNBC by using RNA-sequencing and bioinformatics analysis.Materials and methods: Fresh breast tumor tissues were obtained from 34 patients who were admitted to the Breast Center, Peking University People's Hospital, from June 2020 to December 2020; the patients were pathologically diagnosed with primary breast cancer and underwent surgery for the resection of tumor tissues. Tumor-tissue RNA was extracted and the generated cDNA libraries were sequenced using the NextSeq platform, after which the differentially expressed genes (DEGs) between TNBC and other subtypes of breast cancer were identified and DEG functional-enrichment analysis was performed. Next, weighted gene co-expression network analysis (WGCNA) was used to identify the most significant module and hub genes in TNBC, and then the correlations between the hub genes and the prognosis of TNBC patients were analyzed through survival analysis. Lastly, qRT-PCR analysis was used to validate the expression levels of hub genes in tumor tissues from TNBC and other subtypes of breast cancer.Results: Comparison of TNBC tissues and tissues from other subtypes of breast cancer led to the identification of 273 DEGs in TNBC: 172 upregulated and 101 downregulated genes. In Gene Ontology analysis of the DEGs, five terms were significantly enriched, "developmental process," "anatomical structure development," "tissue development," "cell cycle," and "epithelium development," and in Kyoto Encyclopedia of Genes and Genomes pathway analysis, the most significantly enriched pathways for all DEGs were "cell cycle," "mitophagy-animal," and "autophagy-animal." Furthermore, we identified the core module related to TNBC and screened for hub genes by using WGCNA, and after verifying the top 100 genes based on survival analysis, we selected four genes as the hub genes: SERPINB4, SMR3A, FERMT1, and STARD4; elevated expression of these genes was associated with poor overall survival (OS) of TNBC patients. Notably, qRT-PCR results indicated that FERMT1 mRNA expression was significantly upregulated in TNBC samples. Conclusion: The DEG profiles between tissues from TNBC and other subtypes of breast cancer were identified using RNA-sequencing and bioinformatics analysis. FERMT1 was significantly upregulated in TNBC tumor tis-sues, and increased expression of FERMT1 was associated with poor OS of TNBC patients. FERMT1 could serve as a specific biomarker of and therapeutic target in TNBC.