Abstract

BACKGROUND: SETDB1, an H3K9-specific histone methyltransferase, plays important roles in the progression of various human cancers. However, the expression patterns and its clinical roles of SETDB1 remain elusive in breast cancer (BC).

MATERIAL AND METHODS: The transcriptional level of SETDB1 and survival data in BC were analyzed through UALCAN, ONCOMINE, and Pan Cancer Prognostics Database. SETDB1 protein expression was assessed by immunohistochemistry (IHC) in 159 BC tissue samples. The associations between SETDB1 expression and clinical pathological characteristics of patients were analyzed. The GEO dataset GSE108656 was downloaded and analyzed to identify the differentially expressed genes (DEGs) between control and BC cells targeting interference with SETDB. The DEGs were further integrated by bioinformatics analysis to decipher the key signaling pathways and hub genes that are regulated by SETDB.

RESULTS: The public databases showed the level of SETDB1 mRNA was significantly upregulated in BC. Our IHC results demonstrated the level of SETDB1 protein was associated with tumor size (P=0.028), histopathological grading (P=0.012), lymph node metastasis (P<0.001), and TNM stage (P<0.001). High expression of SETDB1 indicated worse overall survival (P=0.015) and shorter relapse-free survival (P=0.027). The bioinformatic analysis of GSE108656 suggested that the SETDB1-related DEGs was mainly enriched in antigen processing and presentation, as well as immune networks in BC. The cytoHubba analysis suggested the top 10 hub genes were IL6, BMP4, CD74, PECAM1, HLA-DPA1, HLA-DRA, LAMC1, CTSB, SERPINA1, and CTSD.

CONCLUSIONS: The results suggest that SETDB1 is an oncogene and can serve as a prognostic biomarker for BC. However, the mechanisms of SETDB1 in BC remain to be explored.

Keywords: Immunochemistry, Prognosis, Triple Negative Breast Neoplasms, Biomarkers, Tumor, Breast Neoplasms, Computational Biology, Databases, Genetic, Gene Expression, Gene Expression Profiling, Gene Expression Regulation, Neoplastic, gene ontology, Gene Regulatory Networks, Histone Methyltransferases, Histone-Lysine N-Methyltransferase, Neoplasm Recurrence, Local, Oncogenes, RNA, Messenger, transcriptome