Downregulated ZNF132 predicts unfavorable outcomes in breast Cancer via Hypermethylation modification

• Main Authors: Zhao Liu, Jiaxin Liu, Ruimiao Liu, Man Xue, Weifan Zhang, Xinhui Zhao, Jiang Zhu, Peng Xia
• Format: Article
• Language: English
• Published: BMC 2021-04-01
• Series: BMC Cancer
• Subjects: ZNF132; Breast cancer; Bioinformatic; Methylation; Diagnosis; Prognosis
• Online Access: https://doi.org/10.1186/s12885-021-08112-z

Abstract Background An important mechanism that promoter methylation-mediated gene silencing for gene inactivation is identified in human tumorigenesis. Methylated genes have been found in breast cancer (BC) and beneficial biomarkers for early diagnosis. Prognostic assessment of breast cancer remain little known. Zinc finger protein 132 (ZNF132) is downregulated by promoter methylation in prostate cancer and esophageal squamous cell carcinoma. However, no study provides information on the status of ZNF132, analyzes diagnosis and prognostic significance of ZNF132 in BC. Methods In the present study, the expression of ZNF132 mRNA and protein level was determined based on the Cancer Genome Atlas (TCGA) RNA-Seq database and clinical samples analysis and multiple cancer cell lines verification. P rognostic significance of ZNF132 in BC was assessed using the Kaplan-Meier plotter. Molecular mechanisms exploration of ZNF132 in BC was performed using the multiple bioinformatic tools. Hypermethylated status of ZNF132 in BC cell lines was confirmed via Methylation specific polymerase chain reaction (MSP) analysis. Results The expression of ZNF132 both the mRNA and protein levels was downregulated in BC tissues. These results were obtained based on TCGA database and clinical sample analysis. Survival analysis from the Kaplan-Meier plotter revealed that the lower level of ZNF132 was associated with a shorter Relapse Free Survival (RFS) time. Receiver operating characteristic curve (ROC) of 0.887 confirmed ZNF132 had powerful sensitivity and specificity to distinguish between BC and adjacent normal tissues. Bioinformatic analysis showed that 6% ((58/960)) alterations of ZNF132 were identified from cBioPortal. ZNF132 participated in multiple biological pathways based on the Gene Set Enrichment Analysis (GSEA) database including the regulation of cell cycle and glycolysis. Finally, MSP analysis demonstrated that ZNF132 was hypermethylated in a panel of breast cancer cell lines and 5-aza-2′-deoxycytidine (5-Aza-dC) treatment restored ZNF132 expression in partial cell lines. Conclusions Results revealed that hypermethylation of ZNF132 contributed to its downregulated expression and could be identified as a new diagnostic and prognostic marker in BC.