Identification of MTHFD2 as a novel prognosis biomarker in esophageal carcinoma patients based on transcriptomic data and methylation profiling. Issue 37 (11th September 2020)

• Record Type: Journal Article
• Authors: Wang, Jianlin; Luo, Judong; Sun, Zhiqiang; Sun, Fei; Kong, Ze; Yu, Jingping
• Other Names: Ding. Jianxun section editor.
• Is Part Of: Medicine. Volume 99:Issue 37(2020)
• Publication Date: 2020-09-11
• Subjects: biomarker -- DNA methylation -- esophageal carcinoma -- one carbon folate metabolism -- prognosis; Medicine -- Periodicals; Medicine -- Periodicals; Médecine -- Périodiques; Geneeskunde; Medicine; Periodicals; Periodicals; 610.5
• DOI: 10.1097/MD.0000000000022194
• Languages: English
• ISSNs: 0025-7974

Abstract

Abstract : Abstract: DNA methylation is an important epigenetic regulatory mechanism in esophageal carcinoma (EC) and is associated with genomic instability and carcinogenesis. In the present study, we aimed to identify tumor biomarkers for predicting prognosis of EC patients. We downloaded mRNA expression profiles and DNA methylation profiles associated with EC from the Gene Expression Omnibus database. Differentially expressed and differentially methylated genes between tumor tissues and adjacent normal tissue samples were identified. Functional enrichment analyses were performed, followed by the construction of protein–protein interaction networks. Data were validated based on methylation profiles from The Cancer Genome Atlas. Candidate genes were further verified according to survival analysis and Cox regression analysis. We uncovered multiple genes with differential expression or methylation in tumor samples compared with normal samples. After taking the intersection of 3 differential gene sets, we obtained a total of 232 overlapping genes. Functional enrichment analysis revealed that these genes are related to pathways such as "glutathione metabolism, " "p53 signaling pathway, " and "focal adhesion." Furthermore, 8 hub genes with inversed expression and methylation correlation were identified as candidate genes. The abnormal expression levels of MSN, PELI1, and MTHFD2 were correlated with overall survival times in EC patients ( P < .05). Only MTHFD2 was significantly associated with a pathologic stage according to univariate analysis ( P = .037) and multivariate analysis ( P = .043). Our study identified several novel EC biomarkers with prognostic value by integrated analysis of transcriptomic data and methylation profiles. MTHFD2 could serve as an independent biomarker for predicting prognosis and pathological stages of EC.