DNA methylation‐based diagnostic and prognostic biomarkers of nonsmoking lung adenocarcinoma patients

• Published in: Journal of cellular biochemistry 2019-08, Vol.120 (8), p.13520-13530
• Main Authors: Zhang, Xiaoming, Gao, Chundi, Liu, Lijuan, Zhou, Chao, Liu, Cun, Li, Jia, Zhuang, Jing, Sun, Changgang
• Format: Article
• Language: English
• Subjects: Adenocarcinoma; Annotations; Bioinformatics; Biomarkers; Collagen (type I); CXCL12 protein; Deoxyribonucleic acid; Diagnostic systems; DNA; DNA methylation; DNA microarrays; E-cadherin; ErbB-2 protein; expression; gen; Gene expression; Genes; lung adenocarcinoma; Lung cancer; Medical prognosis; methylation; Pathogenesis; Proteins
• ISSN: 0730-2312; 1097-4644
• DOI: 10.1002/jcb.28627

Currently, there are few studies on patients with nonsmoking lung adenocarcinoma, and the pathogenesis is still unclear. The role of DNA methylation in the pathogenesis of cancer is gradually being recognized. The purpose of this study was to determine the abnormal methylation genes and pathways involved in nonsmoking lung adenocarcinoma patients. Gene expression microarray data (GSE10072, GSE43458) and gene methylation microarray data (GSE62948) were downloaded from the Gene Expression Omnibus (GEO) database and differentially expressed genes were obtained through GEO2R. Next, we analyzed the function and enrichment of the selected genes using Database for Annotation, Visualization, and Integrated Discovery. The protein‐protein interaction (PPI) networks were constructed using the Search Tool for the Retrieval of Interacting Genes database and visualized in Cytoscape. Finally, we performed module analysis of the PPI network using Molecular Complex Detection. And we obtained 10 hub genes by Cytoscape Centiscape. We analyzed the independent prognostic value of each hub gene in nonsmoking nonsmall cell lung cancer patients through Kaplan‐Meier plotter. Seven hub genes (CXCL12, CDH1, CASP3, CREB1, COL1A1, ERBB2, and ENO2) were closely related to the overall survival time. This study provides an effective bioinformatics basis for further understanding the pathogenesis and prognosis of nonsmoking lung adenocarcinoma patients. Hub genes with prognostic value could be selected as effective biomarkers for timely diagnosis and prognostic of nonsmoking lung adenocarcinoma patients. In this paper, methylation information and gene expression data of nonsmoking lung adenocarcinoma patients were extracted from the Gene Expression Omnibus database, and the abnormal methylated genes were screened by functional and pathway enrichment analysis. What is more, the relationship between the key abnormal methylated genes and the prognosis of lung adenocarcinoma was discussed. The research based on high‐throughput data mining showed the important role of methylation in the pathogenesis of lung adenocarcinoma at the molecular level, and hub genes were selected as effective biomarkers for the timely diagnosis and prognostic of nonsmoking lung adenocarcinoma patients.