Identification of Key Genes for Nasopharyngeal Carcinoma by Gene Expression and DNA Methylation Data Integration Analysis

Abstract Background: The pathogenesis of Nasopharyngeal carcinoma (NPC) is very complicated. The present study aimed to identity some candidate genes as biomarkers for NPC diagnosis and pathogenesis.Methods: Three Microarray datasets GSE53819, GSE64634 and GSE12452 and a methylation array (GSE52068) were re-analyzed. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis of the differentially expressed genes (DEGs) were applied. STRING software was used to construct a protein-protein interaction (PPI) network of DEGs and visualized by Cytoscape. Random Forest (RF) algorithm was performed to construct classifiers and identified key genes.Results: A total of 91 DEGs were screened from the three datasets. GO term and KEGG pathway analysis suggested that the DEGs were predominantly enriched in drug metabolism-cytochrome P450 pathway, metabolism of xenobiotics by cytochrome P450 pathway, chemical carcinogenesis pathway, ciliary part, motile cilium, axoneme, microtubule and ciliary plasm. We obtained nine hub genes and one significant module. We constructed a classifier based on DEGs and found CLIC6 and CLU have the best classification ability. Finally, five hypermethylated and downregulated genes (hyper-down) were identified by integrating methylation data.Conclusions: With gene expression and methylation data integration analysis, several key genes were identified may be potential biomarkers for NPC diagnosis and pathogenesis.