Identification of candidate aberrantly methylated and differentially expressed genes in thyroid cancer

Abstract

Aberrant methylation of DNA sequences plays a criticle role in finding novel aberrantly methylated genes and pathways in thyroid cancer (THCA). This study aimed to integrate three cohorts profile datasets to find novel aberrantly methylated genes and pathways in THCA. Data of gene expression profiling microarrays (GSE33630 and GSE65144) and gene methylation profiling microarrays (GSE51090) were downloaded from the Gene Expression Omnibus database. Aberrantly methylated and differentially expressed genes were sorted and pathways were analyzed. Functional and enrichment analyses of selected genes were performed using the String database. A protein‐protein interaction network was constructed using the Cytoscape software, and module analysis was performed using Molecular Complex detection. In total, we identified 12 hypomethylation/high‐expression genes and 30 hypermethylation/low‐expression genes at the screening step and, finally, found 6 mostly changed hub genes including PPARGC1A, CREBBP, EP300, CD44, SPP1, and MMP9. Pathway analysis showed that aberrantly methylated differentially expressed genes were mainly associated with the thyroid hormone signaling pathway, AMP‐activated protein kinase (AMPK) signaling pathway, and cell cycle process in THCA. After validation in the Cancer Genome Atlas database, the methylation and expression status of hub genes was significantly altered and the same with our results. Taken together, we identified novel aberrantly methylated genes and pathways in THCA, which could improve our understanding of the cause and underlying molecular events, and these candidate genes could serve as aberrant methylation‐based biomarkers for precise diagnosis and treatment of THCA.