Although the incidence of thyroid carcinoma is reported to be the highest among malignancies of endocrine system, its diagnosis is still unsatisfactory. This study sought to explore the key DNA methylation-driven genes in the development of papillary thyroid carcinoma (PTC) via a bioinformatic analysis based on the Cancer Genome Atlas (TCGA) database and was validated using the Gene Expression Omnibus (GEO) database. The level 3 DNA methylation, mRNA expression, and clinical data of 499 patients with PTC were obtained from the TCGA database. The R package LIMMA, edgeR, and MethylMix were applied to explore the DNA methylation-driven genes in PTC. The ConsensusPathDB software, DAVID, and STRING databases were used for Gene Ontology (GO) enrichment and Kyoto Encyclopedia of Genes and Genomes pathway analyses, as well as protein/protein interaction network construction individually. To verify the result, the explored genes were validated using GSE97466 data set retrieved from the GEO database. Fifty-seven (57) methylation-driven genes were detected via MethylMix based on a beta mixture model that compared the DNA methylation state of tumor tissues with that of the normal tissues. Eventually, three genes (TNFRSF1A, CLDN1, and CASP1) were identified to be the most potential biomarkers for the diagnosis or treatment of PTC. These results suggest the crucial roles of TNFRSF1A, CLDN1, and CASP1 in the tumorigenesis of PTC and provide a vital bioinformatic basis for further experimental validations and clinical applications.
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