Identification of aberrantly methylated differentially expressed genes in papillary thyroid carcinoma using integrated bioinformatic analysis

Background: DNA methylation has been reported as one of the most critical epigenetic aberrations during the tumorigenesis and development of papillary thyroid carcinoma (PTC). Although PTC has been explored by gene expression and DNA methylation studies, the regulatory mechanisms of the methylation on the gene expression was poorly clarified.Results: In this study, the comparisons between PTC and NT revealed 4995 methylated probes and 1446 differentially expressed transcripts cross-validated by The Cancer Genome Atlas (TCGA) database. The integrative analysis between DNA methylation and gene expression revealed 123 and 29 genes with hypomethylation/overexpression and hypermethylation/downexpression correlation, respectively. The DNA methylation pattern of seven selected CpGs (A: UNC80-cg04507925; B: TPO-cg09757588; C: LHX8-cg11842415; D: DLG2-cg16986720; E: FOXJ1-cg20373432; F: PALM2-cg21204870; G: IPCEF1-cg24635109, of which the candidate promoter CpG sites were preliminarily identified with the least absolute shrinkage and selection operator (LASSO) regression analysis. Then, the risk prognosis model was constructed by stepwise regression analysis. Furthermore, the receiver operating characteristic (ROC) and nomogram based on the verified independent prognostic factors was established for the prognostic prediction showed that it was able to predict 3-, 5-, and 7-year survival accurately. Kaplan-Meier survival estimate demonstrated that low DLG2 expression and DLG2-cg16986720 hypermethylation were independent biomarkers for OS. From the comprehensive meta-analysis, the combined Standardised Mean Difference (SMD) of DLG2 was 0.94 with 95% CI of (0.46,1.43), indicating that less DLG2 was expressed in the PTC tissue than in the normal tissue (PConclusions: The current study validated that DLG2 was lowly expressed in PTC. More importantly, DLG2 hypermethylation might function as a latent tumor biomarker in the prognosis prediction for PTC. The results of bioinformatics analyses may present a new method for investigating the pathogenesis of PTC. DNA methylation loss in non-promoter, poor CGI and enhancer-enriched regions was a significant event in PTC. In addition to the promoter region, gene body and 3’UTR methylation have also the potential to influence the gene expression levels (both, repressing and inducing). The integrative analysis revealed genes potentially regulated by DNA methylation pointing out potential drivers and biomarkers related to PTC development.