Specific Glioma Prognostic Subtype Distinctions Based on DNA Methylation Patterns

DNA methylation is an important regulator of gene expression and may provide an important basis for effective glioma diagnosis and therapy. Here, we explored specific prognosis subtypes based on DNA methylation status using 653 gliomas from The Cancer Genome Atlas (TCGA) database. Five subgroups were distinguished by consensus clustering using 11,637 cytosines preceding a guanosine (CpGs) that significantly influenced survival. The specific DNA methylation patterns were correlated with age, tumor stage, and prognosis. Additionally, weighted gene co-expression network analysis (WGCNA) analysis of CpG sites revealed that 11 of them could distinguish the samples into high- and low-methylation groups and could classify the prognostic information of samples after cluster analysis of the training set samples using the hierarchical clustering algorithm. Similar results were obtained from the test set and 12 glioma patients. Moreover, in vitro experiments revealed an inverse relationship between methylation level and migration ability or insensitivity to temozolomide (or radiotherapy) of glioma cells based on the final prognostic predictor. Thus, these results suggested that the model constructed in this study could provide guidance for clinicians regarding the prognosis of various epigenetic subtypes.