Identification of glioblastoma-specific prognostic biomarkers via an integrative analysis of DNA methylation and gene expression.

摘要: Glioblastoma (GBM) is the most aggressive and lethal tumor of central nervous system. The present study set out to identify reliable prognostic predictive biomarkers for patients with GBM. RNA-sequencing data were obtained from Cancer Genome Atlas database DNA methylation downloaded using University California Santa Cruz-Xena database. expression differences between GBM, survival times <1 ≥1 year investigated. A protein-protein interaction network was constructed functional enrichment analyses differentially expressed methylated genes performed. Hub identified Cytoscape plug-in cytoHubba software. Survival analysis performed survminer package, in order determine values hub genes. 71 that hypomethylated at high levels, four hypermethylated low levels These predominantly enriched 'JAK-STAT signaling pathway', 'transcriptional misregulation cancer' 'ECM-receptor interaction', which are associated GBM development. Among 24 identified, 15 possessed potential value. An integrative approach implemented analyze association changes gene assess time. results suggest these CpG-based may be useful practical tools predicting prognosis However, future research on and/or required develop personalized treatments