Integrative analysis of DNA methylation and gene expression to identify key epigenetic genes in glioblastoma

Abstract

Glioblastoma (GBM) ranks the most common and aggressive primary brain malignant tumor worldwide. However, the survival rates of patients remain very poor. Therefore, molecular oncology of GBM are urgently needed. In this study, we performed an integrative analysis of DNA methylation and gene expression to identify key epigenetic genes in GBM. The methylation and gene expression of GBM patients in The Cancer Genome Atlas (TCGA) database were downloaded. After data preprocessing, we identified 4,881 differentially expressed genes (DEGs) between tumor and normal samples, including 1,111 upregulated and 3,770 downregulated genes. Then, we randomly separated all samples into training set (n = 69) and testing set (n = 69). We next obtained 11,269 survival-methylation sites by univariate and multivariate Cox regression analyses. In the correlation analysis, we defined 198 low promoter methylation with high gene expression as epigenetically induced (EI) genes and 111 high promoter methylation with low gene expression as epigenetically suppressed (ES) genes. Key markers including C1orf61 and FAM50B were selected with a Pearson correlation coefficient greater than 0.75. Further, we chose the 20 CpG methylation sites of above two genes in unsupervised clustering analysis using the Euclidean distance. We found that the prognosis of the hypomethylated group was significantly better than that in the hypermethylated group (log-rank test p -value = 0.011). Based on the validation in the TCGA testing set and GEO dataset, we validated the prognostic value of our signature ( p -value = 0.02 in TCGA and 0.012 in GEO). In conclusion, our findings provided predictive and prognostic value as methylation-based biomarkers for the diagnosis and treatment of GBM.

The Emerging Roles of RNA Modifications in Glioblastoma

“…Epigenetic alterations are considered as promising markers for GBM diagnosis [159][160][161][162], although this study is just the first step for their possible applications in GBM diagnosis. Besides, some epigenetic status really account for the outcome of GBM.…”

Genome‐wide identification of CpG island methylator phenotype related gene signature as a novel prognostic biomarker of gastric cancer

“…CpG island methylator phenotype (CIMP) in tumors, which has been initially described and broadly debated in colorectal cancer ( Hughes et al, 2013 ). Lately CIMP has been described in other tumor types including bladder, breast, glioblastoma, pancreatic and prostate cancers, as well as for gastric adenocarcinomas and is considered to be helpful for predicting prognosis ( Jia et al, 2019 ; Moarii, Reyal & Vert, 2015 ; Ueki et al, 2000 ). In GC, conflicting conclusions regarding the prognostic association of CIMP have been scattered among previous studies, owing to the limitation of selected DNA methylation markers and the presence of multiple confounding factors in these studies ( An et al, 2005 ; Ben Ayed-Guerfali et al, 2011 ; Park et al, 2010 ).…”

Transcriptome analysis and prognostic model construction based on splicing profiling in glioblastoma

“…treatment of GBM (36). Additionally, a previous study has validated that a family with sequence similarity to FAM50B serves a key role as methylation-based biomarkers for the diagnosis and treatment of GBM (37). Furthermore, by specifically inhibiting HSPA5, a new compound known as HA15 was able to increase the unfolded protein response and lead to the death of cancer cells by concomitant induction of autophagy and apoptosis, both in vitro and in vivo (38).…”