DNA methylation in glioblastoma: impact on gene expression and clinical outcome

Abstract

Background: Changes in promoter DNA methylation pattern of genes involved in key biological pathways have been reported in glioblastoma. Genome-wide assessments of DNA methylation levels are now required to decipher the epigenetic events involved in the aggressive phenotype of glioblastoma, and to guide new treatment strategies.

Results: We performed a whole-genome integrative analysis of methylation and gene expression profiles in 40 newly diagnosed glioblastoma patients. We also screened for associations between the level of methylation of CpG sites and overall survival in a cohort of 50 patients uniformly treated by surgery, radiotherapy and chemotherapy with concomitant and adjuvant temozolomide (STUPP protocol). The methylation analysis identified 616 CpG sites differentially methylated between glioblastoma and control brain, a quarter of which was differentially expressed in a concordant way. Thirteen of the genes with concordant CpG sites displayed an inverse correlation between promoter methylation and expression level in glioblastomas: B3GNT5, FABP7, ZNF217, BST2, OAS1, SLC13A5, GSTM5, ME1, UBXD3, TSPYL5, FAAH, C7orf13, and C3orf14. Survival analysis identified six CpG sites associated with overall survival. SOX10 promoter methylation status (two CpG sites) stratified patients similarly to MGMT status, but with a higher Area Under the Curve (0.78 vs. 0.71, p-value < 5e-04). The methylation status of the FNDC3B, TBX3, DGKI, and FSD1 promoters identified patients with MGMT-methylated tumors that did not respond to STUPP treatment (p-value < 1e-04).

Conclusions: This study provides the first genome-wide integrative analysis of DNA methylation and gene expression profiles obtained from the same GBM cohort. We also present a methylome-based survival analysis for one of the largest uniformly treated GBM cohort ever studied, for more than 27,000 CpG sites. We have identified genes whose expression may be tightly regulated by epigenetic mechanisms and markers that may guide treatment decisions.

Figure 1

Mean of the maximal gene expression values by β-value bins (5% wide), in GBMs (n = 40). The expression values presented are normalized and log-transformed intensities. Errors bars are also shown. Gray rectangles define the β-value ranges for which a change in maximal expression values is observed.

Figure 2

Hierarchical clustering of the 616DM CpG sites in GBMs vs. control brain (N). For each CpG site, a horizontal black bar on the right indicates membership of the hypermethylated subset, a CpG island (CGI), or the location within the promoter of a PRC2 target.

Figure 3

Analysis of the hypermethylated CpGs located within PRC2-targeted promoters. (A) Heatmap of the hypermethylated CpGs located within PRC2-targeted promoters. Samples are ranked horizontally as a function of their mean β-values. Two clusters representing extreme methylation changes (Δβ) relative to control samples (N) are framed. (B) EZH2 and DNMT3A expression level in control samples, GBM samples, the low- and the high-Δβ clusters. The expression values presented are normalized and log-transformed intensities.

Figure 4

Expression and methylation profiles for the SERPINB1 gene in GBM patients (n = 40). The expression values presented are normalized and log-transformed intensities. The methylation values are β-values.

Figure 5

Kaplan-Meier estimation of overall survival in 50 GBMs treated in accordance with the STUPP protocol. Patients were assigned to groups according to the methylation status of (A) MGMT, (B) SOX10 site #2, (C) MGMT and FNDC3B, and (D) MGMT and TBX3. M: methylated; NM: non methylated. P-values for the difference in OS (log-rank test), size and median survival of each group are also reported. See Table 1 for β-values cut-offs.