Quantitative analysis of MGMT promoter methylation in glioblastoma suggests nonlinear prognostic effect

Abstract

Abstract Background Epigenetic inhibition of the O6-methylguanine-DNA-methyltransferase (MGMT) gene has emerged as a clinically relevant prognostic marker in glioblastoma (GBM). Methylation of the MGMT promoter has been shown to increase chemotherapy efficacy. While traditionally reported as a binary marker, recent methodological advancements have led to quantitative methods of measuring promoter methylation, providing clearer insight into its functional relationship with survival. Methods A CLIA assay and bisulfite sequencing was utilized to develop a quantitative, 17-point, MGMT promoter methylation index. GBMs of 240 newly diagnosed patients were sequenced and risk for mortality was assessed. Nonlinearities were captured by fitting splines to Cox proportional hazard models and plotting smoothed residuals. Covariates included age, Karnofsky performance status, IDH1 mutation, and extent of resection. Results Median follow-up time and progression-free survival were 16 and 9 months, respectively. A total of 176 subjects experienced death. A one-unit increase in promoter CpG methylation resulted in a 4% reduction in hazard (95% CI 0.93–0.99, P < .005). GBM patients with low levels of promoter methylation (1-6 CpG sites) fared markedly worse (HR = 1.62, 95% CI 1.03–2.54, P < .036) than individuals who were unmethylated. Subjects with medium levels of promoter methylation (7–12 sites) had the greatest reduction in hazard (HR = 0.48, 95% CI 0.29–0.80, P < .004), followed by individuals in the highest promoter methylation tertile (HR = 0.62, 95% CI 0.40–0.97, P < .035). Conclusions Our findings suggest that the relationship between the extent of MGMT promoter methylation and survival in GBM may be nonlinear. These findings challenge the current understanding of MGMT and underlines the clinical importance of determining its prognostic utility. Potential limitations include censoring, sample size, and extraneous mutations.