Defining the recommended gray zone in MGMT promoter methylation pyrosequencing reporting: A robust translatable method to implement new EANO guidelines

Wickens, Polly; Cruickshank, Gabrielle; Wildman, Jack; Doyle, George; Whittaker, Ed; Waller, Sara; McKeeve, Claire; Faulkner, Claire; Yarram-Smith, Laura; White, Paul; Kurian, Kathreena M

Abstract

Abstract

Background: The DNA repair protein O6-methylguanine-DNA methyltransferase (MGMT) may cause resistance of tumour cells to alkylating agents, and is a predictive biomarker in high-grade gliomas treated with temozolomide. Recent EANO guidelines recommend internal validation of MGMT methylation cut-offs and reporting of gray zone values. This study aimed to develop a method to derive a gray zone from pyrosequencing MGMT methylation data.

Methods: We developed a method to find the optimal gray zone using pyrosequencing MGMT methylation values (CpG sites 72-83) from 308 glioblastoma cases with overall survival data. Each integer below the methylated threshold defined a new possible gray zone and categorisation which was used as a variable in a multivariate Cox proportional hazards regression model. The optimal gray zone was selected as the option that had a statistically different survival function from the methylated and unmethylated groups. We applied the method to a validation cohort of 115 glioblastoma cases.

Results: Our method successfully identified a gray zone in our development cohort. The following categorisation gave 3 distinct survival functions: methylated >=12% (n=152 cases), gray zone 5-12% (n=43), unmethylated <5% (n=113). This categorisation was better at predicting survival than the existing categorisation (methylated >=12%, unmethylated <12%). Validating our method showed a sufficient sample size and time to follow up is recommended to apply our method.

Conclusions: We have developed a translatable method to identify the optimal MGMT gray zone from pyrosequencing data in line with recent EANO guidelines, to enhance clinical decision-making.

• Journal Article Type: Article
• Acceptance Date: Mar 13, 2025
• Deposit Date: Mar 13, 2025
• Journal: Neuro Oncology Advances
• Electronic ISSN: 2632-2498
• Publisher: Oxford University Press (OUP)
• Peer Reviewed: Peer Reviewed
• Public URL: https://uwe-repository.worktribe.com/output/13940972
• Publisher URL: https://academic.oup.com/noa