Defining the recommended gray zone in O6-methylguanine-DNA methyltransferase promoter methylation pyrosequencing reporting: A robust, translatable method to implement new EANO guidelines.

定义 O6-甲基鸟嘌呤-DNA 甲基转移酶启动子甲基化焦磷酸测序报告中推荐的灰色区域:一种稳健、可转化的方法来实施新的 EANO 指南

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作者:Taylor Polly, Cruickshank Gabrielle, Wildman Jack, Doyle George, Whittaker Ed, Walker Sara, McKeeve Claire, Faulkner Claire, Yarram-Smith Laura, White Paul, Kurian Kathreena M
BACKGROUND: The DNA repair protein O6-methylguanine-DNA methyltransferase (MGMT) may cause resistance of tumor cells to alkylating agents and is a predictive biomarker in high-grade gliomas treated with temozolomide. Recent European Association of Neuro-Oncology (EANO) guidelines recommend internal validation of MGMT methylation cutoffs 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 categorization 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, with the largest log-likelihood ratio test statistic. 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 categorization gave 3 distinct survival functions: methylated ≥12% (n†=†152 cases), gray zone 5%-12% (n†=†43), and unmethylated <5% (n†=†113). This categorization was better at predicting survival than the existing categorization (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.

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