Abstract

Abstract BACKGROUND MGMT promoter methylation in IDH-mutant gliomas was associated with improved survival in a recent study (PMID 35386566) but did not account for the updated WHO classification of CNS tumors. We evaluated the prognostic value of MGMT methylation in IDH-mutant gliomas incorporating the 2021 WHO classification. METHODS We retrospectively identified 431 patients with IDH-mutant gliomas treated at a single institution from 2010-2020. Kaplan-Meier method was used to estimate OS and PFS rates. Log-Rank test was used to evaluate differences between groups. RESULTS Median age was 36.2 years. MGMT promoter was methylated in 49.6%, unmethylated in 17.2%, partially methylated in 6.7%, and untested in 26.5%. Histological diagnosis was consistent with astrocytoma in 45.7%, oligodendroglioma in 33.9%, glioblastoma in 16.4%, and oligoastrocytoma in 4%. After accounting for 1p/19q and CDKN2A statuses, 190 patients had an integrated diagnosis of astrocytoma, grade 2 or 3; 94 had astrocytoma, grade 4; and 147 had oligodendroglioma, grade 2 or 3. There were 101 death events. Median OS was 33.36 years and median PFS was 5.67 years in MGMT methylated gliomas, compared to median OS of 12.54 years (p=0.0064) and median PFS of 3.91 years (p=0.0034) in unmethylated tumors. Upon univariate subgroup analysis, MGMT methylation was associated with significantly longer OS in histological astrocytomas, grade 2 or 4. However, when stratifying patients according to 2021 WHO classification of CNS tumors, there was no significant difference in OS between MGMT methylated and unmethylated astrocytomas or oligodendrogliomas, irrespective of WHO grade. CONCLUSION MGMT promoter methylation was associated with prolonged OS in histological astrocytomas, IDH-mutant. However, MGMT status did not impact survival after incorporating 2021 WHO classification of CNS tumors, suggesting that 1p/19q co-deletion and CDKN2A homozygous deletion are stronger prognostic factors in our cohort. The number of survival events was limited; larger datasets are required for more definitive conclusions.

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