The distribution of isocitrate dehydrogenase mutations, O6-methylguanine-DNA methyltransferase promoter methylation, and 1p/19q codeletion in different glioma subtypes and their correlation with glioma prognosis in Taiwanese population: A single center study

The molecular characteristics of glioma patients, such as 1p/19q codeletion, MGMT promoter region methylation, and IDH1/IDH2 mutations, carry important information for tumor classification, biological behavior, and the prediction of patient survival. We sought to address the clinical characteristics of brain tumor patients in the Taiwanese population. Our aim was to compare the H&E-based classification and the 2016 WHO classification in glioma patients. 192 patients were recruited in this study including glioblastomas (GBMs) and lower-grade gliomas (LGGs). We performed assays to determine the statuses of 1p/19q codeletion, MGMT promoter methylation, and IDH mutations in tumors and assessed their associations with survival time. We also compared the difference between H&E and WHO 2016 classification. Using the H&E classification, the overall survival time (OST) was associated with IDH status in astrocytoma and oligoastrocytoma patients but not in oligodendroglioma and GBM patients. However, OST showed no significant correlation with MGMT promoter methylation in all the groups. Furthermore, no significant association was observed between 1p/19q codeletion and OST in GBM patients. Using the WHO 2016 classification, our results indicated that astrocytoma and oligodendroglioma patients with mutant IDH showed a significantly prolonged OST than patients with wild-type IDH. However, only oligodendroglioma patients with MGMT hypermethylation demonstrated statistically significant difference. Prognostic factors, including the age at diagnosis, IDH mutations, MGMT promoter methylation, and 1p/19q codeletion, could independently predict patient survival. Based on the WHO 2016 classification of glioma, the new histological groups provide a better and objective method to categorize glioma patients and predict patient survival.