Prognostic impact of genetic alterations and methylation classes in meningioma

Meningiomas are classified based on histological features, but genetic and epigenetic features are emerging as relevant biomarkers for outcome prediction and may supplement histomorphological evaluation. We investigated meningioma-relevant mutations and their correlation with DNA methylation clusters and patient survival times. Formalin-fixed and paraffin-embedded samples of 126 meningioma patients (WHO grade I 52/126; 41.3%; WHO grade II: 48/126; 38.1%; WHO grade III: 26/126; 20.6%) were investigated. We analyzed NF2, TRAF7, KLF4, ARID, SMO, AKT, TERT promotor, PIK3CA, and SUFU mutations using panel sequencing and correlated them to DNA methylation classes (MC) determined using 850k EPIC arrays. The TRAKL mutation genotype was characterized by the presence of any of the following mutations: TRAF7, AKT1, and KLF4. Survival data including progression-free survival (PFS) and overall survival (OS) was retrieved from chart review. Mutations were evident in 90/126 (71.4%) specimens with mutations in NF2 (39/126; 31.0%), TRAF7 (39/126; 31.0%) and KLF4 (25/126; 19.8%) being the most frequent ones. Two or more mutations were observed in 35/126 (27.8%) specimens. While TRAKL was predominantly found in benign MC, NF2 was associated with malign MC (p < 0.05). TRAF7, KLF4, and TRAKL mutation genotype were associated with improved PFS and OS (p < 0.05). TERT promotor methylation, intermediate, and malign MC were associated with impaired PFS and OS (p < 0.05). Methylation cluster showed better prognostic discrimination for PFS and OS (c-index 0.77/0.75) than each of the individual mutations (c-index 0.63/0.68). In multivariate analysis correcting for age, gender, MC, and WHO grade, none of the individual mutations except TERT remained an independent significant prognostic factor for PFS. Molecular profiling including mutational analysis and DNA methylation classification may facilitate more precise prognostic assessment and identification of potential targets for personalized therapy in meningioma patients.