Foramen magnum (FM) meningiomas pose significant surgical challenges and have high morbidity and mortality rates. This study aimed to investigate the distribution of clinically actionable mutations in FM meningiomas and identify clinical characteristics associated with specific mutational profiles. The authors conducted targeted next-generation sequencing of 62 FM meningiomas from three international institutions, covering all relevant meningioma genes (AKT1, KLF4, NF2, POLR2A, PIK3CA, SMO, TERT promoter, and TRAF7). Patients with a radiation-induced meningioma or neurofibromatosis type 2 (NF2) were excluded from the study. Additionally, patient and tumor characteristics, including age, sex, radiological features, and tumor location, were retrospectively collected and evaluated. The study cohort consisted of 46 female and 16 male patients. Clinically significant driver mutations were detected in 58 patients (93.5%). The most commonly observed alteration was TRAF7 mutations (26, 41.9%), followed by AKT1E17K mutations (19, 30.6%). Both mutations were significantly associated with an anterolateral tumor location relative to the brainstem (p = 0.0078). NF2 mutations were present in 11 cases (17.7%) and were associated with posterior tumor location, in contrast to tumors with TRAF7 and AKT1E17K mutations. Other common mutations in FM meningiomas included POLR2A mutations (8, 12.9%; 6 POLR2AQ403K and 2 POLR2AH439_L440del), KLF4K409Q mutations (7, 11.3%), and PIK3CA mutations (4, 6.5%; 2 PIK3CAH1047R and 2 PIK3CAE545K). POLR2A and KLF4 mutations exclusively occurred in female patients and showed no significant association with specific tumor locations. All tumors harboring AKT1E17K and POLR2A mutations displayed meningothelial histology. Ten tumors exhibited intratumoral calcification, which was significantly more frequent in NF2-mutant compared with AKT1-mutant FM meningiomas (p = 0.047). These findings provide important insights into the molecular genetics and clinicopathological characteristics of FM meningiomas. The identification of specific genetic alterations associated with tumor location, volume, calcification, histology, and sex at diagnosis may have implications for personalized treatment strategies in the future.
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