Integrating genetic, epigenetic, and machine learning–based computational pathology approaches for refining molecular and prognostic classification of meningiomas

Recent advances in the molecular understanding of meningiomas have challenged traditional morphology-based grading, particularly for CNS WHO grade 2 tumors, which exhibit heterogeneous clinical behavior. The fifth edition of the WHO CNS Tumour Classification integrates key molecular markers, such as TERT promoter mutations and CDKN2A/B homozygous deletions as criteria for high-grade meningioma designation. However, these alterations remain uncommon in lowergrade tumors, necessitating improved molecular-clinicopathological stratification frameworks to better predict prognosis and guide treatment. In this context, AI-driven histopathological models like Hetairos have achieved robust classification accuracy relying on morphological features but show limitations in prognostication. Arraybased DNA methylation profiling has emerged as a powerful tool enabling refined risk stratification through integrative analysis of epigenetic patterns and copy number variations, including clinically significant 1p/22q co-deletions linked to recurrence risk. Despite its advantages, methylation profiling is limited by costs, expertise, and tissue requirements. Thus, complementary use of widely accessible methods such as fluorescence in situ hybridization (FISH) and immunohistochemical surrogates (e.g., p16 and MTAP) for CDKN2A/B loss assessment offer a practical alternative for routine diagnostics. This integrated investigation highlights the enhanced prognostic power derived from combining molecular analyses with traditional pathology, advocating for the adoption of standardized, scalable approaches to improve meningioma patient management through tailored therapies, particularly radiotherapy allocation. By addressing diagnostic complexities posed by tumor heterogeneity with multidimensional molecular tools, this study contributes to more precise, personalized stratification in meningioma care