Meningioma Diagnosis and Treatment Strategies

Meningiomas are the most frequent primary intracranial tumours in adults, exhibiting a spectrum from benign to highly aggressive phenotypes. Diagnosis typically begins with neuroimaging, principally magnetic resonance imaging, to characterise tumour location, size and morphological features. Contrast enhancement and volumetric assessment inform differential diagnosis and surgical planning. Definitive grading relies on histopathological examination, supplemented increasingly by molecular markers and DNA methylation profiles to refine prognostication. Treatment strategies are stratified by grade and patient factors. Gross total surgical resection remains the cornerstone for low‐ and intermediate‐grade tumours, whereas atypical or anaplastic lesions often warrant adjuvant radiotherapy or stereotactic radiosurgery to reduce recurrence risk. Emerging systemic approaches targeting molecular drivers and the tumour microenvironment are under evaluation for refractory cases. Noninvasive techniques such as liquid biopsy and advanced imaging analytics promise earlier detection of recurrence and tailored follow-up intervals. A multidisciplinary framework integrating neurosurgery, radiation oncology, neuroradiology and molecular diagnostics underpins optimal management, with ongoing efforts focused on minimising morbidity and maximising quality of life for patients worldwide.

Research from Nature Portfolio

Recent studies have identified tumour-specific DNA methylation signatures detectable in blood and plasma, enabling noninvasive diagnosis of meningioma and prediction of recurrence risk. Machine learning models trained on these methylation profiles demonstrate high accuracy in distinguishing meningioma subtypes and forecasting tumour behaviour, paving the way for personalised monitoring strategies. Separate integrated genomic analyses of primary atypical meningiomas reveal recurrent loss of the NF2 gene in association with chromosomal instability and epigenetic dysregulation via polycomb repressive complex 2. Upregulation of EZH2 and cell cycle transcription factors such as E2F2 and FOXM1 characterise these tumours, highlighting potential therapeutic targets distinct from those in tumours with TERT promoter alterations. These insights refine the molecular taxonomy of de novo atypical meningiomas and inform the development of targeted epigenetic inhibitors.

Meningioma Diagnosis and Treatment Strategies publication trend

The graph below shows the total number of articles in meningioma diagnosis and treatment strategies across all publications each year (not limited to Nature Index journals).

Technical terms

Liquid biopsy: A minimally invasive test that detects tumour-derived molecules, such as DNA methylation markers, in blood or plasma.

DNA methylation: An epigenetic modification of cytosine residues influencing gene expression and serving as a biomarker for tumour classification.

Organoid: A three-dimensional cell culture model derived from patient tumour tissue that recapitulates key histological and molecular features.

Single-cell RNA sequencing (scRNA-Seq): A technique that profiles gene expression at the single-cell level to reveal intratumoral heterogeneity.

Radiomic features: Quantitative metrics extracted from imaging data that quantify tumour shape, texture and intensity.

Semantic features: Qualitative descriptors of imaging appearances, such as necrosis, heterogeneity and margin irregularity, used to infer tumour grade.

References

1. Detection of diagnostic and prognostic methylation-based signatures in liquid biopsy specimens from patients with meningiomas. Nature Communications (2023).
2. Novel Human Meningioma Organoids Recapitulate the Aggressiveness of the Initiating Cell Subpopulations Identified by ScRNA‐Seq. Advanced Science (2023).
3. Meningioma: International Consortium on Meningiomas consensus review on scientific advances and treatment paradigms for clinicians, researchers, and patients. Neuro-Oncology (2024).
4. Integrated genomic analyses of de novo pathways underlying atypical meningiomas. Nature Communications (2017).
5. Radiographic prediction of meningioma grade by semantic and radiomic features. PLOS ONE (2017).