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◆ Neurosurgical focus2026-09-01

Integrating molecular classification into postoperative intracranial meningioma management.

Brooke C Braman, David R Raleigh

原始摘要(英文原文)· Original abstract
Meningioma risk stratification has historically been defined by the Simpson grade of resection and the histological grade of tumor tissue. Recent scientific advances have elucidated the molecular architecture of meningioma, and multiple groups have developed molecular classification systems that refine meningioma risk stratification. Reported meningioma molecular classification systems use DNA methylation or gene expression profiling, copy number alterations, DNA mutations, or multiple molecular and histological variables combined into individual models. While the details of meningioma molecular classification systems may vary, concordance is observed across unsupervised systems that are not trained on clinical outcomes, suggesting conserved tumor biology. Moreover, some molecular classification systems outperform the WHO grade in risk stratification and can identify meningiomas that may benefit from radiotherapy or targeted therapies. According to this emerging paradigm, patients with molecular high-risk meningioma may be guided toward postoperative radiotherapy or targeted therapies. In contrast, patients with molecular low-risk meningioma may be followed with serial postoperative imaging in the right clinical context. Practical and logistical barriers must be overcome to implement meningioma molecular classification into clinical practice, and prospective randomized trials are needed to validate emerging molecular risk stratification systems and define the subsets of patients who might benefit the most from their use. In the interim, clinicians are increasingly recognizing the value of meningioma molecular classification and are already implementing these approaches into the postoperative management of patients with meningioma.
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Integrating molecular classification into postoperative intracranial meningioma management. — 科研速览 Science Skim