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Merging the Histologic and Molecular Data Into an Integrated Score Significantly Improves Precision in Stratification of Meningiomas

Retrospectively and prospectively validated data from a multicentre retrospective analysis allowed to the German Consortium on Aggressive Meningiomas researchers to devise and validate an integrated score that leverages the advantages of WHO grading, specific copy-number variations (CNVs), and methylation-based classifications. Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grades 1 and 2 meningiomas. Dr. Felix Sahm of the Department of Neuropathology, University Hospital Heidelberg and CCU Neuropathology, German Consortium for Translational Cancer Research, German Cancer Research Centre in Heidelberg, Germany and colleagues, who derived a comprehensive grading algorithm that provides most accurate prediction for individual patients with meningioma, published their findings on 7 October 2021 in the Journal of Clinical Oncology.

The authors wrote in the study background that meningiomas are the most frequent primary intracranial tumours. Patient outcome varies widely from benign to highly aggressive. However, only biomarkers for highly aggressive meningioma are established, whereas no molecularly based stratification exists for the patients with low- and intermediate-risk meningioma. In particular, TERT promoter mutation or homozygous deletion of CDKN2A/B is included in the 2021 WHO classification as independent criteria of WHO grade 3 meningioma. However, the most pressing clinical need is not to identify high-grade meningioma, but to distinguish patients with low from those with intermediate risk of recurrence.

The WHO classification of meningiomas stratifies patient cohorts into three groups with low to high risk of progression. Various approaches to increase risk prediction accuracy for individual patients with meningioma exist. CNVs are enriched in aggressive meningiomas, and methylation-based classification was introduced as a novel tool for meningioma stratification. Yet, these approaches lack comprehensive validation and integration into one unified classification concept, preventing their routine application.

The German Consortium on Aggressive Meningiomas investigators generated DNA methylation data and copy-number information for 3,031 meningiomas from 2,868 patients, and mutation data for 858 samples. They analyzed DNA methylation subgroups, CNVs, mutations, and WHO grading. Prediction power for outcome was assessed in a retrospective cohort of 514 patients, validated on a retrospective cohort of 184, and on a prospective cohort of 287 cases.

Compared with the WHO classification, CNV and methylation subgrouping independently resulted in increased prediction accuracy of risk of recurrence. Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy. This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (p = 0.005).

Besides the overall stratification advantage, the integrated score separated more precisely for risk of progression at the diagnostically challenging interface of WHO grades 1 and 2 tumours with hazard ratios of 4.34 and 3.34 in retrospective and prospective validation cohorts.

The authors concluded that integrated molecular-morphologic score has immediate effect on risk stratification for a substantial number of patients and holds potential to transform the work-up of diagnostic meningioma samples similar to the way on how molecular profiling has changed assessment and treatment decisions for parenchymal brain tumours.

The study was supported by the Else Kröner Fresenius Foundation, the German Cancer Aid, and the Hertie Foundation.


Maas SLN, Stichel D, Hielscher T, et al. Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated. JCO; Published online 7 October 2021. DOI: 10.1200/JCO.21.00784.



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