Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated
Authors: Maas Sybren L. N. , Stichel Damian , Hielscher Thomas , Sievers Philipp , Berghoff Anna S. , Schrimpf Daniel , Sill Martin , Euskirchen Philipp , Blume Christina , Patel Areeba , Dogan Helin , Reuss David , Dohmen Hildegard , Stein Marco , Reinhardt Annekathrin , Suwala Abigail K. , Wefers Annika K. , Baumgarten Peter , Ricklefs Franz , Rushing Elisabeth J. , Bewerunge-Hudler Melanie , Ketter Ralf , Schittenhelm Jens , Jaunmuktane Zane , Leu Severina , Greenway Fay E. A. , Bridges Leslie R. , Jones Timothy , Grady Conor , Serrano Jonathan , Golfinos John , Sen Chandra , Mawrin Christian , Jungk Christine , Hänggi Daniel , Westphal Manfred , Lamszus Katrin , Etminan Nima , Jungwirth Gerhard , Herold-Mende Christel , Unterberg Andreas , Harter Patrick N. , Wirsching Hans-Georg , Neidert Marian C. , Ratliff Miriam , Platten Michael , Snuderl Matija , Aldape Kenneth D. , Brandner Sebastian , Hench Jürgen , Frank Stephan , Pfister Stefan M. , Jones David T. W. , Reifenberger Guido , Acker Till , Wick Wolfgang , Weller Michael , Preusser Matthias , von Deimling Andreas , Sahm Felix ,   For the German Consortium on Aggressive Meningiomas (KAM)
Published: October 2021

PURPOSE

Meningiomas are the most frequent primary intracranial tumors. Patient outcome varies widely from benign to highly aggressive, ultimately fatal courses. Reliable identification of risk of progression for individual patients is of pivotal importance. However, only biomarkers for highly aggressive tumors are established ( CDKN2A/B and TERT), whereas no molecularly based stratification exists for the broad spectrum of patients with low- and intermediate-risk meningioma.

METHODS

DNA methylation data and copy-number information were generated for 3,031 meningiomas (2,868 patients), and mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNVs), mutations, and WHO grading were analyzed. 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 multicenter cases.

RESULTS

Both CNV- and methylation family–based subgrouping independently resulted in increased prediction accuracy of risk of recurrence compared with the WHO classification (c-indexes WHO 2016, CNV, and methylation family 0.699, 0.706, and 0.721, respectively). Merging all risk stratification approaches into an integrated molecular-morphologic score resulted in further substantial increase in accuracy (c-index 0.744). This integrated score consistently provided superior accuracy in all three cohorts, significantly outperforming WHO grading (c-index difference P = .005). Besides the overall stratification advantage, the integrated score separates more precisely for risk of progression at the diagnostically challenging interface of WHO grade 1 and grade 2 tumors (hazard ratio 4.34 [2.48-7.57] and 3.34 [1.28-8.72] retrospective and prospective validation cohorts, respectively).

CONCLUSION

Merging these layers of histologic and molecular data into an integrated, three-tiered score significantly improves the precision in meningioma stratification. Implementation into diagnostic routine informs clinical decision making for patients with meningioma on the basis of robust outcome prediction.