PATH-39. INTEGRATED MOLECULAR-MORPHOLOGICAL MENINGIOMA CLASSIFICATION: A MULTICENTER RETROSPECTIVE ANALYSIS, RETRO- AND PROSPECTIVELY VALIDATED
Authors: Maas Sybren , Stichel Damian , Hielscher Thomas , Sievers Philipp , Berghoff Anna , Schrimpf Daniel , Sill Martin , Euskirchen Philipp , Reuss David , Dohmen Hildegard , Stein Marco , Baumgarten Peter , Ricklefs Franz , Rushing Elizabeth , Bewerunge-Hudler Melanie , Ketter Ralf , Schittenhelm Jens , Jaunmuktane Zane , Leu Severina , Grady Conor , Serrano Jonathan , Golfinos John , Sen Chandra , Mawrin Christian , Jungk Christine , Hänggi Daniel , Westphal Manfred , Lamszus Katrin , Etminan Nima , Unterberg Andreas , Harter Patrick , Wirsching Hans-Georg , Neidert Marian Christoph , Ratliff Miriam , Platten Michael , Snuderl Matija , Aldape Kenneth , Brandner Sebastian , Hench Jürgen , Frank Stephan , Pfister Stefan , Jones David , Reifenberger Guido , Acker Till , Wick Wolfgang , Weller Michael , Preusser Matthias , von Deimling Andreas , Sahm Felix 
Published: November 2021

PURPOSE

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

PATIENTS AND METHODS

DNA methylation data and copy-number information were generated for 3,031 meningiomas of 2,868 individual patients, with mutation data for 858 samples. DNA methylation subgroups, copy-number variations (CNV), mutations and WHO grading were comparatively analyzed. Prediction power for outcome of these parameters was assessed in an initial retrospective cohort of 514 patients, and validated on a retrospective cohort of 184, and on a prospective cohort of 287 multi-center cases, respectively.

RESULTS

Both CNV and methylation family- (MF)-based subgrouping independently resulted in an increase in prediction accuracy of risk of recurrence compared to the WHO classification (c-indexes WHO 2016, CNV, and MF 0.699, 0.706 and 0.721, respectively). Merging all independently powerful risk stratification approaches into an integrated molecular-morphological score resulted in a 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=0.005). 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 (HR 4.56 [2.97;7.00], 4.34 [2.48;7.57] and 3.34 [1.28; 8.72] for discovery, retrospective, and prospective validation cohort, respectively).

CONCLUSIONS

Merging these layers of histological 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 meningioma patients on the basis of robust outcome prediction.