Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

TY - JOUR

T1 - Integrated Molecular-Morphologic Meningioma Classification: A Multicenter Retrospective Analysis, Retrospectively and Prospectively Validated

AU - Maas, Sybren L N

AU - Stichel, Damian

AU - Hielscher, Thomas

AU - Sievers, Philipp

AU - Berghoff, Anna S

AU - Schrimpf, Daniel

AU - Sill, Martin

AU - Euskirchen, Philipp

AU - Blume, Christina

AU - Patel, Areeba

AU - Dogan, Helin

AU - Reuss, David

AU - Dohmen, Hildegard

AU - Stein, Marco

AU - Reinhardt, Annekathrin

AU - Suwala, Abigail K

AU - Wefers, Annika K

AU - Baumgarten, Peter

AU - Ricklefs, Franz

AU - Rushing, Elisabeth J

AU - Bewerunge-Hudler, Melanie

AU - Ketter, Ralf

AU - Schittenhelm, Jens

AU - Jaunmuktane, Zane

AU - Leu, Severina

AU - Greenway, Fay E A

AU - Bridges, Leslie R

AU - Jones, Timothy

AU - Grady, Conor

AU - Serrano, Jonathan

AU - Golfinos, John

AU - Sen, Chandra

AU - Mawrin, Christian

AU - Jungk, Christine

AU - Hänggi, Daniel

AU - Westphal, Manfred

AU - Lamszus, Katrin

AU - Etminan, Nima

AU - Jungwirth, Gerhard

AU - Herold-Mende, Christel

AU - Unterberg, Andreas

AU - Harter, Patrick N

AU - Wirsching, Hans-Georg

AU - Neidert, Marian C

AU - Ratliff, Miriam

AU - Platten, Michael

AU - Snuderl, Matija

AU - Aldape, Kenneth D

AU - Brandner, Sebastian

AU - Hench, Jürgen

AU - Frank, Stephan

AU - Pfister, Stefan M

AU - Jones, David T W

AU - Reifenberger, Guido

AU - Acker, Till

AU - Wick, Wolfgang

AU - Weller, Michael

AU - Preusser, Matthias

AU - von Deimling, Andreas

AU - Sahm, Felix

AU - German Consortium on Aggressive Meningiomas (KAM)

PY - 2021/12/1

Y1 - 2021/12/1

N2 - 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.

AB - 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.

U2 - 10.1200/JCO.21.00784

DO - 10.1200/JCO.21.00784

M3 - SCORING: Journal article

C2 - 34618539

VL - 39

SP - 3839

EP - 3852

JO - J CLIN ONCOL

JF - J CLIN ONCOL

SN - 0732-183X

IS - 34

ER -