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