A microenvironment-determined risk continuum refines subtyping in meningioma and reveals determinants of machine learning-based tumor classification.
Maas SLN, Tang Y, Stutheit-Zhao E, Rahmanzade R, Blume C, Hielscher T, Zettl F, Benfatto S, Calafato D, Sill M, Benotmane JK, Yabo YA, Behling F, Suwala A, Kardo H, Ritter M, Peyre M, Sankowski R, Okonechnikov K, Sievers P, Patel A, Reuss D, Friedrich MJ, Stichel D, Schrimpf D, Van den Bosch TPP, Beck K, Wirsching HG, Jungwirth G, Hanemann CO, Lamszus K, Etminan N, Unterberg A, Mawrin C, Remke M, Ayrault O, Lichter P, Reifenberger G, Platten M, Kacprowski T, List M, Pauling JK, Baumbach J, Milde T, Grossmann R, Ram Z, Ratliff M, Mallm JP, Neidert MC, Bos EM, Prinz M, Weller M, Acker T, Hartmann FJ, Preusser M, Tabatabai G, Herold-Mende C, Krieg SM, Jones DTW, Pfister SM, Wick W, Kalamarides M, von Deimling A, Heiland DH, Hovestadt V, Gerstung M, Schlesner M; German “Aggressive Meningiomas” Consortium (KAM); Sahm F.
Maas SLN, et al. Among authors: list m.
Nat Genet. 2026 Feb;58(2):341-354. doi: 10.1038/s41588-025-02475-w. Epub 2026 Feb 9.
Nat Genet. 2026.
PMID: 41663806
Free PMC article.