%0 Journal Article
%A Delaidelli, Alberto
%A Burwag, Fares
%A Ben-Neriah, Susana
%A Suk, Yujin
%A Shyp, Taras
%A Kosteniuk, Suzanne
%A Dunham, Christopher
%A Cheng, Sylvia
%A Okonechnikov, Konstantin
%A Schrimpf, Daniel
%A von Deimling, Andreas
%A Ellezam, Benjamin
%A Perreault, Sébastien
%A Singh, Sheila
%A Hawkins, Cynthia
%A Kool, Marcel
%A Pfister, Stefan
%A Steidl, Christian
%A Hughes, Christopher
%A Korshunov, Andrey
%A Sorensen, Poul H
%T High-resolution proteomic analysis of medulloblastoma clinical samples identifies therapy resistant subgroups and MYC immunohistochemistry as a powerful outcome predictor.
%J Neuro-Oncology
%V nn
%@ 1522-8517
%C Oxford
%I Oxford Univ. Press
%M DKFZ-2025-00486
%P nn
%D 2025
%Z epub
%X While international consensus and the 2021 WHO classification recognize multiple molecular medulloblastoma subgroups, these are difficult to identify in clinical practice utilizing routine approaches. As a result, biology-driven risk stratification and therapy assignment for medulloblastoma remains a major clinical challenge. Here, we report mass spectrometry-based analysis of clinical samples for medulloblastoma subgroup discovery, highlighting a MYC-driven prognostic signature and MYC immunohistochemistry (IHC) as a clinically tractable method for improved risk stratification.We analyzed 56 formalin fixed paraffin embedded (FFPE) medulloblastoma samples by data independent acquisition mass spectrometry identifying a MYC proteome signature in therapy resistant Group 3 medulloblastoma. We validated MYC IHC prognostic and predictive value across two Group 3/4 medulloblastoma clinical cohorts (n=362) treated with standard therapies.After exclusion of WNT tumors, MYC IHC was an independent predictor of therapy resistance and death [HRs 23.6 and 3.23; 95
%K FFPE proteomics (Other)
%K MYC (Other)
%K Medulloblastoma (Other)
%K biomarker (Other)
%K risk-stratification (Other)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:40040502
%R 10.1093/neuonc/noaf046
%U https://inrepo02.dkfz.de/record/299528