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@ARTICLE{Delaidelli:299528,
      author       = {A. Delaidelli and F. Burwag and S. Ben-Neriah and Y. Suk
                      and T. Shyp and S. Kosteniuk and C. Dunham and S. Cheng and
                      K. Okonechnikov$^*$ and D. Schrimpf$^*$ and A. von
                      Deimling$^*$ and B. Ellezam and S. Perreault and S. Singh
                      and C. Hawkins and M. Kool$^*$ and S. Pfister$^*$ and C.
                      Steidl and C. Hughes and A. Korshunov$^*$ and P. H.
                      Sorensen},
      title        = {{H}igh-resolution proteomic analysis of medulloblastoma
                      clinical samples identifies therapy resistant subgroups and
                      {MYC} immunohistochemistry as a powerful outcome predictor.},
      journal      = {Neuro-Oncology},
      volume       = {nn},
      issn         = {1522-8517},
      address      = {Oxford},
      publisher    = {Oxford Univ. Press},
      reportid     = {DKFZ-2025-00486},
      pages        = {nn},
      year         = {2025},
      note         = {epub},
      abstract     = {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; $95\%$ confidence interval (CI) 1.04-536.18
                      and 1.84-5.66; P = .047 and < .001]. Notably, only $~50\%$
                      of the MYC IHC positive tumors harbored MYC amplification.
                      Accordingly, cross-validated survival models incorporating
                      MYC IHC outperformed current risk stratification schemes
                      including MYC amplification, and reclassified $~20\%$ of
                      patients into a more appropriate very high-risk
                      category.This study provides a high-resolution proteomic
                      dataset that can be used as a reference for future biomarker
                      discovery. Biology-driven clinical trials should consider
                      MYC IHC status in their design. Integration of MYC IHC in
                      classification algorithms for non-WNT tumors could be
                      rapidly adopted on a global scale, independently of advanced
                      but technically challenging molecular profiling techniques.},
      keywords     = {FFPE proteomics (Other) / MYC (Other) / Medulloblastoma
                      (Other) / biomarker (Other) / risk-stratification (Other)},
      cin          = {B062 / HD01 / B300},
      ddc          = {610},
      cid          = {I:(DE-He78)B062-20160331 / I:(DE-He78)HD01-20160331 /
                      I:(DE-He78)B300-20160331},
      pnm          = {312 - Funktionelle und strukturelle Genomforschung
                      (POF4-312)},
      pid          = {G:(DE-HGF)POF4-312},
      typ          = {PUB:(DE-HGF)16},
      pubmed       = {pmid:40040502},
      doi          = {10.1093/neuonc/noaf046},
      url          = {https://inrepo02.dkfz.de/record/299528},
}