TY - JOUR
T1 - High-resolution proteomic analysis of medulloblastoma clinical samples identifies therapy resistant subgroups and MYC immunohistochemistry as a powerful outcome predictor
AU - Delaidelli, Alberto
AU - Burwag, Fares
AU - Ben-Neriah, Susana
AU - Suk, Yujin
AU - Shyp, Taras
AU - Kosteniuk, Suzanne
AU - Dunham, Christopher
AU - Cheng, Sylvia
AU - Okonechnikov, Konstantin
AU - Schrimpf, Daniel
AU - von Deimling, Andreas
AU - Ellezam, Benjamin
AU - Perreault, Sébastien
AU - Singh, Sheila
AU - Hawkins, Cynthia
AU - Kool, Marcel
AU - Pfister, Stefan M
AU - Steidl, Christian
AU - Hughes, Christopher
AU - Korshunov, Andrey
AU - Sorensen, Poul H
N1 - Publisher Copyright:
© The Author(s) 2025. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. All rights reserved.
PY - 2025/10/14
Y1 - 2025/10/14
N2 - Background. 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. Methods. We analyzed 56 formalin fixed paraffin embedded (FFPE) medulloblastoma samples by dataindependent acquisition mass spectrometry identifying a MYC proteome signature in therapy-resistant group 3 medulloblastoma. We validated MYC IHC prognostic and predictive value across 2 groups of 3/4 medulloblastoma clinical cohorts (n = 362) treated with standard therapies. Results. After the 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. Conclusions. 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.
AB - Background. 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. Methods. We analyzed 56 formalin fixed paraffin embedded (FFPE) medulloblastoma samples by dataindependent acquisition mass spectrometry identifying a MYC proteome signature in therapy-resistant group 3 medulloblastoma. We validated MYC IHC prognostic and predictive value across 2 groups of 3/4 medulloblastoma clinical cohorts (n = 362) treated with standard therapies. Results. After the 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. Conclusions. 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.
U2 - 10.1093/neuonc/noaf046
DO - 10.1093/neuonc/noaf046
M3 - Article
C2 - 40040502
SN - 1522-8517
VL - 27
SP - 2431
EP - 2444
JO - Neuro-oncology
JF - Neuro-oncology
IS - 9
ER -