20225-03-13 カナダ・ブリティッシュコロンビア大学(UBC)
<関連情報>
- https://news.ubc.ca/2025/03/new-test-medulloblastoma-high-risk-childhood-brain-tumours/
- https://academic.oup.com/neuro-oncology/advance-article-abstract/doi/10.1093/neuonc/noaf046/8052127?redirectedFrom=fulltext
髄芽腫臨床サンプルの高分解能プロテオミクス解析により、治療抵抗性サブグループと強力な転帰予測因子としてのMYC免疫組織化学が同定された High-resolution proteomic analysis of medulloblastoma clinical samples identifies therapy resistant subgroups and MYC immunohistochemistry as a powerful outcome predictor
Alberto Delaidelli, Fares Burwag, Susana Ben-Neriah, Yujin Suk, Taras Shyp, Suzanne Kosteniuk, Christopher Dunham, Sylvia Cheng, Konstantin Okonechnikov, Daniel Schrimpf …
Neuro-Oncology Published:05 March 2025
DOI:https://doi.org/10.1093/neuonc/noaf046
Abstract
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 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.
Results
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.
Conclusion
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.
