High-resolution proteomic analysis of medulloblastoma clinical samples identifies therapy resistant subgroups and MYC immunohistochemistry as a powerful outcome predictor.

髓母细胞瘤 免疫组织化学 肿瘤科 生物 内科学 医学 癌症研究
作者
Alberto Delaidelli,Fares Burwag,Susana Ben‐Neriah,Yujin Suk,Taras Shyp,Suzanne E. Kosteniuk,Christopher Dunham,Sylvia Cheng,Konstantin Okonechnikov,Daniel Schrimpf,Andreas von Deimling,Benjamin Ellezam,Sébastien Perreault,Sheila K. Singh,Cynthia Hawkins,Marcel Kool,Stefan M. Pfister,Christian Steidl,Christopher Hughes,Andrey Korshunov
出处
期刊:PubMed
标识
DOI:10.1093/neuonc/noaf046
摘要

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.

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