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; Andreas von Deimling; Benjamin Ellezam; Sébastien Perreault; Sheila Singh; Cynthia Hawkins; Marcel Kool; Stefan M Pfister; Christian Steidl; Christopher Hughes; Andrey Korshunov; Poul H Sorensen

doi:10.1093/neuonc/noaf046

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

Neuro Oncol. 2025 Mar 5:noaf046. doi: 10.1093/neuonc/noaf046. Online ahead of print.

Authors

Alberto Delaidelli^{1

2}, Fares Burwag¹, Susana Ben-Neriah³, Yujin Suk^{4

5}, Taras Shyp¹, Suzanne Kosteniuk⁶, Christopher Dunham⁷, Sylvia Cheng⁸, Konstantin Okonechnikov⁹, Daniel Schrimpf¹⁰, Andreas von Deimling¹⁰, Benjamin Ellezam¹¹, Sébastien Perreault¹², Sheila Singh^{4

5

13}, Cynthia Hawkins^{14

15

16}, Marcel Kool^{9

17

18

19

20}, Stefan M Pfister^{9

21}, Christian Steidl^{2

3}, Christopher Hughes²², Andrey Korshunov¹⁰, Poul H Sorensen^{1

2}

Affiliations

¹ Department of Molecular Oncology, British Columbia Cancer Research Centre, Vancouver, BC, V5Z 1L3, Canada.
² Department of Pathology and Laboratory Medicine, University of British Columbia, Vancouver, BC, V6T 1Z3, Canada.
³ Centre for Lymphoid Cancer, BC Cancer, Vancouver, British Columbia, Canada.
⁴ Centre for Discovery in Cancer Research (CDCR), McMaster University, Hamilton, ON, Canada.
⁵ Department of Biochemistry and Biomedical Sciences, McMaster University, Hamilton, ON, Canada.
⁶ Department of Pathology, Rady Faculty of Health Sciences, University of Manitoba, Room 401 Brodie Centre, 727 McDermot Avenue, Winnipeg, MB, Canada.
⁷ Department of Pathology and Laboratory Medicine, Children's and Women's Health Centre of British Columbia, and University of British Columbia, Vancouver, British Columbia, Canada.
⁸ Division of Pediatric Hematology/Oncology/BMT, Department of Pediatrics, British Columbia Children's Hospital, University of British Columbia, Vancouver, British Columbia, Canada.
⁹ Hopp Children's Cancer Center Heidelberg (KiTZ), Division of Pediatric Neurooncology, German Cancer Consortium (DKTK) and German Cancer Research Center (DKFZ).
¹⁰ Department of Neuropathology of Heidelberg University and CCU Neuropathology, German Cancer Research Center, Heidelberg, Germany.
¹¹ Division of Pathology, Department of Pathology and Cell Biology, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada.
¹² Department of Neurosciences, Division of Child Neurology, CHU Sainte-Justine, Université de Montréal, Montréal, Québec, Canada.
¹³ Department of Surgery, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.
¹⁴ Division of Cell Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.
¹⁵ Arthur and Sonia Labatt Brain Tumor Research Centre, The Hospital for Sick Children, Toronto, Ontario, Canada.
¹⁶ Division of Pathology, Hospital for Sick Children, Toronto, Ontario, Canada.
¹⁷ Division of Pediatric Neurooncology, German Cancer Research Center (DKFZ) and German Cancer Research Consortium (DKTK), Heidelberg, Germany.
¹⁸ National Center for Tumor Diseases (NCT), Heidelberg, Germany.
¹⁹ Princess Máxima Center for Pediatric Oncology, Utrecht, the Netherlands.
²⁰ University Medical Center Utrecht, Utrecht, the Netherlands.
²¹ Department of Pediatric Hematology and Oncology, University Hospital, and National Center for Tumor Diseases (NCT), Heidelberg, Germany.
²² Department of Medicine, Dalhousie University, Halifax, Nova Scotia, Canada.

PMID: 40040502
DOI: 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.

Keywords: FFPE proteomics; MYC; Medulloblastoma; biomarker; risk-stratification.

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