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Lookup NU author(s): Dr Stacey RichardsonORCiD, Dr Rebecca Hill, Dr Christopher Kui, Dr Janet Lindsey, Dr Yura Grabovska, Dr Claire Keeling, Dr Louise Pease, Dr Matthew BashtonORCiD, Dr Stephen Crosier, Dr Maria Lastowska, Weronika Zakrzewska, Dr Debbie Hicks, Dr Ed Schwalbe, Dr Daniel WilliamsonORCiD, Professor Simon BaileyORCiD, Professor Steven CliffordORCiD
This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).
© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Neuro-Oncology. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. Background. Less than 5% of medulloblastoma (MB) patients survive following failure of contemporary radiation-based therapies. Understanding the molecular drivers of medulloblastoma relapse (rMB) will be essential to improve outcomes. Initial genome-wide investigations have suggested significant genetic divergence of the relapsed disease. Methods. We undertook large-scale integrated characterization of the molecular features of rMB-molecular subgroup, novel subtypes, copy number variation (CNV), and driver gene mutation. 119 rMBs were assessed in comparison with their paired diagnostic samples (n = 107), alongside an independent reference cohort sampled at diagnosis (n = 282). rMB events were investigated for association with outcome post-relapse in clinically annotated patients (n = 54). Results. Significant genetic evolution occurred over disease-course; 40% of putative rMB drivers emerged at relapse and differed significantly between molecular subgroups. Non-infant MBSHH displayed significantly more chromosomal CNVs at relapse (TP53 mutation-associated). Relapsed MBGroup4 demonstrated the greatest genetic divergence, enriched for targetable (eg, CDK amplifications) and novel (eg, USH2A mutations) events. Importantly, many hallmark features of MB were stable over time; novel subtypes (>90% of tumors) and established genetic drivers (eg, SHH/WNT/P53 mutations; 60% of rMB events) were maintained from diagnosis. Critically, acquired and maintained rMB events converged on targetable pathways which were significantly enriched at relapse (eg, DNA damage signaling) and specific events (eg, 3p loss) predicted survival post-relapse. Conclusions. rMB is characterised by the emergence of novel events and pathways, in concert with selective maintenance of established genetic drivers. Together, these define the actionable genetic landscape of rMB and provide a basis for improved clinical management and development of stratified therapeutics, across disease-course.
Author(s): Richardson S, Hill RM, Kui C, Lindsey JC, Grabovksa Y, Keeling C, Pease L, Bashton M, Crosier S, Vinci M, Andre N, Figarella-Branger D, Hansford JR, Lastowska M, Zakrzewski K, Jorgensen M, Pickles JC, Taylor MD, Pfister SM, Wharton SB, Pizer B, Michalski A, Joshi A, Jacques TS, Hicks D, Schwalbe EC, Williamson D, Ramaswamy V, Bailey S, Clifford SC
Publication type: Article
Publication status: Published
Journal: Neuro-Oncology
Year: 2022
Volume: 24
Issue: 1
Pages: 153-165
Print publication date: 01/01/2022
Online publication date: 17/07/2021
Acceptance date: 02/04/2018
Date deposited: 19/02/2025
ISSN (print): 1522-8517
ISSN (electronic): 1523-5866
Publisher: Oxford University Press
URL: https://doi.org/10.1093/neuonc/noab178
DOI: 10.1093/neuonc/noab178
PubMed id: 34272868
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