Journal
NEURO-ONCOLOGY
Volume 24, Issue 1, Pages 153-165Publisher
OXFORD UNIV PRESS INC
DOI: 10.1093/neuonc/noab178
Keywords
drivers; genomics; medulloblastoma; relapse; subgroups
Categories
Funding
- Cancer Research UK
- INSTINCT network (Brain Tumour Charity)
- INSTINCT network (Children with Cancer UK)
- INSTINCT network (Great Ormond Street Hospital Children's Charity)
- Children's Cancer North
- Action Medical Research
- Tom Grahame Trust
- JGW Patterson Foundation
- Star for Harris
- C.R. Younger Foundation
- Canadian Institutes for Health Research
- MRC [MR/V001647/1] Funding Source: UKRI
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The study revealed that 40% of putative drivers of medulloblastoma relapse emerged at the time of relapse, showing significant differences between molecular subgroups. Compared to diagnosis, there were more events focusing on targetable pathways at relapse, such as CDK amplifications and USH2A mutations. Many genetic features of medulloblastoma remained stable over time after diagnosis.
Background. Less than 5% of medulloblastoma (MB) patients survive following failure of contemporary radiationbased 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 MB SHH displayed significantly more chromosomal CNVs at relapse (TP53 mutation-associated). Relapsed MB Group4 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.
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