Emergence and maintenance of actionable genetic drivers at medulloblastoma relapse

Stacey Richardson, Rebecca M. Hill, Christopher Kui, Janet C. Lindsey, Yura Grabovksa, Claire Keeling, Louise Pease, Matthew Bashton, Stephen Crosier, Maria Vinci, Nicolas André, Dominique Figarella-Branger, Jordan R. Hansford, Maria Lastowska, Krzysztof Zakrzewski, Mette Jorgensen, Jessica C. Pickles, Michael D. Taylor, Stefan M. Pfister, Stephen B. WhartonBarry Pizer, Antony Michalski, Abhijit Joshi, Thomas S. Jacques, Debbie Hicks, Edward C. Schwalbe, Daniel Williamson, Vijay Ramaswamy, Simon Bailey, Steven C. Clifford

Research output: Contribution to journalArticlepeer-review

32 Citations (Scopus)
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Abstract

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 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.

Original languageEnglish
Article numbernoab178
Pages (from-to)153-165
Number of pages13
JournalNeuro-Oncology
Volume24
Issue number1
Early online date17 Jul 2021
DOIs
Publication statusPublished - 1 Jan 2022

Keywords

  • Drivers
  • Genomics
  • Medulloblastoma
  • Relapse
  • Subgroups

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