Emergence and maintenance of actionable genetic drivers at medulloblastoma relapse

authors

  • Richardson Stacey
  • Hill Rebecca
  • Kui Christopher
  • Lindsey Janet
  • Grabovksa Yura
  • Keeling Claire
  • Pease Louise
  • Bashton Matthew
  • Crosier Stephen
  • Vinci Maria
  • André Nicolas
  • Figarella‑branger Dominique
  • Hansford Jordan
  • Lastowska Maria
  • Zakrzewski Krzysztof
  • Jorgensen Mette
  • Pickles Jessica
  • Taylor Michael
  • Pfister Stefan
  • Wharton Stephen
  • Pizer Barry
  • Michalski Antony
  • Joshi Abhijit
  • Jacques Thomas
  • Hicks Debbie
  • Schwalbe Edward
  • Williamson Daniel
  • Ramaswamy Vijay
  • Bailey Simon
  • Clifford Steven

abstract

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 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.

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