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Single-cell DNA sequencing identifies risk-associated clonal complexity and evolutionary trajectories in childhood medulloblastoma development

Marina Danilenko, Masood Zaka, Claire Keeling, Stephen Crosier, Stephanie Lyman, Martina Finetti, Daniel Williamson, Rafiqul Hussain, Jonathan Coxhead, Peixun Zhou, Rebecca M Hill, Debbie Hicks, Vikki Rand, Abhijit Joshi, Edward C Schwalbe, Simon Bailey, Steven C. Clifford*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    10 Citations (Scopus)
    45 Downloads (Pure)

    Abstract

    We reconstructed the natural history and temporal evolution of the most common childhood brain malignancy, medulloblastoma, by single-cell whole-genome sequencing (sc-WGS) of tumours representing its major molecular sub-classes and clinical risk groups. Favourable-risk disease sub-types assessed (MB and infant desmoplastic/nodular MB ) typically comprised a single clone with no evidence of further evolution. In contrast, highest risk sub-classes (MYC-amplified MB and TP53-mutated MB ) were most clonally diverse and displayed gradual evolutionary trajectories. Clinically adopted biomarkers (e.g. chromosome 6/17 aberrations; CTNNB1/TP53 mutations) were typically early-clonal/initiating events, exploitable as targets for early-disease detection; in analyses of spatially distinct tumour regions, a single biopsy was sufficient to assess their status. Importantly, sc-WGS revealed novel events which arise later and/or sub-clonally and more commonly display spatial diversity; their clinical significance and role in disease evolution post-diagnosis now require establishment. These findings reveal diverse modes of tumour initiation and evolution in the major medulloblastoma sub-classes, with pathogenic relevance and clinical potential.
    Original languageEnglish
    Pages (from-to)565-578
    Number of pages14
    JournalActa Neuropathologica
    Volume144
    Issue number3
    Early online date13 Jul 2022
    DOIs
    Publication statusPublished - 1 Sept 2022

    UN SDGs

    This output contributes to the following UN Sustainable Development Goals (SDGs)

    1. SDG 3 - Good Health and Well-being
      SDG 3 Good Health and Well-being

    Keywords

    • Clonal evolution
    • Heterogeneity
    • Medulloblastoma
    • Paediatric cancer

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