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    Multi-site clonality analysis uncovers pervasive heterogeneity across melanoma metastases

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    Authors
    Rabbie, R.
    Ansari-Pour, N.
    Cast, O.
    Lau, D.
    Scott, F.
    Welsh, S. J.
    Parkinson, C.
    Khoja, L.
    Moore, L.
    Tullett, M.
    Wong, K.
    Ferreira, I.
    Gómez, J. M. M.
    Levesque, M.
    Gallagher, F. A.
    Jiménez-Sánchez, A.
    Riva, L.
    Miller, M. L.
    Allinson, K.
    Campbell, P. J.
    Corrie, P.
    Wedge, David C
    Adams, D. J.
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    Affiliation
    Experimental Cancer Genetics, The Wellcome Sanger Institute, Hinxton, Cambridgeshire, UK.
    Issue Date
    2020
    
    Metadata
    Show full item record
    Abstract
    Metastatic melanoma carries a poor prognosis despite modern systemic therapies. Understanding the evolution of the disease could help inform patient management. Through whole-genome sequencing of 13 melanoma metastases sampled at autopsy from a treatment naïve patient and by leveraging the analytical power of multi-sample analyses, we reveal evidence of diversification among metastatic lineages. UV-induced mutations dominate the trunk, whereas APOBEC-associated mutations are found in the branches of the evolutionary tree. Multi-sample analyses from a further seven patients confirmed that lineage diversification was pervasive, representing an important mode of melanoma dissemination. Our analyses demonstrate that joint analysis of cancer cell fraction estimates across multiple metastases can uncover previously unrecognised levels of tumour heterogeneity and highlight the limitations of inferring heterogeneity from a single biopsy.
    Citation
    Rabbie R, Ansari-Pour N, Cast O, Lau D, Scott F, Welsh SJ, et al. Multi-site clonality analysis uncovers pervasive heterogeneity across melanoma metastases. Nat Commun. 2020;11(1):4306.
    Journal
    Nature Communications
    URI
    http://hdl.handle.net/10541/623344
    DOI
    10.1038/s41467-020-18060-0
    PubMed ID
    32855398
    Additional Links
    https://dx.doi.org/10.1038/s41467-020-18060-0
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1038/s41467-020-18060-0
    Scopus Count
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    All Paterson Institute for Cancer Research

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