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    Melanoma models for the next generation of therapies

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    Authors
    Patton, E. E.
    Mueller, K. L.
    Adams, D. J.
    Anandasabapathy, N.
    Aplin, A. E.
    Bertolotto, C.
    Bosenberg, M.
    Ceol, C. J.
    Chi, P.
    Herlyn, M.
    Holmen, S. L.
    Karreth, F. A.
    Kaufman, C. K.
    Khan, S.
    Kobold, S.
    Leucci, E.
    Levy, C.
    Lombard, D. B.
    Lund, A. W.
    Marie, K. L.
    Marine, J. C.
    Marais, Richard
    McMahon, M.
    Robles-Espinoza, C. D.
    Ronai, Z. A.
    Samuels, Y.
    Soengas, M. S.
    Villanueva, J.
    Weeraratna, A. T.
    White, R. M.
    Yeh, I.
    Zhu, J.
    Zon, L. I.
    Hurlbert, M. S.
    Merlino, G.
    Show allShow less
    Affiliation
    MRC Human Genetics Unit and Cancer Research UK Edinburgh Centre, MRC Institute of Genetics & Molecular Medicine, The University of Edinburgh, Western General Hospital, Crewe Road, Edinburgh EH4 2XU
    Issue Date
    2021
    
    Metadata
    Show full item record
    Abstract
    There is a lack of appropriate melanoma models that can be used to evaluate the efficacy of novel therapeutic modalities. Here, we discuss the current state of the art of melanoma models including genetically engineered mouse, patient-derived xenograft, zebrafish, and ex vivo and in vitro models. We also identify five major challenges that can be addressed using such models, including metastasis and tumor dormancy, drug resistance, the melanoma immune response, and the impact of aging and environmental exposures on melanoma progression and drug resistance. Additionally, we discuss the opportunity for building models for rare subtypes of melanomas, which represent an unmet critical need. Finally, we identify key recommendations for melanoma models that may improve accuracy of preclinical testing and predict efficacy in clinical trials, to help usher in the next generation of melanoma therapies.
    Citation
    Patton EE, Mueller KL, Adams DJ, Anandasabapathy N, Aplin AE, Bertolotto C, et al. Melanoma models for the next generation of therapies. Cancer Cell. 2021.
    Journal
    Cancer Cell
    URI
    http://hdl.handle.net/10541/623806
    DOI
    10.1016/j.ccell.2021.01.011
    PubMed ID
    33545064
    Additional Links
    https://dx.doi.org/10.1016/j.ccell.2021.01.011
    Type
    Article
    Language
    en
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ccell.2021.01.011
    Scopus Count
    Collections
    All Paterson Institute for Cancer Research

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