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    Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer

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    PIIS221112471630924X.pdf
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    Author
    Witkiewicz, Agnieszka K.
    Balaji, Uthra
    Eslinger, Cody
    McMillan, Elizabeth
    Conway, William
    Posner, Bruce
    Mills, Gordon B.
    O’Reilly, Eileen M.
    Knudsen, Erik S.
    Affiliation
    Department of Pathology, University of Arizona
    University of Arizona Cancer Center, University of Arizona
    Department of Medicine, University of Arizona
    Issue Date
    2016-08
    
    Metadata
    Show full item record
    Publisher
    Cell Press
    Citation
    Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer 2016 Cell Reports
    Journal
    Cell Reports
    Rights
    This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    Pancreatic ductal adenocarcinoma (PDAC) harbors the worst prognosis of any common solid tumor, and multiple failed clinical trials indicate therapeutic recalcitrance. Here, we use exome sequencing of patient tumors and find multiple conserved genetic alterations. However, the majority of tumors exhibit no clearly defined therapeutic target. High-throughput drug screens using patient-derived cell lines found rare examples of sensitivity to monotherapy, with most models requiring combination therapy. Using PDX models, we confirmed the effectiveness and selectivity of the identified treatment responses. Out of more than 500 single and combination drug regimens tested, no single treatment was effective for the majority of PDAC tumors, and each case had unique sensitivity profiles that could not be predicted using genetic analyses. These data indicate a shortcoming of reliance on genetic analysis to predict efficacy of currently available agents against PDAC and suggest that sensitivity profiling of patient-derived models could inform personalized therapy design for PDAC.
    ISSN
    22111247
    DOI
    10.1016/j.celrep.2016.07.023
    Version
    Final published version
    Sponsors
    The authors thank members of the E.S.K. and A.K.W. laboratories for thoughtprovoking discussion, technical assistance, and help with manuscript preparation. Nicholas Borja and Eboni Holloman assisted with select animal studies. Ngoc Haoi assisted with informatics and figure development. The Tissue Management Shared Resource of the Simmons Cancer Center (Cheryl Lewis, manager) assisted with the acquisition of the tissue and coordinating histological and immunohistochemical analysis of tumor specimens. The High-Throughput Screening core and Tissue Management Shared Resource are supported by the Cancer Center Support grant of the Simmons Cancer Center (P30 CA142543). The research is supported by grants to A.K.W. and E.S.K. from the NIH (CA142543-05S2).
    Additional Links
    http://linkinghub.elsevier.com/retrieve/pii/S221112471630924X
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.celrep.2016.07.023
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