Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer
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Final Published Version
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 ArizonaUniversity of Arizona Cancer Center, University of Arizona
Department of Medicine, University of Arizona
Issue Date
2016-08
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Cell PressCitation
Integrated Patient-Derived Models Delineate Individualized Therapeutic Vulnerabilities of Pancreatic Cancer 2016 Cell ReportsJournal
Cell ReportsRights
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
22111247Version
Final published versionSponsors
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/S221112471630924Xae974a485f413a2113503eed53cd6c53
10.1016/j.celrep.2016.07.023