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dc.contributor.authorKumar, D.
dc.contributor.authorLisok, A.
dc.contributor.authorDahmane, E.
dc.date.accessioned2019-03-29T14:47:38Z
dc.date.available2019-03-29T14:47:38Z
dc.date.issued2019
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-85060855025&doi=10.1172%2fJCI122216&partnerID=40&md5=0e01ca87ec600363f7e1e39386eb90d0
dc.identifier.urihttp://hdl.handle.net/10713/8708
dc.description.abstractImmune checkpoint therapies have shown tremendous promise in cancer therapy. However, tools to assess their target engagement, and hence the ability to predict their efficacy, have been lacking. Here, we show that target engagement and tumor-residence kinetics of antibody therapeutics targeting programmed death ligand-1 (PD-L1) can be quantified noninvasively. In computational docking studies, we observed that PD-L1-targeted monoclonal antibodies (atezolizumab, avelumab, and durvalumab) and a high-affinity PD-L1-binding peptide, WL12, have common interaction sites on PD-L1. Using the peptide radiotracer [64Cu]WL12 in vivo, we employed positron emission tomography (PET) imaging and biodistribution studies in multiple xenograft models and demonstrated that variable PD-L1 expression and its saturation by atezolizumab, avelumab, and durvalumab can be quantified independently of biophysical properties and pharmacokinetics of antibodies. Next, we used [64Cu]WL12 to evaluate the impact of time and dose on the unoccupied fraction of tumor PD-L1 during treatment. These quantitative measures enabled, by mathematical modeling, prediction of antibody doses needed to achieve therapeutically effective occupancy (defined as >90%). Thus, we show that peptide-based PET is a promising tool for optimizing dose and therapeutic regimens employing PD-L1 checkpoint antibodies, and can be used for improving therapeutic efficacy. Copyright 2018 American Society for Clinical Investigation. All right reserved.en_US
dc.description.sponsorshipWe would like thank the University of Wisconsin and Washington University Cyclotron teams for 64CuCl2 production. Funding for this study was provided by Allegheny Health Network-Johns Hopkins Cancer Research Fund (to SN), NIH 1R01CA236616 (to SN), and NIH P41EB024495 (to MGP). Core resources (flow cytometry, histology, and imaging) were supported by NIH P30CA006973.en_US
dc.description.urihttps://dx.doi.org/10.1172/JCI122216en_US
dc.language.isoen_USen_US
dc.publisherAmerican Society for Clinical Investigationen_US
dc.relation.ispartofJournal of Clinical Investigation
dc.subjectprogrammed death ligand-1en_US
dc.subjectpeptide-based PETen_US
dc.subjectdrug-target engagementen_US
dc.subjectimmune checkpoint therapeuticsen_US
dc.subject.lcshCancer--Treatmenten_US
dc.subject.meshPositron-Emission Tomographyen_US
dc.titlePeptide-based PET quantifies target engagement of PD-L1 therapeuticsen_US
dc.typeArticleen_US
dc.identifier.doi10.1172/JCI122216
dc.identifier.pmid30457978


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