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dc.contributor.authorConroy, Jeffrey M.-
dc.contributor.authorPabla, Sarabjot-
dc.contributor.authorNesline, Mary K.-
dc.contributor.authorGlenn, Sean T.-
dc.contributor.authorPapanicolau-Sengos, Antonios-
dc.contributor.authorBurgher, Blake-
dc.contributor.authorAndreas, Jonathan-
dc.contributor.authorGiamo, Vincent-
dc.contributor.authorWang, Yirong-
dc.contributor.authorLenzo, Felicia L.-
dc.contributor.authorBshara, Wiam-
dc.contributor.authorKhalil, Maya-
dc.contributor.authorDy, Grace K.-
dc.contributor.authorMadden, Katherine G.-
dc.contributor.authorShirai, Keisuke-
dc.contributor.authorDragnev, Konstantin-
dc.contributor.authorTafe, Laura J.-
dc.contributor.authorZhu, Jason-
dc.contributor.authorLabriola, Matthew-
dc.contributor.authorMarin, Daniele-
dc.contributor.authorMcCall, Shannon J.-
dc.contributor.authorClarke, Jeffrey-
dc.contributor.authorGeorge, Daniel J.-
dc.contributor.authorZhang, Tian-
dc.contributor.authorZibelman, Matthew-
dc.contributor.authorGhatalia, Pooja-
dc.contributor.authorAráujo-Fernández, Isabel-
dc.contributor.authorCruz Merino, L. de la-
dc.contributor.authorSingavi, Arun-
dc.contributor.authorGeorge, Ben-
dc.contributor.authorMacKinnon, Alexander C.-
dc.contributor.authorThompson, Jonathan-
dc.contributor.authorSingh, Rajbir-
dc.contributor.authorJacob, Robin-
dc.contributor.authorKasuganti, Deepa-
dc.contributor.authorShah, Neel-
dc.contributor.authorDay, Roger-
dc.contributor.authorGalluzzi, Lorenzo-
dc.contributor.authorGardner, Mark-
dc.contributor.authorMorrison, Carl-
dc.date.accessioned2020-06-09T10:26:33Z-
dc.date.available2020-06-09T10:26:33Z-
dc.date.issued2019-
dc.identifierdoi: 10.1186/s40425-018-0489-5-
dc.identifiere-issn: 2051-1426-
dc.identifier.citationJournal for ImmunoTherapy of Cancer 7: 18 (2019)-
dc.identifier.urihttp://hdl.handle.net/10261/213880-
dc.description.abstract[Background] PD-L1 immunohistochemistry (IHC) has been traditionally used for predicting clinical responses to immune checkpoint inhibitors (ICIs). However, there are at least 4 different assays and antibodies used for PD-L1 IHC, each developed with a different ICI. We set to test if next generation RNA sequencing (RNA-seq) is a robust method to determine PD-L1 mRNA expression levels and furthermore, efficacy of predicting response to ICIs as compared to routinely used, standardized IHC procedures.-
dc.description.abstract[Methods] A total of 209 cancer patients treated on-label by FDA-approved ICIs, with evaluable responses were assessed for PD-L1 expression by RNA-seq and IHC, based on tumor proportion score (TPS) and immune cell staining (ICS). A subset of serially diluted cases was evaluated for RNA-seq assay performance across a broad range of PD-L1 expression levels.-
dc.description.abstract[Results] Assessment of PD-L1 mRNA levels by RNA-seq demonstrated robust linearity across high and low expression ranges. PD-L1 mRNA levels assessed by RNA-seq and IHC (TPS and ICS) were highly correlated (p < 2e-16). Sub-analyses showed sustained correlation when IHC results were classified as high or low by clinically accepted cut-offs (p < 0.01), and results did not differ by tumor type or anti-PD-L1 antibody used. Overall, a combined positive PD-L1 result (≥1% IHC TPS and high PD-L1 expression by RNA-Seq) was associated with a 2-to-5-fold higher overall response rate (ORR) compared to a double negative result. Standard assessments of sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) showed that a PD-L1 positive assessment for melanoma samples by RNA-seq had the lowest sensitivity (25%) but the highest PPV (72.7%). Among the three tumor types analyzed in this study, the only non-overlapping confidence interval for predicting response was for “RNA-seq low vs high” in melanoma.-
dc.description.abstract[Conclusions] Measurement of PD-L1 mRNA expression by RNA-seq is comparable to PD-L1 expression by IHC both analytically and clinically in predicting ICI response. RNA-seq has the added advantages of being amenable to standardization and avoidance of interpretation bias. PD-L1 by RNA-seq needs to be validated in future prospective ICI clinical studies across multiple histologies.-
dc.description.sponsorshipThis research was funded by OmniSeq, Inc. (Buffalo, NY).-
dc.languageeng-
dc.publisherBMJ Publishing Group-
dc.relation.isversionofPublisher's version-
dc.rightsopenAccess-
dc.subjectAtezolizumab-
dc.subjectAvelumab-
dc.subjectCancer immunotherapy-
dc.subjectDurvalumab-
dc.subjectNivolumab-
dc.subjectPembrolizumab-
dc.subjectPD-L1-
dc.subjectBiomarkers-
dc.titleNext generation sequencing of PD-L1 for predicting response to immune checkpoint inhibitors-
dc.typeartículo-
dc.identifier.doi10.1186/s40425-018-0489-5-
dc.relation.publisherversionhttp://dx.doi.org/10.1186/s40425-018-0489-5-
dc.date.updated2020-06-09T10:26:33Z-
dc.rights.licensehttp://creativecommons.org/licenses/by/4.0/-
dc.contributor.funderOmniSeq-
dc.relation.csic-
dc.identifier.pmid30678715-
dc.type.coarhttp://purl.org/coar/resource_type/c_6501es_ES
item.openairetypeartículo-
item.grantfulltextopen-
item.cerifentitytypePublications-
item.openairecristypehttp://purl.org/coar/resource_type/c_18cf-
item.fulltextWith Fulltext-
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