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Assessment of PD-L1 (programmed cell death 1 ligand 1) expression by immunohistochemical analysis has been used as a predictive diagnostic test to identify responders and guide treatment in trials of the PD-1 (programmed cell death 1) axis inhibitors. The definition of PD-L1 positive lacks standardization, and prediction of response by immunohistochemical analysis is additionally limited by the subjective nature of this technique.To examine whether PD-L1 antibody reagents are interchangeable by quantitatively comparing the expression of the PD-L1 protein.In this immunohistochemistry standardization study, 30 randomly selected cases of lung cancer resected from January 1, 2008, through December 31, 2009, were obtained from Yale Pathology Archives with a range of expression of PD-L1. To test for protein measurement, rather than clinical utility, a PD-L1 index tissue microarray, including cell line and tissue controls, was used. The results were then validated on a commercially available, genetically defined PD-L1 engineered cell line array with a range of controlled protein-expressing cell lines using 6 monoclonal antibodies (SP142, E1L3N, 9A11, SP263, 22c3, and 28-8). Protein levels were measured by quantitative immunofluorescence and quantitative chromogenic assessment. Data analysis was performed from September 2015 through May 2016.Concordance between 4 antibodies revealed regression for tumor tissue cores (R2 = 0.42-0.91) and cell line cores (R2 = 0.83-0.97) by quantitative immunofluorescence in the PD-L1 index tissue microarray. All 6 antibodies had high levels of concordance (R2 = 0.76-0.99) when using chromogenic staining in isogenic cell lines.Because the antibodies are highly concordant, these results suggest that assays based on the use of these antibodies could yield concordant results. They further suggest that previously described differences in PD-L1 expression in tissue are independent of the antibody used and likely attributable to tumor heterogeneity, assay- or platform-specific variables, or other factors.