Agreement between Programmed Cell Death Ligand-1 Diagnostic Assays across Multiple Protein Expression Cutoffs in Non-Small Cell Lung Cancer

Purpose: Immunotherapies targeting programmed cell death-1 (PD-1) and programmed cell death ligand-1 (PD-L1) demonstrate encouraging antitumor activity and manageable tolerability in non-small cell lung cancer (NSCLC), especially in patients with high tumor PD-L1 expression, as detected by companion or complementary diagnostic assays developed for individual agents. A laboratory is unlikely to use multiple assay platforms. Furthermore, commercially available diagnostic assays are not standardized, and different assay methods could lead to inappropriate treatment selection. This study establishes the extent of concordance between three validated, commercially available PD-L1 IHC diagnostic assays for NSCLC patients [Ventana SP263 (durvalumab), Dako 22C3 (pembrolizumab), and Dako 28-8 (nivolumab)]. Experimental Design: Five hundred formalin-fixed, paraffin-embedded archival NSCLC samples were obtained from commercial sources. Stained slides were read in batches on an assay-by-assay basis by a single pathologist trained in all methods, in a Clinical Laboratory Improvements Amendments program-certified laboratory. An additional pathologist performed an independent review of 200 stained samples for each assay. Results: PD-L1 expression was evaluable with all assays in 493 samples. The three assays showed similar patterns of tumor membrane staining, with high correlation between percent PD-L1 staining. An overall percentage agreement of >90% was achieved between assays at multiple expression cutoffs, including 1%, 10%, 25%, and 50% tumor membrane staining. Conclusions: This study builds optimism that harmonization between assays may be possible, and that the three assays studied could potentially be used interchangeably to identify patients most likely to respond to anti-PD-1/PD-L1 immunotherapies, provided the appropriate clinically defined algorithm and agent are always linked. (C) 2017 AACR.