INTRODUCTION
The Blueprint Programmed Death Ligand 1 (PD-L1) Immunohistochemistry (IHC) Assay Comparison Project is an industrial-academic collaborative partnership to provide information on the analytical and clinical comparability of four PD-L1 IHC assays used in clinical trials.
METHODS
A total of 39 NSCLC tumors were stained with four PD-L1 IHC assays (22C3, 28-8, SP142, and SP263), as used in the clinical trials. Three experts in interpreting their respective assays independently evaluated the percentages of tumor and immune cells staining positive at any intensity. Clinical diagnostic performance was assessed through comparisons of patient classification above and below a selected expression cutoff and by agreement using various combinations of assays and cutoffs.
RESULTS
Analytical comparison demonstrated that the percentage of PD-L1-stained tumor cells was comparable when the 22C3, 28-8, and SP263 assays were used, whereas the SP142 assay exhibited fewer stained tumor cells overall. The variability of immune cell staining across the four assays appears to be higher than for tumor cell staining. Of the 38 cases, 19 (50.0%) were classified above and five (13%) were classified below the selected cutoffs of all assays. For 14 of the 38 cases (37%), a different PD-L1 classification would be made depending on which assay/scoring system was used.
CONCLUSIONS
The Blueprint PD-L1 IHC Assay Comparison Project revealed that three of the four assays were closely aligned on tumor cell staining whereas the fourth showed consistently fewer tumor cells stained. All of the assays demonstrated immune cell staining, but with greater variability than with tumor cell staining. By comparing assays and cutoffs, the study indicated that despite similar analytical performance of PD-L1 expression for three assays, interchanging assays and cutoffs would lead to "misclassification" of PD-L1 status for some patients. More data are required to inform on the use of alternative staining assays upon which to read different specific therapy-related PD-L1 cutoffs.