Quantitative assessment of PD-L1 as an analyte in immunohistochemistry diagnostic assays using a standardized cell...

Programmed death 1 ligand 1 (PD-L1) Immunohistochemistry (IHC) is the key FDA-approved predictive marker to identify responders to anti-PD1 axis drugs. Multiple PD-L1 IHC assays with various antibodies and cut points have been used in clinical trials across tumor types. Comparative performance characteristics of these assays have been extensively studied qualitatively but not quantitatively. Here we evaluate the use of a standardized PD-L1 Index tissue microarray (TMA) to objectively determine agreement between antibody assays for PD-L1 applying quantitative digital image analysis. Using a specially constructed Index TMA containing a panel of ten isogenic cell lines in triplicate, we tested identical but independently grown batches of isogenic cells to prove Index TMAs can be produced in large quantities and hence serve as a standardization tool. Then the Index TMAs were evaluated using quantitative immunofluorescence (QIF) to validate the TMA itself and also to compare antibodies including E1L3N, SP142 and SP263. Next, an inter-laboratory and inter-assay comparison of 5 PD-L1 chromogenic IHC assays (US Food and Drug Administration (FDA) approved and lab developed test (LDT)) were performed at 12 sites around the USA. As previously reported, the SP142 FDA assay failed to detect low levels of PD-L1 in cell lines distinguished by the other four assays. The assays for 22C3 FDA, 28-8-FDA, SP263 FDA, and E1L3N LDT were highly similar across sites and all laboratories showed a high consistency over time for all assays using this Index TMA. In conclusion, we were able to objectively quantify PD-L1 expression on a standardized Index TMA using digital image analysis and we confirmed previous subjective assessments of these assays, but now in a multi-institutional setting. We envision commercial use of this Index TMA or similar smaller version as a useful standardization mechanism to compare results between institutions and to identify abnormalities while running routine clinical samples.