Impact of Decalcification, Cold Ischemia, and Deglycosylation on Performance of Programmed Cell Death Ligand-1 Antibodies With Different Binding Epitopes: Comparison of 7 Clones.

Programmed cell death ligand-1 (PD-L1) expression levels in patients' tumors have demonstrated clinical utility across many cancer types and are used to determine treatment eligibility. Several independently developed PD-L1 immunohistochemical (IHC) predictive assays are commercially available and have demonstrated different levels of staining between assays, generating interest in understanding the similarities and differences between assays. Previously, we identified epitopes in the internal and external domains of PD-L1, bound by antibodies in routine clinical use (SP263, SP142, 22C3, and 28-8). Variance in performance of assays utilizing these antibodies, observed following exposure to preanalytical factors such as decalcification, cold ischemia, and duration of fixation, encouraged additional investigation of antibody-binding sites, to understand whether binding site structures/conformations contribute to differential PD-L1 IHC assay staining. We proceeded to further investigate the epitopes on PD-L1 bound by these antibodies, alongside the major clones utilized in laboratory-developed tests (E1L3N, QR1, and 73-10). Characterization of QR1 and 73-10 clones demonstrated that both bind the PD-L1 C-terminal internal domain, similar to SP263/SP142. Our results also demonstrate that under suboptimal decalcification or fixation conditions, the performance of internal domain antibodies is less detrimentally affected than that of external domain antibodies 22C3/28-8. Furthermore, we show that the binding sites of external domain antibodies are susceptible to deglycosylation and conformational structural changes, which directly result in IHC staining reduction or loss. The binding sites of internal domain antibodies were unaffected by deglycosylation or conformational structural change. This study demonstrates that the location and conformation of binding sites, recognized by antibodies employed in PD-L1 diagnostic assays, differ significantly and exhibit differing degrees of robustness. These findings should reinforce the need for vigilance when performing clinical testing with different PD-L1 IHC assays, particularly in the control of cold ischemia and the selection of fixation and decalcification conditions.

Mapping the binding sites of antibodies utilized in programmed cell death ligand-1 predictive immunohistochemical assays for use with immuno-oncology therapies.

Programmed cell death ligand-1 (PD-L1) expression levels in patient tumor samples have proven clinical utility across various cancer types. Several independently developed PD-L1 immunohistochemical (IHC) predictive assays are commercially available. Published studies using the VENTANA PD-L1 (SP263) Assay, VENTANA PD-L1 (SP142) Assay, Dako PD-L1 IHC 22C3 pharmDx assay, Dako PD-L1 IHC 28-8 pharmDx assay, and laboratory-developed tests utilizing the E1L3N antibody (Cell Signaling Technology), have demonstrated differing levels of PD-L1 staining between assays, resulting in conjecture as to whether antibody-binding epitopes could be responsible for discordance between assays. Therefore, to understand the performance of different PD-L1 predictive immunohistochemistry assays, we aimed to distinguish the epitopes within the PD-L1 protein responsible for antibody binding. The sites at which antibody clones SP263, SP142, 22C3, 28-8, and E1L3N bind to recombinant PD-L1 were assessed using several methods, including conformational peptide array, surface plasmon resonance, and/or hydrogen/deuterium exchange mass spectrometry. Putative binding sites were confirmed by site-directed mutagenesis of PD-L1, followed by western blotting and immunohistochemical analysis of cell lines expressing mutant constructs. Our results demonstrate that clones SP263 and SP142 bind to an identical epitope in the cytoplasmic domain at the extreme C-terminus of PD-L1, distinct from 22C3 and 28-8. Using mutated PD-L1 constructs, an additional clone, E1L3N, was also found to bind to the cytoplasmic domain of PD-L1. The E1L3N binding epitope overlaps considerably with the SP263/SP142 binding site but is not identical. Clones 22C3 and 28-8 have binding profiles in the extracellular domain of PD-L1, which differ from one another. Despite identifying epitope binding variance among antibodies, evidence indicates that only the SP142 assay generates significantly discordant immunohistochemical staining, which can be resolved by altering the assay protocol. Therefore, inter-assay discordances are more likely attributable to tumor heterogeneity, assay, or platform variables rather than antibody epitope.

Correction: Mapping the binding sites of antibodies utilized in programmed cell death ligand-1 predictive immunohistochemical assays for use with immuno-oncology therapies.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Interobserver Reliability of Programmed Cell Death Ligand-1 Scoring Using the VENTANA PD-L1 (SP263) Assay in NSCLC.

INTRODUCTION: The VENTANA PD-L1 (SP263) Assay is approved for use with anti-programmed cell death-1/programmed cell death ligand-1 (PD-1/PD-L1) therapies in NSCLC and urothelial carcinoma. Here, we investigate interobserver reliability of the SP263 assay, applied to PD-L1 scoring of tumor cells (TCs) in NSCLC. METHODS: Six practicing European pulmonary pathologists independently scored the proportion of TCs expressing PD-L1 (TC score) from 200 archival, commercially sourced, formalin-fixed paraffin-embedded NSCLC resections stained using the SP263 assay. Agreement in scores was analyzed using the intraclass correlation coefficient and concordance in patient's classification using Fleiss' kappa. RESULTS: Results from 172 samples showed strong pair-wise correlations between pathologists (R2 >0.89) for TC scoring with an intraclass correlation coefficient of 0.96. Overall agreement was greater than 90% for TC of 1% and above, and greater than 94% for TCs of at least 25% and at least 50%. Fleiss' kappa showed substantial agreement for TC of 1% and above, and almost perfect agreement for TCs of at least 25% and at least 50%. CONCLUSIONS: Assessment of TC score in NSCLC was highly reproducible using the SP263 assay, building confidence in the accuracy of this assay in selection of patients for anti-PD-1/PD-L1 therapy.

Relevance of deep learning to facilitate the diagnosis of HER2 status in breast cancer.

Tissue biomarker scoring by pathologists is central to defining the appropriate therapy for patients with cancer. Yet, inter-pathologist variability in the interpretation of ambiguous cases can affect diagnostic accuracy. Modern artificial intelligence methods such as deep learning have the potential to supplement pathologist expertise to ensure constant diagnostic accuracy. We developed a computational approach based on deep learning that automatically scores HER2, a biomarker that defines patient eligibility for anti-HER2 targeted therapies in breast cancer. In a cohort of 71 breast tumour resection samples, automated scoring showed a concordance of 83% with a pathologist. The twelve discordant cases were then independently reviewed, leading to a modification of diagnosis from initial pathologist assessment for eight cases. Diagnostic discordance was found to be largely caused by perceptual differences in assessing HER2 expression due to high HER2 staining heterogeneity. This study provides evidence that deep learning aided diagnosis can facilitate clinical decision making in breast cancer by identifying cases at high risk of misdiagnosis.