The Dako PD-L1 (22C3) antibody is used in immunohistochemistry (IHC) to measure tumor programmed death-ligand 1 (PD-L1) levels, serving as a common companion diagnostic to the check point inhibitor drug pembrolizumab in non-small cell lung cancer (NSCLC). Yet for the practicing pathologist, interpretation of the PD-L1 (22C3) IHC assay is cumbersome and time-consuming resulting in poor intra- and inter-pathologist precision. We have developed a clinically validated PD-L1 (22C3) image analysis (IA) assay that was previously shown to perform equivalently to manual pathologist scoring, require less labor, and produce standardized and reproducible results with greater precision than manual scoring across repeated assessment. However, there is growing literature on the significance of macrophage PD-L1 positivity for predicting treatment response, highlighting the need to differentiate PD-L1 positivity in tumor cells versus macrophages. This need is further underscored by the tendency of manual and digital reads to confuse alveolar macrophages as tumor cells. In this study, we have applied a novel machine learning solution for tissue and alveolar macrophage detection to our PD-L1 (22C3) IA assay to improve its digital scoring accuracy in NSCLC as well as generate additional complementary data on the presence and PD-L1 positivity status of tissue and alveolar macrophages.

24 whole tissue NSCLC samples were purchased and IHC stained for PD-L1. Stained slides were scanned at 20X magnification and analyzed using Flagship's IA solutions that separate tumor and stromal compartments, identify tissue and alveolar macrophages, and quantify PD-L1 expression. Resulting image markups of cell detection and PD-L1 expression were reviewed by an MD pathologist for acceptance. PD-L1 staining was evaluated by digital IA and manual pathology in the sample's tumor compartment for Tumor Proportion Score (TPS). Applying the tissue and alveolar macrophage solution to the PD-L1 (22C3) assay successfully removed macrophages from the digital TPS assessment and generated additional data on tissue and alveolar macrophages (% present, % PD-L1 positive) without significantly impacting the integrity of the IA assay (i.e., the correlation between the digital and manual TPS remained high). This preliminary data demonstrates the robust performance of the clinically validated PD-L1 (22C3) IA assay, even when accounting for tissue and alveolar macrophages. Ongoing experiments include testing the macrophage algorithm on a larger sample of NSCLC tissues to determine the correlation and treatment cut-off concordance between digital and manual scoring obtained by three pathologists. A follow-up clinical validation study of the sensitivity, specificity, accuracy, and precision of this updated PD-L1 (22C3) IA assay is also pending.

Citation Format: Roberto Gianani, Will Paces, Elliott Ergon, Vitria Adisetiyo, Charles Caldwell. A novel image analysis assay for determining programmed death-ligand 1 (22C3) in non-small cell lung cancer that accounts for tissue and alveolar macrophages [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 435.