Abstract 2225: Image analysis-based PD-L1 companion and complementary diagnostics
Authors: Krueger Joseph S. , Gianani Roberto , Hirsch Brooke , Pieterse Stefan , Aeffner Famke , Young David 
Published: July 2016

The PD-1 pathway, comprised of the immune cell co-receptor Programmed Death 1 (PD-1) and its ligands PD-L1 and PD-L2, mediates local immunosuppression in the tumor microenvironment. Immune checkpoint modulators are designed to block the local immunosuppression caused by this pathway. The FDA approved anti-PD-1 antibody therapies Opdivo® (nivolumab; Bristol-Myers Squibb) and Keytruda® (prembrolizumab; Merck & Co) rely on PD-L1 immunohistochemistry (IHC) in vitro diagnostic (IVD) tests to determine the PD-L1 status in patients in non-small cell lung cancer (NSCLC), in order to predict response to these drugs. The current complementary diagnostic for Opdivo® (Dako 28-8 PharmDx®) relies on a pathologist scoring paradigm which considers any patient with ≥1% positive tumor cells an optimal candidate for Opdivo® treatment. However, overall survival (OS) is further increased when patients have ≥5% or ≥10% PD-L1 positive tumor cells. This scoring approach is vastly different than the PD-L1 scoring approach used in the Keytruda® companion diagnostic (Dako 22C3 PharmDx®), which utilizes a ≥50% positive tumor cells value to predict a positive Overall Response Rate (ORR; OS not yet determined). Thus, the 28-8 test for Opdivo® utilizes a more precise approach than the 22C3 test for Keytruda®, and requires a more calibrated scoring approach. This calibrated approach for Opdivo® requires the difficult challenge of pathologists reliably distinguishing membrane staining to define the fine gradations of 1%, 5% and 10% PD-L1 positive neoplastic cells. To best meet this challenge, we developed a digital Tissue Image Analysis (TIA) solution which enabled accurate, unbiased quantification of PD-L1 on a cell-by-cell basis to classify the percentage positive tumor cells in patients with high granularity. Using Flagship's proprietary CellMapTM algorithm, we evaluated 40 formalin-fixed paraffin-embedded (FFPE) NS-NSCLC samples which were stained using the Dako 28-8 PharmDx® PD-L1 IHC test. The TIA strategy digitally separated tumor cells from other cell types, and quantified membrane staining intensity according to a consistent threshold. The performance of the resulting IHC-TIA assay was evaluated in the context of a CLIA validation study performed by Flagship. The results demonstrated equivalency to the manually scored IVD reference standard; however, the TIA scoring of this assay provided consistent, unbiased, and more detailed scoring of PD-L1 stained tissues for determining the patients with ≥1, ≥5, and ≥10% PD-L1 positive tumor cells with greater confidence than a manual scoring approach. Moving forward, these TIA tools can be utilized to assess PD-L1 positive cell frequencies with greater reliability and granularity to identify optimal treatment cutpoints for these and other PD-L1 IHC tests used to predict response to PD-L1/PD-1 inhibitors.

Citation Format: Joseph S. Krueger, Roberto Gianani, Brooke Hirsch, Stefan Pieterse, Famke Aeffner, David Young. Image analysis-based PD-L1 companion and complementary diagnostics. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2225.