Abstract B069: Characterization of inflammatory cell patterns and densities using multiplex immunohistochemistry immuno-oncology assays
Authors: Dauffenbach Lisa M. , Kerfoot Christopher A. , Sia Gela , Masci Anthony , Zimmermann Johannes , Lesniak Jan , Budco Alexei , Lippok Svenja , Schneider Katrin , Korn René , Wiestler Tobias , Medrikova Dasa , Leiß Florian 
Published: August 2018

Abstract
Definiens and Mosaic Laboratories developed an immuno-oncology (IO) panel consisting of multiplex chromogenic IHC assays and image and data analysis solutions to determine a standardized profile of the tumor microenvironment in non-small cell lung cancer (NSCLC). Expression of PD-L1 on tumor and immune cells, the density of infiltrating immune cell populations, and their spatial pattern have been shown to be predictive for response to immunotherapy. These factors are currently being evaluated to determine whether they can guide treatment across different categories of immunotherapies (e.g., checkpoint inhibition, vaccination, CAR-T cell therapy, or combinations thereof). Multiplex chromogenic IHC assays were developed for PDL1/CD68/CD3 and FoxP3/PD-1/CD8 and single-stain IHC was used to detect cells that were positive for granzyme B. Image analysis were optimized to detect biomarker positive cells (e.g., PD-L1+, CD3-, CD68-), double positive cells (e.g., PD-L1+, CD3-, CD68+), negative cells, or percent of area positive for Granzyme B. Densities for each cell population were quantified and pathologist annotations were used to distinguish between tumor core and invasive margin regions. Machine learning with random forests and decision trees was used to automatically distinguish tumor and stroma compartments to evaluate differences in densities of infiltrating immune cells. Densities of the different cell populations and their spatial relationships were analyzed to assign cases to one of the following immune status categories: acquired immune resistance, immune tolerance, adaptive checkpoint inhibitor resistance (all three are subtypes of high immune cell density), impaired infiltration, immune ignorance, intrinsic checkpoint inhibitor resistance (subtypes of low immune cell density). NSCLC tissues were analyzed and examples of biomarker profiles for each category are shown. The distribution of immune categories between squamous and non-squamous NSCLC subtypes and a comparison of immune cell densities and spatial relationships are shown. We conclude that the IO panel can be used to establish standardized immune profiles in NCCLC. In the future, it can be used to search for novel prognostic and predictive signatures and to establish the prevalence of patients with defined biomarker profiles in different subsets of patients (e.g, different stages, morphologic subtypes, or mutational status).
Citation Format: Lisa M. Dauffenbach, Christopher A. Kerfoot, Gela Sia, Anthony Masci, Johannes Zimmermann, Jan Lesniak, Alexei Budco, Svenja Lippok, Katrin Schneider, René Korn, Tobias Wiestler, Dasa Medrikova, Florian Leiß. Characterization of inflammatory cell patterns and densities using multiplex immunohistochemistry immuno-oncology assays [abstract]. In: Proceedings of the AACR-NCI-EORTC International Conference: Molecular Targets and Cancer Therapeutics; 2017 Oct 26-30; Philadelphia, PA. Philadelphia (PA): AACR; Mol Cancer Ther 2018;17(1 Suppl):Abstract nr B069.