Abstract 3633: Immunofluorescence profiling of co-expression of multiple immune checkpoints in malignant and tumor infiltrated lymphocytes in non-small cell lung carcinomas using image analysis system

Background: The immunocheckpoint represents a group of membrane proteins expressing on immune cells, composed of multiple co-inhibitory and co-stimulatory pathways. They are involved in eliminating unwanted substances while maintaining self-tolerance, which play a crucial role in immunomodulation. Malignant cells (MCs), on the other hand, often tends to take advantage of immunocheckpoints, for instance, by activating inhibitory checkpoint pathways in situ, to evade immune responses. Therefore, cancer immunotherapies, which target key immune checkpoints to restore effective anti-tumor immune function, emerge as a revolutionary strategy during recent years. The aim of this study was analyze a full range of checkpoint available to investigate their role in the microenvironment and their frequent co-expression in MCs and tumor infiltrated lymphocytes (TILs) in non-small cell lung carcinomas. Material and Methods: 4 µm-thick histology sections obtained from formalin-fixed paraffin-embedded (FFPE) tissues from a TMA containing 256 NSCLCs (adenocarcinomas, ADC=156; squamous cell carcinomas, SCC=100); were used for multiplex immunofluorescence (mIF) analyses. Nine immune markers including PD-L1, B7-H3, B7-H4, IDO-1, ICOS, OX-40, LAG3, TIM3, VISTA, CD3 and CD20 was optimized for immunofluorescence. Two mIF immunocheckpoints panels were composed included seven antibodies as follows: Panel 1: AE1/AE3, PD-L1, B7-H3, B7-H4, IDO1, VISTA, and CD3; and Panel 2: AE1/AE3, ICOS, LAG3, TIM3, OX40, CD3, and CD20. For quantitative image analysis of mIF markers, the stained TMA slides were scanned using the Polaris™ multispectral microscope (Perkin Elmer) and analyzed using the inForm™ 2.3.1 software. Results: In this preliminary report using the median density in MCs and TILs expressing those markers, we identified overall higher expression of immunocheckpoints in SCC than ADC. The higher density co-expression by MCs (AE/AE3+) was B7-H3 + IDO-1+ following by B7-H3+PD-L1+ expression when compared with the other markers (P~0.001) in the panel 1. Furthermore, we observed higher densities of TILs (CD3+) expressing IDO-1+ as well as B7-H3+ and high densities of TILs (CD3+) co-expressing B7-H3+PD-L1+ when compared the other (P~0.001) markers in the same panel. In panel 2, we observed higher densities of TILs (CD3+) expression ICOS+ than the other markers (P~0.001). Conclusions: Here, we describe a mIF platform with computational image processing workflows, enabling simultaneous evaluation of 12 biomarkers to FFPE tissue section. These data highlight digital image processing pipelines to the community for examining immune complexity of immunocheckpoints expression in MCs and TILs to improve biomarker discovery and assessment. Citation Format: Edwin Roger Parra, Mei Jiang, Jiexin Zhang, Carmen Behrens, Jack Lee, John Victor Heymach, Marie-Andree Forget, Cara Haymaker, Chantale Bernatchez, Cesar Moran, Jianjun Zhang, Don Gibbons, Ignacio Wistuba. Immunofluorescence profiling of co-expression of multiple immune checkpoints in malignant and tumor infiltrated lymphocytes in non-small cell lung carcinomas using image analysis system [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 3633.