e21012 Background: Pathologic classification of immune phenotype is challenging since there is no consensus on how to assess spatial relations of tumor-infiltrating lymphocyte (TIL) on cancer epithelium (CE) and cancer stroma (CS) in whole-slide images (WSI). We previously suggested that the artificial intelligence (AI)-powered tissue analyzer, Lunit SCOPE IO, can classify immune phenotype, and that its predictions are correlated with the clinical outcome of immune checkpoint inhibitor (ICI) in non-small cell lung cancer (NSCLC). In this study, we designed a pathologic validation of immune phenotype using multiplex immunohistochemistry. Methods: Lunit SCOPE IO was developed based on a 2.8 x 109 micrometer2 area of CE or CS, and 5.9 x 106 TILs from 3,166 H&E Whole-Slide Image (WSI) of multiple cancer types, annotated by board-certified pathologists. H&E WSIs were divided into 1 mm2-sized tiles, where we classified immune phenotype (IP) based on TIL density on CE and TIL density on CS. Representative IP was determined based on the overall proportion of tile-level IPs in each WSI. Multiplex immunohistochemistry (mIHC) staining with CD3, CD8, CD20, CD68, FOXP3, CK, and DAPI was performed in NSCLC tumor tissues (n = 99) treated with immune checkpoint inhibitors (ICI) at the Samsung Medical Center. A normalized number of cells expressing each marker was calculated by dividing the total number of marker-positive cells by the number of DAPI-positive cells in each WSI. Results: The proportions of inflamed IP, immune-excluded IP, and immune desert IP in the analysis set were 46.5%, 29.3%, and 24.2%. respectively. Median progression-free survival of ICI was 6.4 m in inflamed IP, 1.9 m in immune-excluded IP, and 1.6 m in immune-desert IP (hazard ratio of inflamed versus others: 0.43, confidence interval 0.27-0.68, P = 0.000188). Multiplex IHC results showed that the normalized CD3-positive cells and CD8-positive cells, which play a role of anti-tumor activity, were highly enriched in inflamed IP compared to those in other IPs (CD3: fold change [FC] 1.57, P = 0.0182; CD8: FC 1.24, P = 0.0697), whereas FOXP3-positive cells, linked to the immunosuppressive activity, were enriched in immune-excluded IP (FC 1.26, P = 0.0656). We also noted that CD68-positive cells were significantly enriched in immune-desert IP (FC 1.76, P = 0.00467). Conclusions: The immune cell subset in WSI is distinct according to the immune phenotype, as CD3- or CD8-positive cells are enriched in inflamed IP rather than immune-excluded IP as classified by AI-powered TIL analysis of H&E image.
1286P Senescent immune phenotype (SIP) status predicts resistance to immune checkpoint blockers (ICB) among CMV+ advanced non-small cell lung cancer (aNSCLC) patients
