Abstract 4333: Spatial analysis of tumor-infiltrating lymphocytes in tumor microenvironment as biomarker for immune checkpoint inhibition in biliary tract cancer (2023)

Abstract Background: Recently, anti-PD-L1 in combination with cytotoxic chemotherapy has shown significant survival benefit in a randomized phase 3 trial for unresectable or metastatic biliary tract cancer (BTC). However, no biomarker including PD-L1 expression has been established to predict clinical outcomes, and there is an unmet need for a novel predictive biomarker for anti-PD-1 or PD-L1 therapy. Here, we assessed TILs using artificial intelligence (AI)-powered spatial analysis in advanced BTC treated with anti-PD-1 beyond 1st line treatment. Methods: An AI-powered whole-slide image (WSI) analyzer (Lunit SCOPE IO, Lunit, Seoul, Korea) was used to segment tumor epithelium and stroma, and identification of intratumor TIL (iTIL) and stromal TIL (sTIL). H&amp;E stained WSI from pre-treatment samples was acquired from Asan Medical Center (n =166), and a total of 154 samples (92.8%) after quality control were used for the final analysis. Immune phenotypes (IP) were defined as follow: inflamed as high iTIL and sTIL; immune-excluded as low iTIL and high sTIL; immune-desert as low TIL overall. Among them, 20 patients were available for multi-color flow cytometry analysis (FACS) using peripheral blood mononuclear cells, collected at baseline, C1D8, and C2D1. Results: All patients (n=154) were treated with anti-PD-1 (pembrolizumab or nivolumab) monotherapy, and 72 of 154 patients (46.8%) were treated as 2nd line. Gemcitabine plus cisplatin (GemCis) was used prior to anti-PD-1 as first-line therapy in all patients. Overall, 15 (9.7%) patients showed inflamed IP. With median follow-up duration of 15.4 months, the inflamed IP group showed better overall survival (17.2 vs. 6.6 months, P=0.03), and progression-free survival (PFS; 4.5 vs. 2.6 months, P=0.09) along with higher PFS rate at 12 months (33.3% vs. 11.5%, P=0.035), and overall response rate (26. 7% vs. 8.6%, P=0.053) than other phenotype groups. There was no significant difference in median PFS with GemCis among IP groups (P=0.74). In the FACS available subgroup, inflamed IP showed higher baseline central memory T (Tcm)+effector memory T (Tem)/Tnaive ratio than other IPs. With the administration of anti-PD-1, Tcm+Tem/Tnaive ratio was increased, while the proportion of PD1+CD8+T, CD39+CD8+T, CD103+CD8+T and Treg were decreased in the inflamed IP group than other phenotype groups. Conclusions: Immune phenotypes classified by AI-powered spatial TIL analysis was effective to predict the clinical outcomes of patients with advanced BTC treated with anti-PD-1 therapy. Citation Format: Yeong Hak Bang, Kyunghye Bang, Jin Ho Shin, Hyunseok Yoon, Kyu-Pyo Kim, Inkeun Park, Jae Ho Jeong, Heung-Moon Chang, Baek-Yeol Ryoo, Chiyoon Oum, Seulki Kim, Yoojoo Lim, Gahee Park, Chan-Young Ock, Changhoon Yoo. Spatial analysis of tumor-infiltrating lymphocytes in tumor microenvironment as biomarker for immune checkpoint inhibition in biliary tract cancer. [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 4333.