Differential implications of tumor endothelial cell and lymphocyte densities in advanced hepatocellular carcinoma patients treated with immunotherapy
Gwangil Kim, Beodeul Kang, Jung Yong Hong, Haeyoun Kang, Jung Sun Kim, Sohyun Hwang, Sung Hwan Lee, Sang Hoon Jung, Chansik An, Won Suk Lee, Chiyoon Oum, Gahee Park, Mingu Kang, Yoojoo Lim, Jin Woo Oh, Siraj M. Ali, Chan-Young Ock, Chan Kim, Ho Yeong Lim, Hong Jae Chon
npj Precision Oncology, 2025
Abstract
We investigated whether artificial intelligence (AI)-based tumor microenvironment profiling correlates with treatment efficacy in unresectable hepatocellular carcinoma (HCC) patients treated with immune checkpoint inhibitor (ICI) therapies. Spatial distribution of immune/non-immune cells from pretreatment H&E images of 163 patients was retrospectively analyzed using an AI/deep-learning model. High tumor endothelial cell (TEC) density was associated with significantly longer progression-free survival (PFS) in the atezolizumab plus bevacizumab (atezo-bev) cohort (HR 0.51 [0.27-0.97]; p = 0.037) but not in the anti-PD-1 monotherapy cohort (HR 1.02 [0.59-1.77]; p = 0.935). Conversely, inflamed immune phenotype, characterized by high intratumoral TIL densities, predicted longer PFS after anti-PD-1 monotherapy (HR 0.50 [0.25-0.99]; p = 0.042) but not after atezo-bev (HR 0.92 [0.50-1.69]; p = 0.762). Our exploratory analysis using AI/deep-learning model demonstrated high TEC density predicted superior outcomes with atezo-bev, while TIL presence correlated with improved anti-PD-1 monotherapy efficacy in HCC patients, suggesting potential clinical applicability in treatment selection.