Background & Aims: Tumor-infiltrating lymphocytes (TILs), particularly CD8+ TILs, are key prognostic markers in many cancers. However, their prognostic value in hepatocellular carcinoma (HCC) remains controversial, with different evidence. Given the heterogeneous outcomes in patients with HCC undergoing liver resection, this study aims to develop an AI-based system to quantify CD8+ TILs and assess their prognostic value for patients with HCC.

Methods: We conducted a retrospective multicenter study on patients undergoing liver resection across three cohorts (N = 514). We trained a deep neural network and a random forest model to segment tumor regions and locate CD8+ TILs in H&E and CD8-stained whole-slide images. We quantified CD8+ TIL density and established an Automated CD8+ Tumor-infiltrating Lymphocyte Scoring (ATLS-8) system to assess its prognostic value.

Results: In the discovery cohort, the 5-year overall survival (OS) rates were 34.05% for ATLS-8 low-score and 65.03% for ATLS-8 high-score groups (hazard ratio [HR] 2.40; 95% CI, 1.37-4.19;  = 0.015). These findings were confirmed in validation cohort 1, which had 5-year OS rates of 28.57% and 68.73% (HR 3.38; 95% CI, 1.27-9.02;  = 0.0098), and validation cohort 2, which had 59.26% and 81.48% (HR 2.74; 95% CI, 1.05-7.15;  = 0.031). ATLS-8 improved the prognostic model based on clinical variables (C-index 0.770 0.757; 0.769 0.727; 0.712 0.642 in three cohorts).

Conclusions: We developed an automated system using CD8-stained whole-slide images to assess immune infiltration (ATLS-8). In patients with HCC undergoing resection, higher CD8+ TIL density correlates with better OS, as per ATLS-8 assessment. This system is a promising tool for advancing clinical immune microenvironment assessment and outcome prediction.

Impact And Implications: CD8+ tumor-infiltrating lymphocytes (TILs) have been identified as a prognostic factor associated with many cancers. In this study, CD8+ TILs were identified as an independent prognostic factor for overall survival in patients with hepatocellular carcinoma who undergoing liver resection. Therefore, ATLS-8, a novel digital biomarker based on whole-slide image-level CD8+ TILs, could play an important role in the prognostic assessment of patients with HCC and could be integrated into clinicopathological models to participate in the decision-making and prognostic assessment of patients. The scoring system combined with artificial intelligence is essential for automated, quantitative, whole-slide image-level assessment of TILs, which can be widely applied to quantify the immune profile of multi-cancer disease types with the discussion of subsequent immunotherapy.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11803844PMC
http://dx.doi.org/10.1016/j.jhepr.2024.101270DOI Listing

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