TIL（肿瘤浸润淋巴细胞）聚集优化肝细胞癌患者的预后

The prognostic role of tumor-infiltrating lymphocytes (TILs) in hepatocellular carcinoma (HCC) remains elusive.

This study explored the association between TIL aggregation in early-stage HCC tissues and patient survival. Individual patient-level data from 353 patients diagnosed with HCC who underwent radical hepatectomy were retrospectively analyzed. TIL aggregation was analyzed using an artificial neural network algorithm to define the immune phenotypes (IPs) within hematoxylin and eosin-stained whole-slide images. The association between TIL aggregation and survival was compared among IPs, and an optimized TIL phenotype was validated with clinical variables.

Among the 8 IP features measured using the artificial neural network algorithm, TIL density K50 , a metric generated by an assigned density of each cell based on its distance with the 50 nearest lymphocytes, was associated with improved disease-free survival in univariate (hazard ratio, 0. 282; 95% CI, 0. 181-0. 439; P < . 0001) and multivariate analyses (hazard ratio, 0.

315; 95% CI, 0. 115-0. 860; P = . 024) after adjusting for clinical factors. When TIL density K50 is combined with clinical factors (TIL-clinical-integrated [TCI] model), area under the curve performance for disease-free survival and overall survival was improved to 0. 798 and 0. 781 in the training cohort and 0. 759 and 0. 723 in the validation cohort, respectively.

Furthermore, subgroup analyses indicated that its predictive value is particularly strong for very late recurrence and survival up to <8 years. Abundant TILs in HCC tissue are associated with reduced late recurrence risk and improved survival, suggesting a potential time-dependent prognostic role of TILs in early-stage HCC.