Annals of Gastroenterological Surgery (Nov 2023)

Impact of a new liver immune status index among patients with hepatocellular carcinoma after initial hepatectomy

  • Yuki Imaoka,
  • Masahiro Ohira,
  • Ichiya Chogahara,
  • Tomoaki Bekki,
  • Kouki Imaoka,
  • Koki Sato,
  • Marlen Doskali,
  • Ryosuke Nakano,
  • Takuya Yano,
  • Fumihiro Hirata,
  • Shintaro Kuroda,
  • Hiroyuki Tahara,
  • Kentaro Ide,
  • Kohei Ishiyama,
  • Tsuyoshi Kobayashi,
  • Yuka Tanaka,
  • Hideki Ohdan

DOI
https://doi.org/10.1002/ags3.12702
Journal volume & issue
Vol. 7, no. 6
pp. 987 – 996

Abstract

Read online

Abstract Aim The anti‐tumor effects of natural killer (NK) cells vary among individuals. Tumor necrosis factor‐related apoptosis‐inducing ligand (TRAIL) expressed on liver NK cells is a marker of anti‐tumor cytotoxicity against hepatocellular carcinoma (HCC) in immune cell therapy. This study aimed to develop a liver immune status index (LISI) that predicts low TRAIL expression and validates its ability to predict recurrence after initial hepatectomy for primary HCC. Methods A functional analysis of liver NK cells co‐cultured with interleukin‐2 for 3 days was performed of 40 liver transplant donors. The LISI, which predicted low TRAIL expression (25% quartile: <33%) in liver NK cells, was calculated using multiple logistic regression analysis. Next, 586 initial hepatectomy cases were analyzed based on the LISI. Results Our model was based on the Fibrosis‐4 index+0.1 (odds ratio [OR], 1.33), body mass index (OR, 0.61), and albumin levels+0.1 (OR, 0.54). The area under the receiver operating characteristic curve (AUC) of the LISI for low TRAIL expression was 0.89. Stratification of the recurrence rates (RR) revealed that LISI was an independent predictive factor of RR (moderate risk: hazard ratio, 1.44; high risk: hazard ratio, 3.02). The AUC was similar for the LISI, albumin–indocyanine green evaluation grade, albumin–bilirubin score, and geriatric nutritional risk index for predicting RR. Among the vascular invasion cases, the LISI was more useful than the other indexes. Conclusion Our model facilitates the prediction of RR in high‐risk patients by providing LISI to predict the anti‐tumor effects of NK cells.

Keywords