Development and validation of an Immune-related Gene-based model for predicting prognosis and immunotherapy outcomes in hepatocellular carcinoma patients

Abstract

Abstract Predicting disease prognosis and the efficacy of immunotherapy presents a significant challenge in the treatment of hepatocellular carcinoma (HCC). By analyzing transcriptome sequencing data from 69 patients and identifying differentially expressed immune genes, a prognostic index named the immune-related gene prognostic index (IRGPI) was established by Lasso-Cox regression. The IRGPI, which consists of six key genes, was found to be a significant predictor of poor prognosis in patients with high IRGPI scores. The model’s predictive accuracy was confirmed via receiver operating characteristic (ROC) curve analysis, with area under the curve (AUC) values of 0.85, 0.779, and 0.857 for 1-, 3-, and 5-year survival predictions, respectively. Additionally, patients with high IRGPI scores had increased levels of Treg cells and neutrophils, advanced tumor staging, microvascular invasion grading, and immune checkpoint expression. The IRGPI was also effective in predicting the efficacy of immunotherapy in the IMvigor210 dataset, demonstrating its potential as a valuable tool for assessing patient prognosis and guiding immunotherapy strategies in HCC.

Keywords

• Hepatocellular carcinoma
• Immune-related genes
• Prognosis
• Immunotherapy