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

Bibliographic Details
Title: Development and validation of an Immune-related Gene-based model for predicting prognosis and immunotherapy outcomes in hepatocellular carcinoma patients
Authors: Penghui You, Xiaoling Liu, Min Wang, Yanbing Zhan, Lihong Chen, Yi Chen
Source: Scientific Reports, Vol 15, Iss 1, Pp 1-10 (2025)
Publisher Information: Nature Portfolio, 2025.
Publication Year: 2025
Collection: LCC:Medicine
LCC:Science
Subject Terms: Hepatocellular carcinoma, Immune-related genes, Prognosis, Immunotherapy, Medicine, Science
More Details: 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.
Document Type: article
File Description: electronic resource
Language: English
ISSN: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-025-90183-0
Access URL: https://doaj.org/article/392966cf48fb4d69be8b92561a9f8916
Accession Number: edsdoj.392966cf48fb4d69be8b92561a9f8916
Database: Directory of Open Access Journals
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More Details
ISSN:20452322
DOI:10.1038/s41598-025-90183-0
Published in:Scientific Reports
Language:English