Biomarker-Based Precision Prediction of Immunotherapy Response in Hepatocellular Carcinoma.

ABSTRACT: Background: Hepatocellular carcinoma (HCC) remains a major global health challenge with limited treatment options for advanced disease. Although immune checkpoint inhibitors (ICIs) have shown clinical benefits, response rates remain low, emphasizing the need for reliable biomarkers to guide patient selection. Given the critical role of metabolic reprogramming in immune modulation, this study aimed to identify a metabolic gene signature predictive of immunotherapy response in HCC. Methods: Three independent transcriptomic datasets (GSE279750, GSE215011, and GSE235863) comprising 35 ICI-treated HCC samples were integrated after quality control and ComBat batch correction. Differentially expressed genes were identified using DESeq2 and limma, followed by integration of the meta-

SUBMITTER: Chao HW 

PROVIDER: S-EPMC12786039 | biostudies-literature | 2025 Dec

REPOSITORIES: biostudies-literature