Study on screening predictive biomarkers for hepatocellular carcinoma immunotherapy based on proteomics

This study aimed to screen potential predictive biomarkers for immunotherapy of hepatocellular carcinoma (HCC). Differentially expressed proteins (DEPs) were analyzed between the immunotherapy responder group and non-responder group. Combined with Gene Ontology (GO) enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analysis, immune-related pathways were screened out, and the distribution of significantly DEPs in these pathways was analyzed. Construct an independent protein-protein interaction (PPI) network and analyze the involved immune-related regulatory pathways. Our bioinformatic analyses indicate that HLA-A, UGT1A6, UGT1A3 and FMO5 might be candidate predictive biomarkers for HCC immunotherapy efficacy, which could provide preliminary insights for personalized immunotherapy strategy development for HCC.