ArticleBiochemistry and biophysics reports2025
Identification of immune escape-related prognostic genes and immune infiltration analysis in hepatocellular carcinoma based on bioinformatics.
Article in Biochemistry and biophysics reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Immune escape is a critical barrier to effective cancer immunotherapy for cancers such as hepatocellular carcinoma (HCC). The aim of this study was to identify prognostic genes associated with immune escape and to analyse immune infiltration in HCC. Methods: The TCGA-LIHC cohort gene expression matrix and TCGA cohort were downloaded from the UCSC Xena and TCGA databases, respectively, for differential expression analysis, as well as for clinical data and survival information. Additionally, gene expression matrices from HCC tumor tissue samples were downloaded from the ICGC database to validate prognostic models. Subsequently, enrichment analysis utilizing the Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) were conducted. Risk modeling was subsequently performed, followed by univariate and multivariate Cox regression analyses, as well as LASSO regression analysis. Overall survival (OS) curves, receiver operating characteristic (ROC) curves, and nomograms were also generated. Finally, immune infiltration analysis was performed by single-sample genomic enrichment analysis (ssGSEA) and GeneMANIA to predict the functions and pathways of associated with prognostic genes. Results: A total of 4489 differential expression genes were obtained, including 3259 up-regulated, and 1230 down-regulated. Among them, 2123 GO biological functions and 334 KEGG results were enriched. Subsequently, eight differential genes related to immune escape became candidate genes. Finally, we constructed a risk model using three genes, CEP55, GPAA1 and PIGU, and demonstrated better results. The results of immune infiltration showed that the prognostic genes affected the patient's condition through these immune cells. Subsequently, we performed drug sensitivity analysis and finally discovered that CEP55 and PIGU were positively associated with five drugs in the high-risk group. And these three key prognostic genes have high expression levels in HCC tumor tissues. Conclusion: Our study found that three prognostic genes: CEP55, GPAA1 and PIGU have good prognostic value for HCC patients, and are the pivotal prognostic biomarkers.
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