Integrated analysis reveals an immune evasion prognostic signature for predicting the overall survival in patients with hepatocellular carcinoma.

Abstract

Background: The development of immunotherapy has enriched the treatment of hepatocellular carcinoma (HCC), but the efficacy is not as expected, which may be due to immune evasion. Immune evasion is related to the immune microenvironment of HCC, but there is little research on it.

Methods: We employed unsupervised clustering analysis to categorize patients from TCGA based on 182 immune evasion-related genes (IEGs). We utilized single-sample gene set enrichment analysis (ssGSEA) and CIBERSORT to calculate differences in immune cell infiltration between clusters. The differences in immune cells and immune-related pathways were assessed using GSEA. We constructed an immune escape prognosis signature (IEPS) using univariate Cox and LASSO Cox algorithms and evaluated the predictive performance of IEPS with receiver operating characteristic (ROC) curves and survival curves. Additionally, we established a nomogram for clinical application based on IEPS. IHC validated the expression of Carbamoyl phosphate synthetase 2, Aspartate transcarbamylase, and Dihydroorotase (CAD) and Phosphatidylinositol Glycan Anchor Biosynthesis Class U (PIGU) in HCC. We transfected liver cancer cell lines with siRNA and overexpression plasmids, and confirmed the relationship between CAD, PIGU, and the potential downstream TGF-β1 in HCC using qRT-PCR and Western blot. Finally, we validated the tumor response of CAD overexpression using an animal model.

Results: Unsupervised clustering analysis based on IEGs divided HCC patients from TCGA into two groups. There were significant differences in prognosis and immune characteristics between the two groups of patients. Scoring of TCGA patients using IEPS revealed that higher scores were associated with poorer overall survival (OS). Validation was performed using the ICGC database. TIME analysis indicated that patients in the high-IEPS group were in an immunosuppressive state, possibly due to a significant increase in Treg infiltration. Compared to normal liver cells, HCC cells expressed higher levels of CAD and PIGU. Cellular experimental results showed a positive correlation between CAD, PIGU and the potential downstream TGF-β1 expression. Animal experiments demonstrated that CAD significantly promoted tumor progression, with an increase in Treg infiltration.

Conclusion: IEPS has strong prognostic value for HCC patients, and CAD and PIGU provide perspectives on new biomarkers and therapeutic targets for HCC.