Glycosylation-Related Genes predict prognosis in Hepatocellular carcinoma

Abstract

Abstract (1) Background：Hepatocellular carcinoma (HCC) remains a significant challenge in the field of oncology despite improvements in diagnosis and treatment with surgical resection, liver transplantation, and various local therapies. Advanced HCC is particularly difficult to manage due to the lack of suitable molecular targets and drug resistance, which negatively impact prognosis. Glycosylation, an essential post-translational modification of proteins, has been implicated in HCC tumor biology, including tumor invasion, metabolism, and the immune response. This study aims to investigate the relationship between glycosylation-related genes, the immune microenvironment, and the prognosis of HCC, with the potential to identify novel prognostic biomarkers and therapeutic targets. (2) Methods and results：The TCGA database were utilized to acquire clinical data and glycosylation-related gene expression data of HCC patients, which were then used to stratify patients into high- and low-immune subgroups based on their immune score, level, and status using ESTIMATE, CIBERSORT, and ssGSEA analyses. We found that a higher immune score, level, and status were associated with a better prognosis for HCC patients. To identify potential prognostic biomarkers, we applied univariate Cox regression analysis, the LASSO algorithm, and multivariate Cox regression analysis to generate a list of eight candidate genes, which were then used to establish a prognostic risk model. Additionally, a prognostic nomogram was developed that successfully predicted the survival and prognosis of HCC patients. The identification of glycosylation-related genes and their association with the immune microenvironment in HCC offers promising clinical implications for the development of novel prognostic biomarkers and therapeutic targets. (3) Conclusions: The observed correlation between glycosylation-related genes and the immune microenvironment of hepatocellular carcinoma holds promising implications for clinical prediction. These findings suggest that glycosylation-related genes may serve as important biomarkers for predicting the immune response in hepatocellular carcinoma patients.