A novel model based on ubiquitination-related gene to predict prognosis and immunotherapy response in hepatocellular carcinoma

基于泛素化相关基因的新型模型预测肝细胞癌的预后和免疫治疗反应

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Abstract

BACKGROUND: Hepatocellular carcinoma (HCC) is a common cancer that is increasingly becoming a global health problem and a major public health concern. In order to improve patient outcomes, additional biomarkers and targets must be explored. Ubiquitination-related genes (URGs), as tumor regulators, exhibit multiple functions in tumor development. Our objective was to examine the influence of URGs on the prognosis of patients with HCC. METHODS: By utilizing unsupervised cluster analysis, we were able to identify URGs in the database and create a risk score profile for predicting the prognosis of patients with HCC. The model's clinical application was explored using subject operating characteristic curves, survival analysis, and correlation analysis. We additionally examined the variances in clinical traits, immune infiltration, somatic genetic alterations, and responsiveness to treatment among high- and low-risk populations identified by the prognostic model. Scores for immune cell infiltration and immune-related pathway activity were determined by performing ssGSEA enrichment analysis. Additionally, to investigate potential mechanisms, we utilized GO, KEGG and GSVA analyses. RESULTS: We developed a risk scoring model that relies on genes associated with ubiquitination. As the risk score increased, the malignancy and prognosis of the tumor worsened. The high-risk and low-risk groups exhibited notable disparities in relation to the immune microenvironment, genes associated with immune checkpoints, sensitivity to drugs, and response to immunotherapy. CONCLUSION: The utilization of a risk model that relies on genes associated with ubiquitination can serve as a biomarker to assess the prognosis of patients with HCC, and aid in the selection of suitable therapeutic agents.

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