T cell-related ubiquitination genes as prognostic indicators in hepatocellular carcinoma
10.3760/cma.j.cn115396-20250125-00019
- VernacularTitle:探索建立T细胞相关泛素化基因模型预测肝细胞癌患者预后
- Author:
Zheng CHEN
1
;
Zheyu ZHOU
;
Yihang YUAN
;
Chaobo CHEN
Author Information
1. 南京鼓楼医院集团宿迁医院肝胆外科，宿迁 223800
- Keywords:
Carcinoma, hepatocellular;
Ubiquitination;
Prognosis;
T cell;
Immunotherapy response
- From:
International Journal of Surgery
2025;52(4):226-230
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To construct a novel clinical prognosis signature for hepatocellular carcinoma (HCC) patients using T cell-related ubiquitination genes.Methods:Transcriptome and clinical data of 371 liver cancer and 50 normal samples were obtained from the TCGA database, and microarray sequencing data of 221 liver cancer samples were selected from the GSE14520 dataset. Single-cell RNA sequencing (scRNA-seq) data of HCC patients were analyzed to identify T cell-related marker genes. These were combined with ubiquitination-related genes. Weighted gene co-expression network analysis (WGCNA) was performed on TCGA transcriptome data to select key genes, resulting in the identification of T cell-related ubiquitination genes. A prognostic model was then constructed using LASSO-Cox regression. Finally, a nomogram was created by combining risk scores and clinical parameters. Count data were expressed by examples and percentages(%). Spearman correlation test was used for correlation analysis. Kaplan-Meier method and Log-rank test were used for survival analysis.Results:Initially, 1 458 T cell-related marker genes were identified. Intersection with 797 ubiquitination-related genes led to the identification of 94 common genes. WGCNA analysis revealed the prognosis-related module MEturquoise. After performing differential gene analysis, Kaplan-Meier analysis, and COX regression, 16 candidate genes were confirmed. LASSO-COX algorithm accurately selected five key genes- UBE2S, PSMD1, FBXL5, UBE2E1, and PSMA7—to construct the prognostic model. Kaplan-Meier analysis indicated that the risk score of the prognostic model was significantly associated with the prognosis of HCC patients (Log-rank test=0.001). Both univariate and multivariate COX regression analysed demonstrated that the risk score was an independent prognostic factor for HCC patients( P<0.05). Finally, a nomogram was constructed by combining the risk score and clinical parameters, providing a more accurate prediction of patient prognosis. Conclusion:The T cell-related ubiquitination gene prognostic model can effectively predict the prognosis of patients with liver cancer.
