Full Text | PDF

J Cancer 2024; 15(9):2580-2600. doi:10.7150/jca.93425 This issue Cite

Research Paper

Prognostic and Immune Landscape Analysis of Ubiquitination-related Genes in Hepatocellular Carcinoma: Based on Bulk and Single-cell RNA Sequencing Data

Zibo Yuan^1,2,#, Qingwei Zhu^1,2,#, Qingsong Wu³, Zhe Zhang³, Junwei Guo³, Gongqiang Wu⁴, Cuiping Zheng⁵, Qiuran Xu², Dongsheng Huang^2,✉, Di Cui^2,6,✉

1. Qingdao Medical College, Qingdao University, Qingdao, 266000, China.
2. The Key Laboratory of Tumor Molecular Diagnosis and Individualized Medicine of Zhejiang Province, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310000, China.
3. The Second Clinical Medical College of Zhejiang Chinese Medical University, Hangzhou, 310000, China.
4. Department of Hematology, Dongyang People's Hospital of Zhejiang Provincial, Dongyang, 322100, China.
5. Department of Hematology and Chemotherapy, Wenzhou Central Hospital, Wenzhou, 325000, China.
6. General Surgery, Cancer Center, Department of Hepatobiliary and Pancreatic Surgery and Minimally Invasive Surgery, Zhejiang Provincial People's Hospital (Affiliated People's Hospital), Hangzhou Medical College, Hangzhou, 310014, China.
# These authors contributed equally: Zibo Yuan, Qingwei Zhu.

✉ Corresponding authors: Dongsheng Huang, E-mail: dshuangedu.cn; Di Cui, E-mail: cuidiedu.cn.

Abstract

Background: Despite significant advances in tumor immunotherapy, hepatocellular carcinoma (HCC) remains a malignancy with a challenging prognosis. The increasing research emphasizes the crucial role of ubiquitination in tumor immunotherapy. However, the establishment of prognostic signatures based on ubiquitination-related genes (UbRGs) and their role in immunotherapy are still lacking in HCC.

Methods: We employed datasets from TCGA and GEO for transcriptome differential expression analysis and single-cell RNA sequencing analysis. Applying weighted gene co-expression network analysis, cox regression, lasso, selection and visualization of the most relevant features, and gradient boosting machine, we identified hub UbRGs as a gene signature to develop a prognostic model. We evaluated the predictive utility concerning clinical characteristics as well as its role in the immune landscape and immunotherapy potential. Additionally, western blotting, reverse transcription-quantitative PCR, and immunofluorescence were employed to detect the expression and sub-localization of hub genes.

Results: Three hub UbRGs (BOP1, CDC20, and UBE2S) were identified as a gene signature. In particular, the high-risk group exhibited notable characteristics, including higher tumor mutation burden, enrichment in immune-related pathways, up-regulation immune checkpoint, and higher immunity scores. Treatment response to immunotherapy varied based on the expression of PD-1 and CTLA-4. Furthermore, single-cell data analysis revealed heterogeneous expression of hub UbRGs across different cell subtypes, while cytological experiments provided additional confirmation of the high expression of hub UbRGs in HCC.

Conclusion: Our study provides valuable insights into the identification of novel ubiquitination-related biomarkers with potential applications for prognosis, immunotherapy prediction, and drug sensitivity in HCC.

Keywords: hepatocellular carcinoma, ubiquitination, tumor immune microenvironment, immune checkpoints, risk model, drug sensitivity

Citation styles

©2025 Ivyspring International Publisher. Terms of use