A Novel Four-Gene Signature Based on Nonsense-Mediated RNA Decay for Predicting Prognosis in Hepatocellular Carcinoma: Bioinformatics Analysis and Functional Validation

Jiaxin Zhao; Cheng Wang; Liang Zhao; Huiying Zhou; Rui Wu; Tao Zhang; Jiawei Ding; Junjie Zhou; Huilin Zheng; Lei Zhang; Tianci Kong; Jie Zhou; Zhenhua Hu

doi:10.2147/JHC.S450711

A Novel Four-Gene Signature Based on Nonsense-Mediated RNA Decay for Predicting Prognosis in Hepatocellular Carcinoma: Bioinformatics Analysis and Functional Validation

J Hepatocell Carcinoma. 2024 Apr 23:11:747-766. doi: 10.2147/JHC.S450711. eCollection 2024.

Authors

Jiaxin Zhao¹, Cheng Wang¹, Liang Zhao¹, Huiying Zhou¹, Rui Wu¹, Tao Zhang¹, Jiawei Ding¹, Junjie Zhou², Huilin Zheng³, Lei Zhang³, Tianci Kong³, Jie Zhou⁴, Zhenhua Hu^{1

4}

Affiliations

¹ Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Fourth Affiliated Hospital, School of Medicine, Zhejiang University, Yiwu, Zhejiang Province, People's Republic of China.
² Department of Radiology, Fourth Affiliated Hospital, School of Medicine, Zhejiang University, Yiwu, Zhejiang Province, People's Republic of China.
³ Zhejiang Provincial Collaborative Innovation Center of Agricultural Biological Resource Biochemical Manufacturing, School of Biological and Chemical Engineering, Zhejiang University of Science and Technology, Hangzhou, Zhejiang Province, People's Republic of China.
⁴ Department of Hepatobiliary and Pancreatic Surgery, Department of Surgery, First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang Province, People's Republic of China.

Abstract

Purpose: Nonsense-mediated RNA decay (NMD), a surveillance pathway for selective degradation of aberrant mRNAs, is associated with cancer progression. Its potential as a predictor for aggressive hepatocellular carcinoma (HCC) is unclear. Here, we present an innovative NMD risk model for predicting HCC prognosis.

Methods: The Cancer Genome Atlas (TCGA) data of 374 liver HCC (LIHC) and 50 normal liver samples were extracted. A risk model based on NMD-related genes was developed through least absolute shrinkage and selection operator Cox (LASSO-Cox) regression of the LIHC-TCGA data. Prognostic validation was done using GSE54236, GSE116174, and GSE76427 data. Univariate and multivariate Cox regression analyses were conducted to assess the prognostic value of the model. We also constructed nomograms for survival prediction. Tumor immune infiltration was evaluated using the CIBERSORT algorithm, and the tumor cell phenotype was assessed. Finally, mouse experiments verified UPF3B knockdown effects on HCC tumor characteristics.

Results: We developed a risk model based on four NMD-related genes (PABPC1, RPL8, SMG5, and UPF3B) and validated it using GSE54236, GSE116174, and GSE76427 data. The model effectively distinguished high- and low-risk groups corresponding to unfavorable and favorable HCC outcomes. Its prognostic prediction accuracy was confirmed through time-dependent ROC analysis, and clinical-use nomograms with calibration curves were developed. Single-cell RNA sequencing results indicated significantly higher expression of SMG5 and UPF3B in tumor cells. Knockdown of SMG5 and UPF3B inhibited HCC cell proliferation, invasion, and migration, while affecting cell-cycle progression and apoptosis. In vivo, UPF3B knockdown delayed tumor growth and increased immune cell infiltration.

Conclusion: Our NMD-related gene-based risk model can help identify therapeutic targets and biomarkers for HCC. Additionally, it assists clinicians in predicting the prognosis of HCC patients.

Keywords: LASSO; biomarker; hepatocellular carcinoma; nonsense-mediated RNA decay; survival; tumor immunity.

Grants and funding

This study was supported by National key research and development program (2022YFA1104600), Key Research and Development Program of Zhejiang Province (No.2020C03057), Key Science and Technology Program of Zhejiang Province (No. WKJ-ZJ-1818).