Research Paper Volume 15, Issue 23 pp 13901—13919
Crosstalk of cuproptosis-related prognostic signature and competing endogenous RNAs regulation in hepatocellular carcinoma
- 1 Department of Oncology, Guoyang County People’s Hospital, Guoyang Branch of Anhui Provincial Hospital, Guoyang 233607, Anhui, China
- 2 Department of Oncology, Fuyang Hospital of Anhui Medical University, Fuyang 236000, Anhui, China
- 3 Department of Anesthesia, Shaoxing People’s Hospital, Shaoxing 312000, Zhejiang, China
- 4 Department of Cardiovascular Medicine, Fuyang Hospital of Anhui Medical University, Fuyang 236000, Anhui, China
- 5 The First Affiliated Hospital, Nanchang University, Nanchang 330006, Jiangxi, China
- 6 Department of Cardiac Surgery, The First Affiliated Hospital of Anhui Medical University, Hefei 230000, Anhui, China
- 7 The Second Clinical College of Guangzhou Medical University, Guangzhou 510030, Guangdong, China
- 8 School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang 453003, Henan, China
- 9 Institute of Medical and Health Science, Hebei Medical University, Shijiazhuang 050017, Hebei, China
- 10 The Second Clinical Medical College, Lanzhou University, Lanzhou 730000, Gansu, China
- 11 Department of Hepatobiliary Surgery, Fuyang People’s Hospital, Fuyang 236000, Anhui, China
- 12 Department of Oncology, The First Affiliated Hospital of Anhui Medical University, Hefei 230000, Anhui, China
Received: July 26, 2023 Accepted: October 23, 2023 Published: December 10, 2023
https://doi.org/10.18632/aging.205273How to Cite
Copyright: © 2023 Zhu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Abstract
Background: Cuproptosis is a new type of programmed cell death involved in the regulation of neuroendocrine tumors, immune microenvironment, and substance metabolism. However, the role of cuproptosis-related genes (CRGs) in Hepatocellular carcinoma (HCC) remains unclear.
Method: Through multiple bioinformatics analysis, we constructed a prognostic gene model and competing endogenous RNA (ceRNA) network. The correlation between CRGs and prognosis, immune infiltration, immune checkpoints, microsatellite instability (MSI) and tumor mutational burden (TMB) was analyzed by Kaplan-Meier curve, univariate Cox, multivariate regression, and Spearman’s analysis in HCC patients. Besides, the qRT-PCR and immunohistochemistry assays were used to determine prognostic CRGs mRNA and protein expression in HCC.
Results: We established a novel 3-gene signature related to CRGs for evaluating the prognosis of HCC patients. HCC patients with high risk scores had a poor prognosis with an area under the curve of 0.737, 0.646, and 0.634 on 1-year, 3-year, and 5-year receiver operating characteristic curves. Significant correlation was observed between prognostic CRGs and immune infiltration, immune checkpoints, MSI and TMB. We also developed five ceRNA networks to regulate the occurrence and progression of HCC. CDKN2A, DLAT, and PDHA1 protein expression was up-regulated in HCC versus normal tissues. Besides, the mRNA expression levels of CDKN2A, DLAT, GLS, and PDHA1 were elevated in the HCC cell lines compared to the normal liver cell lines.
Conclusions: This novel prognostic CRGs signature could be accurately predict the prognosis of patients with HCC. The ceRNA regulatory network might be potential prognostic biomarkers and therapeutic targets for HCC patients.
Abbreviations
CeRNA: Competing endogenous RNA; CIs: Confidence intervals; CRGs: Cuproptosis-related genes; GEPIA: Gene Expression Profiling Interactive Analysis; GO: Gene Ontology; GTEx: The Genotype-Tissue Expression; HCC: Hepatocellular carcinoma; HPA: The Human Protein Atlas; HRs: Hazard ratios; KEGG: Kyoto Encyclopedia of Genes and Genomes; MSI: Microsatellite instability; OS: Overall survival; ROC: Receiver operating characteristic; STRING: Search Tool for The Retrieval of Interacting Genes; TCA: Tricarboxylic acid; TCGA: The Cancer Genome Atlas; TIMER2.0: The Tumor Immune Estimation Resource, version 2; TMB: Tumor mutational burden.