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Xu S, Liu H, Tian R, Xie J, Chen S, Luo J, Zhu H, Wang Y, Li Z. Construction and validation of a prognostic model with RNA binding protein-related mRNAs for the HBV-related hepatocellular carcinoma patients. Front Oncol 2022; 12:970613. [PMID: 36212461 PMCID: PMC9539435 DOI: 10.3389/fonc.2022.970613] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2022] [Accepted: 09/05/2022] [Indexed: 11/28/2022] Open
Abstract
Hepatocellular carcinoma (HCC) is a common malignancy worldwide with poor clinical outcomes, and the infection of hepatitis B virus (HBV) is the leading cause of this disease. Mounting evidence shows that RNA binding proteins (RBPs) can modulate the progression of cancers. However, the functions and clinical implications of RBP-related mRNAs in HBV-related HCC remain largely unclear. Therefore, we aim to develop a prognostic model based on the RBP-related mRNAs for HBV-related HCC patients. Firstly, we identified 626 differentially expressed RBP-related mRNAs in the HBV-related HCC through the Pearson correlation analysis. Subsequently, the Kaplan-Meier survival, univariate, Least Absolute Shrinkage and Selection Operator (LASSO), and multivariate Cox regression analyses were used to construct a prognostic model comprised of five RBP-related mRNAs. Furthermore, the patients were categorized into the high- and low-risk groups by the prognostic model and the patients in the high-risk group had a poor prognosis. Additionally, the prognostic model was an independent predictor of prognosis, and the accuracy of the prognostic model was proved by the receiver operator characteristic (ROC) analysis. Furthermore, the functional enrichment analysis revealed that various cancer-promoting processes were enriched in the high-risk group. Taken together, our study may provide the HBV-related HCC biomarkers of prognosis to improve the clinical outcomes of patients.
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Affiliation(s)
- Shaohua Xu
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
| | - Hui Liu
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
| | - Renyun Tian
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
| | - Jiahui Xie
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
| | - Su Chen
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
| | - Junyun Luo
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
| | - Haizhen Zhu
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
- Research Center of Cancer Prevention & Treatment, Translational Medicine Research Center of Liver Cancer, Hunan Cancer Hospital, Changsha, China
- *Correspondence: Haizhen Zhu, ; Yirong Wang, ; Zhaoyong Li,
| | - Yirong Wang
- Bioinformatics Center, College of Biology, Hunan University, Changsha, China
- *Correspondence: Haizhen Zhu, ; Yirong Wang, ; Zhaoyong Li,
| | - Zhaoyong Li
- Hunan Provincial Key Laboratory of Medical Virology, Institute of Pathogen Biology and Immunology of College of Biology, Hunan University, Changsha, China
- Research Institute of Hunan University in Chongqing, Chongqing, China
- *Correspondence: Haizhen Zhu, ; Yirong Wang, ; Zhaoyong Li,
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