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Meng H, Jiang L, Jia P, Niu R, Bu F, Zhu Y, Pan X, Li J, Liu J, Zhang Y, Huang C, Lv X, Li J. Inhibition of circular RNA ASPH reduces the proliferation and promotes the apoptosis of hepatic stellate cells in hepatic fibrosis. Biochem Pharmacol 2023; 210:115451. [PMID: 36758707 DOI: 10.1016/j.bcp.2023.115451] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 02/02/2023] [Accepted: 02/03/2023] [Indexed: 02/09/2023]
Abstract
Circular RNAs (circRNAs) are a newly identified form of non-coding RNA that play a crucial role in various pathological processes. However, the expression profile and function of circRNAs in hepatic fibrosis (HF) remain largely unknown. In this study, we showed that a novel circRNA ASPH (circASPH) mediates HF by targeting the miR-139-5p/Notch1 axis. We investigated the expression profile of circRNAs in hepatocyte exosomes of mice with HF using circRNA-sequencing and found significant upregulation of circASPH. Loss- and gain-of-function analysis of circASPH was performed to assess its role in HF. Furthermore, we performed luciferase reporter assay, RNA pull-down, and fluorescence in situ hybridization analyses and confirmed that circASPH directly binds to miR-139-5p. We also found that circASPH was upregulated in liver fibrogenesis. Downregulation of circASPH expression inhibited hepatic stellate cell (HSC) activation and proliferation, induced apoptosis, and attenuated mouse liver fibrogenic injury. Mechanistically, circASPH directly targeted miR-139-5p to regulate the expression of Notch1 in HF. Thus, downregulation of circASPH may suppress the activation of HSCs and HF through the circASPH/miR-139-5p/Notch1 axis. Our findings indicated that circASPH may be a potential biomarker for HF diagnosis and therapy.
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Affiliation(s)
- Hongwu Meng
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Lingfeng Jiang
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Pengcheng Jia
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Ruowen Niu
- The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Fangtian Bu
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Yan Zhu
- The First Affiliated Hospital of Anhui Medical University, Hefei 230022, China
| | - Xueyin Pan
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Juanjuan Li
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Jinyu Liu
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Yilong Zhang
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China
| | - Cheng Huang
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China.
| | - Xiongwen Lv
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China.
| | - Jun Li
- Inflammation and Immune Mediated Diseases Laboratory of Anhui Province, Anhui Institute of Innovative Drugs, School of Pharmacy, Anhui Medical University, Hefei 230032, China.
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Zhang Y, Zhang X, Shen Z, Qiu Q, Tong X, Pan J, Zhu M, Hu X, Gong C. BmNPV circular RNA-encoded peptide VSP39 promotes viral replication. Int J Biol Macromol 2023; 228:299-310. [PMID: 36563818 DOI: 10.1016/j.ijbiomac.2022.12.173] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/10/2022] [Revised: 11/23/2022] [Accepted: 12/07/2022] [Indexed: 12/24/2022]
Abstract
CircRNAs are covalently closed single-stranded circular RNA molecules, which are not easily degraded by endonucleases and play vital roles in many biological processes. Currently, most studies on circRNAs focus on endogenous circRNAs in cells, and there are few studies on virus-encoded circRNAs. In this study, a viral circRNA (circRNA-000010) derived from the region (-/bp: 114514-115,319) of the complementary strand of Bombyx mori Nucleopolyhedrovirus (BmNPV) genome was identified with the circRNA-sequencing. The authenticity of viral circRNA-000010 was further confirmed by reverse transcription PCR, reverse transcription-rolling circle amplification (TCA), in situ hybridization, immunofluorescent staining, and Northern blotting. The results of overexpression and knockdown experiments showed that circRNA-000010 promoted viral replication. Furthermore, a viral small peptide VSP39 with 39 amino acid residues translated by circRNA-000010 but not its linear molecule was confirmed. Finally, VSP39 was found to promote viral replication. Our findings indicated that a viral circRNA encoded by BmNPV promoted viral replication. These findings will provide new clues for further understanding coding information of the BmNPV genome and open a new insight for investigating host-virus interactions.
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Affiliation(s)
- Yaxin Zhang
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China
| | - Xing Zhang
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China
| | - Zeen Shen
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China
| | - Qunnan Qiu
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China
| | - Xinyu Tong
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China
| | - Jun Pan
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China
| | - Min Zhu
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China
| | - Xiaolong Hu
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China; Institute of Agricultural Biotechnology and Ecological Research, Soochow University, Suzhou 215123, China.
| | - Chengliang Gong
- School of Biology & Basic Medical Science, Soochow University, Suzhou 215123, China; Institute of Agricultural Biotechnology and Ecological Research, Soochow University, Suzhou 215123, China.
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Liu X, Li J, Wang Q, Bai L, Xing J, Hu X, Li S, Li Q. Analysis on heterogeneity of hepatocellular carcinoma immune cells and a molecular risk model by integration of scRNA-seq and bulk RNA-seq. Front Immunol 2022; 13:1012303. [PMID: 36311759 PMCID: PMC9606610 DOI: 10.3389/fimmu.2022.1012303] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Accepted: 09/26/2022] [Indexed: 11/29/2022] Open
Abstract
Background Studies have shown that hepatocellular carcinoma (HCC) heterogeneity is a main cause leading to failure of treatment. Technology of single-cell sequencing (scRNA) could more accurately reveal the essential characteristics of tumor genetics. Methods From the Gene Expression Omnibus (GEO) database, HCC scRNA-seq data were extracted. The FindCluster function was applied to analyze cell clusters. Autophagy-related genes were acquired from the MSigDB database. The ConsensusClusterPlus package was used to identify molecular subtypes. A prognostic risk model was built with the Least Absolute Shrinkage and Selection Operator (LASSO)-Cox algorithm. A nomogram including a prognostic risk model and multiple clinicopathological factors was constructed. Results Eleven cell clusters labeled as various cell types by immune cell markers were obtained from the combined scRNA-seq GSE149614 dataset. ssGSEA revealed that autophagy-related pathways were more enriched in malignant tumors. Two autophagy-related clusters (C1 and C2) were identified, in which C1 predicted a better survival, enhanced immune infiltration, and a higher immunotherapy response. LASSO-Cox regression established an eight-gene signature. Next, the HCCDB18, GSA14520, and GSE76427 datasets confirmed a strong risk prediction ability of the signature. Moreover, the low-risk group had enhanced immune infiltration and higher immunotherapy response. A nomogram which consisted of RiskScore and clinical features had better prediction ability. Conclusion To precisely assess the prognostic risk, an eight-gene prognostic stratification signature was developed based on the heterogeneity of HCC immune cells.
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Affiliation(s)
- Xiaorui Liu
- Department of Infection, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jingjing Li
- Department of Infection, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Qingxiang Wang
- Department of physical examination&Blood collection Xuchang Blood Center, Xuchang, China
| | - Lu Bai
- Department of Infection, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Jiyuan Xing
- Department of Infection, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Xiaobo Hu
- Department of Infection, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
| | - Shuang Li
- Bioinformatics R&D Department, Hangzhou Mugu Technology Co., Ltd, Hangzhou, China
| | - Qinggang Li
- Department of Infection, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, China
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