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Yang N, Song Y, Li Y, Dong B, Yang J, Guo Z. Characterization of lncRNA-associated ceRNA network to uncover novel potential biomarkers in coronary artery disease. Medicine (Baltimore) 2023; 102:e35913. [PMID: 38013355 PMCID: PMC10681391 DOI: 10.1097/md.0000000000035913] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Accepted: 10/12/2023] [Indexed: 11/29/2023] Open
Abstract
The purpose of this study was to construct a competitive endogenous RNA (ceRNA) network related to long non-coding RNA (lncRNAs) via the bioinformatics analysis, reveal the pathogenesis of coronary heart disease (CAD) and develop new biomarkers for CAD. The gene expression datasets of peripheral blood of CAD were downloaded from the Gene Expression Omnibus (GEO) database. The differentially expressed mRNAs, miRNAs and lncRNAs (DEmRNAs, DEmiRNAs and DElncRNAs) were identified. Subsequently, a ceRNA network involving lncRNAs, miRNAs, and mRNAs was built. Moreover, DElncRNAs in the cytoplasm were screened and a DElncRNA-associated ceRNA network was established. In total, 1860 DEmRNAs, 393 DElncRNAs and 20 DEmiRNAs were filtrated in patients with CAD compared with normal controls. Functional analysis suggested that DEmRNAs significantly enriched in CAD-related pathways, such as PI3K-Akt signaling pathways and MAPK signaling pathway. The ceRNA network contained 12 DEmiRNAs, 30 DElncRNAs and 537 DEmRNAs. Afterwards, the cytoplasm ceRNA network was consisted of 537 DEmRNAs, 12 DEmiRNAs and 12 DElncRNAs. Such as, up-regulated LncRNA-HOX transcript antisense RNA (HOTAIR) was interacted with down-regulated has-miR-326 and has-miR-1. The successful construction of lncRNA-associated ceRNA network is helpful to better clarify the pathogenesis of CAD and provide potential peripheral blood biomarkers for CAD.
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Affiliation(s)
- Ning Yang
- Department of Cardiovasular Medicine, Tianjin Chest Hospital, Tianjin, China
| | - Yanqiu Song
- Institute of Cardiology Research, Tianjin Chest Hospital, Tianjin, China
| | - Yang Li
- Department of Cardiovasular Medicine, Tianjin Chest Hospital, Tianjin, China
| | - Bo Dong
- Department of Cardiovasular Medicine, Tianjin Chest Hospital, Tianjin, China
| | - Jingyu Yang
- Department of Cardiovasular Medicine, Tianjin Chest Hospital, Tianjin, China
| | - Zhigang Guo
- Department of Cardiovasular Surgery, Tianjin Chest Hospital, Tianjin, China
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Wang C, He Z. Integrating bulk and single-cell RNA sequencing data reveals epithelial-mesenchymal transition molecular subtype and signature to predict prognosis, immunotherapy efficacy, and drug candidates in low-grade gliomas. Front Pharmacol 2023; 14:1276466. [PMID: 38053842 PMCID: PMC10694300 DOI: 10.3389/fphar.2023.1276466] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2023] [Accepted: 11/06/2023] [Indexed: 12/07/2023] Open
Abstract
Objective: Epithelial-mesenchymal transition (EMT) is a tightly regulated and dynamic process occurring in both embryonic development and tumor progression. Our study aimed to comprehensively explore the molecular subtypes, immune landscape, and prognostic signature based on EMT-related genes in low-grade gliomas (LGG) in order to facilitate treatment decision-making and drug discovery. Methods: We curated EMT-related genes and performed molecular subtyping with consensus clustering algorithm to determine EMT expression patterns in LGG. The infiltration level of diverse immune cell subsets was evaluated by implementing the single-sample gene set enrichment analysis (ssGSEA) and ESTIMATE algorithms. The distinctions in clinical characteristics, mutation landscape, and immune tumor microenvironment (TME) among the subtypes were subjected to further investigation. Gene Set Variation Analysis (GSVA) was performed to explore the biological pathways that were involved in subtypes. The chemo drug sensitivity and immunotherapy of subtypes were estimated through GDSC database and NTP algorithm. To detect EMT subtype-related prognostic gene modules, the analysis of weighted gene co-expression network (WGCNA) was performed. The LASSO algorithm was utilized to construct a prognostic risk model, and its efficacy was verified through an independent CGGA dataset. Finally, the expression of the hub genes from the prognostic model was evaluated through the single-cell dataset and in-vitro experiment. Results: The TCGA-LGG dataset revealed the creation of two molecular subtypes that presented different prognoses, clinical implications, TME, mutation landscapes, chemotherapy, and immunotherapy. A three-gene signature (SLC39A1, CTSA and CLIC1) based on EMT expression pattern were established through WGCNA analysis. Low-risk patients showed a positive outlook, increased immune cell presence, and higher expression of immune checkpoint proteins. In addition, several promising drugs, including birinapant, fluvastatin, clofarabine, dasatinib, tanespimycin, TAK-733, GDC-0152, AZD8330, trametinib and ingenol-mebutate had great potential to the treatment of high risk patients. Finally, CTSA and CLIC1 were highly expressed in monocyte cell through single-cell RNA sequencing analysis. Conclusion: Our research revealed non-negligible role of EMT in the TME diversity and complexity of LGG. A prognostic signature may contribute to the personalized treatment and prognostic determination.
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Affiliation(s)
- Chengcheng Wang
- Department of Pharmacy, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, Shandong, China
| | - Zheng He
- Department of Neurosurgery, Qilu Hospital (Qingdao), Cheeloo College of Medicine, Shandong University, Qingdao, Shandong, China
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Chen X, Tang H, Lu K, Niu Z, Sheng W, Hwang HY, Pang PYK, Phillips JD, Khoynezhad A, Qu X, Li B, Han W. Gene modules and genes associated with postoperative atrial fibrillation: weighted gene co-expression network analysis and circRNA-miRNA-mRNA regulatory network analysis. J Thorac Dis 2023; 15:4949-4960. [PMID: 37868904 PMCID: PMC10586969 DOI: 10.21037/jtd-23-1179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 08/31/2023] [Indexed: 10/24/2023]
Abstract
Background Atrial fibrillation (AF) is the most common complication in patients undergoing cardiac surgery. However, the pathogenesis of postoperative AF (POAF) is elusive, and research related to this topic is sparse. Our study aimed to identify key gene modules and genes and to conduct a circular RNA (circRNA)-microRNA (miRNA)-messenger RNA (mRNA) regulatory network analysis of POAF on the basis of bioinformatic analysis. Methods The GSE143924 and GSE97455 data sets from the Gene Expression Omnibus (GEO) database were analyzed. Weighted gene co-expression network analysis (WGCNA) was used to identify the key gene modules and genes related to POAF. A circRNA-miRNA-mRNA regulatory network was also built according to differential expression analysis. Functional enrichment analysis was further performed according to Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Results WGCNA identified 2 key gene modules and 44 key genes that were significantly related to POAF. Functional enrichment analysis of these key genes implicated the following important biological processes (BPs): endosomal transport, protein kinase B signaling, and transcription regulation. The circRNA-miRNA-mRNA regulatory network suggested that KLF10 may take critical part in POAF. Moreover, 2 novel circRNAs, hsa_circRNA_001654 and hsa_circRNA_005899, and 2 miRNAs, hsa-miR-19b-3p and hsa-miR-30a-5p, which related with KLF10, were involved in the network. Conclusions Our study provides foundational expression profiles following POAF based on WGCNA. The circRNA-miRNA-mRNA network offers insights into the BPs and underlying mechanisms of POAF.
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Affiliation(s)
- Xiaomeng Chen
- Department of Cardiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Department of Cardiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Huaiguang Tang
- Department of Cardiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Department of Cardiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Kongmiao Lu
- Department of Pulmonary and Critical Care Medicine, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Zhaozhuo Niu
- Department of Cardiovascular Surgery, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Wei Sheng
- Department of Cardiovascular Surgery, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Ho Young Hwang
- Department of Thoracic and Cardiovascular Surgery, Seoul National University Hospital, Seoul National University College of Medicine, Seoul, Republic of Korea
| | - Philip Y. K. Pang
- Department of Cardiothoracic Surgery, National Heart Centre Singapore, Singapore, Singapore
| | - Joseph D. Phillips
- Section of Thoracic Surgery, Dartmouth-Hitchcock Medical Center, 1 Medical Center Dr., Lebanon, NH, USA
| | - Ali Khoynezhad
- Department of Cardiovascular Surgery, MemorialCare Heart and Vascular Institute, Long Beach, CA, USA
| | - Xiaolu Qu
- Department of Pulmonary and Critical Care Medicine, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Bingong Li
- Department of Cardiology, Qingdao Municipal Hospital, Qingdao University, Qingdao, China
- Department of Cardiology, Qingdao Municipal Hospital, University of Health and Rehabilitation Sciences, Qingdao, China
| | - Wei Han
- Department of Pulmonary and Critical Care Medicine, University of Health and Rehabilitation Sciences, Qingdao, China
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Zhou D, Zhu Y, Jiang P, Zhang T, Zhuang J, Li T, Qi L, Wang Y. Identifying pyroptosis- and inflammation-related genes in intracranial aneurysms based on bioinformatics analysis. Biol Res 2023; 56:50. [PMID: 37752552 PMCID: PMC10523789 DOI: 10.1186/s40659-023-00464-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 09/20/2023] [Indexed: 09/28/2023] Open
Abstract
BACKGROUND Intracranial aneurysm (IA) is the most common cerebrovascular disease, and subarachnoid hemorrhage caused by its rupture can seriously impede nerve function. Pyroptosis is an inflammatory mode of cell death whose underlying mechanisms involving the occurrence and rupture of IAs remain unclear. In this study, using bioinformatics analysis, we identified the potential pyroptosis-related genes (PRGs) and performed their inflammatory response mechanisms in IAs. METHODS The mRNA expression matrix of the IA tissue was obtained from the Gene Expression Omnibus database, and 51 PRGs were obtained from previous articles collected from PubMed. The differentially expressed PRGs (DEPRGs) were performed using R software. Subsequently, we performed enrichment analysis, constructed a protein-protein interaction network, performed weighted gene coexpression network analysis (WGCNA) and external validation using another dataset, and identified a correlation between hub genes and immune cell infiltration. Finally, the expression and tissue distribution of these hub genes in IA tissues were detected using Western blotting and immunohistochemical (IHC) staining. RESULTS In total, 12 DEPRGs associated with IA were identified in our analysis, which included 11 up-regulated and one down-regulated genes. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses revealed that the DEPRGs were mostly enriched in the NOD-like receptor signaling pathway, interleukin-1 beta production, and the inflammasome complex. Three hub genes, NLRP3, IL1B and IL18, were identified using Cytoscape software and the WGCNA correlation module, and external validation revealed statistically significant differences between the expression of these hub genes in the ruptured and unruptured aneurysm groups (p < 0.05). Furthermore, all AUC values were > 0.75. Immune cell infiltration analysis suggested that the hub genes are related to CD8 T cell, macrophages and mast cells. Finally, IHC staining revealed that the protein levels of these hub genes were higher in ruptured and unruptured IA tissues than in normal tissues (p < 0.05). CONCLUSION The results of bioinformatics analysis showed that pyroptosis is closely related to the formation and rupture of IA, and identified three potential hub genes involved in the pyroptosis and infiltration ofcells. Our findings may improve the understanding of the mechanisms underlying pyroptosis in IA.
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Affiliation(s)
- Donglin Zhou
- Department of Neurosurgery, Qilu Hospital of Shandong University, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, 107 Wenhua Western Road, Jinan, 250012, Shandong, China
| | - Yimin Zhu
- Department of Orthopedics, Qilu Hospital of Shandong University, Jinan, China
| | - Peng Jiang
- Jiangsu Center for the Collaboration and Innovation of Cancer Biotherapy, Cancer Institute, Xuzhou Medical University, Xuzhou, China
| | - Tongfu Zhang
- Department of Neurosurgery, Qilu Hospital of Shandong University, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, 107 Wenhua Western Road, Jinan, 250012, Shandong, China
- Department of Neurosurgery, Yangxin County People's Hospital, Binzhou, China
| | - Jianfeng Zhuang
- Department of Neurosurgery, Qilu Hospital of Shandong University, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, 107 Wenhua Western Road, Jinan, 250012, Shandong, China
| | - Tao Li
- Department of Neurosurgery, The Third Affiliated Hospital of Shandong First Medical University, Jinan, China
| | - Linzeng Qi
- Department of Orthopedics, Qilu Hospital of Shandong University, Jinan, China
| | - Yunyan Wang
- Department of Neurosurgery, Qilu Hospital of Shandong University, Cheeloo College of Medicine and Institute of Brain and Brain-Inspired Science, Shandong University, 107 Wenhua Western Road, Jinan, 250012, Shandong, China.
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Jin Y, Ren W, Liu J, Tang X, Shi X, Pan D, Hou L, Yang L. Identification and validation of potential hypoxia-related genes associated with coronary artery disease. Front Physiol 2023; 14:1181510. [PMID: 37637145 PMCID: PMC10447898 DOI: 10.3389/fphys.2023.1181510] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2023] [Accepted: 08/01/2023] [Indexed: 08/29/2023] Open
Abstract
Introduction: Coronary artery disease (CAD) is one of the most life-threatening cardiovascular emergencies with high mortality and morbidity. Increasing evidence has demonstrated that the degree of hypoxia is closely associated with the development and survival outcomes of CAD patients. However, the role of hypoxia in CAD has not been elucidated. Methods: Based on the GSE113079 microarray dataset and the hypoxia-associated gene collection, differential analysis, machine learning, and validation of the screened hub genes were carried out. Results: In this study, 54 differentially expressed hypoxia-related genes (DE-HRGs), and then 4 hub signature genes (ADM, PPFIA4, FAM162A, and TPBG) were identified based on microarray datasets GSE113079 which including of 93 CAD patients and 48 healthy controls and hypoxia-related gene set. Then, 4 hub genes were also validated in other three CAD related microarray datasets. Through GO and KEGG pathway enrichment analyses, we found three upregulated hub genes (ADM, PPFIA4, TPBG) were strongly correlated with differentially expressed metabolic genes and all the 4 hub genes were mainly enriched in many immune-related biological processes and pathways in CAD. Additionally, 10 immune cell types were found significantly different between the CAD and control groups, especially CD8 T cells, which were apparently essential in cardiovascular disease by immune cell infiltration analysis. Furthermore, we compared the expression of 4 hub genes in 15 cell subtypes in CAD coronary lesions and found that ADM, FAM162A and TPBG were all expressed at higher levels in endothelial cells by single-cell sequencing analysis. Discussion: The study identified four hypoxia genes associated with coronary heart disease. The findings provide more insights into the hypoxia landscape and, potentially, the therapeutic targets of CAD.
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Affiliation(s)
- Yuqing Jin
- Department of Epidemiology, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Weiyan Ren
- Department of Epidemiology, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Jiayi Liu
- Department of Epidemiology, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Xuejiao Tang
- Department of Epidemiology, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Xinrui Shi
- Department of Epidemiology, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Dongchen Pan
- Department of Epidemiology, School of Public Health, Hebei Medical University, Shijiazhuang, China
| | - Lianguo Hou
- Biochemistry Research Laboratory, School of Basic Medicine, Hebei Medical University, Shijiazhuang, China
| | - Lei Yang
- Department of Epidemiology, School of Public Health, Hebei Medical University, Shijiazhuang, China
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Zheng PF, Hong XQ, Liu ZY, Zheng ZF, Liu P, Chen LZ. m6A regulator-mediated RNA methylation modification patterns are involved in the regulation of the immune microenvironment in ischaemic cardiomyopathy. Sci Rep 2023; 13:5904. [PMID: 37041267 PMCID: PMC10090050 DOI: 10.1038/s41598-023-32919-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Accepted: 04/04/2023] [Indexed: 04/13/2023] Open
Abstract
The role of RNA N6-methyladenosine (m6A) modification in the regulation of the immune microenvironment in ischaemic cardiomyopathy (ICM) remains largely unclear. This study first identified differential m6A regulators between ICM and healthy samples, and then systematically evaluated the effects of m6A modification on the characteristics of the immune microenvironment in ICM, including the infiltration of immune cells, the human leukocyte antigen (HLA) gene, and HALLMARKS pathways. A total of seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15 and YTHDF3, were identified using a random forest classifier. A diagnostic nomogram based on these seven key m6A regulators could effectively distinguish patients with ICM from healthy subjects. We further identified two distinct m6A modification patterns (m6A cluster-A and m6A cluster-B) that are mediated by these seven regulators. Meanwhile, we also noted that one m6A regulator, WTAP, was gradually upregulated, while the others were gradually downregulated in the m6A cluster-A vs. m6A cluster-B vs. healthy subjects. In addition, we observed that the degree of infiltration of the activated dendritic cells, macrophages, natural killer (NK) T cells, and type-17 T helper (Th17) cells gradually increased in m6A cluster-A vs. m6A cluster-B vs. healthy subjects. Furthermore, m6A regulators, including FTO, YTHDC1, YTHDF3, FMR1, ZC3H13, and RBM15 were significantly negatively correlated with the above-mentioned immune cells. Additionally, several differential HLA genes and HALLMARKS signalling pathways between the m6A cluster-A and m6A cluster-B groups were also identified. These results suggest that m6A modification plays a key role in the complexity and diversity of the immune microenvironment in ICM, and seven key m6A regulators, including WTAP, ZCH3H13, YTHDC1, FMR1, FTO, RBM15, and YTHDF3, may be novel biomarkers for the accurate diagnosis of ICM. Immunotyping of patients with ICM will help to develop immunotherapy strategies with a higher level of accuracy for patients with a significant immune response.
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Affiliation(s)
- Peng-Fei Zheng
- Cardiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, ChangshaHunan, 410000, China
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Xiu-Qin Hong
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Zheng-Yu Liu
- Cardiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, ChangshaHunan, 410000, China
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Zhao-Fen Zheng
- Cardiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, ChangshaHunan, 410000, China
- Clinical Research Center for Heart Failure in Hunan Province, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
- Epidemiology Department, Hunan Provincial People's Hospital, No. 61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Peng Liu
- Department of Cardiology, The Central Hospital of ShaoYang, No. 36 QianYuan Lane, Daxiang District, Shaoyang, 422000, Hunan, China.
| | - Lu-Zhu Chen
- Department of Cardiology, The Central Hospital of ShaoYang, No. 36 QianYuan Lane, Daxiang District, Shaoyang, 422000, Hunan, China.
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Dong H, Yan SB, Li GS, Huang ZG, Li DM, Tang YL, Le JQ, Pan YF, Yang Z, Pan HB, Chen G, Li MJ. Identification through machine learning of potential immune- related gene biomarkers associated with immune cell infiltration in myocardial infarction. BMC Cardiovasc Disord 2023; 23:163. [PMID: 36978012 PMCID: PMC10052851 DOI: 10.1186/s12872-023-03196-w] [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: 10/04/2022] [Accepted: 03/22/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND To investigate the potential role of immune-related genes (IRGs) and immune cells in myocardial infarction (MI) and establish a nomogram model for diagnosing myocardial infarction. METHODS Raw and processed gene expression profiling datasets were archived from the Gene Expression Omnibus (GEO) database. Differentially expressed immune-related genes (DIRGs), which were screened out by four machine learning algorithms-partial least squares (PLS), random forest model (RF), k-nearest neighbor (KNN), and support vector machine model (SVM) were used in the diagnosis of MI. RESULTS The six key DIRGs (PTGER2, LGR6, IL17B, IL13RA1, CCL4, and ADM) were identified by the intersection of the minimal root mean square error (RMSE) of four machine learning algorithms, which were screened out to establish the nomogram model to predict the incidence of MI by using the rms package. The nomogram model exhibited the highest predictive accuracy and better potential clinical utility. The relative distribution of 22 types of immune cells was evaluated using cell type identification, which was done by estimating relative subsets of RNA transcripts (CIBERSORT) algorithm. The distribution of four types of immune cells, such as plasma cells, T cells follicular helper, Mast cells resting, and neutrophils, was significantly upregulated in MI, while five types of immune cell dispersion, T cells CD4 naive, macrophages M1, macrophages M2, dendritic cells resting, and mast cells activated in MI patients, were significantly downregulated in MI. CONCLUSION This study demonstrated that IRGs were correlated with MI, suggesting that immune cells may be potential therapeutic targets of immunotherapy in MI.
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Affiliation(s)
- Hao Dong
- Department of Cardiovascular Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Shi-Bai Yan
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Guo-Sheng Li
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Zhi-Guang Huang
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Dong-Ming Li
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Yu-Lu Tang
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Jia-Qian Le
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Yan-Fang Pan
- Department of Pathology, Hospital of Guangxi Liugang Medical Co.LTD./Guangxi Liuzhou Dingshun Forensic Expert Institute, No.9, Queershan Rd, Liuzhou, Guangxi Zhuang Autonomous Region, 545002, People's Republic of China
| | - Zhen Yang
- Department of Gerontology, NO.923 Hospital of Chinese People's Liberation Army, No. 1 Tangcheng Rd, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Hong-Bo Pan
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Gang Chen
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China
| | - Ming-Jie Li
- Department of Pathology/ Forensic Medicine, The First Affiliated Hospital of Guangxi Medical University, No.6 Shuangyong Road, Nanning, Guangxi Zhuang Autonomous Region, 530021, People's Republic of China.
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Barreiro K, Lay AC, Leparc G, Tran VDT, Rosler M, Dayalan L, Burdet F, Ibberson M, Coward RJM, Huber TB, Krämer BK, Delic D, Holthofer H. An in vitro approach to understand contribution of kidney cells to human urinary extracellular vesicles. J Extracell Vesicles 2023; 12:e12304. [PMID: 36785873 PMCID: PMC9925963 DOI: 10.1002/jev2.12304] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 12/26/2022] [Accepted: 01/05/2023] [Indexed: 02/15/2023] Open
Abstract
Extracellular vesicles (EV) are membranous particles secreted by all cells and found in body fluids. Established EV contents include a variety of RNA species, proteins, lipids and metabolites that are considered to reflect the physiological status of their parental cells. However, to date, little is known about cell-type enriched EV cargo in complex EV mixtures, especially in urine. To test whether EV secretion from distinct human kidney cells in culture differ and can recapitulate findings in normal urine, we comprehensively analysed EV components, (particularly miRNAs, long RNAs and protein) from conditionally immortalised human kidney cell lines (podocyte, glomerular endothelial, mesangial and proximal tubular cells) and compared to EV secreted in human urine. EV from cell culture media derived from immortalised kidney cells were isolated by hydrostatic filtration dialysis (HFD) and characterised by electron microscopy (EM), nanoparticle tracking analysis (NTA) and Western blotting (WB). RNA was isolated from EV and subjected to miRNA and RNA sequencing and proteins were profiled by tandem mass tag proteomics. Representative sets of EV miRNAs, RNAs and proteins were detected in each cell type and compared to human urinary EV isolates (uEV), EV cargo database, kidney biopsy bulk RNA sequencing and proteomics, and single-cell transcriptomics. This revealed that a high proportion of the in vitro EV signatures were also found in in vivo datasets. Thus, highlighting the robustness of our in vitro model and showing that this approach enables the dissection of cell type specific EV cargo in biofluids and the potential identification of cell-type specific EV biomarkers of kidney disease.
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Affiliation(s)
- Karina Barreiro
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
| | - Abigail C. Lay
- Bristol RenalBristol Medical SchoolFaculty of Health SciencesUniversity of BristolBristolUK
| | - German Leparc
- Boehringer Ingelheim Pharma GmbH & Co. KG BiberachBiberachGermany
| | - Van Du T. Tran
- Vital‐IT GroupSIB Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Marcel Rosler
- Boehringer Ingelheim Pharma GmbH & Co. KG BiberachBiberachGermany
| | - Lusyan Dayalan
- Bristol RenalBristol Medical SchoolFaculty of Health SciencesUniversity of BristolBristolUK
| | - Frederic Burdet
- Vital‐IT GroupSIB Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Mark Ibberson
- Vital‐IT GroupSIB Swiss Institute of BioinformaticsLausanneSwitzerland
| | - Richard J. M. Coward
- Bristol RenalBristol Medical SchoolFaculty of Health SciencesUniversity of BristolBristolUK
| | - Tobias B. Huber
- III Department of MedicineUniversity Medical Center Hamburg‐EppendorfHamburgGermany
| | - Bernhard K. Krämer
- Fifth Department of Medicine (Nephrology/Endocrinology/Rheumatology/Pneumology)University Medical Centre MannheimUniversity of HeidelbergMannheimGermany
| | - Denis Delic
- Boehringer Ingelheim Pharma GmbH & Co. KG BiberachBiberachGermany
- Fifth Department of Medicine (Nephrology/Endocrinology/Rheumatology/Pneumology)University Medical Centre MannheimUniversity of HeidelbergMannheimGermany
| | - Harry Holthofer
- Institute for Molecular Medicine Finland (FIMM)University of HelsinkiHelsinkiFinland
- III Department of MedicineUniversity Medical Center Hamburg‐EppendorfHamburgGermany
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Liu WP, Li P, Zhan X, Qu LH, Xiong T, Hou FX, Wang JK, Wei N, Liu FQ. Identification of molecular subtypes of coronary artery disease based on ferroptosis- and necroptosis-related genes. Front Genet 2022; 13:870222. [PMID: 36204316 PMCID: PMC9531137 DOI: 10.3389/fgene.2022.870222] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/25/2022] [Accepted: 08/12/2022] [Indexed: 11/13/2022] Open
Abstract
Aim: Coronary artery disease (CAD) is a heterogeneous disorder with high morbidity, mortality, and healthcare costs, representing a major burden on public health. Here, we aimed to improve our understanding of the genetic drivers of ferroptosis and necroptosis and the clustering of gene expression in CAD in order to develop novel personalized therapies to slow disease progression.Methods: CAD datasets were obtained from the Gene Expression Omnibus. The identification of ferroptosis- and necroptosis-related differentially expressed genes (DEGs) and the consensus clustering method including the classification algorithm used km and distance used spearman were performed to differentiate individuals with CAD into two clusters (cluster A and cluster B) based expression matrix of DEGs. Next, we identified four subgroup-specific genes of significant difference between cluster A and B and again divided individuals with CAD into gene cluster A and gene cluster B with same methods. Additionally, we compared differences in clinical information between the subtypes separately. Finally, principal component analysis algorithms were constructed to calculate the cluster-specific gene score for each sample for quantification of the two clusters.Results: In total, 25 ferroptosis- and necroptosis-related DEGs were screened. The genes in cluster A were mostly related to the neutrophil pathway, whereas those in cluster B were mostly related to the B-cell receptor signaling pathway. Moreover, the subgroup-specific gene scores and CAD indices were higher in cluster A and gene cluster A than in cluster B and gene cluster B. We also identified and validated two genes showing upregulation between clusters A and B in a validation dataset.Conclusion: High expression of CBS and TLR4 was related to more severe disease in patients with CAD, whereas LONP1 and HSPB1 expression was associated with delayed CAD progression. The identification of genetic subgroups of patients with CAD may improve clinician knowledge of disease pathogenesis and facilitate the development of methods for disease diagnosis, classification, and prognosis.
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Affiliation(s)
- Wen-Pan Liu
- Cardiovascular Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
- Department of Cardiothoracic Surgery, The First People’s Hospital of Kunming City and Ganmei Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Peng Li
- Department of Surgery, Nanzhao County People’s Hospital, Nanyang, Henan, China
| | - Xu Zhan
- Department of Cardiothoracic Surgery, The First Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Lai-Hao Qu
- Department of Cardiothoracic Surgery, Yan’an Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Tao Xiong
- Department of Cardiothoracic Surgery, Yan’an Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China
| | - Fang-Xia Hou
- Cardiovascular Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
| | - Jun-Kui Wang
- Cardiovascular Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
| | - Na Wei
- Cardiovascular Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
- *Correspondence: Na Wei, ; Fu-Qiang Liu,
| | - Fu-Qiang Liu
- Cardiovascular Department, Shaanxi Provincial People’s Hospital, Xi’an, Shaanxi, China
- *Correspondence: Na Wei, ; Fu-Qiang Liu,
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Zheng PF, Zou QC, Chen LZ, Liu P, Liu ZY, Pan HW. Identifying patterns of immune related cells and genes in the peripheral blood of acute myocardial infarction patients using a small cohort. J Transl Med 2022; 20:321. [PMID: 35864510 PMCID: PMC9306178 DOI: 10.1186/s12967-022-03517-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Accepted: 07/04/2022] [Indexed: 12/31/2022] Open
Abstract
Background The immune system plays a vital role in the pathophysiology of acute myocardial infarction (AMI). However, the exact immune related mechanism is still unclear. This research study aimed to identify key immune-related genes involved in AMI. Methods CIBERSORT, a deconvolution algorithm, was used to determine the proportions of 22 subsets of immune cells in blood samples. The weighted gene co-expression network analysis (WGCNA) was used to identify key modules that are significantly associated with AMI. Then, CIBERSORT combined with WGCNA were used to identify key immune-modules. The protein–protein interaction (PPI) network was constructed and Molecular Complex Detection (MCODE) combined with cytoHubba plugins were used to identify key immune-related genes that may play an important role in the occurrence and progression of AMI. Results The CIBERSORT results suggested that there was a decrease in the infiltration of CD8 + T cells, gamma delta (γδ) T cells, and resting mast cells, along with an increase in the infiltration of neutrophils and M0 macrophages in AMI patients. Then, two modules (midnightblue and lightyellow) that were significantly correlated with AMI were identified, and the salmon module was found to be significantly associated with memory B cells. Gene enrichment analysis indicated that the 1,171 genes included in the salmon module are mainly involved in immune-related biological processes. MCODE analysis was used to identify four different MCODE complexes in the salmon module, while four hub genes (EEF1B2, RAC2, SPI1, and ITGAM) were found to be significantly correlated with AMI. The correlation analysis between the key genes and infiltrating immune cells showed that SPI1 and ITGAM were positively associated with neutrophils and M0 macrophages, while they were negatively associated with CD8 + T cells, γδ T cells, regulatory T cells (Tregs), and resting mast cells. The RT-qPCR validation results found that the expression of the ITGAM and SPI1 genes were significantly elevated in the AMI samples compared with the samples from healthy individuals, and the ROC curve analysis showed that ITGAM and SPI1 had a high diagnostic efficiency for the recognition of AMI. Conclusions Immune cell infiltration plays a crucial role in the occurrence and development of AMI. ITGAM and SPI1 are key immune-related genes that are potential novel targets for the prevention and treatment of AMI. Supplementary Information The online version contains supplementary material available at 10.1186/s12967-022-03517-1.
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Affiliation(s)
- Peng-Fei Zheng
- Cardiology Department, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China.,Clinical Research Center for Heart Failure in Hunan Province, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China.,Institute of Cardiovascular Epidemiology, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Qiong-Chao Zou
- Cardiology Department, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China.,Clinical Research Center for Heart Failure in Hunan Province, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China.,Institute of Cardiovascular Epidemiology, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China
| | - Lu-Zhu Chen
- Department of Cardiology, The Central Hospital of ShaoYang, No.36 QianYuan lane, Daxiang District, Shaoyang, 422000, Hunan, China
| | - Peng Liu
- Department of Cardiology, The Central Hospital of ShaoYang, No.36 QianYuan lane, Daxiang District, Shaoyang, 422000, Hunan, China
| | - Zheng-Yu Liu
- Cardiology Department, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China. .,Clinical Research Center for Heart Failure in Hunan Province, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China. .,Institute of Cardiovascular Epidemiology, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China.
| | - Hong-Wei Pan
- Cardiology Department, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China. .,Clinical Research Center for Heart Failure in Hunan Province, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China. .,Institute of Cardiovascular Epidemiology, Hunan Provincial People's Hospital, No.61 West Jiefang Road, Furong District, Changsha, 410000, Hunan, China.
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Wang H, Liu D, Song P, Jiang F, Zhang T. Microarray-Based Prediction of Polycythemia after Exposure to High Altitudes. Genes (Basel) 2022; 13:genes13071193. [PMID: 35885976 PMCID: PMC9316656 DOI: 10.3390/genes13071193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2022] [Revised: 06/24/2022] [Accepted: 06/30/2022] [Indexed: 12/05/2022] Open
Abstract
In high-altitude environments, the prevalence of high-altitude polycythemia (HAPC) ranges between 5 and 18 percent. However, there is currently no effective treatment for this condition. Therefore, disease prevention has emerged as a critical strategy against this disease. Here, we looked into the microarray profiles of GSE135109 and GSE29977, linked to either short- or long-term exposure to the Qinghai Tibet Plateau (QTP). The results revealed inhibition in the adaptive immune response during 30 days of exposure to QTP. Following a gene set enrichment analysis (GSEA) discovered that genes associated with HAPC were enriched in Cluster1, which showed a dramatic upregulation on the third day after arriving at the QTP. We then used GeneLogit to construct a logistic prediction model, which allowed us to identify 50 genes that classify HAPC patients. In these genes, LRRC18 and HCAR3 were also significantly altered following early QTP exposure, suggesting that they may serve as hub genes for HAPC development. The in-depth study of a combination of the datasets of transcriptomic changes during exposure to a high altitude and whether diseases occur after long-term exposure in Hans can give us some inspiration about genes associated with HAPC development during adaption to high altitudes.
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Affiliation(s)
- Haijing Wang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China; (H.W.); (D.L.); (P.S.); (F.J.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Medical School, Qinghai University, Xining 810016, China
- Qinghai Provincial Key Laboratory of Animal Ecological Genomics, Xining 810008, China
| | - Daoxin Liu
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China; (H.W.); (D.L.); (P.S.); (F.J.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Qinghai Provincial Key Laboratory of Animal Ecological Genomics, Xining 810008, China
- Kunlun College, Qinghai University, Xining 810016, China
| | - Pengfei Song
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China; (H.W.); (D.L.); (P.S.); (F.J.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Qinghai Provincial Key Laboratory of Animal Ecological Genomics, Xining 810008, China
| | - Feng Jiang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China; (H.W.); (D.L.); (P.S.); (F.J.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Qinghai Provincial Key Laboratory of Animal Ecological Genomics, Xining 810008, China
| | - Tongzuo Zhang
- Key Laboratory of Adaptation and Evolution of Plateau Biota, Northwest Institute of Plateau Biology, Chinese Academy of Sciences, Xining 810001, China; (H.W.); (D.L.); (P.S.); (F.J.)
- University of Chinese Academy of Sciences, Beijing 100049, China
- Qinghai Provincial Key Laboratory of Animal Ecological Genomics, Xining 810008, China
- Correspondence:
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Xu X, Zou R, Liu X, Liu J, Su Q. Epithelial-mesenchymal transition-related genes in coronary artery disease. Open Med (Wars) 2022; 17:781-800. [PMID: 35529472 PMCID: PMC9034345 DOI: 10.1515/med-2022-0476] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/03/2021] [Revised: 02/26/2022] [Accepted: 03/22/2022] [Indexed: 11/15/2022] Open
Abstract
Abstract
Epithelial-mesenchymal transition (EMT) is critical in the development of coronary artery disease (CAD). However, landscapes of EMT-related genes have not been fully established in CAD. We identified the differentially expressed mRNAs and lncRNAs (DElncRNAs) from the Gene Expression Omnibus database. Pearson’s correlation analysis, the least absolute shrinkage and selection operator regression, and support vector machine reverse feature elimination algorithms were used to screen EMT-related lncRNAs. The cis–trans regulatory networks were constructed based on EMT-related lncRNAs. Quantitative real-time polymerase chain reaction was performed to validate the expression of EMT-related genes in a cohort of six patients with CAD and six healthy controls. We further estimated the infiltration of the immune cells in CAD patients with five algorithms, and the correlation between EMT-related genes and infiltrating immune cells was analyzed. We identified eight EMT-related lncRNAs in CAD. The area under curve value was greater than 0.95. The immune analysis revealed significant CD8 T cells, monocytes, and NK cells in CAD and found that EMT-related lncRNAs were correlated with these immune cell subsets. Moreover, SNAI2, an EMT-TF gene, was found in the trans-regulatory network of EMT-related lncRNAs. Further, we found SNAI2 as a biomarker for the diagnosis of CAD but it also had a close correlation with immune cell subsets in CAD. Eight EMT-related lncRNAs and SNAI2 have important significance in the diagnosis of CAD patients.
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Affiliation(s)
- Xiang Xu
- Department of Cardiology, The Second Affiliated Hospital of Kunming Medical University, Kunming City, Yunnan Province, China
| | - Renchao Zou
- Department of Hepatobiliary Surgery, The Second Affiliated Hospital of Kunming Medical University, Kunming City, Yunnan Province, China
| | - Xiaoyong Liu
- Department of Cardiology, The Second Affiliated Hospital of Kunming Medical University, Kunming City, Yunnan Province, China
| | - Jia Liu
- Department of Laboratory Animal Science, Kunming Medical University, Kunming City, Yunnan Province, 650500, China
| | - Qianqian Su
- Department of Laboratory Animal Science, Kunming Medical University, Kunming City, Yunnan Province, 650500, China
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