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Zhang LM, Liang XL, Xiong GF, Xing XL, Zhang QJ, Zhang BR, Liu MW. Analysis and identification of oxidative stress-ferroptosis related biomarkers in ischemic stroke. Sci Rep 2024; 14:3803. [PMID: 38360841 PMCID: PMC10869843 DOI: 10.1038/s41598-024-54555-2] [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: 07/20/2023] [Accepted: 02/14/2024] [Indexed: 02/17/2024] Open
Abstract
Studies have shown that a series of molecular events caused by oxidative stress is associated with ferroptosis and oxidation after ischemic stroke (IS). Differential analysis was performed to identify differentially expressed mRNA (DEmRNAs) between IS and control groups. Critical module genes were identified using weighted gene co-expression network analysis (WGCNA). DEmRNAs, critical module genes, oxidative stress-related genes (ORGs), and ferroptosis-related genes (FRGs) were crossed to screen for intersection mRNAs. Candidate mRNAs were screened based on the protein-protein interaction (PPI) network and the MCODE plug-in. Biomarkers were identified based on two types of machine learning algorithms, and the intersection was obtained. Functional items and related pathways of the biomarkers were identified using gene set enrichment analysis (GSEA). Finally, single-sample GSEA (ssGSEA) and Wilcoxon tests were used to identify differential immune cells. An miRNA-mRNA-TF network was created. Quantitative real-time polymerase chain reaction (qRT-PCR) was performed to verify the expression levels of biomarkers in the IS and control groups. There were 8287 DE mRNAs between the IS and control groups. The genes in the turquoise module were selected as critical module genes for IS. Thirty intersecting mRNAs were screened for overlaps. Seventeen candidate mRNAs were also identified. Four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) were identified using two types of machine-learning algorithms. GSEA results indicated that the biomarkers were associated with steroid biosynthesis. Nine types of immune cells (activated B cells and neutrophils) were markedly different between the IS and control groups. We identified 3747 miRNA-mRNA-TF regulatory pairs in the miRNA-mRNA-TF regulatory network, including hsa-miR-4469-CDKN1A-BACH2 and hsa-miR-188-3p-GPX4-ATF2. CDKN1A, PRDX1, and PRDX6 were upregulated in IS samples compared with control samples. This study suggests that four biomarkers (CDKN1A, GPX4, PRDX1, and PRDX6) are significantly associated with IS. This study provides a new reference for the diagnosis and treatment of IS.
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Affiliation(s)
- Lin-Ming Zhang
- Department of Neurology, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Xing-Ling Liang
- Department of Emergency, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Gui-Fei Xiong
- Department of Emergency, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Xuan-Lin Xing
- Department of Emergency, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Qiu-Juan Zhang
- Department of Emergency, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Bing-Ran Zhang
- Department of Emergency, The First Affiliated Hospital of Kunming Medical University, Kunming, 650032, Yunnan, China
| | - Ming-Wei Liu
- Department of Emergency, People's Hospital of Dali Bai Autonomous Prefecture, No. 35 Renmin South Road, Xiaguan Street, Dalí, 671000, Yunnan, China.
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Caño-Carrillo S, Castillo-Casas JM, Franco D, Lozano-Velasco E. Unraveling the Signaling Dynamics of Small Extracellular Vesicles in Cardiac Diseases. Cells 2024; 13:265. [PMID: 38334657 PMCID: PMC10854837 DOI: 10.3390/cells13030265] [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: 12/29/2023] [Revised: 01/28/2024] [Accepted: 01/30/2024] [Indexed: 02/10/2024] Open
Abstract
Effective intercellular communication is essential for cellular and tissue balance maintenance and response to challenges. Cellular communication methods involve direct cell contact or the release of biological molecules to cover short and long distances. However, a recent discovery in this communication network is the involvement of extracellular vesicles that host biological contents such as proteins, nucleic acids, and lipids, influencing neighboring cells. These extracellular vesicles are found in body fluids; thus, they are considered as potential disease biomarkers. Cardiovascular diseases are significant contributors to global morbidity and mortality, encompassing conditions such as ischemic heart disease, cardiomyopathies, electrical heart diseases, and heart failure. Recent studies reveal the release of extracellular vesicles by cardiovascular cells, influencing normal cardiac function and structure. However, under pathological conditions, extracellular vesicles composition changes, contributing to the development of cardiovascular diseases. Investigating the loading of molecular cargo in these extracellular vesicles is essential for understanding their role in disease development. This review consolidates the latest insights into the role of extracellular vesicles in diagnosis and prognosis of cardiovascular diseases, exploring the potential applications of extracellular vesicles in personalized therapies, shedding light on the evolving landscape of cardiovascular medicine.
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Affiliation(s)
| | | | | | - Estefanía Lozano-Velasco
- Cardiovascular Development Group, Department of Experimental Biology, University of Jaén, 23071 Jaén, Spain; (S.C.-C.); (J.M.C.-C.); (D.F.)
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Sevoflurane-induced POCD-associated exosomes delivered miR-584-5p regulates the growth of human microglia HMC3 cells through targeting BDNF. Aging (Albany NY) 2022; 14:9890-9907. [PMID: 36455873 PMCID: PMC9831737 DOI: 10.18632/aging.204398] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Accepted: 11/17/2022] [Indexed: 01/03/2023]
Abstract
BACKGROUND Inhalation of sevoflurane can cause neuronal apoptosis, and cognitive disorders, inducing to the occurrence and progression of post operative cognitive dysfunction (POCD). This study aimed to explore the roles of sevoflurane-induced POCD-associated exosomes on HMC3 cells and its related mechanisms. METHODS Exosomes were isolated from the plasma of sevoflurane-induced POCD or non-POCD patients, and were then sent for small RNA sequencing. Real-time quantitative PCR (RT-qPCR) was used to verify the sequencing results, and miR-584-5p was chosen for subsequent study. HMC3 cells were respectively transfected with POCD-derived exosomes and miR-584-5p mimics, and cell viability and apoptosis were measured. Dual-luciferase reporter gene assay was applied to confirm the target of miR-584-5p. RESULTS After sequencing, 301 differentially expressed miRNAs were identified, including 184 up-regulated miRNAs and 117 down-regulated miRNAs, and were significantly enriched in 3577 GO terms and 121 KEGG pathways. Due to the high level of miR-584-5p in sevoflurane-treated POCD-derived exosomes, HMC3 cells with miR-584-5p enrichment were successfully established. Compared with the control group, POCD-derived exosomes and miR-584-5p significantly inhibited viability and promoted apoptosis of HMC3 cells (P < 0.05). The IL-1β and TNF-α levels were significantly increased after POCD-derived exosomes and miR-584-5p mimics treatment compared to the control group (P < 0.05). Besides, POCD-derived exosomes and miR-584-5p mimics significantly down-regulated the expression levels of BDNF and p-TrkB, and up-regulated Caspase 3 and IL-1β. Finally, BDNF was confirmed to be the target of miR-584-5p. CONCLUSIONS Sevoflurane-induced POCD-associated exosomes delivered miR-584-5p may regulate the growth of HMC3 cells via targeting BDNF.
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Ding Y, Wang F, Guo Y, Yang M, Zhang H. Integrated Analysis and Validation of Autophagy-Related Genes and Immune Infiltration in Acute Myocardial Infarction. COMPUTATIONAL AND MATHEMATICAL METHODS IN MEDICINE 2022; 2022:3851551. [PMID: 36238493 PMCID: PMC9553342 DOI: 10.1155/2022/3851551] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Revised: 08/16/2022] [Accepted: 09/07/2022] [Indexed: 11/24/2022]
Abstract
Background Acute myocardial infarction (AMI) is one of the most critical conditions of coronary heart disease with many uncertainties regarding reduction of ischemia/reperfusion injury, medical treatment strategies, and other aspects. The inflammatory immune response has a bidirectional regulatory role in AMI and plays an essential role in myocardial remodeling after AMI. The purpose of our research was tantamount to explore possible mechanisms of AMI and to analyze the relationship with the immune microenvironment. Methods We firstly analyzed the expression profile of GSE61144 and HADb to identify differentially expressed autophagy-related genes (DEARGs). Then, we performed GO, functional enrichment analysis, and constructed PPI network by Metascape. A lncRNA-miRNA-mRNA ceRNA network was built, and hub genes were extracted by Cytoscape. After that, we used CIBERSORT algorithm to estimate the proportion of immunocytes, followed by correlation analysis to find relationships between hub DEARGs and immunocyte subsets. Finally, we verified those hub genes in another dataset and cellular experiments qPCR. Results Compared with controls, we identified 44 DEARGs and then filtered the genes of MCODE by constructing PPI network for further analysis. A total of 45 lncRNAs, 24 miRNAs, 19 mRNAs, 162 lncRNA-miRNA pairs, and 37 mRNA-miRNA pairs were used to construct a ceRNA network, and 4 hub DEARGs (BCL2, MAPK1, RAF1, and PRKAR1A) were extracted. We then estimated 5 classes of immunocytes that differed between AMI and controls. According to the results of correlation analysis, these 4 hub DEARGs may play modulatory effects in immune infiltrating cells, notably in CD8+ T cells and neutrophils. Finally, the same results were verified in GSE60993 and qPCR experiments. Conclusion Our findings suggest that those hub DEARGs (BCL2, MAPK1, RAF1, and PRKAR1A) and immunocytes probably play functions in the progression of AMI, providing potential diagnostic markers and new perspectives for treatment of AMI.
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Affiliation(s)
- Yan Ding
- Department of Cardiology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518033, China
| | - Feng Wang
- Department of Cardiology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518033, China
| | - Yousheng Guo
- Department of Cardiology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518033, China
| | - Mingwei Yang
- Department of Cardiology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518033, China
| | - Huanji Zhang
- Department of Cardiology, The Eighth Affiliated Hospital, Sun Yat-Sen University, Shenzhen 518033, China
- Guangdong Innovative Engineering and Technology Research Center for Assisted Circulation, Shenzhen 518033, China
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Zheng Y, Gao W, Zhang Q, Cheng X, Liu Y, Qi Z, Li T. Ferroptosis and Autophagy-Related Genes in the Pathogenesis of Ischemic Cardiomyopathy. Front Cardiovasc Med 2022; 9:906753. [PMID: 35845045 PMCID: PMC9279674 DOI: 10.3389/fcvm.2022.906753] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/29/2022] [Accepted: 05/19/2022] [Indexed: 11/13/2022] Open
Abstract
Background Obesity plays an important role in type 2 diabetes mellitus (T2DM) and myocardial infarction (MI). Ferroptosis and ferritinophagy are related to metabolic pathways, such as fatty acid metabolism and mitochondrial respiration. We aimed to investigate the ferroptosis- and autophagy-related differentially expressed genes (DEGs) that might be potential targets for MI progression. Methods GSE116250 was analyzed to obtain DEGs. A Venn diagram was used to obtain the overlapping ferroptosis- and autophagy-related DEGs. The enrichment pathway analysis was performed and the hub genes were obtained. Pivotal miRNAs, transcription factors, and drugs with the hub genes interactions were also predicted. The MI mice model was constructed, and qPCR analysis and single-cell sequencing were used to validate the hub genes. Results Utilizing the limma package and the Venn diagram, 26 ferroptosis-related and 29 autophagy-related DEGs were obtained. The list of ferroptosis-related DEGs was analyzed, which were involved in the cellular response to a toxic substance, cellular oxidant detoxification, and the IL-17 signaling pathway. The list of autophagy-related DEGs was involved in the regulation of autophagy, the regulation of JAK-STAT signaling pathway, and the regulation of MAPK cascade. In the protein-protein interaction network, the hub DEGs, such as IL-6, PTGS2, JUN, NQO1, NOS3, LEPR, NAMPT, CDKN2A, CDKN1A, and Snai1, were obtained. After validation using qPCR analysis in the MI mice model and single-cell sequencing, the 10 hub genes can be the potential targets for MI deterioration. Conclusion The screened hub genes, IL-6, PTGS2, JUN, NQO1, NOS3, LEPR, NAMPT, CDKN2A, CDKN1A, and Snai1, may be therapeutic targets for patients with MI and may prevent adverse cardiovascular events.
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Affiliation(s)
- Yue Zheng
- School of Medicine, Nankai University, Tianjin, China
- Department of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China
- Nankai University Affiliated Third Center Hospital, Nankai University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
| | - Wenqing Gao
- School of Medicine, Nankai University, Tianjin, China
- Department of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China
- Nankai University Affiliated Third Center Hospital, Nankai University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
| | - Qiang Zhang
- School of Medicine, Nankai University, Tianjin, China
- Department of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China
- Nankai University Affiliated Third Center Hospital, Nankai University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
| | - Xian Cheng
- School of Medicine, Nankai University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Department of Heart Center, The Third Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Yanwu Liu
- School of Medicine, Nankai University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Department of Heart Center, The Third Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Zhenchang Qi
- School of Medicine, Nankai University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Department of Heart Center, The Third Central Clinical College of Tianjin Medical University, Tianjin, China
| | - Tong Li
- School of Medicine, Nankai University, Tianjin, China
- Department of Heart Center, The Third Central Hospital of Tianjin, Tianjin, China
- Nankai University Affiliated Third Center Hospital, Nankai University, Tianjin, China
- Tianjin Key Laboratory of Extracorporeal Life Support for Critical Diseases, Tianjin, China
- Artificial Cell Engineering Technology Research Center, Tianjin, China
- Department of Heart Center, The Third Central Clinical College of Tianjin Medical University, Tianjin, China
- *Correspondence: Tong Li,
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