Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes
BackgroundIschemia reperfusion injury (IRI) is an inevitable process in renal transplantation, which is closely related to serious postoperative complications such as delayed graft function (DGF), acute rejection and graft failure. Neutrophil extracellular traps (NETs) are extracellular DNA structur...
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Frontiers Media S.A.
2022-12-01
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| Series: | Frontiers in Immunology |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1047367/full |
| _version_ | 1797987661331300352 |
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| author | Jiyue Wu Jiyue Wu Feilong Zhang Feilong Zhang Xiang Zheng Xiang Zheng Jiandong Zhang Jiandong Zhang Peng Cao Peng Cao Zejia Sun Zejia Sun Wei Wang Wei Wang |
| author_facet | Jiyue Wu Jiyue Wu Feilong Zhang Feilong Zhang Xiang Zheng Xiang Zheng Jiandong Zhang Jiandong Zhang Peng Cao Peng Cao Zejia Sun Zejia Sun Wei Wang Wei Wang |
| author_sort | Jiyue Wu |
| collection | DOAJ |
| description | BackgroundIschemia reperfusion injury (IRI) is an inevitable process in renal transplantation, which is closely related to serious postoperative complications such as delayed graft function (DGF), acute rejection and graft failure. Neutrophil extracellular traps (NETs) are extracellular DNA structures decorated with various protein substances released by neutrophils under strong signal stimulation. Recently, NETs have been found to play an important role in the process of IRI. This study aimed to comprehensively analyze the expression landscape of NET-related genes (NRGs) during IRI, identify clusters with different degrees of IRI and construct robust DGF and long-term graft survival predictive strategies.MethodsThe microarray and RNA-seq datasets were obtained from the GEO database. Differentially expressed NRGs (DE-NRGs) were identified by the differential expression analysis, and the NMF algorithm was used to conduct a cluster analysis of IRI samples. Machine learning algorithms were performed to screen DGF-related hub NRGs, and DGF and long-term graft survival predictive strategies were constructed based on these hub NRGs. Finally, we verified the expression of Cxcl1 and its effect on IRI and NETs generation in the mouse IRI model.ResultsThis study revealed two IRI clusters (C1 and C2 clusters) with different molecular features and clinical characteristics. Cluster C1 was characterized by active metabolism, mild inflammation and lower incidence of DGF, while Cluster C2 was inflammation activated subtype with a higher incidence of DGF. Besides, based on DGF-related hub NRGs, we successfully constructed robust DGF and long-term graft survival predictive strategies. The mouse renal IRI model verified that Cxcl1 was significantly upregulated in renal tissues after IRI, and using a CXCL8/CXCL1 inhibitor could significantly improve renal function, alleviate renal tubular necrosis, tissue inflammatory response, and NET formation.ConclusionThis study identified two distinct IRI clusters based on DE-NRGs and constructed robust prediction methods for DGF and graft survival, which can provide references for early prevention and individualized treatment of various postoperative complications after renal transplantation. |
| first_indexed | 2024-04-11T07:51:54Z |
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| id | doaj.art-b2134e95b71a4b6c8fe94da4f01266ee |
| institution | Directory Open Access Journal |
| issn | 1664-3224 |
| language | English |
| last_indexed | 2024-04-11T07:51:54Z |
| publishDate | 2022-12-01 |
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| series | Frontiers in Immunology |
| spelling | doaj.art-b2134e95b71a4b6c8fe94da4f01266ee2022-12-22T04:36:03ZengFrontiers Media S.A.Frontiers in Immunology1664-32242022-12-011310.3389/fimmu.2022.10473671047367Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genesJiyue Wu0Jiyue Wu1Feilong Zhang2Feilong Zhang3Xiang Zheng4Xiang Zheng5Jiandong Zhang6Jiandong Zhang7Peng Cao8Peng Cao9Zejia Sun10Zejia Sun11Wei Wang12Wei Wang13Department of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaInstitute of Urology, Capital Medical University, Beijing, ChinaDepartment of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaInstitute of Urology, Capital Medical University, Beijing, ChinaDepartment of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaInstitute of Urology, Capital Medical University, Beijing, ChinaDepartment of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaInstitute of Urology, Capital Medical University, Beijing, ChinaDepartment of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaInstitute of Urology, Capital Medical University, Beijing, ChinaDepartment of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaInstitute of Urology, Capital Medical University, Beijing, ChinaDepartment of Urology, Beijing Chaoyang Hospital, Capital Medical University, Beijing, ChinaInstitute of Urology, Capital Medical University, Beijing, ChinaBackgroundIschemia reperfusion injury (IRI) is an inevitable process in renal transplantation, which is closely related to serious postoperative complications such as delayed graft function (DGF), acute rejection and graft failure. Neutrophil extracellular traps (NETs) are extracellular DNA structures decorated with various protein substances released by neutrophils under strong signal stimulation. Recently, NETs have been found to play an important role in the process of IRI. This study aimed to comprehensively analyze the expression landscape of NET-related genes (NRGs) during IRI, identify clusters with different degrees of IRI and construct robust DGF and long-term graft survival predictive strategies.MethodsThe microarray and RNA-seq datasets were obtained from the GEO database. Differentially expressed NRGs (DE-NRGs) were identified by the differential expression analysis, and the NMF algorithm was used to conduct a cluster analysis of IRI samples. Machine learning algorithms were performed to screen DGF-related hub NRGs, and DGF and long-term graft survival predictive strategies were constructed based on these hub NRGs. Finally, we verified the expression of Cxcl1 and its effect on IRI and NETs generation in the mouse IRI model.ResultsThis study revealed two IRI clusters (C1 and C2 clusters) with different molecular features and clinical characteristics. Cluster C1 was characterized by active metabolism, mild inflammation and lower incidence of DGF, while Cluster C2 was inflammation activated subtype with a higher incidence of DGF. Besides, based on DGF-related hub NRGs, we successfully constructed robust DGF and long-term graft survival predictive strategies. The mouse renal IRI model verified that Cxcl1 was significantly upregulated in renal tissues after IRI, and using a CXCL8/CXCL1 inhibitor could significantly improve renal function, alleviate renal tubular necrosis, tissue inflammatory response, and NET formation.ConclusionThis study identified two distinct IRI clusters based on DE-NRGs and constructed robust prediction methods for DGF and graft survival, which can provide references for early prevention and individualized treatment of various postoperative complications after renal transplantation.https://www.frontiersin.org/articles/10.3389/fimmu.2022.1047367/fullneutrophil extracellular trapsischemia reperfusion injuryrenal transplantationdelayed graft functiongraft failureacute rejection |
| spellingShingle | Jiyue Wu Jiyue Wu Feilong Zhang Feilong Zhang Xiang Zheng Xiang Zheng Jiandong Zhang Jiandong Zhang Peng Cao Peng Cao Zejia Sun Zejia Sun Wei Wang Wei Wang Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes Frontiers in Immunology neutrophil extracellular traps ischemia reperfusion injury renal transplantation delayed graft function graft failure acute rejection |
| title | Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes |
| title_full | Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes |
| title_fullStr | Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes |
| title_full_unstemmed | Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes |
| title_short | Identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap-related genes |
| title_sort | identification of renal ischemia reperfusion injury subtypes and predictive strategies for delayed graft function and graft survival based on neutrophil extracellular trap related genes |
| topic | neutrophil extracellular traps ischemia reperfusion injury renal transplantation delayed graft function graft failure acute rejection |
| url | https://www.frontiersin.org/articles/10.3389/fimmu.2022.1047367/full |
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