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Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway
Acute aortic dissection (AAD) is a life-threatening disease. Despite the higher risk of mortality, currently there are no effective therapies that can ameliorate AAD development or progression. Identification of meaningful clusters of co-expressed genes or representative biomarkers for AAD may help...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723018/ https://www.ncbi.nlm.nih.gov/pubmed/29255427 http://dx.doi.org/10.3389/fphys.2017.01010 |
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author | Wang, Tao He, Xingwei Liu, Xintian Liu, Yujian Zhang, Wenjun Huang, Qiang Liu, Wanjun Xiong, Luyang Tan, Rong Wang, Hongjie Zeng, Hesong |
author_facet | Wang, Tao He, Xingwei Liu, Xintian Liu, Yujian Zhang, Wenjun Huang, Qiang Liu, Wanjun Xiong, Luyang Tan, Rong Wang, Hongjie Zeng, Hesong |
author_sort | Wang, Tao |
collection | PubMed |
description | Acute aortic dissection (AAD) is a life-threatening disease. Despite the higher risk of mortality, currently there are no effective therapies that can ameliorate AAD development or progression. Identification of meaningful clusters of co-expressed genes or representative biomarkers for AAD may help to identify new pathomechanisms and foster development of new therapies. To this end, we performed a weighted gene co-expression network analysis (WGCNA) and calculated module-trait correlations based on a public microarray dataset (GSE 52093) and discovered 9 modules were found to be related to AAD. The module which has the strongest positive correlation with AAD was further analyzed and the top 10 hub genes SLC20A1, GINS2, CNN1, FAM198B, MAD2L2, UBE2T, FKBP11, SLMAP, CCDC34, and GALK1 were identified. Furthermore, we validated the data by qRT-PCR in an independent sample set originated from our study center. Overall, the qRT-PCR results were consistent with the results of the microarray analysis. Intriguingly, the highest change was found for FKBP11, a protein belongs to the FKBP family of peptidyl-prolyl cis/trans isomerases, which catalyze the folding of proline-containing polypeptides. In congruent with the gene expression analysis, FKBP11 expression was induced in cultured endothelial cells by angiotensin II treatment and endothelium of the dissected aorta. More importantly we show that FKBP11 provokes inflammation in endothelial cells by interacting with NF-kB p65 subunit, resulting in pro-inflammatory cytokines production. Accordingly, siRNA mediated knockdown of FKBP11 in cultured endothelial cells suppressed angiotensin II induced monocyte transmigration through the endothelial monolayer. Based on these data, we hypothesize that pro-inflammatory cytokines elicited by FKBP11 overexpression in the endothelium under AAD condition could facilitate transendothelial migration of the circulating monocytes into the aorta, where they differentiate into active macrophages and secrete MMPs and other extracellular matrix (ECM) degrading proteins, contributing to sustained inflammation and AAD. Taken together, our data identify important role of FKBP11 which can serve as biomarker and/or therapeutic target for AAD. |
format | Online Article Text |
id | pubmed-5723018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-57230182017-12-18 Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway Wang, Tao He, Xingwei Liu, Xintian Liu, Yujian Zhang, Wenjun Huang, Qiang Liu, Wanjun Xiong, Luyang Tan, Rong Wang, Hongjie Zeng, Hesong Front Physiol Physiology Acute aortic dissection (AAD) is a life-threatening disease. Despite the higher risk of mortality, currently there are no effective therapies that can ameliorate AAD development or progression. Identification of meaningful clusters of co-expressed genes or representative biomarkers for AAD may help to identify new pathomechanisms and foster development of new therapies. To this end, we performed a weighted gene co-expression network analysis (WGCNA) and calculated module-trait correlations based on a public microarray dataset (GSE 52093) and discovered 9 modules were found to be related to AAD. The module which has the strongest positive correlation with AAD was further analyzed and the top 10 hub genes SLC20A1, GINS2, CNN1, FAM198B, MAD2L2, UBE2T, FKBP11, SLMAP, CCDC34, and GALK1 were identified. Furthermore, we validated the data by qRT-PCR in an independent sample set originated from our study center. Overall, the qRT-PCR results were consistent with the results of the microarray analysis. Intriguingly, the highest change was found for FKBP11, a protein belongs to the FKBP family of peptidyl-prolyl cis/trans isomerases, which catalyze the folding of proline-containing polypeptides. In congruent with the gene expression analysis, FKBP11 expression was induced in cultured endothelial cells by angiotensin II treatment and endothelium of the dissected aorta. More importantly we show that FKBP11 provokes inflammation in endothelial cells by interacting with NF-kB p65 subunit, resulting in pro-inflammatory cytokines production. Accordingly, siRNA mediated knockdown of FKBP11 in cultured endothelial cells suppressed angiotensin II induced monocyte transmigration through the endothelial monolayer. Based on these data, we hypothesize that pro-inflammatory cytokines elicited by FKBP11 overexpression in the endothelium under AAD condition could facilitate transendothelial migration of the circulating monocytes into the aorta, where they differentiate into active macrophages and secrete MMPs and other extracellular matrix (ECM) degrading proteins, contributing to sustained inflammation and AAD. Taken together, our data identify important role of FKBP11 which can serve as biomarker and/or therapeutic target for AAD. Frontiers Media S.A. 2017-12-04 /pmc/articles/PMC5723018/ /pubmed/29255427 http://dx.doi.org/10.3389/fphys.2017.01010 Text en Copyright © 2017 Wang, He, Liu, Liu, Zhang, Huang, Liu, Xiong, Tan, Wang and Zeng. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Physiology Wang, Tao He, Xingwei Liu, Xintian Liu, Yujian Zhang, Wenjun Huang, Qiang Liu, Wanjun Xiong, Luyang Tan, Rong Wang, Hongjie Zeng, Hesong Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway |
title | Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway |
title_full | Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway |
title_fullStr | Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway |
title_full_unstemmed | Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway |
title_short | Weighted Gene Co-expression Network Analysis Identifies FKBP11 as a Key Regulator in Acute Aortic Dissection through a NF-kB Dependent Pathway |
title_sort | weighted gene co-expression network analysis identifies fkbp11 as a key regulator in acute aortic dissection through a nf-kb dependent pathway |
topic | Physiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5723018/ https://www.ncbi.nlm.nih.gov/pubmed/29255427 http://dx.doi.org/10.3389/fphys.2017.01010 |
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