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Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models
Thoracic aortic aneurysm and dissection (TAAD) is a high-risk aortic disease. Mouse models are usually used to explore the pathological progression of TAAD. In our studies, we performed bioinformatics analysis on a microarray dataset (GSE36778) and verified experiments to define the integrated hub g...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959095/ https://www.ncbi.nlm.nih.gov/pubmed/35356426 http://dx.doi.org/10.3389/fgene.2022.823769 |
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author | Zhang, Xiaoping Yang, Zuozhen Li, Xiaoyan Liu, Xuxia Wang, Xipeng Qiu, Tao Wang, Yueli Li, Tongxun Li, Qingle |
author_facet | Zhang, Xiaoping Yang, Zuozhen Li, Xiaoyan Liu, Xuxia Wang, Xipeng Qiu, Tao Wang, Yueli Li, Tongxun Li, Qingle |
author_sort | Zhang, Xiaoping |
collection | PubMed |
description | Thoracic aortic aneurysm and dissection (TAAD) is a high-risk aortic disease. Mouse models are usually used to explore the pathological progression of TAAD. In our studies, we performed bioinformatics analysis on a microarray dataset (GSE36778) and verified experiments to define the integrated hub genes of TAAD in three different mouse models. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein–protein interaction (PPI) network analyses, and histological and quantitative reverse transcription-PCR (qRT–PCR) experiments were used in our study. First, differentially expressed genes (DEGs) were identified, and twelve common differentially expressed genes were found. Second, genes related to the cell cycle and inflammation were enriched by using GO and PPI. We focused on filtering and validating eighteen hub genes that were upregulated. Then, expression data from human ascending aortic tissues in the GSE153434 dataset were also used to verify our findings. These results indicated that cell cycle-related genes participate in the pathological mechanism of TAAD and provide new insight into the molecular mechanisms of TAAD. |
format | Online Article Text |
id | pubmed-8959095 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89590952022-03-29 Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models Zhang, Xiaoping Yang, Zuozhen Li, Xiaoyan Liu, Xuxia Wang, Xipeng Qiu, Tao Wang, Yueli Li, Tongxun Li, Qingle Front Genet Genetics Thoracic aortic aneurysm and dissection (TAAD) is a high-risk aortic disease. Mouse models are usually used to explore the pathological progression of TAAD. In our studies, we performed bioinformatics analysis on a microarray dataset (GSE36778) and verified experiments to define the integrated hub genes of TAAD in three different mouse models. Gene Ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG) and protein–protein interaction (PPI) network analyses, and histological and quantitative reverse transcription-PCR (qRT–PCR) experiments were used in our study. First, differentially expressed genes (DEGs) were identified, and twelve common differentially expressed genes were found. Second, genes related to the cell cycle and inflammation were enriched by using GO and PPI. We focused on filtering and validating eighteen hub genes that were upregulated. Then, expression data from human ascending aortic tissues in the GSE153434 dataset were also used to verify our findings. These results indicated that cell cycle-related genes participate in the pathological mechanism of TAAD and provide new insight into the molecular mechanisms of TAAD. Frontiers Media S.A. 2022-03-08 /pmc/articles/PMC8959095/ /pubmed/35356426 http://dx.doi.org/10.3389/fgene.2022.823769 Text en Copyright © 2022 Zhang, Yang, Li, Liu, Wang, Qiu, Wang, Li and Li. https://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) and the copyright owner(s) 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 | Genetics Zhang, Xiaoping Yang, Zuozhen Li, Xiaoyan Liu, Xuxia Wang, Xipeng Qiu, Tao Wang, Yueli Li, Tongxun Li, Qingle Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models |
title | Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models |
title_full | Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models |
title_fullStr | Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models |
title_full_unstemmed | Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models |
title_short | Bioinformatics Analysis Reveals Cell Cycle-Related Gene Upregulation in Ascending Aortic Tissues From Murine Models |
title_sort | bioinformatics analysis reveals cell cycle-related gene upregulation in ascending aortic tissues from murine models |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8959095/ https://www.ncbi.nlm.nih.gov/pubmed/35356426 http://dx.doi.org/10.3389/fgene.2022.823769 |
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