Cargando…

Bioinformatics analysis and verification of gene targets for benign tracheal stenosis

BACKGROUND: Tracheal injury could cause intratracheal scar hyperplasia which in turn causes benign tracheal stenosis (TS). With the increasing use of mechanical ventilation and ventilator, the incidence of TS is increasing. However, the molecular mechanisms of TS have not been elucidated. It is sign...

Descripción completa

Detalles Bibliográficos
Autores principales: Li, Xu‐ze, Wang, Zi‐chen, Qiu, Yong, Ma, Shu‐xian, Meng, Ling‐bing, Wu, Wen‐hao, Zhang, Pei, Yang, Wei, Song, Wen‐ping, Huang, Lining
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284051/
https://www.ncbi.nlm.nih.gov/pubmed/32309912
http://dx.doi.org/10.1002/mgg3.1245
_version_ 1783544388648960000
author Li, Xu‐ze
Wang, Zi‐chen
Qiu, Yong
Ma, Shu‐xian
Meng, Ling‐bing
Wu, Wen‐hao
Zhang, Pei
Yang, Wei
Song, Wen‐ping
Huang, Lining
author_facet Li, Xu‐ze
Wang, Zi‐chen
Qiu, Yong
Ma, Shu‐xian
Meng, Ling‐bing
Wu, Wen‐hao
Zhang, Pei
Yang, Wei
Song, Wen‐ping
Huang, Lining
author_sort Li, Xu‐ze
collection PubMed
description BACKGROUND: Tracheal injury could cause intratracheal scar hyperplasia which in turn causes benign tracheal stenosis (TS). With the increasing use of mechanical ventilation and ventilator, the incidence of TS is increasing. However, the molecular mechanisms of TS have not been elucidated. It is significant to further explore the molecular mechanisms of TS. METHODS: The repeatability of public data was verified. Differently expressed genes (DEGs) and most significant genes were identified between TS and normal samples. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed. The comparative toxicogenomics database were analyzed. TS patients were recruited and RT‐qPCR were performed to verify the most significant genes. RESULTS: There exist strong correlations among samples of TS and normal group. There was a total of 194 DEGs, including 61 downregulated DEGs and 133 upregulated DEGs. GO were significantly enriched in mitotic nuclear division, cell cycle, and cell division. Analysis of KEGG indicated that the top pathways were cell cycle, and p53 pathway. MKI67(OMIM:176741), CCNB1(OMIM:123836), and CCNB2(OMIM:602755) were identified as the most significant genes of TS, and validated by the clinical samples. CONCLUSION: Bioinformatics methods might be useful method to explore the mechanisms of TS. In addition, MKI67, CCNB1, and CCNB2 might be the most significant genes of TS.
format Online
Article
Text
id pubmed-7284051
institution National Center for Biotechnology Information
language English
publishDate 2020
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-72840512020-06-11 Bioinformatics analysis and verification of gene targets for benign tracheal stenosis Li, Xu‐ze Wang, Zi‐chen Qiu, Yong Ma, Shu‐xian Meng, Ling‐bing Wu, Wen‐hao Zhang, Pei Yang, Wei Song, Wen‐ping Huang, Lining Mol Genet Genomic Med Original Articles BACKGROUND: Tracheal injury could cause intratracheal scar hyperplasia which in turn causes benign tracheal stenosis (TS). With the increasing use of mechanical ventilation and ventilator, the incidence of TS is increasing. However, the molecular mechanisms of TS have not been elucidated. It is significant to further explore the molecular mechanisms of TS. METHODS: The repeatability of public data was verified. Differently expressed genes (DEGs) and most significant genes were identified between TS and normal samples. Enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) were analyzed. The comparative toxicogenomics database were analyzed. TS patients were recruited and RT‐qPCR were performed to verify the most significant genes. RESULTS: There exist strong correlations among samples of TS and normal group. There was a total of 194 DEGs, including 61 downregulated DEGs and 133 upregulated DEGs. GO were significantly enriched in mitotic nuclear division, cell cycle, and cell division. Analysis of KEGG indicated that the top pathways were cell cycle, and p53 pathway. MKI67(OMIM:176741), CCNB1(OMIM:123836), and CCNB2(OMIM:602755) were identified as the most significant genes of TS, and validated by the clinical samples. CONCLUSION: Bioinformatics methods might be useful method to explore the mechanisms of TS. In addition, MKI67, CCNB1, and CCNB2 might be the most significant genes of TS. John Wiley and Sons Inc. 2020-04-20 /pmc/articles/PMC7284051/ /pubmed/32309912 http://dx.doi.org/10.1002/mgg3.1245 Text en © 2020 The Authors. Molecular Genetics & Genomic Medicine published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Original Articles
Li, Xu‐ze
Wang, Zi‐chen
Qiu, Yong
Ma, Shu‐xian
Meng, Ling‐bing
Wu, Wen‐hao
Zhang, Pei
Yang, Wei
Song, Wen‐ping
Huang, Lining
Bioinformatics analysis and verification of gene targets for benign tracheal stenosis
title Bioinformatics analysis and verification of gene targets for benign tracheal stenosis
title_full Bioinformatics analysis and verification of gene targets for benign tracheal stenosis
title_fullStr Bioinformatics analysis and verification of gene targets for benign tracheal stenosis
title_full_unstemmed Bioinformatics analysis and verification of gene targets for benign tracheal stenosis
title_short Bioinformatics analysis and verification of gene targets for benign tracheal stenosis
title_sort bioinformatics analysis and verification of gene targets for benign tracheal stenosis
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7284051/
https://www.ncbi.nlm.nih.gov/pubmed/32309912
http://dx.doi.org/10.1002/mgg3.1245
work_keys_str_mv AT lixuze bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT wangzichen bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT qiuyong bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT mashuxian bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT menglingbing bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT wuwenhao bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT zhangpei bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT yangwei bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT songwenping bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis
AT huanglining bioinformaticsanalysisandverificationofgenetargetsforbenigntrachealstenosis