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Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics

Diabetic ulcers (DUs) are characterised by a high incidence and disability rate. However, its pathogenesis remains elusive. Thus, a deep understanding of the underlying mechanisms for the pathogenesis of DUs has vital implications. The weighted gene co‐expression network analysis was performed on th...

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Autores principales: Zhang, Zhan, Zhang, Ying, Yang, Dan, Luo, Yue, Luo, Ying, Ru, Yi, Song, Jiankun, Fei, Xiaoya, Chen, Yiran, Li, Bin, Jiang, Jingsi, Kuai, Le
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Blackwell Publishing Ltd 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885479/
https://www.ncbi.nlm.nih.gov/pubmed/36181454
http://dx.doi.org/10.1111/iwj.13900
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author Zhang, Zhan
Zhang, Ying
Yang, Dan
Luo, Yue
Luo, Ying
Ru, Yi
Song, Jiankun
Fei, Xiaoya
Chen, Yiran
Li, Bin
Jiang, Jingsi
Kuai, Le
author_facet Zhang, Zhan
Zhang, Ying
Yang, Dan
Luo, Yue
Luo, Ying
Ru, Yi
Song, Jiankun
Fei, Xiaoya
Chen, Yiran
Li, Bin
Jiang, Jingsi
Kuai, Le
author_sort Zhang, Zhan
collection PubMed
description Diabetic ulcers (DUs) are characterised by a high incidence and disability rate. However, its pathogenesis remains elusive. Thus, a deep understanding of the underlying mechanisms for the pathogenesis of DUs has vital implications. The weighted gene co‐expression network analysis was performed on the main data from the Gene Expression Omnibus database. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were adopted to analyse the potential biological function of the most relevant module. Furthermore, we utilised CytoHubba and protein–protein interaction network to identify the hub genes. Finally, the hub genes were validated by animal experiments in diabetic ulcer mice models. The expression of genes from the turquoise module was found to be strongly related to DUs. GO terms, KEGG analysis showed that biological functions are closely related to immune response. The hub genes included IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1, which were higher in wounds of DUs mice than that in normal lesions. Additionally, we also demonstrated that the expression of hub genes was correlated with the immune response using immune checkpoint, immune cell infiltration, and immune scores. These data suggests that IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1 are crucial for DUs.
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spelling pubmed-98854792023-02-01 Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics Zhang, Zhan Zhang, Ying Yang, Dan Luo, Yue Luo, Ying Ru, Yi Song, Jiankun Fei, Xiaoya Chen, Yiran Li, Bin Jiang, Jingsi Kuai, Le Int Wound J Original Articles Diabetic ulcers (DUs) are characterised by a high incidence and disability rate. However, its pathogenesis remains elusive. Thus, a deep understanding of the underlying mechanisms for the pathogenesis of DUs has vital implications. The weighted gene co‐expression network analysis was performed on the main data from the Gene Expression Omnibus database. Gene Ontology (GO) terms, Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis were adopted to analyse the potential biological function of the most relevant module. Furthermore, we utilised CytoHubba and protein–protein interaction network to identify the hub genes. Finally, the hub genes were validated by animal experiments in diabetic ulcer mice models. The expression of genes from the turquoise module was found to be strongly related to DUs. GO terms, KEGG analysis showed that biological functions are closely related to immune response. The hub genes included IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1, which were higher in wounds of DUs mice than that in normal lesions. Additionally, we also demonstrated that the expression of hub genes was correlated with the immune response using immune checkpoint, immune cell infiltration, and immune scores. These data suggests that IFI35, IFIT2, MX2, OASL, RSAD2, and XAF1 are crucial for DUs. Blackwell Publishing Ltd 2022-10-01 /pmc/articles/PMC9885479/ /pubmed/36181454 http://dx.doi.org/10.1111/iwj.13900 Text en © 2022 The Authors. International Wound Journal published by Medicalhelplines.com Inc (3M) and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Original Articles
Zhang, Zhan
Zhang, Ying
Yang, Dan
Luo, Yue
Luo, Ying
Ru, Yi
Song, Jiankun
Fei, Xiaoya
Chen, Yiran
Li, Bin
Jiang, Jingsi
Kuai, Le
Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics
title Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics
title_full Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics
title_fullStr Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics
title_full_unstemmed Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics
title_short Characterisation of key biomarkers in diabetic ulcers via systems bioinformatics
title_sort characterisation of key biomarkers in diabetic ulcers via systems bioinformatics
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9885479/
https://www.ncbi.nlm.nih.gov/pubmed/36181454
http://dx.doi.org/10.1111/iwj.13900
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