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Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis
The present study aimed to identify key genes and pathways associated with spinal cord injury (SCI) and subsequently investigate possible therapeutic targets for the condition. The array data of GSE20907 was downloaded from the Gene Expression Omnibus database and 24 gene chips, including 3-day, 4-d...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5646972/ https://www.ncbi.nlm.nih.gov/pubmed/28731189 http://dx.doi.org/10.3892/mmr.2017.7060 |
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author | Zhu, Zonghao Shen, Qiang Zhu, Liang Wei, Xiaokang |
author_facet | Zhu, Zonghao Shen, Qiang Zhu, Liang Wei, Xiaokang |
author_sort | Zhu, Zonghao |
collection | PubMed |
description | The present study aimed to identify key genes and pathways associated with spinal cord injury (SCI) and subsequently investigate possible therapeutic targets for the condition. The array data of GSE20907 was downloaded from the Gene Expression Omnibus database and 24 gene chips, including 3-day, 4-day, 1-week, 2-week and 1-month post-SCI together with control propriospinal neurons, were used for the analysis. The raw data was normalized and then the differentially expressed genes (DEGs) in the (A) 2-week post-SCI group vs. control group, (B) 1-month post-SCI group vs. control group, (C) 1-month and 2-week post-SCI group vs. control group, and (D) all post-SCI groups vs. all control groups, were analyzed with a limma package. Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for DEGs were performed. Cluster analysis was performed using ClusterOne plugins. All the DEGs identified were associated with immune and inflammatory responses. Signal transducer and activator of transcription 3 (STAT3), erb-B2 receptor tyrosine kinase 4 (ERBB4) and cytochrome B-245, α polypeptide (CYBA) were in the network diagrams of (A), (C) and (D), respectively. The enrichment analysis of DEGs identified in all samples demonstrated that the DEGs were also enriched in the chemokine signaling pathway (enriched in STAT3) and the high-affinity immunoglobulin E receptor (FcεRI) signaling pathway [enriched in proto-oncogene, src family tyrosine kinase (LYN)]. Immune and inflammatory responses serve significant roles in SCI. STAT3, ERBB4 and CYBA may be key genes associated with SCI at certain stages. Furthermore, STAT3 and LYN may be involved in the development of SCI via the chemokine and FcεRI signaling pathways, respectively. |
format | Online Article Text |
id | pubmed-5646972 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-56469722017-10-24 Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis Zhu, Zonghao Shen, Qiang Zhu, Liang Wei, Xiaokang Mol Med Rep Articles The present study aimed to identify key genes and pathways associated with spinal cord injury (SCI) and subsequently investigate possible therapeutic targets for the condition. The array data of GSE20907 was downloaded from the Gene Expression Omnibus database and 24 gene chips, including 3-day, 4-day, 1-week, 2-week and 1-month post-SCI together with control propriospinal neurons, were used for the analysis. The raw data was normalized and then the differentially expressed genes (DEGs) in the (A) 2-week post-SCI group vs. control group, (B) 1-month post-SCI group vs. control group, (C) 1-month and 2-week post-SCI group vs. control group, and (D) all post-SCI groups vs. all control groups, were analyzed with a limma package. Gene Ontology annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses for DEGs were performed. Cluster analysis was performed using ClusterOne plugins. All the DEGs identified were associated with immune and inflammatory responses. Signal transducer and activator of transcription 3 (STAT3), erb-B2 receptor tyrosine kinase 4 (ERBB4) and cytochrome B-245, α polypeptide (CYBA) were in the network diagrams of (A), (C) and (D), respectively. The enrichment analysis of DEGs identified in all samples demonstrated that the DEGs were also enriched in the chemokine signaling pathway (enriched in STAT3) and the high-affinity immunoglobulin E receptor (FcεRI) signaling pathway [enriched in proto-oncogene, src family tyrosine kinase (LYN)]. Immune and inflammatory responses serve significant roles in SCI. STAT3, ERBB4 and CYBA may be key genes associated with SCI at certain stages. Furthermore, STAT3 and LYN may be involved in the development of SCI via the chemokine and FcεRI signaling pathways, respectively. D.A. Spandidos 2017-10 2017-07-21 /pmc/articles/PMC5646972/ /pubmed/28731189 http://dx.doi.org/10.3892/mmr.2017.7060 Text en Copyright: © Zhu et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , 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 | Articles Zhu, Zonghao Shen, Qiang Zhu, Liang Wei, Xiaokang Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis |
title | Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis |
title_full | Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis |
title_fullStr | Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis |
title_full_unstemmed | Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis |
title_short | Identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis |
title_sort | identification of pivotal genes and pathways for spinal cord injury via bioinformatics analysis |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5646972/ https://www.ncbi.nlm.nih.gov/pubmed/28731189 http://dx.doi.org/10.3892/mmr.2017.7060 |
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