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Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods

The present study aimed to explore the molecular mechanisms underlying the development of thoracic spinal cord injury (SCI). The gene expression profile of GSE20907, which included 12 thoracic non-injured spinal cord control samples and 12 thoracic transected spinal cord samples at different stages...

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Autores principales: WANG, WEIGUO, LIU, RONGJUN, XU, ZHANWANG, NIU, XIUFENG, MAO, ZHAOHU, MENG, QINGXI, CAO, XUECHENG
Formato: Online Artículo Texto
Lenguaje:English
Publicado: D.A. Spandidos 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4758289/
https://www.ncbi.nlm.nih.gov/pubmed/26497545
http://dx.doi.org/10.3892/mmr.2015.4442
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author WANG, WEIGUO
LIU, RONGJUN
XU, ZHANWANG
NIU, XIUFENG
MAO, ZHAOHU
MENG, QINGXI
CAO, XUECHENG
author_facet WANG, WEIGUO
LIU, RONGJUN
XU, ZHANWANG
NIU, XIUFENG
MAO, ZHAOHU
MENG, QINGXI
CAO, XUECHENG
author_sort WANG, WEIGUO
collection PubMed
description The present study aimed to explore the molecular mechanisms underlying the development of thoracic spinal cord injury (SCI). The gene expression profile of GSE20907, which included 12 thoracic non-injured spinal cord control samples and 12 thoracic transected spinal cord samples at different stages of SCI, was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package in R/Bioconductor. DEG-associated pathways were analyzed using the Kyoto encyclopedia of genes and genomes database. A protein-protein interaction (PPI) network was constructed and transcription factors (TFs) were predicted using cytoscape. Compared with the control samples, there were 1,942, 396, 188 and 396 DEGs identified at day 3 (d3), week 1 (wk1), wk2 and month 1 (m1), respectively. Cluster analysis indicated that the DEGs at m1 were similar to those in the control group. Downregulated DEGs were enriched in nervous system disease pathways, such as Parkinson's disease. Upregulated DEGs were enriched in immune response-associated pathways, such as Fc γ R-mediated phagocytosis at early stages (d3 and wk1). Upregulated DEGs were enriched in pathways associated with cancer and pyrimidine metabolism at wk2 and m1, respectively. In the PPI network, nodes including RAC2, CD4, STAT3 and JUN were identified. Furthermore, ATF3, JUN and EGR1 were identified as TFs associated with SCI. In conclusion, the results of the present study showed that the number of DEGs decreased in a time-dependent manner following SCI. OLIG1, ATF3 and JUN may represent SCI regeneration-associated genes. Immune-associated inflammation was shown to be important in SCI, and SCI exhibits causal associations with other diseases, including cardiovascular disease and cancers. The present study provided novel insight into the molecular mechanisms of SCI regeneration, which may aid in the development of strategies to enhance recovery following SCI.
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spelling pubmed-47582892016-03-04 Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods WANG, WEIGUO LIU, RONGJUN XU, ZHANWANG NIU, XIUFENG MAO, ZHAOHU MENG, QINGXI CAO, XUECHENG Mol Med Rep Articles The present study aimed to explore the molecular mechanisms underlying the development of thoracic spinal cord injury (SCI). The gene expression profile of GSE20907, which included 12 thoracic non-injured spinal cord control samples and 12 thoracic transected spinal cord samples at different stages of SCI, was obtained from the Gene Expression Omnibus database. Differentially expressed genes (DEGs) were identified using the limma package in R/Bioconductor. DEG-associated pathways were analyzed using the Kyoto encyclopedia of genes and genomes database. A protein-protein interaction (PPI) network was constructed and transcription factors (TFs) were predicted using cytoscape. Compared with the control samples, there were 1,942, 396, 188 and 396 DEGs identified at day 3 (d3), week 1 (wk1), wk2 and month 1 (m1), respectively. Cluster analysis indicated that the DEGs at m1 were similar to those in the control group. Downregulated DEGs were enriched in nervous system disease pathways, such as Parkinson's disease. Upregulated DEGs were enriched in immune response-associated pathways, such as Fc γ R-mediated phagocytosis at early stages (d3 and wk1). Upregulated DEGs were enriched in pathways associated with cancer and pyrimidine metabolism at wk2 and m1, respectively. In the PPI network, nodes including RAC2, CD4, STAT3 and JUN were identified. Furthermore, ATF3, JUN and EGR1 were identified as TFs associated with SCI. In conclusion, the results of the present study showed that the number of DEGs decreased in a time-dependent manner following SCI. OLIG1, ATF3 and JUN may represent SCI regeneration-associated genes. Immune-associated inflammation was shown to be important in SCI, and SCI exhibits causal associations with other diseases, including cardiovascular disease and cancers. The present study provided novel insight into the molecular mechanisms of SCI regeneration, which may aid in the development of strategies to enhance recovery following SCI. D.A. Spandidos 2015-12 2015-10-14 /pmc/articles/PMC4758289/ /pubmed/26497545 http://dx.doi.org/10.3892/mmr.2015.4442 Text en Copyright: © Wang 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
WANG, WEIGUO
LIU, RONGJUN
XU, ZHANWANG
NIU, XIUFENG
MAO, ZHAOHU
MENG, QINGXI
CAO, XUECHENG
Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods
title Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods
title_full Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods
title_fullStr Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods
title_full_unstemmed Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods
title_short Further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods
title_sort further insight into molecular mechanism underlying thoracic spinal cord injury using bioinformatics methods
topic Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4758289/
https://www.ncbi.nlm.nih.gov/pubmed/26497545
http://dx.doi.org/10.3892/mmr.2015.4442
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