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Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases
Spinal cord injury (SCI) and ankylosing spondylitis (AS) are common inflammatory diseases in spine surgery. However, it is a project where the relationship between the two diseases is ambiguous and the efficiency of drug discovery is limited. Therefore, the study aimed to investigate new drug therap...
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/PMC8914062/ https://www.ncbi.nlm.nih.gov/pubmed/35281834 http://dx.doi.org/10.3389/fgene.2022.799970 |
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author | Wang, Chenfeng Ma, Hongdao Wu, Weiqing Lu, Xuhua |
author_facet | Wang, Chenfeng Ma, Hongdao Wu, Weiqing Lu, Xuhua |
author_sort | Wang, Chenfeng |
collection | PubMed |
description | Spinal cord injury (SCI) and ankylosing spondylitis (AS) are common inflammatory diseases in spine surgery. However, it is a project where the relationship between the two diseases is ambiguous and the efficiency of drug discovery is limited. Therefore, the study aimed to investigate new drug therapies for SCI and AS. First, text mining was used to obtain the interacting genes related to SCI and AS, and then, the functional analysis was conducted. Protein–protein interaction (PPI) networks were constructed by STRING online and Cytoscape software to identify hub genes. Last, hub genes and potential drugs were performed after undergoing drug–gene interaction analysis, and MicroRNA and transcription factors regulatory networks were also analyzed. Two hundred five genes common to “SCI” and “AS” identified by text mining were enriched in inflammatory responses. PPI network analysis showed that 30 genes constructed two significant modules. Ultimately, nine (SST, VWF, IL1B, IL6, CXCR4, VEGFA, SERPINE1, FN1, and PROS1) out of 30 genes could be targetable by a total of 13 drugs. In conclusion, the novel core genes contribute to a novel insight for latent functional mechanisms and present potential prognostic indicators and therapeutic targets in SCI and AS. |
format | Online Article Text |
id | pubmed-8914062 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-89140622022-03-12 Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases Wang, Chenfeng Ma, Hongdao Wu, Weiqing Lu, Xuhua Front Genet Genetics Spinal cord injury (SCI) and ankylosing spondylitis (AS) are common inflammatory diseases in spine surgery. However, it is a project where the relationship between the two diseases is ambiguous and the efficiency of drug discovery is limited. Therefore, the study aimed to investigate new drug therapies for SCI and AS. First, text mining was used to obtain the interacting genes related to SCI and AS, and then, the functional analysis was conducted. Protein–protein interaction (PPI) networks were constructed by STRING online and Cytoscape software to identify hub genes. Last, hub genes and potential drugs were performed after undergoing drug–gene interaction analysis, and MicroRNA and transcription factors regulatory networks were also analyzed. Two hundred five genes common to “SCI” and “AS” identified by text mining were enriched in inflammatory responses. PPI network analysis showed that 30 genes constructed two significant modules. Ultimately, nine (SST, VWF, IL1B, IL6, CXCR4, VEGFA, SERPINE1, FN1, and PROS1) out of 30 genes could be targetable by a total of 13 drugs. In conclusion, the novel core genes contribute to a novel insight for latent functional mechanisms and present potential prognostic indicators and therapeutic targets in SCI and AS. Frontiers Media S.A. 2022-02-25 /pmc/articles/PMC8914062/ /pubmed/35281834 http://dx.doi.org/10.3389/fgene.2022.799970 Text en Copyright © 2022 Wang, Ma, Wu and Lu. 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 Wang, Chenfeng Ma, Hongdao Wu, Weiqing Lu, Xuhua Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases |
title | Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases |
title_full | Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases |
title_fullStr | Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases |
title_full_unstemmed | Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases |
title_short | Drug Discovery in Spinal Cord Injury With Ankylosing Spondylitis Identified by Text Mining and Biomedical Databases |
title_sort | drug discovery in spinal cord injury with ankylosing spondylitis identified by text mining and biomedical databases |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8914062/ https://www.ncbi.nlm.nih.gov/pubmed/35281834 http://dx.doi.org/10.3389/fgene.2022.799970 |
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