Cargando…
Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data
Osteoarthritis (OA) is the most prevalent chronic degenerative disease that affects the health of the elderly. The present study aimed to identify significant genes involved in OA via bioinformatics analysis. A gene expression dataset (GSE104793) was downloaded from the Gene Expression Omnibus. Bioi...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8593859/ https://www.ncbi.nlm.nih.gov/pubmed/34815758 http://dx.doi.org/10.3892/etm.2021.10928 |
_version_ | 1784599846407110656 |
---|---|
author | Liang, Fan Peng, Le Ma, Yong-Gang Hu, Wei Zhang, Wei-Bing Deng, Ming Li, Ya-Ming |
author_facet | Liang, Fan Peng, Le Ma, Yong-Gang Hu, Wei Zhang, Wei-Bing Deng, Ming Li, Ya-Ming |
author_sort | Liang, Fan |
collection | PubMed |
description | Osteoarthritis (OA) is the most prevalent chronic degenerative disease that affects the health of the elderly. The present study aimed to identify significant genes involved in OA via bioinformatics analysis. A gene expression dataset (GSE104793) was downloaded from the Gene Expression Omnibus. Bioinformatics analysis was then performed in order to identify differentially expressed genes (DEGs) between untreated chondrocytes and chondrocytes cultured with interleukin-1β (IL-1β) for 24 h. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using Metascape. A protein-protein interaction network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes. Gene set enrichment analysis (GSEA) was performed using GSEA software. Furthermore, chondrocytes were extracted and treated with IL-1β (10 ng/ml) for 24 h, and reverse-transcription quantitative PCR was used to confirm differential expression of hub genes. Patient samples were also collected to verify the bioinformatic analysis results. Based on the cut-off criteria used for determination of the DEGs, a total of 844 DEGs, including 498 upregulated and 346 downregulated DEGs, were identified. The DEGs were mainly enriched in the GO terms and KEGG pathways ‘inflammatory response’, ‘negative regulation of cell proliferation’, ‘ossification’, ‘taxis’, ‘blood vessel morphogenesis’, ‘extracellular structure organization’, ‘mitotic cell cycle process’ and ‘TNF signaling pathway’. The majority of the PCR results, namely the differential expression of kininogen 2, complement C3, cyclin B1, cell division cycle 20, cyclin A2, 1-phosphatidylinositol 4-kinase, BUB1 mitotic checkpoint serine/threonine kinase, kinesin family member 11, cyclin B2 and BUB1 mitotic checkpoint serine/threonine kinase B were consistent with the bioinformatics results. Collectively, the present observations provided a regulation network of IL-1β-stimulated chondrocytes, which may provide potential targets of OA therapy. |
format | Online Article Text |
id | pubmed-8593859 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-85938592021-11-22 Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data Liang, Fan Peng, Le Ma, Yong-Gang Hu, Wei Zhang, Wei-Bing Deng, Ming Li, Ya-Ming Exp Ther Med Articles Osteoarthritis (OA) is the most prevalent chronic degenerative disease that affects the health of the elderly. The present study aimed to identify significant genes involved in OA via bioinformatics analysis. A gene expression dataset (GSE104793) was downloaded from the Gene Expression Omnibus. Bioinformatics analysis was then performed in order to identify differentially expressed genes (DEGs) between untreated chondrocytes and chondrocytes cultured with interleukin-1β (IL-1β) for 24 h. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using Metascape. A protein-protein interaction network of DEGs was constructed using the Search Tool for the Retrieval of Interacting Genes. Gene set enrichment analysis (GSEA) was performed using GSEA software. Furthermore, chondrocytes were extracted and treated with IL-1β (10 ng/ml) for 24 h, and reverse-transcription quantitative PCR was used to confirm differential expression of hub genes. Patient samples were also collected to verify the bioinformatic analysis results. Based on the cut-off criteria used for determination of the DEGs, a total of 844 DEGs, including 498 upregulated and 346 downregulated DEGs, were identified. The DEGs were mainly enriched in the GO terms and KEGG pathways ‘inflammatory response’, ‘negative regulation of cell proliferation’, ‘ossification’, ‘taxis’, ‘blood vessel morphogenesis’, ‘extracellular structure organization’, ‘mitotic cell cycle process’ and ‘TNF signaling pathway’. The majority of the PCR results, namely the differential expression of kininogen 2, complement C3, cyclin B1, cell division cycle 20, cyclin A2, 1-phosphatidylinositol 4-kinase, BUB1 mitotic checkpoint serine/threonine kinase, kinesin family member 11, cyclin B2 and BUB1 mitotic checkpoint serine/threonine kinase B were consistent with the bioinformatics results. Collectively, the present observations provided a regulation network of IL-1β-stimulated chondrocytes, which may provide potential targets of OA therapy. D.A. Spandidos 2022-01 2021-10-27 /pmc/articles/PMC8593859/ /pubmed/34815758 http://dx.doi.org/10.3892/etm.2021.10928 Text en Copyright: © Liang et al. https://creativecommons.org/licenses/by-nc-nd/4.0/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 Liang, Fan Peng, Le Ma, Yong-Gang Hu, Wei Zhang, Wei-Bing Deng, Ming Li, Ya-Ming Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data |
title | Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data |
title_full | Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data |
title_fullStr | Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data |
title_full_unstemmed | Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data |
title_short | Bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with IL-1β using microarray data |
title_sort | bioinformatics analysis and experimental validation of differentially expressed genes in mouse articular chondrocytes treated with il-1β using microarray data |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8593859/ https://www.ncbi.nlm.nih.gov/pubmed/34815758 http://dx.doi.org/10.3892/etm.2021.10928 |
work_keys_str_mv | AT liangfan bioinformaticsanalysisandexperimentalvalidationofdifferentiallyexpressedgenesinmousearticularchondrocytestreatedwithil1busingmicroarraydata AT pengle bioinformaticsanalysisandexperimentalvalidationofdifferentiallyexpressedgenesinmousearticularchondrocytestreatedwithil1busingmicroarraydata AT mayonggang bioinformaticsanalysisandexperimentalvalidationofdifferentiallyexpressedgenesinmousearticularchondrocytestreatedwithil1busingmicroarraydata AT huwei bioinformaticsanalysisandexperimentalvalidationofdifferentiallyexpressedgenesinmousearticularchondrocytestreatedwithil1busingmicroarraydata AT zhangweibing bioinformaticsanalysisandexperimentalvalidationofdifferentiallyexpressedgenesinmousearticularchondrocytestreatedwithil1busingmicroarraydata AT dengming bioinformaticsanalysisandexperimentalvalidationofdifferentiallyexpressedgenesinmousearticularchondrocytestreatedwithil1busingmicroarraydata AT liyaming bioinformaticsanalysisandexperimentalvalidationofdifferentiallyexpressedgenesinmousearticularchondrocytestreatedwithil1busingmicroarraydata |