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Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset
BACKGROUND: To better understand the process of osteoarthritic degenerative meniscal lesions (DMLs) formation, this study analyzed the dataset GSE52042 using bioinformatics methods to identify the pivotal genes and pathways related to osteoarthritic DMLs. MATERIAL/METHODS: The GSE52042 dataset, comp...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
International Scientific Literature, Inc.
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884941/ https://www.ncbi.nlm.nih.gov/pubmed/31758856 http://dx.doi.org/10.12659/MSM.920636 |
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author | Huan, Xu Jinhe, Ying Rongzong, Zheng |
author_facet | Huan, Xu Jinhe, Ying Rongzong, Zheng |
author_sort | Huan, Xu |
collection | PubMed |
description | BACKGROUND: To better understand the process of osteoarthritic degenerative meniscal lesions (DMLs) formation, this study analyzed the dataset GSE52042 using bioinformatics methods to identify the pivotal genes and pathways related to osteoarthritic DMLs. MATERIAL/METHODS: The GSE52042 dataset, comprising diseased meniscus samples and healthier meniscus samples, was downloaded and the differentially-expressed genes (DEGs) were extracted. The reactome pathways assessment and functional analysis were performed using the “ClusterProfiler” package and “ReactomePA” package of Bioconductor. The protein–protein interaction network was constructed, followed by the extraction of hub genes and modules. RESULTS: A set of 154 common DEGs, including 64 upregulated DEGs and 90 downregulated DEGs, were obtained. GO analysis suggested that the DEGs primarily participated in positive regulation of the mitotic cell cycle and extracellular matrix organization. Reactome pathway analysis showed that the DEGs were predominantly enriched in TP53, which regulates transcription of genes involved in G2 cell cycle arrest and extracellular matrix organization. The top 10 hub genes were TYMS, AURKA, CENPN, NUSAP1, CENPM, TPX2, CDK1, UBE2C, BIRC5, and CCNB1. The genes in the 2 modules were primarily associated with M Phase and keratan sulfate degradation. CONCLUSIONS: A series of pivotal genes and reactome pathways were identified elucidate the molecular mechanisms involved in the formation of osteoarthritic DMLs and to discover potential therapeutic targets. |
format | Online Article Text |
id | pubmed-6884941 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | International Scientific Literature, Inc. |
record_format | MEDLINE/PubMed |
spelling | pubmed-68849412019-12-04 Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset Huan, Xu Jinhe, Ying Rongzong, Zheng Med Sci Monit Molecular Biology BACKGROUND: To better understand the process of osteoarthritic degenerative meniscal lesions (DMLs) formation, this study analyzed the dataset GSE52042 using bioinformatics methods to identify the pivotal genes and pathways related to osteoarthritic DMLs. MATERIAL/METHODS: The GSE52042 dataset, comprising diseased meniscus samples and healthier meniscus samples, was downloaded and the differentially-expressed genes (DEGs) were extracted. The reactome pathways assessment and functional analysis were performed using the “ClusterProfiler” package and “ReactomePA” package of Bioconductor. The protein–protein interaction network was constructed, followed by the extraction of hub genes and modules. RESULTS: A set of 154 common DEGs, including 64 upregulated DEGs and 90 downregulated DEGs, were obtained. GO analysis suggested that the DEGs primarily participated in positive regulation of the mitotic cell cycle and extracellular matrix organization. Reactome pathway analysis showed that the DEGs were predominantly enriched in TP53, which regulates transcription of genes involved in G2 cell cycle arrest and extracellular matrix organization. The top 10 hub genes were TYMS, AURKA, CENPN, NUSAP1, CENPM, TPX2, CDK1, UBE2C, BIRC5, and CCNB1. The genes in the 2 modules were primarily associated with M Phase and keratan sulfate degradation. CONCLUSIONS: A series of pivotal genes and reactome pathways were identified elucidate the molecular mechanisms involved in the formation of osteoarthritic DMLs and to discover potential therapeutic targets. International Scientific Literature, Inc. 2019-11-23 /pmc/articles/PMC6884941/ /pubmed/31758856 http://dx.doi.org/10.12659/MSM.920636 Text en © Med Sci Monit, 2019 This work is licensed under Creative Common Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0 (https://creativecommons.org/licenses/by-nc-nd/4.0/) ) |
spellingShingle | Molecular Biology Huan, Xu Jinhe, Ying Rongzong, Zheng Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset |
title | Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset |
title_full | Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset |
title_fullStr | Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset |
title_full_unstemmed | Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset |
title_short | Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset |
title_sort | identification of pivotal genes and pathways in osteoarthritic degenerative meniscal lesions via bioinformatics analysis of the gse52042 dataset |
topic | Molecular Biology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6884941/ https://www.ncbi.nlm.nih.gov/pubmed/31758856 http://dx.doi.org/10.12659/MSM.920636 |
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