ArticleMedical science monitor : international medical journal of experimental and clinical research2019
Identification of Pivotal Genes and Pathways in Osteoarthritic Degenerative Meniscal Lesions via Bioinformatics Analysis of the GSE52042 Dataset.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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8 citing papers in PubMed, 36 citations in OpenAlex.
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- Paeoniflorin, the Main Monomer Component of Paeonia lactiflora, Exhibits Anti-inflammatory Properties in Osteoarthritis Synovial Inflammation.Chinese journal of integrative medicine · 2024Article
- TPX2 upregulates MMP13 to promote the progression of lipopolysaccharide-induced osteoarthritis.PeerJ · 2024Article
- Screening crucial lncRNAs and genes in osteoarthritis by integrated analysis.Advances in rheumatology (London, England) · 2023Article
- A Study on the Potential Mechanism of Shujin Dingtong Recipe against Osteoarthritis Based on Network Pharmacology and Molecular Docking.Computational and mathematical methods in medicine · 2022Article
- Long-term dynamic compression enhancement TGF-β3-induced chondrogenesis in bovine stem cells: a gene expression analysis.BMC genomic data · 2021Article
- Identification of Novel Targets of Knee Osteoarthritis Shared by Cartilage and Synovial Tissue.International journal of molecular sciences · 2020Article
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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 AND 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.
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