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中国医药导刊 ›› 2023, Vol. 25 ›› Issue (5): 515-521.

• 临床医药 • 上一篇    下一篇

骨不连基因表达谱的差异基因表达及免疫细胞浸润分析

熊伟1, 程凌1*, 邵子晨2, 王高1, 李松1, 陆华龙1   

  1. 1.南昌市洪都中医院, 江西 南昌 330000;
    2.江西中医药大学临床医学院, 江西 南昌 330004
  • 收稿日期:2023-03-02 修回日期:2023-03-20 出版日期:2023-05-28 发布日期:2023-05-28
  • 基金资助:
    江西省重点研发计划项目(项目编号:20202BBGL73004;项目名称:J型针刀推切法治疗屈指肌腱狭窄性腱鞘炎的临床疗效研究);南昌市科技支撑计划项目(项目编号:洪科字〔2022〕146号;项目名称:TRPV4通路,针刀治疗盘源性腰痛关键因素?一项基于大鼠模型的实验室研究);江西省中医药中青年骨干人才(第四批)培养计划(项目编号:赣中医药科教字〔2022〕7号;项目名称:江西省中医药中青年骨干人才)

Differential Gene Expression and Immune Cell Infiltration Analysis of Bone Nonunion Gene Expression Profile

  1. 1.Nanchang Hongdu Hospital of Traditional Chinese Medicine, Jiangxi Nanchang 330000, China;
    2.School of Clinical Medicine, Jiangxi University of Traditional Chinese Medicine, Jiangxi Nanchang 330004, China
  • Received:2023-03-02 Revised:2023-03-20 Online:2023-05-28 Published:2023-05-28

摘要: 目的:运用综合生物信息学识别与骨不连相关的关键基因,并分析免疫细胞在骨不连相关微环境中的作用。方法:通过GEO公共数据库获取骨不连(GSE93138)的基因表达数据集。在鉴定骨不连的差异表达基因后,利用Cytoscape软件构建蛋白互作(PPI)网络,识别关键基因。最后在R语言的基础上实现GO功能富集、KEGG通路富集及免疫细胞浸润的研究。结果:本研究在骨不连中鉴定了1774个差异基因(892个上调基因和882个下调基因),其中26个是关键基因,其中排名前6的基因为LCK、CHD4、MTA3、MTA1、MTA2和FYN。GO和KEGG途径富集分析表明,这些基因在免疫、炎症和骨代谢途径中显著富集。免疫细胞浸润分析显示,活化树突状细胞、巨噬细胞、肥大细胞、中性粒细胞、辅助性T细胞17(Th17)在骨不连中呈现高表达。结论:本研究通过生物信息学确定了与骨不连相关的26个关键基因,其中排名前6的基因为LCK、CHD4、MTA3、MTA1、MTA2和FYN。强调了活化树突状细胞、巨噬细胞、肥大细胞、中性粒细胞和辅助性T细胞17等免疫细胞在骨不连发病机制中的重要性。本研究结果将为骨不连的预防、诊断和治疗的研究提供新的思路,但仍需要进一步的体内外实验验证与支持。

关键词: font-size:medium, ">骨不连;生物信息学;差异表达基因;关键基因;免疫细胞

Abstract: Objective: To use comprehensive bioinformatics to identify the key genes related to bone nonunion, and analyze the role of immune cells in the microenvironment related to bone nonunion. Methods: The gene expression data set of bone nonunion (GSE93138) was obtained through the GEO public database. After identifying the differentially expressed genes of bone nonunion, the protein interaction (PPI) network was constructed using Cytoscape software to identify the key genes. Finally, on the basis of R language, the research of GO function enrichment, KEGG pathway enrichment and immune cell infiltration was realized. Results: In this study, 1774 differential genes (892 up-regulated genes and 882 down-regulated genes) were identified in bone nonunion, of which 26 were key genes, and the top 6 genes were LCK, CHD4, MTA3, MTA1, MTA2 and FYN. Enrichment analysis of GO and KEGG pathways showed that these genes were significantly enriched in immune, inflammatory and bone metabolism pathways. Immunocyte infiltration analysis showed that activated dendritic cells, macrophages, mast cells, neutrophils and helper T cells 17 showed high expression in bone nonunion. Conclusion: This study identified 26 key genes related to bone nonunion through bioinformatics, among which the top 6 genes are LCK, CHD4, MTA3, MTA1, MTA2 and FYN. The importance of activated dendritic cells, macrophages, mast cells, neutrophils and helper T cells 17 in the pathogenesis of bone nonunion was emphasized. The results of this study will provide new insights into the prevention, diagnosis and treatment of bone nonunion. However, it still needs further validation and support in vitro and in vivo.

Key words: font-size:medium, ">Bone nonunion; Bioinformatics; Differentially expressed genes; Hub genes; Immune cell

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