引用本文: |
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王艺静,高文霞,石凯燕,等.IFN-γ调节间充质干细胞免疫应答的分子机制[J].同济大学学报(医学版),2020,41(6):683-690. [点击复制]
- WANG Yi-jing,GAO Wen-xia,SHI Kai-yan,et al.The mechanism underlying the immune response of mesenchymal stem cellsstimulated by IFN-γ[J].同济大学学报(医学版),2020,41(6):683-690. [点击复制]
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摘要: |
目的通过基因芯片数据,比较不同浓度的炎症因子IFN-γ预处理对间充质干细胞(mesenchymal stem/stromal cells, MSCs)免疫应答的影响。方法从GEO数据库下载GSE77814骨髓间充质干细胞经不同浓度的IFN-γ预处理及未处理的基因表达数据,借助GEO2R分析差异基因(differentially expressed genes, DEGs)。随后对差异基因进行GO富集分析(DAVID数据库)、KEGG通路富集分析(KEGG Mapper/GSEA)、蛋白分析(Uniprot数据库)、并构建差异基因蛋白质-蛋白质相互作用关系(PPI),筛选hub基因。结果IFN-γ低浓度组与未处理组相比,共筛选出152个差异基因(以下简称IFN-γ-L DEGs),其中133个为上调基因,19个为下调基因。IFN-γ高浓度组与未处理组相比,共筛选出648个差异基因(以下简称IFN-γ-H DEGs),其中431个为上调基因,217个为下调基因。差异基因多与免疫反应、炎症、病毒反应相关。IFN-γ高浓度处理比低浓度处理上调表达更多趋化因子和抑炎因子。IFN-γ-H DEGs同IFN-γ-L DEGs在GO富集分析、KEGG通路富集分析、蛋白分析上的结果接近,但IFN-γ-H DEGs在代谢通路上富集显著。结论炎症因子IFN-γ对MSCs的转录组具有较大影响,尤其是对免疫应答相关的基因,并且与处理浓度有密切关系。此外,MSCs行使免疫抑制能力可能需要较高浓度的炎症因子授权。 |
关键词: 间充质干细胞 免疫应答 免疫调节 IFN-γ GEO数据库 |
DOI:10.16118/j.1008-0392.2020.06.002 |
投稿时间:2020-07-17 |
基金项目:国家自然科学基金(81601975);科技部重点研发计划课题(2016YFA0100801) |
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The mechanism underlying the immune response of mesenchymal stem cellsstimulated by IFN-γ |
WANG Yi-jing,GAO Wen-xia,SHI Kai-yan,SHI Jia-yu,SUN Yi |
(Tongji University School of Medicine, Shanghai 200092, China;Tongji University School of Medicine, Shanghai 200092, China; Stem Cell Translational Research Center, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China) |
Abstract: |
ObjectiveTo investigate the effect of IFN-γ stimulation on immune response of mesenchymal stem/stromal cells(MSCs) and its mechanism. MethodsThe gene expression data of GSE77814 MSCs primed by IFN-γ of different concentrations were downloaded from GEO database and the differentially expressed genes(DEGs) were obtained through GEO2R. DEGs were further submitted to enrichment analysis for GO function(DAVID database) and KEGG signaling pathway(KEGG Mapper/GSEA); and Uniprot database for protein analysis. The PPI networks were constructed and key target genes were obtained. ResultsA total of 152 DEGs, including 133 up-regulated genes and 19 down-regulated genes, were selected by comparing with the control group(IFN-γ-L DEGs). A total of 648 DEGs, including 431 up-regulated genes and 217 down-regulated genes, were selected by comparing the group primed with high concentration IFN-γ(IFN-γ-H DEGs). These DEGs were mainly involved in immune response, inflammation and virus response. There were more genes related to chemokines and anti-immune cytokines in IFN-γ-H DEGs. DEGs obtained from both groups were similar in enrichment analysis for GO function and KEGG signaling pathway, as well as protein analysis. It is worth noting that metabolism pathway was highly enriched in IFN-γ-H DEGs. ConclusionInflammatory cytokines IFN-γ has a great impact on the transcriptome of MSCs, especially for the immune related genes. The influence was also associated with concentration of IFN-γ. Besides, the inflammatory stimuli with high concentration may be necessary for the activation of immune-suppressive ability of MSCs. |
Key words: mesenchymal stem/stromal cells immune response immune modulation IFN-γ GEO database |