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皮肌炎:免疫景观、生物标志物和潜在候选药物。

Dermatomyositis: immunological landscape, biomarkers, and potential candidate drugs.

机构信息

Department of Rheumatology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, Henan, China.

Department of Oncology, The First Affiliated Hospital of Zhengzhou University, No. 1 Jianshe East Road, Zhengzhou, 450052, China.

出版信息

Clin Rheumatol. 2021 Jun;40(6):2301-2310. doi: 10.1007/s10067-020-05568-5. Epub 2021 Jan 3.

Abstract

INTRODUCTION

Dermatomyositis (DM) is a rare inflammatory disease characterized by the invasion of the skin and muscles. Environmental, genetic, and immunological factors contribute to disease pathology. To date, no bioinformatics studies have been conducted on the potential pathogenic genes and immune cell infiltration in DM. Therefore, we aimed to identify differentially expressed genes (DEGs) and immune cells, as well as potential pathogenic genes and immune characteristics, which may be useful for the diagnosis and treatment of DM.

METHOD

GSE1551, GSE5370, GSE39454, and GSE48280 from Gene Expression Omnibus were included in our study. Limma, ClusterProfiler, and Kyoto Encyclopedia of Genes and Genomes were used to identify DEGs, Gene Ontology (GO), and perform pathway analyses, respectively. Cytoscape was used to construct the protein-protein interaction (PPI) network. Small-molecule drugs were identified using a connectivity map (CMap), and the TIMER database was used to identify infiltrating cells.

RESULTS

DEG analysis identified 12 downregulated and 163 upregulated genes. GO analysis showed that DEGs were enriched in immune-related pathways. Ten hub genes were identified from the PPI network. Additionally, CMap analysis showed that caffeic acid, sulfaphenazole, molindone, tiabendazole, and bacitracin were potential small-molecule drugs with therapeutic significance. We identified eight immune cells with differential infiltration in patients with DM and controls. Finally, we constructed a powerful diagnostic model based on memory B cells, M1, and M2 macrophages.

CONCLUSIONS

This study explored the potential molecular mechanism and immunological landscape of DM and may guide future research and treatment of DM.

KEY POINTS

• We explored the molecular mechanism and immunological landscape of dermatomyositis. • GO analysis showed that DEGs were enriched in immune-related pathways. • We predicted small-molecular drugs with potential therapeutic significance based on bioanalytical techniques. • We identified six immune cells with differential infiltration in patients with DM and controls.

摘要

简介

皮肌炎(DM)是一种罕见的炎症性疾病,其特征是皮肤和肌肉受侵。环境、遗传和免疫因素共同导致了疾病的病理过程。迄今为止,尚未有针对 DM 潜在致病基因和免疫细胞浸润的生物信息学研究。因此,我们旨在鉴定差异表达基因(DEGs)和免疫细胞,以及潜在的致病基因和免疫特征,这可能有助于 DM 的诊断和治疗。

方法

本研究纳入了基因表达综合数据库中的 GSE1551、GSE5370、GSE39454 和 GSE48280。使用 Limma、ClusterProfiler 和京都基因与基因组百科全书分别进行差异表达基因分析、基因本体论(GO)分析和通路分析。使用 Cytoscape 构建蛋白质-蛋白质相互作用(PPI)网络。使用连接图谱(CMap)鉴定小分子药物,使用 TIMER 数据库鉴定浸润细胞。

结果

DEG 分析鉴定出 12 个下调基因和 163 个上调基因。GO 分析显示 DEGs 富集于免疫相关通路。从 PPI 网络中鉴定出 10 个枢纽基因。此外,CMap 分析显示咖啡酸、磺胺苯吡唑、莫利酮、噻苯达唑和杆菌肽可能是具有治疗意义的潜在小分子药物。我们鉴定出 8 种在 DM 患者和对照组中差异浸润的免疫细胞。最后,我们构建了基于记忆 B 细胞、M1 和 M2 巨噬细胞的强大诊断模型。

结论

本研究探索了 DM 的潜在分子机制和免疫学特征,可能为未来 DM 的研究和治疗提供指导。

关键点

  • 我们探索了皮肌炎的分子机制和免疫学特征。

  • GO 分析显示 DEGs 富集于免疫相关通路。

  • 我们基于生物分析技术预测了具有潜在治疗意义的小分子药物。

  • 我们鉴定出 6 种在 DM 患者和对照组中差异浸润的免疫细胞。

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