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《中华肺部疾病杂志》[ISSN:1006-6977/CN:61-1281/TN]

卷:

期数:

2024年02期

页码:

212-217

栏目:

论著

出版日期:

2024-04-20

文章信息/Info

Title:

Identifying hub genes and pathways in idiopathic pulmonary fibrosis based on transcriptomics

作者:

邱凌霄¹; 王创业¹; 卿 斌¹; 刘锦程¹; 张鑫烨²; 武文娟³; 邢德冰⁴; 郭 亮¹; 徐 智¹; 王 斌¹

400037 重庆,陆军(第三)军医大学第二附属医院呼吸与危重症医学科¹、中医科⁴
450052 郑州,郑州大学第一附属医院胸外科²
450003 郑州,河南省人民医院老年医学科³

Author(s):

Qiu Lingxiao¹;  Wang Chuangye¹;  Qing Bin¹;  Liu Jincheng¹;  Zhang Xinye²;  Wu Wenjuan³;  Xing Debing⁴;  Guo Liang¹;  Xu Zhi¹;  Wang Bin¹.

¹Department of Pulmonary and Critical Care Medicine, The Second Affiliated Hospital of Army Medical University, Chongqing 400037, China; ²Thoracic Surgery Department, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China; ³Department of Geriatrics, Henan Provincial People's Hospital, Zhengzhou 450003, China; ⁴Department of Traditional Chinese Medicine, The Second Affiliated Hospital of Army Medical University, Chongqing 400037, China.

关键词:

特发性肺纤维化;  差异表达基因;  基因表达综合数据库

Keywords:

Idiopathic pulmonary fibrosis;  Differentially expressed genes;  Gene Expression Omnibus database

分类号:

R563

DOI:

10.3877/cma.j.issn.1674-6902.2024.02.008

摘要:

目的 基于转录组学数据筛选特发性肺纤维化(idiopathic pulmonary fibrosis, IPF)致病的枢纽基因和相关信号通路。方法 从基因表达综合(gene expression omnibus, GEO)数据库中下载GSE17978数据集,应用GEO2R筛选差异表达基因(differentially expressed genes, DEGs),采用R软件ggplot2包和Heatmap包分别绘制DEGs的火山图和热图。采用R软件的clusterProfiler包进行DEGs基因本体论(gene ontology, GO)和京都基因与基因组百科全书(Kyoto encyclopedia of genes and genomes, KEGG)通路分析。采用R软件中的ggplot2包绘制气泡图。运用STRING和Cytoscape软件构建DEGs的蛋白质互作网络,应用Cytoscape的Cytohubba插件筛选参与IPF发病的枢纽基因。采用GSE10667数据集验证DEGs的差异表达。结果 共获得92个DEGs,其中上调基因49个,下调基因43个; GO分析和KEGG通路富集结果显示,DEGs主要在细胞外基质组织、胶原蛋白结合、PI3K-Akt信号通路及TGF-β信号通路等显著富集。运用STRING和cytoscape构建了DEGs的蛋白质互作网络,与IPF相关10个枢纽基因为FN1、CXCL12、DCN、COL1A1、MMP2、SPARC、SPP1、POSTN、COL1A2和COL3A1,其中9个枢纽基因在验证数据集GSE10667中有显著差异表达。结论 获得的92个DEGs和9个枢纽基因可能是IPF潜在的生物标志物。

Abstract:

Objective Based on transcriptomic data, identify hub genes and related signaling pathways involved in the pathogenesis of idiopathic pulmonary fibrosis(IPF). Methods GSE17978 dataset was downloaded from the GEO database. GEO2R tool was utilized to screen differentially expressed genes(DEGs). Ggplot2 package and Heatmap package in the R software were used to draw volcano maps and heat maps for DEGs. The R software clusterProfiler package was used to perform Gene Ontology(GO)and Kyoto Encyclopedia of Genes and Genomes(KEGG)pathway analysis on DEGs. The R software ggplot2 package was used to draw bubble charts. Using STRING and Cytoscape software to construct a protein-protein interaction network of DEGs. Cytohubba plugin in Cytoscape was performed to screen the hub genes involved in IPF. The GSE10667 dataset was used to verify the hub genes of DEGs. Results A total of 92 DEGs were obtained, including 49 up-regulated genes and 43 down-regulated genes. GO analysis and KEGG pathway enrichment analysis showed that DEGs are mainly enriched in extracellular matrix organization, collagen-containing extracellular matrix, PI3K-Akt signaling pathway, and TGF-beta signaling pathway. Protein-protein interaction networks of DEGs was constructed using STRING and Cytoscape, and 10 hub genes(FN1, CXCL12, DCN, COL1A1, MMP2, SPARC, SPP1, POSTN, COL1A2 and COL3A1)related to IPF were identified. Among above 10 hub genes, 9 genes showed significant differential expression in the validation dataset GSE10667. Conclusion The obtained 92 DEGs and 9 hub genes may be potential biomarkers of IPF.

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备注/Memo

备注/Memo:

基金项目: 重庆市科卫联合医学科研项目(2020FYYX179) 陆军军医大学第二附属医院“青博计划”(2023YQB057) 通信作者: 王 斌, Email: wangbin@tmmu.edu.cn

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更新日期/Last Update: 2024-04-20