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生物信息学方法研究特发性肺纤维化中 miRNA-基因网络的潜在分子机制与构建

Underlying Molecular Mechanism and Construction of a miRNA-Gene Network in Idiopathic Pulmonary Fibrosis by Bioinformatics.

机构信息

Department of Respiratory and Critical Care Medicine, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an 710004, China.

出版信息

Int J Mol Sci. 2023 Aug 27;24(17):13305. doi: 10.3390/ijms241713305.

Abstract

Idiopathic pulmonary fibrosis (IPF) is a chronic, progressive lung disease, but its pathogenesis is still unclear. Bioinformatics methods were used to explore the differentially expressed genes (DEGs) and to elucidate the pathogenesis of IPF at the genetic level. The microarray datasets GSE110147 and GSE53845 were downloaded from the Gene Expression Omnibus (GEO) database and analyzed using GEO2R to obtain the DEGs. The DEGs were further analyzed for Gene Ontology (GO) and Kyoto Encyclopedia of Genomes (KEGG) pathway enrichment using the DAVID database. Then, using the STRING database and Cytoscape, a protein-protein interaction (PPI) network was created and the hub genes were selected. In addition, lung tissue from a mouse model was validated. Lastly, the network between the target microRNAs (miRNAs) and the hub genes was constructed with NetworkAnalyst. A summary of 240 genes were identified as DEGs, and functional analysis highlighted their role in cell adhesion molecules and ECM-receptor interactions in IPF. In addition, eight hub genes were selected. Four of these hub genes (, , , and ) were screened for animal validation. The IHC and RT-qPCR of lung tissue from a mouse model confirmed the results above. Then, miR-181b-5p, miR-4262, and miR-155-5p were predicted as possible key miRNAs. Eight hub genes may play a key role in the development of IPF. Four of the hub genes were validated in animal experiments. MiR-181b-5p, miR-4262, and miR-155-5p may be involved in the pathophysiological processes of IPF by interacting with hub genes.

摘要

特发性肺纤维化(IPF)是一种慢性、进行性肺部疾病,但发病机制仍不清楚。本研究采用生物信息学方法,旨在从基因水平探讨 IPF 的差异表达基因(DEGs),并阐明其发病机制。从基因表达综合数据库(GEO)下载微阵列数据集 GSE110147 和 GSE53845,使用 GEO2R 进行分析,获得 DEGs。使用 DAVID 数据库对 DEGs 进行基因本体论(GO)和京都基因与基因组百科全书(KEGG)通路富集分析。然后,使用 STRING 数据库和 Cytoscape 创建蛋白质-蛋白质相互作用(PPI)网络,并选择枢纽基因。此外,对小鼠模型的肺组织进行验证。最后,使用 NetworkAnalyst 构建靶微小 RNA(miRNA)和枢纽基因之间的网络。鉴定出 240 个基因作为 DEGs,功能分析突出了它们在细胞黏附分子和细胞外基质-受体相互作用中的作用。此外,还选择了 8 个枢纽基因。其中 4 个枢纽基因(、、和)用于动物验证。对小鼠模型肺组织的免疫组化和 RT-qPCR 验证了上述结果。然后,预测 miR-181b-5p、miR-4262 和 miR-155-5p 可能作为关键 miRNA。这 8 个枢纽基因可能在 IPF 的发生发展中发挥关键作用。其中 4 个枢纽基因在动物实验中得到验证。miR-181b-5p、miR-4262 和 miR-155-5p 可能通过与枢纽基因相互作用参与 IPF 的病理生理过程。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5622/10487482/24b5d7b75403/ijms-24-13305-g001.jpg

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