| 陈建敏,王志勇,张楠楠,陈清法.基于长链非编码RNA调控ceRNA网络的缺血性脑卒中相关分子机制[J].中国康复医学杂志,2024,(1):53~61 |
| 基于长链非编码RNA调控ceRNA网络的缺血性脑卒中相关分子机制 点此下载全文 |
| 陈建敏 王志勇 张楠楠 陈清法 |
| 福建医科大学附属第一医院康复医学科，福建省福州市，350005 |
| 基金项目：福建省科技创新联合资金引领项目（2020Y9110）；福建省卫生健康青年科研课题（2020QNA044）；福建医科大学启航基金（2019QH1026） |
| DOI：10.3969/j.issn.1001-1242.2024.01.008 |
| 摘要点击次数: 382 |
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| 摘要： |
| 摘要
目的：利用生物信息学分析筛选缺血性脑卒中（IS）的差异表达基因，构建竞争性内源RNA（ceRNA）调控网络，探讨IS的相关分子机制。
方法：从GEO数据库下载IS相关的miRNA、mRNA和lncRNA测序数据，借助R软件获取差异基因，通过starBase、miRDB和 miRwalk数据库进行lncRNA- miRNA和miRNA- mRNA关系预测，并构建ceRNA网络。预测与差异分析的结果取交集后筛选出差异靶基因（DETmRNAs），利用 DAVID 数据库进行KEGG和GO富集分析，String 数据库构建蛋白互作网络（PPI），采用Cytoscape软件识别核心靶基因。
结果：共筛选出存在明显差异表达的miRNAs 20个，mRNAs 1512个，lncRNAs 278个，并成功构建了5lncRNAs-6miRNAs-102mRNAs互作的ceRNA网络。筛选出的285个DETmRNAs所富集的功能主要包括染色质的组织、磷蛋白磷酸酶活性的负向调节和细胞周期等生物学过程，涉及白细胞经内皮迁移、血小板激活等信号通路，最终识别出排名前10的核心靶基因为CREB1、MAPK1、GSK3B、SP1、PIK3R1、NR3C1、NCOR1、NFATC1、SETD2、NSD1。
结论：构建ceRNA网络有助于进一步认识IS的分子机制和筛选潜在的生物标志物，为后续康复治疗靶点的确定和制定康复策略提供一些线索。 |
| 关键词：缺血性脑卒中 生物信息学 GEO数据库 ceRNA调控网络 生物标志物 |
| lncRNA-mediated ceRNA network molecular mechanisms on ischemic stroke Download Fulltext |
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| Department of Rehabilitation Medicine， The First Affiliated Hospital，Fujian Medical University，Fuzhou，350005 |
| Fund Project: |
| Abstract: |
| Abstract
Objective： To construct the regulatory network of competitive endogenous RNA（ceRNA） and explore the molecular mechanism of ischemic stroke（IS） by using bioinformatic analysis to screen the differentially-expressed genes .
Method： The expression profiles of miRNA， mRNA and lncRNA in IS were downloaded from the NCBI GEO database. Differentially-expressed miRNAs， lncRNAs， and mRNAs were identified by the limma package in R software. The prediction of the relationship of lncRNA- miRNA and miRNA- mRNA were performed by starBase, miRDB and miRwalk databases. The results of prediction and differential analysis were taken to intersect and screened out differentially-expressed target mRNA （DETmRNAs）, Kyoto Encyclopedia of Genes and Genomes （KEGG）and gene ontology （GO） enrichment analysis was performed by using the DAVID database. The protein-protein interaction （PPI） network was constructed by using the STRING database and the core target genes in the network were identified by Cytoscape software.
Result： A total of 20 differentially-expressed miRNAs，1512 lncRNAs， and 278 mRNAs were identified, and a ceRNA network was successfully constructed with the interactions of 5 lncRNAs-6 miRNAs-102 mRNAs in IS. The 285 DETmRNAs functions are mostly involved in the biological process such as chromatin organization， negative regulation of phosphoprotein phosphatase activity， or cell cycle. KEGG mainly enriched the signaling pathway including leukocyte trans-endothelial migration and platelet activation. The top 10 core genes were CREB1， MAPK1， GSK3B， SP1， PIK3R1， NR3C1， NCOR1， NFATC1， SETD2， and NSD1.
Conclusion： The construction of the ceRNA network can help to further understand the molecular mechanism of IS and screen potential biomarkers， providing clues to further define rehabilitation targets and develop rehabilitation strategies. |
| Keywords:ischemic stroke bioinformatic analysis GEO database CeRNA regulatory network biomarker |
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