详细信息

间充质干细胞恶性转化相关关键基因的生物信息学分析     被引量:5

Bioinformatic Analysis of Related Key Genes in Malignant Transformation of Mesenchymal Stem Cells

文献类型:期刊文献

中文题名:间充质干细胞恶性转化相关关键基因的生物信息学分析

英文题名:Bioinformatic Analysis of Related Key Genes in Malignant Transformation of Mesenchymal Stem Cells

作者:骆亚莉[1,2];刘永琦[2];安方玉[2];任春贞[2];李玲[2];李程豪[2];赵娜[3];赵枫[3]

第一作者:骆亚莉

机构:[1]甘肃中医药大学基础医学院病理教研室;[2]甘肃中医药大学甘肃省高校重大疾病分子医学与中医药防治研究省级重点实验室;[3]甘肃中医药大学公共卫生学院

第一机构:甘肃中医药大学基础医学院(敦煌医学研究所)

年份:2017

卷号:21

期号:4

起止页码:329

中文期刊名:生命科学研究

外文期刊名:Life Science Research

收录:CSTPCD;;CSCD:【CSCD_E2017_2018】;

基金:国家自然科学基金资助项目(81360588;81760804)

语种:中文

中文关键词:间充质干细胞(MSCs);恶性转化;风险关键基因;生物信息学;文献数据挖掘

外文关键词:mesenchymal stem cells (MSCs); malignant transformation; risk-related key genes; bioinformatics; literature data mining

摘要:筛选间充质干细胞发生恶性转化相关的关键基因,可为进一步的相关性研究提供参考和依据。研究首先基于文献挖掘的方法,从已公开发表的研究中统计出间充质干细胞发生恶性转化的相关基因,随后运用生物信息学方法对上述基因进行分析,同时用在线软件构建基因所表达蛋白质的相互作用网络,并将相应网络进一步可视化处理,计算网络及各个节点的拓扑特性。结果显示,近年内的文献共涉及187个基因或其表达产物,有1 253种GO分类,KEGG通路分析显示,主要参与信号转导通路、细胞粘附、周期调节等;此外,共筛选出关键节点21个。生物信息学筛选的关键基因可用于提示间充质干细胞可能发生恶性转化的趋向,也有助于分析间充质干细胞恶性转化的可能机制。
The key genes associated with malignant transformation of mesenchymal stem cells were screened to provide reference and basis for further research. Techniques in bioinformatics were applied for the malignant transformation risk genes of mesenchymal stem cells, which were obtained from published studies. Then, the complex protein-protein network was built by nodes expressed by those genes through online STRING software. The network was visualized and quantified using the Cytoscape software for analysis. Results showed that there were 187 related genes and a total of 1 253 functional classifications by the Gene Ontolo- gy (GO) and 100 pathways by the Kyoto Encyclopedia of Genes and Genomes (KEGG), mainly involved in the signal transduction, cell adhesion, cell cycle regulation and so on. Among the genes only 23 GO classifications and 32 KEGG pathways were significant. Finally 21 key risk genes were selected from the protein- protein network. The related key genes screened by bioinformatics could be used in indicating the tendency for malignant transformation of mesenchymal stem ceils, and also help analyze the possible mechanism.

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