摘要
染料木素是一种天然的小分子物质,在多种肿瘤中显示出抗肿瘤作用,探究染料木素作用于骨肉瘤的靶基因。从DrugBank下载与染料木素有关的靶基因,分别导入string数据库中进行分析,用Cytoscape作出蛋白质相互作用(PPI)网络,同时用插件Cytohubb分析PPI,获得25个关键基因,再用WebGestalt分析25个基因的KEGG通路,选取与骨肉瘤相关通路的靶基因,得到的靶基因用HCMDB数据库验证,最后用miRDB预测靶基因的miRNA并在GSE65071数据库中进行验证。一共筛选出13个与染料木素有关的靶基因,选择其中药理作用不明的11个基因进行后续分析,string数据库中获得284个与11个靶基因有关的基因,使用WebGestalt分析25个关键基因,随后选取NF-kappaB和Rap1信号通路的靶基因在HCMDB数据库中进行验证,最后使用miRDB和GES65071数据库得到hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p和hsa-miR-200a-3p。研究显示CXCL8,CXCL12,LPAR1和CNR1;hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p和hsa-miR-200a-3p可能成为骨肉瘤的治疗靶基因。
Genistein is a kind of natural small molecular substance,which has shown anti-tumor effect in a variety of tumors.This paper explores the genes of genistein against osteosarcoma through bioinformatics analysis.Target genes associated with genistein were downloaded from DrugBank and imported to string database for analysis.With PPI network diagram created by Cytoscape,the plugin Cytohubb was applied to analyze the PPI network and 25 hub genes were acquired.WebGestalt was adopted to analyze KEGG pathways of 25 genes,and the target genes of the pathways associated with osteosarcoma were selected.The obtained target genes were verified using HCMDB.The miRNA of the genes were predicted by miRDB and verified in GSE65071 database.A total of 13 target genes associated with genistein were selected,and 11 genes whose pharmacological activities were not clear were chosen for subsequent analysis.From the string database,284 genes related to 11 target genes were obtained,and 25 hub genes were analyzed using WebGestalt.Subsequently,the target genes of NF-kappa B and Rap1 signaling pathways were selected and verified in the HCMDB database.Lastly,miRDB and GSE65071 databases to acquire hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p,and hsa-miR-200a-3p.The study showed that CXCL8,CXCL12,LPAR1,and CNR1,as well as hsa-miR-23b-3p,hsa-miR-23a-3p,hsa-miR-141-3p,and hsa-miR-200a-3p might be the therapeutic target genes for osteosarcoma.
作者
郭良煜
余铃
陈敬腾
龚长天
施玉博
郭卫春
GUO Liangyu;YU Ling;CHEN Jingteng;GONG Changtian;SHI Yubo;GUO Weichun(Department of Orthopedics,Renmin Hospital of Wuhan University,Wuhan 430060,China)
出处
《生物信息学》
2021年第1期47-54,共8页
Chinese Journal of Bioinformatics