基于生物信息学和CMap数据库分析肺癌相关基因及潜在治疗药物

Identification of hub genes and potential candidate drugs for lung cancer via bioinformatics and CMap

目的基于生物信息学和关联性图谱(CMap)数据库筛选肺癌相关基因及其潜在的治疗药物,为肺癌的治疗提供新思路。方法从基因表达数据库(GEO)中选择GSE89039、GSE118370和GSE136043,采用R软件筛选差异表达基因(DEGs),将DEGs进行GO和KEGG富集分析,并构建蛋白质-蛋白质相互作用(PPI)网络;使用基因表达谱交互分析(GEPIA)验证枢纽基因的表达以及预后价值;采用CMap数据库筛选具有肺癌治疗作用的潜在候选药物。结果我们共确定了530个DEGs,包括150个上调基因和380个下调基因。这些DEGs主要富集在细胞外基质(ECM)-受体相互作用、细胞黏附等方面。PPI网络由527个节点,1298条连接线组成,前十个枢纽基因分别为SDC1、CDH5、FGF2、PECAM1、IL6、CAV1、MMP9、SPP1、VWF、PPARG。通过GEPIA分析这些枢纽基因相关的总生存期(OS),结果显示SPP1对OS具有显著影响。使用CMap数据库筛选出的对肺癌具有潜在治疗作用的FDA批准上市的候选药物,包括腺苷脱氨酶抑制剂(克拉屈滨)、核糖苷还原酶抑制剂(氯法拉滨)、抗病毒药(阿糖腺苷)、拓扑异构酶抑制剂(替尼泊苷)、RNA聚合酶抑制剂(放线菌素)、抗代谢药物(阿糖胞苷)。结论借助生物信息学和CMap数据库挖掘发现克拉屈滨等药物对肺癌具有潜在的治疗作用。本研究为寻找肺癌的治疗方案提供了新的思路,具有重要的临床意义。

Objective To screen hub genes and potential candidate drugs for lung cancer via bioinformatics and CMap,which provided new ideas for the treatment of lung cancer.Methods We obtained three datasets(GSE89039,GSE118370,GSE136043)from the Gene Expression Omnibus(GEO)database.Function annotation and enrichment pathway analysis of the differentially expressed genes(DEGs)were provided by Gene Ontology(GO),Kyoto Encyclopedia of Genes and Genomes(KEGG)and protein-protein interaction(PPI)network,and then we examined the association between the top10 screened hub genes and the overall survival(OS)of lung cancer patients.The candidate drugs with therapeutic effects were identified by Connectivity Map(CMap).Results A total of 530 DEGs were identified,including 150 up-regulated genes and 380 down-regulated genes.These DEGs were mainly involved in extracellular matrix(ECM)-receptor interaction and cell adhesion.The PPI network consisted of 527 nodes with 1298 connection lines.The top 10 hub genes were SDC1,CDH5,FGF2,PECAM1,IL6,CAV1,MMP9,SPP1,VWF and PPARG.GEPIA analysis showed that the expression level of SPP1 had significant impact on OS.Using the CMap,FDA-approved candidate drugs screened with potential therapeutic effects on lung cancer included adenosine deaminase inhibitors(cladribine),riboside reductase inhibitors(clofarabine),antiviral drugs(vidarabine),topoisomerase inhibitors(teniposide),RNA polymerase inhibitors(actinomycin),antimetabolites(cytarabine).Conclusion With the help of bioinformatics and CMap database,it is found that cladribine and other drugs may be candidates for the treatment of lung cancer.This study provides a new way for finding candidate therapeutic drugs and has important clinical significance.