摘要
目的基于生物信息学分析筛选肺腺癌靶基因及评估预后价值。方法对三个数据集(GSE118370、GSE32863、TCGA-LUAD)分别使用limma和edgeR包筛选出肺腺癌差异表达基因,对共同差异基因进行功能富集分析,通过String数据库构建蛋白质-蛋白质相互作用(PPI)网络,采用Cytoscape进行可视化分析并用其插件cytoHubba来筛选关键基因,采用Kaplan-Meier曲线进行总体生存分析。结果共224个共同差异基因,其中上调基因34个,下调基因190个。共同差异基因在血管生成、白细胞调节、免疫反应等生物学过程富集。通过从PPI网络中筛选出8个关键基因,分别为IL6、VWF、PECAM1、SPP1、CDH5、CXCL12、TIMP1、CLDN5。生存分析显示,PECAM1与LUAD的预后有关。肿瘤组织中PECAM1表达高于正常组织,差异有统计学意义(P<0.05)。结论PECAM1是一种与肺腺癌预后相关的新的生物标志物,有望成为肺腺癌的一个治疗的靶点。
Objective To screen the target genes of lung adenocarcinoma based on bioinformatics analysis and evaluate the prognostic value.Methods Three data sets(GSE118370,GSE32863,TCGA-LUAD)were used to screen differentially expressed genes in lung adenocarcinoma using limma and edgeR packages,functional enrichment analysis of common differential genes,and protein-protein interactions were constructed by String database.(PPI)network,using Cytoscape for visual analysis and using its plug-in cytoHubba to screen key genes,Kaplan-Meier curve for overall survival analysis.Results A total of 224 common differential genes,including 34 up-regulated genes and 190 down-regulated genes.Common differential genes are enriched in biological processes such as angiogenesis,leukocyte regulation,and immune response.Eight key genes were screened from the PPI network,namely IL6,VWF,PECAM1,SPP1,CDH5,CXCL12,TIMP1,and CLDN5.Survival analysis showed that PECAM1 was associated with the prognosis of LUAD.The expression of PECAM1 in tumor tissues was higher than that in normal tissues,the difference was statistically significant(P<0.05).Conclusion PECAM1 is a new biomarker related to the prognosis of lung adenocarcinoma and is expected to be a target for the treatment of lung adenocarcinoma.
作者
黄琪峰
郑琳琳
张菁
HUANG Qi-feng;ZHENG Lin-lin;ZHANG Jing(Department of Pharmacy,Sir Run Run Shaw Hospital,Zhejiang University School of Medicine,Hangzhou 310000,Zhejiang,China;Department of Ultrasound,Sir Run Run Shaw Hospital,Zhejiang University School of Medicine,Hangzhou 310000,Zhejiang,China)
出处
《医学信息》
2019年第22期62-65,共4页
Journal of Medical Information
基金
浙江省自然科学基金/药学会联合基金(编号：LYY18H310004)
关键词
肺腺癌
差异表达基因
生物标志物
生物信息学分析
Lung adenocarcinoma
Differentially expressed genes
Biomarkers
Bioinformatics analysis
