摘要
目的:探讨基于基因表达谱的途径在肺腺癌治疗药物筛选中的应用。方法:从GEO数据库中获得GSE10072和GSE7670两个数据集,然后利用dchip软件进行差异表达基因分析,采用基因集富集方法(gene set enrichment analysis,GSEA)对肺腺癌进行通路富集分析,最后通过Connectivity map(Cmap)筛选肺腺癌候选治疗化合物,并进行实验验证。结果:共获得差异表达基因379个,其中上调基因94个,下调基因285个;GSEA主要富集到细胞周期等18条信号通路与肺腺癌相关;通过Cmap分析,筛选到Vorinos-tat、15-delta prostaglandin J2、trichostatin A、tanespi mycin等8种候选药物或化合物,在进一步的实验中也证实15d-PGJ(2)可有效抑制A549细胞的增殖。结论:基于基因表达谱的途径为药物发现提供新思路,加速了药物发现过程。
AIM. To screen the candidate therapeutic compounds for lung adenocarcinoma with gene expression profiles-based approach.METHODS. Two published microarray data （GSE7670 and GSE10072） were downloaded from Gene Expression Omnibus（GEO） web. A meta-analysis were performed with the dchip software, and pathway enrichment analysis was done with gene set enrichment analysis method （GSEA）. Finally, candidate therapeutic compounds for lung adenocarcinoma were screened by Connectivity map analysis. RESULTS：There were 379 differential gene expression, including 94 up-regulated gene and 285 down-regulated gene. Pathway enrichment analysis showed that there were 18 biological pathways related with lung adenocarcinoma. With Connectivity map analysis, We screened out eight candidate compounds, including Vorinostat, 15-delta prostaglandin J2, trichostatin A, tanespimycin, etc. In the following experiment, we demonstrated that 15-delta prostaglandin J2 can inhibit A549 cell prolification. CONCLUSION ： Our results demonstrated that gene expression profiles-based approach is perspective for screening the candidate therapeutic compounds, which accelerates the introduction of compounds into the clinic.
出处
《中国临床药理学与治疗学》
CAS
CSCD
2010年第3期266-272,共7页
Chinese Journal of Clinical Pharmacology and Therapeutics
作者简介
王桂平，男，博士，研究方向：生物信息学与肿瘤治疗药物研究。E—mail：docgpwang@yahoo．com．cn
马文丽，通信作者，女，教授，研究方向：基因芯片技术及其应用。Tel：020—62789097 E-mail：wenli@fimmu．com
