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中国临床药理学与治疗学 ›› 2010, Vol. 15 ›› Issue (3): 266-271.

• 专论 • 上一篇    下一篇

基于基因表达谱的途径筛选肺腺癌治疗药物

王桂平1,2, 叶云1,3, 杨晓勤1, 陈新美1, 梁爽1, 郑文岭1, 马文丽1   

  1. 1南方医科大学基因工程研究所, 广州510515, 广东;
    2广州医学院护理学院,广州510180, 广东;
    3广西工学院生物与化学工程系, 柳州545006, 广西
  • 收稿日期:2010-01-11 修回日期:2010-01-11 发布日期:2020-10-14
  • 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

Gene expression profiles-based approach identifies candidate therapeutic compounds for lung adenocarcinoma

WANG Gui-ping1,2, YE Yun1,3, YANG Xiao-qing1, CHEN Xin-mei1, LIA NG Shuang1, ZHENG Wen-ling1, MA Wen-li1   

  1. 1Institute of Genetic Engineering, Southern Medical University, Guangzhou 510515, Guangdong, China;
    2GuangZhou Medical College, Guangzhou 510180, Guangdong, China;
    3Department of Biological and Chemical Engineering, Guangxi University of Technology, Liuzhou 545006,Guangxi,China
  • Received:2010-01-11 Revised:2010-01-11 Published:2020-10-14

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Co nnect ivity 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V orino stat、15-delta pro staglandin J2、t richo statin A、tanespimy cin 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。

关键词: 基因表达谱, 肺腺癌, Connectivi ty map

Abstract: AIM: To screen the candidate therapeutic compounds for lung adeno carcinoma 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 dchips of tware, 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: The rewere 379 differential gene expression, including 94 up-regulated gene and 285 down-regulated gene. Pathway enrichment analy sis showed that there were 18 biological pathw aysrelated with lung adenocarcinoma. With Connectivity map analysis, We screened out eight candida te compounds, including Vorinostat, 15-delta prostaglandin J2, trichostatin A, tanespimycin, etc. In the following experiment, we demo nst rated 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 the rapeutic compounds, which accelerates the introduction of compounds into the clinic.

Key words: Gene expression profiles, Lung adenocarcinoma, Connectivity map

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