基于生物信息学的激素非依赖型前列腺癌的治疗药物筛选  

Candidate therapeutic agents screening for androgen-independent prostate cancer based on bioinformation methods

作　　者：李铁求[1] 冯春琼[2] 邹亚光[3] 周期赵[1] 梁爽[2] 毛向明[1] 

机构地区：[1]南方医科大学附属南方医院泌尿外科,广东510515 [2]南方医科大学基因工程研究所 [3]南方医科大学附属南方医院口腔科

出　　处：《中国男科学杂志》2010年第9期13-17,25,F0004,共7页Chinese Journal of Andrology

摘　　要：目的筛选雄激素非依赖型前列腺癌(AIPC)新的潜在治疗药物。方法通过FACTA工具从PubMed找出前列腺癌的相关基因进行分类,利用Connectivity Map、DrugBank、ToppGene等生物信息学在线工具筛选出AIPC潜在治疗药物并进行初步验证。结果生物信息学筛选出一些对AIPC潜在的治疗药物,其中包括thioridazine(甲硫达嗪)、novobiocin(新生霉素),并通过实验证实了新生霉素对前列腺癌PC-3细胞的抑制作用并通过生物信息学探讨其可能机制。结论通过生物信息学对雄激素非依赖型前列腺癌差异表达基因的挖掘及药物筛选,是一种合理的药物筛选方法。Objective To screen the candidate therapeutic drugs for androgen-independent prostate cancer （AIPC）. Methods Lists of prostate cancer associated genes were obtained by mining PubMed with FACTA tool. Candidate therapeutic drugs for AIPC were screened by a set of bioinformatics tools including Connectivity Map, DrugBank and ToppGene and then validated. Results Some candidate drugs for AIPC were screened by bioinformatics analysis including thioridazine and novobiocin, then novobiocin was validated to inhibit the growth of prostate cancer cells PC-3. Conclusion Mining differential expressed genes using bioinformatics analysis might be a rational approach for drug discovery of androgen-independent prostate cancer.

关 键 词：生物信息学 前列腺肿瘤 药物筛选试验 抗肿瘤 新生霉素 

分 类 号：R737.25[医药卫生—肿瘤]