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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 for new potential therapeutic agents for androgen independent prostate cancer (AIPC). Methods The FACTA tools were used to find out the related genes of prostate cancer from PubMed. The potential therapeutic drugs of AIPC were screened out and bioinformatics tools such as Connectivity Map, DrugBank and ToppGene were used to validate the potential therapeutic drugs. Results Bioinformatics screened out some potential therapeutic agents for AIPC, including thioridazine and novobiocin, and confirmed the inhibitory effect of novobiocin on prostate cancer PC-3 cells through experiments Explore its possible mechanism through bioinformatics. Conclusion It is a reasonable drug screening method to identify and screen the differentially expressed genes in androgen independent prostate cancer by bioinformatics.