摘要
目的:从分子水平揭示雄激素非依赖型前列腺癌(AIPC)的发病机制,为临床诊疗提供新思路。方法:在公共基因芯片数据库(GEO)中下载前列腺癌的相关基因芯片数据,使用BRB-ArrayTools软件对其进行数据挖掘分析,筛选AIPC相关基因;并利用GATHER在线分析工具进行深入的生物信息学分析。此外,又利用基因集富集分析(GSEA)软件对上述基因芯片数据集进行了基因富集分析。结果:BRB分析发现在AIPC中有87个差异表达基因,其中上调23个,下调64个。这些差异基因的功能主要集中在细胞信号转导、细胞粘附、粘附斑、细胞外基质(ECM)受体相互作用等功能中。GSEA分析发现AIPC相关基因主要在ECM受体相互作用、SONIC_HEDGEHOG以及HDACI_COLON_TSABUT_DN功能基因集中富集。结论:应用BRB-ArrayTools和GSEA分析发现,ECM受体相互作用、细胞粘附过程及Hedgehog信号通路之间的网络调控系统可能与AIPC的发生密切相关。利用生物信息学的方法能有效分析基因芯片数据并获取生物内在信息,为确定雄激素非依赖型前列腺癌的早期诊断标志与治疗靶点提供新的思路。
Objective：To better understand the molecular pathogenesis of androgen independent prostate cancer （AIPC） , and provide novel means for clinical diagnosis and treatment of this malignancy. Methods：The data of whole genomic expression profiles got from the androgen dependent and androgen-independent prostate cancers were obtained from GEO database, a set of bioinformatics tools, such as BRB-ArrayTools, GATHER and GSEA softwares were used to accomplish the data mining, so that we could identify some genes related to androgen-independent prostate cancer. Results： BRB analysis results showed there were eighty-seven differentially expressed genes in androgen independent prostate cancer（AIPC）, 23 up-regulated and 64 down-regulated. These AIPC-related genes played essential roles in such important biological processes as cell signal transduction.cell adhesion, Focal adhesion and ECM-receptor interaction. GSEA analysis results suggested that AIPC-related genes mainly enriched in HSA04512 _ ECM_ RECEPTOR_ INTERACTION, SONIC_ HEDGEHOG and HDACI_ COLON_ TSABUT_DN gene sets. Conelusions：Bioinformafics analysis found that an interaction network involved ECM receptor interaction, cell adhesiona and Hedgehog might play an essential role in AIPC. These would offer a new view for early diagnosis and treat target of AIPC.
出处
《临床泌尿外科杂志》
北大核心
2010年第4期306-310,共5页
Journal of Clinical Urology
