雄激素依赖型与非依赖型前列腺癌基因芯片数据分析

Microarray data analysis in androgen-dependent and androgen-independent prostate cancer

目的根据高通量基因表达谱数据,采用数据挖掘技术识别前列腺癌相关的特征基因与功能,探讨雄激素非依赖型前列腺癌形成的分子机制。方法应用GeneSifter在线分析软件对6个雄激素依赖型前列腺癌(ADPC)和6个雄激素非依赖型前列腺癌(AIPC)基因芯片数据分成两组进行分析。结果筛选得到348个差异表达基因,并发现这些差异表达基因涉及的生物学过程和KEGG通路的一些相关基因。结论雄激素非依赖型前列腺癌的形成可能与GREB1 protein基因表达下调有关,并在细胞通讯和细胞黏附等过程和通路方面与雄激素非依赖型前列腺癌的形成有一定关系。

Objective To investigate the molecular mechanisms of androgen-independent prostate cancer using microarray data. Methods Microarray data from the C, ene Expression Omnibus （ GEO ） was used to examine the molecular changes between androgen-dependent and independent primary prostate tumors. This dataset was analyzed with GeneSifter microarray analysis software （VizX Labs, Seattle, WA）. Results After filtering the data,348 differentially expressed genes were identified. Gene Ontology and KEGG analysis showed that the genes are correlated with RNA metabolism, cell cycle, macromolecule biosynthesis, and cell adhesion. Conclusions The GREB1 protein gene possibly plays an important role in androgen-independent prostate cancer. Gene＇ s changes of cell adhesion and cell communication also contribute to the understanding of androgen-independent prostate cancer.