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目的：从分子水平揭示前列腺癌骨转移的发病机制，为临床诊疗提供新思路。方法在公共基因芯片数据库（GEO）中下载前列腺癌骨转移的相关基因芯片数据，利用BRB-ArrayTools 软件、STRING、ToppGene、GOEAST、DAVID等生物信息学工具进行数据挖掘及生物信息学分析。结果 BRB分析筛选出501个前列腺癌骨转移差异基因，其中上调181个，下调320个。对其进行生物信息学分析发现SPP1、HBB、AR、MMP9、AZGP1、POSTN、FN1、VCAN等基因以及胶原蛋白及其生物合成、细胞黏附、小分子代谢过程、黏着斑、ECM受体相互作用、细胞周期、整合素信号通路等分子生物学过程及通路在前列腺癌骨转移的发生发展中可能起着重要作用。结论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，为发现前列腺癌骨转移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 prostate cancer bone metastasis, and provide novel approaching for clinical diagnosis and treatment of this malignancy. Methods The data of whole genomic expression profiles on prostate cancer bone metastasis were obtained from GEO database.A set of bioinformatics tools, such as BRB-ArrayTools, STRING, ToppGene, GOEAST and DAVID softwares were used to accomplish the data-mining and bioinformatics analysis. Results BRB analysis results showed there were 501 differentially expressed genes related to prostate cancer bone metastasis, including 181 up-regulated and 320 down-regulated. Bioinformatic analysis results suggested that SPP1, HBB, AR, MMP9, AZGP1, POSTN, FN1 and VCAN played essential roles in such important biological processes as collagen biosynthetic,cell adhesion,Focal adhesion,Integrin signalling pathway and ECM-receptor interaction. Conclusion Bioinformatic analysis had a high efficiency in analyzing gene chip data and revealing internal biology information. It will offer a new view to find early biomarkers and treatment targets of prostate cancer bone metastasis.