前列腺癌基因表达谱芯片的生物信息学分析

目的 利用生物信息学方法分析前列腺癌基因表达谱芯片,研究前列腺癌差异表达基因的功能及调控网络.方法 采用GEO数据库中获取的前列腺癌基因表达谱芯片数据,利用R软件及affy、limma、pheatmap、ggplot2等R软件包进行数据挖掘及生物信息学分析.结合生物信息学工具DAVID、GeneMANIA对差异表达基因及其调控网络进行分析.结果 共筛选出前列腺癌与癌旁组织差异表达基因56个,表达上调15个,表达下调41个,前列腺癌与癌旁组织的差异表达基因被富集到不同的子集.其中cav1、slc16a2、cav2、slc16a5、magi2、ptrf、pdlim5、lmod1、abcc6等9个基因被富集到"细胞功能"分类下的"细胞膜组分"子集中,其中cav1、cav2、ptrf影响细胞膜内陷囊状结构的功能,可能在前列腺癌发生发展中发挥重要作用.结论 前列腺癌与癌旁组织的差异表达基因之间存在复杂的调控网络,生物信息学可以从中提取有效信息,为前列腺癌分子机制研究提供思路及数据基础.

An integrative bioinformatics study of gene expression profile in prostate cancer

Objective To analyze gene expression profile for exploring the function and regulatory network of differ-entially expressed genes in prostate cancer by bioinformatics. Methods The data of gene expression profile in prostate cancer were obtained from GEO database. R software and affy, limma, pheatmap, ggplot2 and other R packages were applied for data mining and bioinformatics analysis. Combined with DAVID and GeneMANIA , dif-ferentially expressed genes and their regulatory networks were annotated. Results These differentially expressed genes with statistical significance were 56 genes, 15 upregulated genes, 41 downregulated genes;these genes were enriched into different subgroups. cav1, slc16a2, cav2, slc16a5, magi2, ptrf, pdlim5, lmod1 and abcc6 were en-riched into the "cell membrane component" subgroup of"cell component" category. cav1, cav2 and ptrf regulated the function of caveolae, they may play an important role in the occurrence and development of prostate cancer. Conclusion Differentially expressed genes between prostate cancer and adjacent tissues assemble a complex regu-latory network. Bioinformatics is a tool for data mining of the regulatory network , which provides ideas and data for the molecular mechanisms in prostate cancer.