An integrative bioinformatics study of gene expression profile in prostate cancer / 安徽医科大学学报

ABSTRACT

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 ofcell 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.