RNAi based functional validation of new prostate cancer drug targets.

2094

The discovery and validation of new drug targets is needed for the development of new treatments for prostate cancer. To this end, we applied DNA microarrays to investigate the in vivo gene expression profiles in CWR22 human prostate cancer xenografts during a time course of androgen ablation and following therapy failure in recurrent androgen-independent CWR22R tumors. We identified 251 genes whose expression was associated with therapy response and over-expressed during therapy failure in the androgen-independent prostate cancer. These genes may modulate growth and survival in prostate cancer and represent potential targets for therapeutic intervention (Oncogene. 2001 20(46):6718). Some of these target genes were validated for clinical relevance by tissue microarray (TMA) analysis (Cancer Res. 2002 62(5):1256), including S100P, which is over-expressed in recurrent and advanced prostate tumors. In this study, we have used RNA interference (RNAi), mediated by small interfering RNAs (siRNAs), as a functional genomics tool to investigate the causal role between some of the candidate genes identified by microarray analysis and the survival of cancer cells. For example, siRNAs were designed to silence the expression of S100P. Two different synthetic siRNAs targeting the S100P transcript were transfected into several cell lines including the PC3 prostate cancer cell line. After 48 hours the growth of the S100P siRNA treated cells was reduced by 33% compared to cells transfected with a control siRNA. These results suggest that RNAi based gene silencing is likely to be a valuable tool in the experimental validation of genes that could be potential new anti-cancer drug targets. Additionally, microarray data following RNAi knockdown will also be presented to provide insight into the mechanism by which S100P and other candidate genes induce the survival of androgen-independent prostate cancer. In summary, clinical and RNAi based functional validation of genomic data from the CWR22R xenograft system has revealed new promising drug targets, such as S100P, for the treatment of androgen-independent prostate cancer.