Evaluation of New Drugs for Treatment of Prostate Cancer Patients Using Gene Signatures and the Connectivity Map Database
Final rept. 1 Jun 2011-31 May 2012
BETH ISRAEL DEACONESS MEDICAL CENTER BOSTON MA
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Taking advantage of the Connectivity Map database that contains gene signatures for 1309 drugs we tested the hypothesis that drugs that elicit gene signatures most opposed to metastatic prostate cancer will be effective anti-cancer drugs. Our data provide strong evidence that gene expression profiles can be utilized to predict which drugs may be effective in killing hormone-refractory PCa cells. We have identified a metastatic PCa-specific gene signature by identifying a set of genes commonly deregulated in at least 4 published datasets of metastatic PCa. We have demonstrated that the Connectivity Map database can be exploited to identify potential anti-PCa drugs that can be tested in cell culture and eventually in animal models for preclinical validation. Since the drugs that we selected are FDA approved, clinical trials could be rapidly initiated if the animal experiments are successful. 5 out of 11 drugs, selected as high scorers in the Connectivity Map analysis of metastatic PCa, are indeed potent inducers of apoptosis in PCa cell lines, and 3 of them demonstrate enhanced efficacy in killing of hormone-refractory PCa cells indicating that this set of structurally unrelated drugs indeed elicits anti-PCa activity. These drugs will be tested in PCa mouse models for anti-tumor activity.
- Genetic Engineering and Molecular Biology
- Medicine and Medical Research