Testing New Drugs for Treatment of Melanoma Patients Applying Connectivity Map Database Analysis with Melanoma Gene Signatures.

摘要

This proposal attempted to identify drugs for treating metastatic melanoma by utilizing meta-analysis of melanoma transcriptome data to generate a metastatic melanoma gene signature and apply this gene signature to the Connectivity Map database (C-Map) of drug gene signatures. Results from our study provide strong support that transcriptome analysis can prioritize drugs that may be effective against metastatic melanoma. We generated a metastatic melanoma-specific gene signature by selecting the genes that are commonly perturbed in metastatic melanoma. We showed that the C-Map database of FDA approved and other small molecule drugs can be used to select candidate anti- melanoma drugs that can be evaluated in cell cultures of metastatic melanoma cells and eventually in xenograft models for preclinical validation. We identified several drugs that are predicted to reverse the metastatic phenotype of melanoma and our results indicate that 4 out of 9 drugs, selected as high scorers in the C-Map analysis of metastatic melanoma, are in fact strong inducers of apoptosis in melanoma cell lines, demonstrating that these unrelated drugs may indeed lead to anti-melanoma efficacy. These drugs will be tested in xenograft experiments in mice. Demonstrated anti-tumor efficacy would be key for advancing a drug for human clinical testing.