Prostate cancer is the second most common cause of cancer related deaths in men, yet relatively little is known about the molecular mechanisms of disease progression. Identifying genes that are involved in this process is important to identify new therapeutic targets. Here we propose to establish a novel retroviral shuttle vector mutagenesis technology to identify genes that drive prostate cancer progression. Comparative genome hybridization (CGH), transcriptome deep sequencing, and proteomics have emerged as technologies for prostate cancer gene discovery. However, distinguishing the causal mutations from the entire cancer genome/transcriptome/proteome remains a challenge. We have developed a novel mutagenesis vector that allows efficient high-throughput identification of candidate dysregulated genes. In this approach, integrated lentiviral shuttle vectors mutagenize target cells by dysregulating the expression of nearby genes. Vector provirus:chromosome junctions are rescued as plasmids in bacteria, and these plasmids are sequenced to identify the chromosomal location of each vector provirus. This identifies nearby candidate dysregulated genes that promote cancer growth and/or progression. Our shuttle vector technology overcomes a severe technical limitation of previous retroviral mutagenesis screens, inefficient PCR-based detection. We will take advantage of an established LNCaP xenograft prostate cancer model to establish our novel technology. Using this technology we expect to rapidly identify novel genes that drive prostate cancer in vivo. These genes can be targeted in future studies to inhibit prostate cancer or used as biomarkers. In future studies our approach may be used for other types of cancer to accelerate the pace of cancer research with broad potential impact.
The proposal will use a novel technology to identify genes involved in the progression of prostate cancer. The proposed studies may rapidly identify new prostate cancer genes that can be targeted in future studies to inhibit cancer progression.
|Schinke, Ellyn N; Bii, Victor; Nalla, Arun et al. (2014) A novel approach to identify driver genes involved in androgen-independent prostate cancer. Mol Cancer 13:120|