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Molecular & Cellular Analysis Technologies
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Prostate cancer is the second leading cause of male cancer death in the United States and often results in a reduced quality of life for those living with or treated for this disease. Prostate cancer is commonly treated by androgen ablation therapy and although many tumors initially respond to this treatment, many eventually progress to hormone refractory prostate cancer (HRPC). The genetic basis for the transition to hormone insensitivity is poorly understood. We propose to use a mouse model for invasive prostate cancer that results from prostate specific loss of the tumor suppressor gene Pten. This mouse model is relevant to human disease as PTEN expression is lost in many human prostate tumors and the tumors that form in the mice remain partially sensitive to hormone withdrawal. We will use a novel method for cancer gene discovery in mice, the Sleeping Beauty (SB) transposon system, to promote aggressive tumor formation in this model. The SB transposon is a DMA element that is capable of mobilizing and inserting in a different location in the genome. If a mobilized transposon reinserts near a cancer gene, it can promote changes in expression of that gene that promote the transition from a normal cell to a transformed cancer cell. We have previously generated mice engineered with all the components necessary for mobilizing SB transposons in various tissues in the adult mouse. In unpublished experiments, we have successfully used the SB system to identify genes involved in sarcoma and lymphoma formation in mice, and we believe that SB will prove to be equally as successful in prostate tumor models. By using SB to promote HRPC formation we can both identify the genetic changes that cause a tumor to become insensitive to hormone withdrawal and also generate a useful mouse model of HRPC that will be useful for discovery and testing of novel chemotherapeutic agents for advanced prostate cancer. Finally, this approach represents a novel method for the unbiased molecular/genetic analysis of cancer development and could be used widely in the study of important clinical cancer problems.