Metastasis is one of the most important aspects of neoplastic disease, and one of the most poorly understood. A significant fraction of patients diagnosed with solid tumors already have metastases at the time of primary tumor diagnosis. The dispersal of metastatic tumors throughout the body often precludes surgical removal, and the tumors often prove refractory to anticancer therapies. As a result, many cancer patients succumb to metastatic burden, rather than the primary tumor. Identification of genes that effect this process will have important prognostic value, permitting the identification of those patients that should be closely monitored for metastatic involvement. In addition, identification and characterization of modifier/suppressor genes may reveal novel approaches for the treatment of disseminated tumors and early stage tumors at risk for metastasis that are more effective than current therapeutic strategies. To identify metastasis modifying genes we are using a highly metastatic transgenic mouse model. The FVB/N-TgN(MMTVPyMT) mouse carries the polyoma middle T antigen driven by the mouse mammary tumor virus enhancer/promoter,and develops synchronously appearing multifocal tumors involving all of the mammary glands and develops extensive pulmonary metastases. To identify genetic backgrounds that significantly effect the metastatic phenotype of this model, we bred the transgenic animal to 25 different inbred strains of mice, and the progeny aged to permit tumor induction and potential metastasis. The progeny were subsequently analyzed for metastatic progression. Significant reduction in the number of pulmonary metastases was observed for several strains, including the inbred strains NZB/B1NJ, I/LnJ, C58/J and DBA/2J. Using a mouse genetic mapping resource known as the AKXD recombinant inbred panel and backcrosses generated in our laboratory, we have identified at least three loci that significantly suppress the ability of the tumors to metastasize. Currently we are generating high-resolution genetic mapping reagents to further refine the location of the loci on the genetic map, as well as using microarray and bioinformatic approaches to identify potential candidate genes.
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