The goal of this mouse models of human cancer consortium (MMHCC) application is to further develop the mouse as a predictive model in the search for effective human cancer therapies. With the support of the current MMHCC grant, we have developed innovative tools and approaches to modeling human cancer in the mouse and have made both our tools and strategies accessible to the community. In its initial iteration, RNA interference was applied as a genetic tool to study various cancer phenotypes in the mouse. These experiments were remarkably successful, leading to the identification and characterization of tumor suppressor genes, new modes of tumor suppression involving interplay between senescent cancer cells and the host, and the identification of drug modifying genes. They also functionally established roles for microRNAs as oncogenes and key components of tumor suppressor networks. At the same time, technological advances enabled our team to move beyond these initial objectives into new systems and discovery directions, including the development of new mosaic models, RNAi technology, and genomic platforms for characterizing the cancer genome at virtually every level. In this application, we propose to create a roadmap that synthesizes these efforts, using the mouse to filter data emerging from the many human cancer genomics efforts to identify key mediators of tumor development. We will create mouse models based upon emerging human cancer genomics and existing knowledge of cancer-relevant pathways. Using comparative, genome-wide RNAi screens in mouse and human cell lines and mouse tumors, we will assess the power of the genetically matched mouse models to both identify and validate new therapeutic approaches for human cancer. While we will work primarily in a breast cancer model, the path that we pave will be applicable to virtually any tumor type. The foundation of this MMHCC application is the continuing and demonstrably productive collaboration of a group of investigators, who each bring unique skills to the program. In virtually every case, the collaborating labs have developed key technologies and approaches for analyzing the human cancer genome and for translating that information into mouse models. While the current application is certainly built upon the strong foundations created by the previous grant, we have recruited new investigators to reflect the imperative of integrating and exploiting human cancer genetics through strategies that could scarcely have been envisioned at the prior submission. Indeed, our program is designed to complement the efforts of The Cancer Genome Atlas project by providing a blueprint for the functional annotation of the cancer genome.
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