The development of colorectal cancer (CRC) is a serious and feared malignancy, and the second leading cause of cancer-related death in the United States. Much is known about how CRC develops at early stages, but much remains to be learned about progression of this disease. Clearly it would be desirable to discover the genes and genetic pathways that lead to CRC progression such as metastases. Biomarkers that could be used to detect CRC and to predict tumor progression (invasion/metastasis) are desperately needed in the clinical management of patients at high risk for CRC - such as patients who've had polyps removed in the past. This project can help to address the mission of the National Cancer Institute's plan to create a comprehensive human cancer genome atlas. While some insight has been gained in the somatic changes that can occur in CRC, it is likely that much remains to be learned. An unbiased screen for somatic mutations that could cause CRC or accelerate malignancy after initiation by specific known human CRC mutations would be invaluable. The identification of CRC cancer genes, and the patterns in which these mutations occur in individual cases, will certainly guide future therapies. It is the main goal of this grant to model CRC using a novel system for random, Sleeping Beauty (SB) transposon-based, somatic insertional mutagenesis developed by Drs. Largaespada. Methods to induce CRC by transposition of SB transposon vectors in have already been established by Dr. Largaespada and Dr. Cormier. Candidate CRC genes will be tested for their ability to cause cancer by mouse transgenesis and other assays. The results will also be compared to human CRC genetic alterations. Relevance: This project seeks to define what genes, when altered in GI tract epithelial cells, cause CRC. It is critical to know what genes cause CRC so that effective therapies for this cancer can be developed. A mouse model of CRC will be created in which all the mutated genes that cause the CRC can be identified. Then a subset of these genes will be analyzed carefully for their individual effects in cell and mouse models.