Methods for modeling cancer in mice are extremely varied. Exposure to chemicals, radiation, or viruses, and the use of transgenic technologies have been employed, sometimes in combinations, to generate models of nearly every type of cancer that afflicts people. In some cases, scientists have sought information about the cancer causing capabilities of specific agents, including specific types and doses of radiation, chemicals or specific genes or mutant genes. In other studies, specific genes that can cause cancer were sought. Some approaches start with specific candidate genes. We can consider these approaches “reverse cancer genetics,” that is, studies that start with one or more specific genes whose biological activities will be studied in a mouse. In many cases, the genes studied came from those suspected to contribute to human cancer when mutated or misexpressed in some way. A completely different type of approach for modeling cancer asks “what genes, when mutated, can cause cancer?” These “forward cancer genetics” approaches frequently use random, somatic insertional mutagenesis to induce or accelerate cancer in mice. Thus, cancer genes can be discovered by looking for somatically acquired, tumor-specific insertion mutations near or within genes in tumor genomic DNA. By studying a whole panel of tumors induced this way, one can find genes that are altered by insertion mutation in multiple, independent tumors and thus discover excellent cancer gene candidates and cancer pathways. This chapter reviews available approaches for modeling cancer by insertional mutagenesis in mice. Details about setting up such a screen, identifying insertion sites, interpreting the results and leveraging the information gained to better understand tumor progression and human cancer are described.
|Original language||English (US)|
|Title of host publication||Genetically Engineered Mice for Cancer Research|
|Subtitle of host publication||Design, Analysis, Pathways, Validation and Pre-Clinical Testing|
|Publisher||Springer New York|
|Number of pages||26|
|State||Published - Jan 1 2012|