Most human tumors arise from the self-renewing cells of the epithelia - the linings of the major tissues such as the skin, lung and intestine. Our hypothesis is that while some polymorphisms that influence cancer risk may act specifically in certain tissues, for example hormonal influences on the breast or prostate, many will control the basic underlying properties of growth control and genetic stability that are almost always deregulated during cancer development. We will look for these common genes and polymorphisms using mouse models of susceptibility to skin, lung, colon and prostate tumors. A combination of linkage analysis and haplotyping will be used to refine the regions containing genes that confer increased risk of developing epithelial tumors. Candidate genes will be selected by analysis of allele-specific genetic alterations in tumors using genome wide high density BAC arrays, together with gene expression microarrays to profile both normal tissues and tumors from backcross animals. This analysis will be facilitated by the availability of an extensive database and tissue/tumor bank derived from almost 2000 mice from a series of overlapping interspecific Mus spretus X Mus musculus crosses. In parallel with these studies on mouse models, we have set up an extensive network of collaborations involving multiple groups worldwide with expertise in human population genetics and, most importantly, collections of normal DNA samples from large human population-based case-control or cohort studies. These collaborators have access to DNA samples from patients with cancers from each of the tissues for which we have developed mouse models (skin, lung, colon, prostate), as well as from patients with breast and other cancers. Additional collaborators have focused on collections of human tumor DNA and/or RNA from patients with the same tumor types. Many biological and epidemiological studies have demonstrated relationships between cancer and other disease phenotypes such as inflammation or obesity. We will adopt a Systems Biology approach to genotype-phenotype relationships by setting up a large interspecific backcross designed to collect data on skin tumor incidence, pathology, progression, and metastasis. Serum and blood samples will be stored for subsequent proteomic and functional studies. A series of additional parameters of each mouse in the backcross will be measured including immune function, body weight/obesity, bone density, and inflammatory response. This is an ambitious attempt to collect and analyze large data sets containing information on cancer from both mouse and human perspectives. The results will be important for the prediction of human cancer risk, as well as for development of prevention or therapeutic strategies based on genotype-phenotype networks rather than single genetic targets.
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