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.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA084244-09
Application #
7286400
Study Section
Special Emphasis Panel (ZCA1-SRRB-U (J1))
Program Officer
Marks, Cheryl L
Project Start
1999-09-30
Project End
2009-03-31
Budget Start
2007-04-27
Budget End
2008-03-31
Support Year
9
Fiscal Year
2007
Total Cost
$1,008,772
Indirect Cost
Name
University of California San Francisco
Department
Internal Medicine/Medicine
Type
Schools of Medicine
DUNS #
094878337
City
San Francisco
State
CA
Country
United States
Zip Code
94143
Huang, Phillips Y; Kandyba, Eve; Jabouille, Arnaud et al. (2017) Lgr6 is a stem cell marker in mouse skin squamous cell carcinoma. Nat Genet 49:1624-1632
Quigley, David A; Kandyba, Eve; Huang, Phillips et al. (2016) Gene Expression Architecture of Mouse Dorsal and Tail Skin Reveals Functional Differences in Inflammation and Cancer. Cell Rep 16:1153-1165
Halliwill, Kyle D; Quigley, David A; Kang, Hio Chung et al. (2016) Panx3 links body mass index and tumorigenesis in a genetically heterogeneous mouse model of carcinogen-induced cancer. Genome Med 8:83
Adams, Cassandra J; Yu, Jennifer S; Mao, Jian-Hua et al. (2016) The Trp53 delta proline (Trp53?P) mouse exhibits increased genome instability and susceptibility to radiation-induced, but not spontaneous, tumor development. Mol Carcinog 55:1387-96
Quigley, David (2015) Equalizer reduces SNP bias in Affymetrix microarrays. BMC Bioinformatics 16:238
Quigley, David; Silwal-Pandit, Laxmi; Dannenfelser, Ruth et al. (2015) Lymphocyte Invasion in IC10/Basal-Like Breast Tumors Is Associated with Wild-Type TP53. Mol Cancer Res 13:493-501
McCreery, Melissa Q; Halliwill, Kyle D; Chin, Douglas et al. (2015) Evolution of metastasis revealed by mutational landscapes of chemically induced skin cancers. Nat Med 21:1514-20
Song, Ihn Young; Balmain, Allan (2015) Cellular reprogramming in skin cancer. Semin Cancer Biol 32:32-9
Quigley, David (2014) RNA-seq permits a closer look at normal skin and psoriasis gene networks. J Invest Dermatol 134:1789-1791
Huang, Phillips Y; Balmain, Allan (2014) Modeling cutaneous squamous carcinoma development in the mouse. Cold Spring Harb Perspect Med 4:a013623

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