Tremendous advances in understanding the molecular alterations contributing to cancer development and progression, and in exploiting this knowledge to build better mouse models that accurately recapitulate many aspects of human cancer have been achieved. New mouse models of human cancer have been used to identify candidate susceptibility genes, targets for cancer therapy and biomarkers for prognosis. However, similarly remarkable advances have not been realized in the clinic, especially for colorectal cancer (CRC), which accounts for the fourth largest number of new cancer cases each year and the second largest number of cancer-related deaths. Rather, large population-based studies of CRC have repeatedly proven that interventions to reduce susceptibility and deployment of early detection programs have the largest impact on survival from CRC. Colorectal cancer is largely preventable with appropriate lifestyle changes and curable if detected early and removed surgically. Building on the knowledge that CRC prevention and early detection are likely to have the greatest impact clinically, we propose a radical new approach to modeling human cancer in mice. We have assembled an experienced team of investigators that will exploit existing mouse models to develop and test innovative approaches for prevention, and robust yet economical methods for early detection of CRC. The foundation of our pioneering approach is a remarkable new mouse population called the Collaborative Cross that accurately models both germline and somatic genetic heterogeneity present within patient populations. We will use this experimentally tractable population-level model with clinically relevant environments to identify robust yet safe approaches for CRC prevention. We will also exploit the cancer heterogeneity of this population-level model, our previous discoveries from large-scale mouse and human CRC comparative gene expression profiling, and the unique ecology of the gastrointestinal tract microbiota to develop passive biosensors for early cancer detection. In parallel, a new biomarker-based mini-cam will be engineered to detect the location of nascent CRCs.

Public Health Relevance

Our proposed studies are highly relevant to the health of the US population. Colon cancer causes the second largest number of cancer-related deaths. The only proven ways to reduce loss of human life and financial costs of this disease is prevention and early detection. Consequently, innovative new approaches, as presented in this project, are required to reduce the incidence of life-threatening colon cancer.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project--Cooperative Agreements (U01)
Project #
5U01CA105417-07
Application #
7924193
Study Section
Special Emphasis Panel (ZCA1-SRLB-Q (M1))
Program Officer
Jhappan, Chamelli
Project Start
2004-08-15
Project End
2014-07-31
Budget Start
2010-08-18
Budget End
2011-07-31
Support Year
7
Fiscal Year
2010
Total Cost
$808,248
Indirect Cost
Name
North Carolina State University Raleigh
Department
Genetics
Type
Schools of Earth Sciences/Natur
DUNS #
042092122
City
Raleigh
State
NC
Country
United States
Zip Code
27695
Wells, Ann; Barrington, William T; Dearth, Stephen et al. (2018) Tissue Level Diet and Sex-by-Diet Interactions Reveal Unique Metabolite and Clustering Profiles Using Untargeted Liquid Chromatography-Mass Spectrometry on Adipose, Skeletal Muscle, and Liver Tissue in C57BL6/J Mice. J Proteome Res 17:1077-1090
Barrington, William T; Wulfridge, Phillip; Wells, Ann E et al. (2018) Improving Metabolic Health Through Precision Dietetics in Mice. Genetics 208:399-417
Mulligan, Megan K; Mozhui, Khyobeni; Prins, Pjotr et al. (2017) GeneNetwork: A Toolbox for Systems Genetics. Methods Mol Biol 1488:75-120
Kelly, Scott A; Zhao, Liyang; Jung, Kuo-Chen et al. (2017) Prevention of tumorigenesis in mice by exercise is dependent on strain background and timing relative to carcinogen exposure. Sci Rep 7:43086
Donoghue, Lauren J; Livraghi-Butrico, Alessandra; McFadden, Kathryn M et al. (2017) Identification of trans Protein QTL for Secreted Airway Mucins in Mice and a Causal Role for Bpifb1. Genetics 207:801-812
Kelada, Samir N P (2016) Plethysmography Phenotype QTL in Mice Before and After Allergen Sensitization and Challenge. G3 (Bethesda) 6:2857-65
Wang, WeiBo; Wang, Wei; Sun, Wei et al. (2015) Allele-specific copy-number discovery from whole-genome and whole-exome sequencing. Nucleic Acids Res 43:e90
Rutledge, Holly; Baran-Gale, Jeanette; de Villena, Fernando Pardo-Manuel et al. (2015) Identification of microRNAs associated with allergic airway disease using a genetically diverse mouse population. BMC Genomics 16:633
Didion, John P; Morgan, Andrew P; Clayshulte, Amelia M-F et al. (2015) A multi-megabase copy number gain causes maternal transmission ratio distortion on mouse chromosome 2. PLoS Genet 11:e1004850
McLachlan, Sandra M; Aliesky, Holly; Banuelos, Bianca et al. (2014) Immunoglobulin heavy chain variable region and major histocompatibility region genes are linked to induced graves' disease in females from two very large families of recombinant inbred mice. Endocrinology 155:4094-103

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