Mathematical models of carcinogenesis that are designed to capture important features of the multistage process, from normal cells, via expanding intermediate cell populations, to the appearance of malignant tumors, offer the opportunity to study in greater detail the effects of specific interventions that affect critical biological processes involved in carcinogenesis. The main focus of this proposal is therefore the development of tools and methods for the quantitative evaluation of possible prevention and intervention strategies and to apply them to colorectal cancer. These tools and methods will be based on stochastic models of carcinogenesis that reflect insights gained into the pathogenesis of colon cancer over the past decade, as well as extensions of these models that allow for the incorporation of additional (putative) pathways associated with genomic instability. To achieve this goal with confidence, it is important that the models used for this purpose give satisfactory descriptions of the incidence of colon cancer in the general population. A challenge, so far unmet, is that these models also be consistent with observations on the prevalence and size distribution of adenomatous polyps, pathologically well-characterized precursor lesions to colorectal tumors. These polyps are also the subject of specific cancer screening and intervention strategies. This motivates the mathematical development of statistical and computational tools to analyze relevant data sets: (1) the SEER registry data on colorectal cancer (CRC) incidence, (2) CRC incidence in a large prospective cohort of women (the Shanghai study), (3) the Minnesota Cancer Prevention Research Unit (CPRU) polyp data, and (4) data from a case-control study of CRC and the role of sigmoidoscopy conducted at the Fred Hutchinson Cancer Research Center. Models derived from these analyses and the computational tools developed will facilitate the prediction of benefits associated with specific screening, prevention and intervention strategies. ? ?

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA107028-03
Application #
7183594
Study Section
Biostatistical Methods and Research Design Study Section (BMRD)
Program Officer
Feuer, Eric J
Project Start
2005-03-01
Project End
2009-02-28
Budget Start
2007-03-01
Budget End
2008-02-29
Support Year
3
Fiscal Year
2007
Total Cost
$259,176
Indirect Cost
Name
Fred Hutchinson Cancer Research Center
Department
Type
DUNS #
078200995
City
Seattle
State
WA
Country
United States
Zip Code
98109
Jeon, Jihyoun; Meza, Rafael; Hazelton, William D et al. (2015) Incremental benefits of screening colonoscopy over sigmoidoscopy in average-risk populations: a model-driven analysis. Cancer Causes Control 26:859-70
Luebeck, E Georg; Curtius, Kit; Jeon, Jihyoun et al. (2013) Impact of tumor progression on cancer incidence curves. Cancer Res 73:1086-96
Hazelton, William D; Goodman, Gary; Rom, William N et al. (2012) Longitudinal multistage model for lung cancer incidence, mortality, and CT detected indolent and aggressive cancers. Math Biosci 240:20-34
Kosoff, Rachelle E; Gardiner, Kristin L; Merlo, Lauren M F et al. (2012) Development and characterization of an organotypic model of Barrett's esophagus. J Cell Physiol 227:2654-9
Dewanji, Anup; Jeon, Jihyoun; Meza, Rafael et al. (2011) Number and size distribution of colorectal adenomas under the multistage clonal expansion model of cancer. PLoS Comput Biol 7:e1002213
Hazelton, William D; Luebeck, E Georg (2011) Biomarker-based early cancer detection: is it achievable? Sci Transl Med 3:109fs9
Meza, Rafael; Jeon, Jihyoun; Renehan, Andrew G et al. (2010) Colorectal cancer incidence trends in the United States and United kingdom: evidence of right- to left-sided biological gradients with implications for screening. Cancer Res 70:5419-29
Jean, Larry W; Suchorolski, Martin T; Jeon, Jihyoun et al. (2010) Multiscale estimation of cell kinetics. Comput Math Methods Med 11:239-54
Merlo, Lauren M F; Shah, Najaf A; Li, Xiaohong et al. (2010) A comprehensive survey of clonal diversity measures in Barrett's esophagus as biomarkers of progression to esophageal adenocarcinoma. Cancer Prev Res (Phila) 3:1388-97
Luebeck, E Georg; Moolgavkar, Suresh H; Liu, Amy Y et al. (2008) Does folic acid supplementation prevent or promote colorectal cancer? Results from model-based predictions. Cancer Epidemiol Biomarkers Prev 17:1360-7

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