2004 Fiscal Year Final Research Report Summary
Mathematical Models for Carcinogenesis Based on the Evidence of Molecular Biology and Its Application to Data Analysis
| Project/Area Number |
14380123
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Statistical science
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| Research Institution | HIROSHIMA UNIVERSITY |
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Principal Investigator |
OHTAKI Megu Hiroshima University, Research Institute for Radiation Biology and Medicine, Professor, 原爆放射線医科学研究所, 教授 (20110463)
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| Co-Investigator(Kenkyū-buntansha) |
KAI Mitiaki Oita University of Nursing and Health Sciences, Faculty of Health Sciences, Professor, 看護学部, 教授 (10185697)
IZUMI Shizue Oita University, Faculty of Technique, Associate Professor, 工学部, 助教授 (70344413)
SATOH Kenichi Hiroshima University, Research Institute for Radiation Biology and Medicine, Assistant Professor, 原爆放射線医科学研究所, 講師 (30284219)
NIWA Ohtsura Kyoto University, Radiation Biology Center, Professor, 放射線生物研究センター, 教授 (80093293)
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| Project Period (FY) |
2002 – 2004
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| Keywords | Multi-target model / Apoptsis / Individual difference / Dose-response / Age-dependency / Genomic instabnility |
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| Research Abstract |
We developed multistage models of carcinogenesis and cell death with taking account the effect of genomic instability. As for Armitage-Doll type of multistage models for carcinogenesis, some Monte Carlo simulations on the relationship between the number of stages and mutation rate were done. Using the follow-up data among atomic-bomb survivors and offspring, we examined the property of the models.
The classical multi-target models have been also considered for use in analyzing data of the dose-response relationship. We tried to make some extended models. The target sizes we are concerned with are heterogeneous as simplified using geometric progression. We apply two models for establishing the multi-target models: a Poisson regression model constructed by assuming that the response variable follows Poisson distribution, and a gamma-frailty model as a Poisson mixture model derived by adding random common risks having a gamma distribution.
Based on the theoretical results of our study, we developed several computer programs for analyzing dose-response data, and applied them to many sort of real data sets related to animal experiments, clinical researches and epidemiological studies including atomic bomb survivor's cohort data.
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