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A computational model for colon cancer dynamics

Roznovat, Irina-Afrodita (2014) A computational model for colon cancer dynamics. PhD thesis, Dublin City University.

Abstract
Cancer, a class of diseases, characterized by abnormal cell growth, has demonstrably high impact on human life: complex lifestyle changes, caused by malignancy, affect not only patients, but also family and friends. Cancer development has been linked to genetic and epigenetic abnormalities that affect the regulation of key genes that control cellular mechanisms. These alterations, which target stem cells, may be different or less immediately adverse from one person to another, as various risk factors are cumulative and variable in effect. However, a major issue in cancer research is the lack of precise information on tumour pathways; therefore the delineation of these and of the processes underlying disease proliferation is an important area of investigation. Here, we present a hybrid computational model following a multi-scale approach, which has been developed for colorectal cancer dynamics by linking information from micromolecular to cellular and tissue levels, (e.g. epigenetic events, stem cells, intestinal crypts). The current work aims to i) investigate genetic and epigenetic interdependencies leading to colon cancer initiation and progression; ii) to analyse influence of different risk factors at both molecular and cellular levels during cancer development; iii) to examine aberrant DNA methylation variation in malignant intestinal systems; iv) to evaluate the effect of inhibiting methylation modifications in abnormal colon crypts over time; and v) to assess the impact of deregulations in intestinal crypt dynamics with respect to tumour development. Given its crucial role in cancer development, DNA methylation is the main feature of the colorectal cancer model. Computational modelling is performed at different levels. A network-based model, namely the Epigenetic-Genetic (E-G) Network Model, has been developed to explore interdependencies between genetic and epigenetic events, recorded at different stages of colorectal cancer, (with a focus on gene relationships and tumour pathways). Micro-molecular modifications are studied in relation to ageing and gender, considered to be major risk factors in cancer development. Further, an agent-based model, AgentCrypt, with agents representing three cell types: stem, progenitor and differentiated cells in the colon (and with addition of a Paneth cell group in small intestine), has been developed to describe the dynamics of the intestinal crypt. Comparative analysis on methylation variation between colon and small intestine crypts during cancer initiation and under carcinogen influence is performed. A further extension concentrates on analysing the impact of potential inhibitors on methylation level in the intestinal crypt. Finally, a logistic model, LogisticCrypt, (focusing on cell division, differentiation and apoptosis rates and on cell competition related to the intestinal crypt space), has been built to provide information on the crypt structure at specific time points and to investigate time-intervals to occurrence of major crypt phenomena (such as ‘crypt fission’ and the ‘bottleneck effect’), due to deregulations in intestinal cell number.
Metadata
Item Type:Thesis (PhD)
Date of Award:November 2014
Refereed:No
Supervisor(s):Ruskin, Heather J. and Perrin, Dimitri
Uncontrolled Keywords:Epigenetic and Genetic events; Colon Cancer Modelling; Hybrid computational model; Bayesian network; Agent-based; Logistic model.
Subjects:Biological Sciences > Bioinformatics
Computer Science > Machine learning
Computer Science > Computer simulation
DCU Faculties and Centres:DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Use License:This item is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 License. View License
Funders:CIESCI ERA Net Complexity Project, (EC/IRCSET), the Embark Initiative from the Irish Research Council
ID Code:20212
Deposited On:04 Dec 2014 11:05 by Heather Ruskin . Last Modified 19 Jul 2018 15:04
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