- Author:
- Tessa Paris <tpar054@aucklanduni.ac.nz>
- Date:
- 2010-02-19 14:31:42+13:00
- Desc:
- Changed the abstract
- Permanent Source URI:
- https://models.cellml.org/workspace/komarova_wodarz_2003/rawfile/1eed08c1928d0ec0c7390c0595211d7d1f09622e/komarova_wodarz_2003.cellml
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<!-- FILE : komarova_model_2003.xml
CREATED : 18th December 2003
LAST MODIFIED : 18th December 2003
AUTHOR : Catherine Lloyd
Bioengineering Institute
The University of Auckland
MODEL STATUS : This model conforms to the CellML 1.0 Specification released on
10th August 2001, and the 16/1/02 CellML Metadata 1.0 Specification.
DESCRIPTION : This file contains a CellML description of Komarova and Wodarz's 2003 mathematical model of the evolutionary dynamics of mutator phenotypes in cancer.
CHANGES:
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<title>Modelling the Evolutionary Dynamics of Mutator Phenotypes in Cancer</title>
<author>
<firstname>Catherine</firstname>
<surname>Lloyd</surname>
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<shortaffil>Bioengineering Institute, University of Auckland</shortaffil>
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This is the original unchecked version of the model imported from the previous
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<para>
Eukaryotic cells tend to maintain stable genomes. When DNA is damaged, for example due to environmental agents or free radicals, checkpoint genes detect the damage, delay the cell cycle and then correct the damage. By contrast, cancers are genetically unstable. High mutation rates are connected to the fact that the checkpoint genes in cancerous cells are corrupted. An understanding of the evolutionary dynamics of mutator phenotypes and stable cell populations will allow insight into cancer development and also the possible therapeutic treatments.
</para>
<para>
Both genetic stability and instability can confer advantages and disadvantages for the cells. Stable replication ensures that the phenotype of the cell is maintained, and that deleterious mutations are avoided. However, the induction of checkpoints in stable cells can result in cell cycle arrest, which is a cost. Alternatively, an absence of checkpoints avoids cell cycle arrest, but it can result in deleterious mutations which reduce the overall fitness of the cell.
</para>
<para>
In the study described here, Komarova and Wodarz develop a mathematical model to analyse the dynamic interactions between stable and unstable cell populations (see <xref linkend="fig_cell_diagram"/> below). A main aim was to gain a better understanding of how the extent of the DNA damage experienced by the tissue can influence the relative fitness of the mutator phenotypes. This in turn would lead to an improved understanding of the processes underlying cancer progression, and chemotherapeutic and radiation approaches to cancer treatment.
</para>
<para>
The model has been described here in CellML (the raw CellML description of the Komarova and Wodarz 2003 model can be downloaded in various formats as described in <xref linkend="sec_download_this_model"/>).
</para>
<para>
The complete original paper reference is cited below:
</para>
<para>
Evolutionary Dynamics of Mutator Phenotypes in Cancer: Implications for Chemotherapy, Natalia L. Komarova and Dominik Wodarz, 2003,<emphasis>Cancer Research</emphasis>, 63, 6635-6642. <ulink url="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?cmd=Retrieve&db=PubMed&list_uids=14583456&dopt=Abstract">PubMed ID: 14583456</ulink>
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<caption>Schematic diagram of the model, showing the processes of cell reproduction, DNA damage, repair, cell cycle arrest, mutation and death.</caption>
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Evolutionary Dynamics of Mutator Phenotypes in Cancer: Implications for Chemotherapy
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