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dc.contributor.authorSottoriva, Aen_US
dc.contributor.authorVermeulen, Len_US
dc.contributor.authorTavaré, Sen_US
dc.identifier.citationPLoS computational biology, 2011, 7 (5), pp. e1001132 - ?en_US
dc.description.abstractThe cancer stem cell (CSC) concept is a highly debated topic in cancer research. While experimental evidence in favor of the cancer stem cell theory is apparently abundant, the results are often criticized as being difficult to interpret. An important reason for this is that most experimental data that support this model rely on transplantation studies. In this study we use a novel cellular Potts model to elucidate the dynamics of established malignancies that are driven by a small subset of CSCs. Our results demonstrate that epigenetic mutations that occur during mitosis display highly altered dynamics in CSC-driven malignancies compared to a classical, non-hierarchical model of growth. In particular, the heterogeneity observed in CSC-driven tumors is considerably higher. We speculate that this feature could be used in combination with epigenetic (methylation) sequencing studies of human malignancies to prove or refute the CSC hypothesis in established tumors without the need for transplantation. Moreover our tumor growth simulations indicate that CSC-driven tumors display evolutionary features that can be considered beneficial during tumor progression. Besides an increased heterogeneity they also exhibit properties that allow the escape of clones from local fitness peaks. This leads to more aggressive phenotypes in the long run and makes the neoplasm more adaptable to stringent selective forces such as cancer treatment. Indeed when therapy is applied the clone landscape of the regrown tumor is more aggressive with respect to the primary tumor, whereas the classical model demonstrated similar patterns before and after therapy. Understanding these often counter-intuitive fundamental properties of (non-)hierarchically organized malignancies is a crucial step in validating the CSC concept as well as providing insight into the therapeutical consequences of this model.en_US
dc.format.extente1001132 - ?en_US
dc.subjectMonte Carlo Methoden_US
dc.subjectStochastic Processesen_US
dc.subjectEvolution, Molecularen_US
dc.subjectDNA Methylationen_US
dc.subjectEpigenesis, Geneticen_US
dc.subjectModels, Geneticen_US
dc.subjectComputer Simulationen_US
dc.subjectNeoplastic Stem Cellsen_US
dc.subjectCell Physiological Processesen_US
dc.subjectGenetic Fitnessen_US
dc.titleModeling evolutionary dynamics of epigenetic mutations in hierarchically organized tumors.en_US
dc.typeJournal Article
rioxxterms.typeJournal Article/Reviewen_US
dc.relation.isPartOfPLoS computational biologyen_US
pubs.notes6 monthsen_US
pubs.organisational-group/ICR/Primary Group
pubs.organisational-group/ICR/Primary Group/ICR Divisions
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology
pubs.organisational-group/ICR/Primary Group/ICR Divisions/Molecular Pathology/Evolutionary Genomics & Modelling
pubs.embargo.terms6 monthsen_US
icr.researchteamEvolutionary Genomics & Modellingen_US
dc.contributor.icrauthorSottoriva, Andreaen_US

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