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A deterministic model for the occurrence and dynamics of multiple mutations in hierarchically organized tissues

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons56995

Werner,  Benjamin
Research Group Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons56973

Traulsen,  Arne
Research Group Evolutionary Theory, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Werner_2013.pdf
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Zitation

Werner, B., Dingli, D., & Traulsen, A. (2013). A deterministic model for the occurrence and dynamics of multiple mutations in hierarchically organized tissues. Journal of the Royal Society Interface, 10(85): 20130349. doi:10.1098/rsif.2013.0349.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-0013-AA99-0
Zusammenfassung
Cancers are rarely caused by single mutations, but often develop as a result of the combined effects of multiple mutations. For most cells, the number of possible cell divisions is limited because of various biological constraints, such as progressive telomere shortening, cell senescence cascades or a hierarchically organized tissue structure. Thus, the risk of accumulating cells carrying multiple mutations is low. Nonetheless, many diseases are based on the accumulation of such multiple mutations. We model a general, hierarchically organized tissue by a multi-compartment approach, allowing any number of mutations within a cell. We derive closed solutions for the deterministic clonal dynamics and the reproductive capacity of single clones. Our results hold for the average dynamics in a hierarchical tissue characterized by an arbitrary combination of proliferation parameters. We show that hierarchically organized tissues strongly suppress cells carrying multiple mutations and derive closed solutions for the expected size and diversity of clonal populations founded by a single mutant within the hierarchy. We discuss the example of childhood acute lymphoblastic leukaemia in detail and find good agreement between our predicted results and recently observed clonal diversities in patients. This result can contribute to the explanation of very diverse mutation profiles observed by whole genome sequencing of many different cancers.