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Clonal evolution driven by superdriver mutations

BACKGROUND: Tumors are widely recognized to progress through clonal evolution by sequentially acquiring selectively advantageous genetic alterations that significantly contribute to tumorigenesis and thus are termned drivers. Some cancer drivers, such as TP53 point mutation or EGFR copy number gain,...

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Autores principales: Grossmann, Patrick, Cristea, Simona, Beerenwinkel, Niko
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7370525/
https://www.ncbi.nlm.nih.gov/pubmed/32689942
http://dx.doi.org/10.1186/s12862-020-01647-y
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author Grossmann, Patrick
Cristea, Simona
Beerenwinkel, Niko
author_facet Grossmann, Patrick
Cristea, Simona
Beerenwinkel, Niko
author_sort Grossmann, Patrick
collection PubMed
description BACKGROUND: Tumors are widely recognized to progress through clonal evolution by sequentially acquiring selectively advantageous genetic alterations that significantly contribute to tumorigenesis and thus are termned drivers. Some cancer drivers, such as TP53 point mutation or EGFR copy number gain, provide exceptional fitness gains, which, in time, can be sufficient to trigger the onset of cancer with little or no contribution from additional genetic alterations. These key alterations are called superdrivers. RESULTS: In this study, we employ a Wright-Fisher model to study the interplay between drivers and superdrivers in tumor progression. We demonstrate that the resulting evolutionary dynamics follow global clonal expansions of superdrivers with periodic clonal expansions of drivers. We find that the waiting time to the accumulation of a set of superdrivers and drivers in the tumor cell population can be approximated by the sum of the individual waiting times. CONCLUSIONS: Our results suggest that superdriver dynamics dominate over driver dynamics in tumorigenesis. Furthermore, our model allows studying the interplay between superdriver and driver mutations both empirically and theoretically.
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spelling pubmed-73705252020-07-21 Clonal evolution driven by superdriver mutations Grossmann, Patrick Cristea, Simona Beerenwinkel, Niko BMC Evol Biol Methodology Article BACKGROUND: Tumors are widely recognized to progress through clonal evolution by sequentially acquiring selectively advantageous genetic alterations that significantly contribute to tumorigenesis and thus are termned drivers. Some cancer drivers, such as TP53 point mutation or EGFR copy number gain, provide exceptional fitness gains, which, in time, can be sufficient to trigger the onset of cancer with little or no contribution from additional genetic alterations. These key alterations are called superdrivers. RESULTS: In this study, we employ a Wright-Fisher model to study the interplay between drivers and superdrivers in tumor progression. We demonstrate that the resulting evolutionary dynamics follow global clonal expansions of superdrivers with periodic clonal expansions of drivers. We find that the waiting time to the accumulation of a set of superdrivers and drivers in the tumor cell population can be approximated by the sum of the individual waiting times. CONCLUSIONS: Our results suggest that superdriver dynamics dominate over driver dynamics in tumorigenesis. Furthermore, our model allows studying the interplay between superdriver and driver mutations both empirically and theoretically. BioMed Central 2020-07-20 /pmc/articles/PMC7370525/ /pubmed/32689942 http://dx.doi.org/10.1186/s12862-020-01647-y Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology Article
Grossmann, Patrick
Cristea, Simona
Beerenwinkel, Niko
Clonal evolution driven by superdriver mutations
title Clonal evolution driven by superdriver mutations
title_full Clonal evolution driven by superdriver mutations
title_fullStr Clonal evolution driven by superdriver mutations
title_full_unstemmed Clonal evolution driven by superdriver mutations
title_short Clonal evolution driven by superdriver mutations
title_sort clonal evolution driven by superdriver mutations
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7370525/
https://www.ncbi.nlm.nih.gov/pubmed/32689942
http://dx.doi.org/10.1186/s12862-020-01647-y
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