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Evolutionary dynamics of tumor progression with random fitness values

Author

Listed:
  • Durrett, Rick
  • Foo, Jasmine
  • Leder, Kevin
  • Mayberry, John
  • Michor, Franziska

Abstract

Most human tumors result from the accumulation of multiple genetic and epigenetic alterations in a single cell. Mutations that confer a fitness advantage to the cell are known as driver mutations and are causally related to tumorigenesis. Other mutations, however, do not change the phenotype of the cell or even decrease cellular fitness. While much experimental effort is being devoted to the identification of the functional effects of individual mutations, mathematical modeling of tumor progression generally considers constant fitness increments as mutations are accumulated. In this paper we study a mathematical model of tumor progression with random fitness increments. We analyze a multi-type branching process in which cells accumulate mutations whose fitness effects are chosen from a distribution. We determine the effect of the fitness distribution on the growth kinetics of the tumor. This work contributes to a quantitative understanding of the accumulation of mutations leading to cancer.

Suggested Citation

  • Durrett, Rick & Foo, Jasmine & Leder, Kevin & Mayberry, John & Michor, Franziska, 2010. "Evolutionary dynamics of tumor progression with random fitness values," Theoretical Population Biology, Elsevier, vol. 78(1), pages 54-66.
    • Handle: RePEc:eee:thpobi:v:78:y:2010:i:1:p:54-66
    DOI: 10.1016/j.tpb.2010.05.001
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    References listed on IDEAS

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    1. Durrett, Richard & Moseley, Stephen, 2010. "Evolution of resistance and progression to disease during clonal expansion of cancer," Theoretical Population Biology, Elsevier, vol. 77(1), pages 42-48.
    2. R Craig MacLean & Angus Buckling, 2009. "The Distribution of Fitness Effects of Beneficial Mutations in Pseudomonas aeruginosa," PLOS Genetics, Public Library of Science, vol. 5(3), pages 1-7, March.
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    Cited by:

    1. Foo, Jasmine & Leder, Kevin & Schweinsberg, Jason, 2020. "Mutation timing in a spatial model of evolution," Stochastic Processes and their Applications, Elsevier, vol. 130(10), pages 6388-6413.
    2. Delitala, Marcello & Lorenzi, Tommaso, 2011. "A mathematical model for progression and heterogeneity in colorectal cancer dynamics," Theoretical Population Biology, Elsevier, vol. 79(4), pages 130-138.
    3. Hwai-Ray Tung & Rick Durrett, 2021. "Signatures of neutral evolution in exponentially growing tumors: A theoretical perspective," PLOS Computational Biology, Public Library of Science, vol. 17(2), pages 1-12, February.
    4. Foo, Jasmine & Leder, Kevin & Zhu, Junfeng, 2014. "Escape times for branching processes with random mutational fitness effects," Stochastic Processes and their Applications, Elsevier, vol. 124(11), pages 3661-3697.
    5. Casabán, M.-C. & Company, R. & Egorova, V.N. & Jódar, L., 2024. "A random free-boundary diffusive logistic differential model: Numerical analysis, computing and simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 221(C), pages 55-78.

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