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Delineating the evolutionary dynamics of cancer from theory to reality

Nature Cancer volume 1, pages 580–588 (2020)Cite this article

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Uncovering and quantifying the laws of the evolutionary dynamics of cancer, in particular in the context of specific genetic lesions and in individual patients, has the potential to revolutionize precision oncology. Recent technological advances in the study of human cancer have increased access to in vivo human data and have thereby facilitated the confirmation or refutation of existing theoretical models. In this Perspective, we discuss recent work at the intersection of quantitative mathematical models of cancer evolution and patient data that provides insights into different stages of tumor evolution, including premalignant and malignant progression and response to therapy.

Cancer is a disease of unwanted evolution in which somatic cells acquire mutations that allow them to bypass the sophisticated mechanisms that restrain proliferation and maintain the function and identity of the individual cells of a multicellular organism1. Childhood cancers and some leukemias may require only a single cancer-initiating mutation, but for the majority of adult cancers, multiple checkpoint mechanisms need to be disarmed; this is commonly achieved through multiple driver mutations2. Evolutionary forces are operating throughout the carcinogenic process, through the generation of new mutations that are constantly introduced into the cell population in a stochastic manner, as a consequence of errors in DNA replication and due to environmental factors3 and, finally, through selection of the fittest mutants. There are, however, multiple important differences between organismal evolution and cancer evolution4,5, including the limited time frame (on the order of years or decades) in which somatic evolution of cancer operates relative to that of the evolution of organisms, as well as the sizes of the relevant cell populations, mutation rates, selective advantages provided by mutations and the asexual nature of somatic evolution.

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Fig. 1: Studying the dynamics of cancer through mathematical models, model systems and patient data.
Fig. 2: Mathematical models of cancer initiation and progression.
Fig. 3: Studying evolutionary dynamics of cancer over time and under different conditions.

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Acknowledgements

This work was supported in part by the National Cancer Institute (1R01CA155010-01A1, P01CA206978, U10CA180861). C.J.W. is a Scholar of the Leukemia and Lymphoma Society.

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Authors and Affiliations

  1. Department of Applied Mathematics, University of Washington, Seattle, WA, USA

    Ivana Bozic

  2. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, MA, USA

    Catherine J. Wu

  3. Broad Institute of MIT and Harvard, Cambridge, MA, USA

    Catherine J. Wu

  4. Harvard Medical School, Boston, MA, USA

    Catherine J. Wu

  5. Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA

    Catherine J. Wu

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I.B. and C.J.W. conceived of and wrote this Perspective.

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Correspondence to Ivana Bozic.

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C.J.W. is founder of Neon Therapeutics and is a member of its scientific advisory board and receives research funding from Pharmacyclics.

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Bozic, I., Wu, C.J. Delineating the evolutionary dynamics of cancer from theory to reality. Nat Cancer 1, 580–588 (2020). https://doi.org/10.1038/s43018-020-0079-6

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