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Neutral tumor evolution?

Nature Genetics volume 50, pages 1630–1633 (2018)Cite this article

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To the Editor — Tumor growth is an evolutionary process that is governed by somatic mutation, clonal selection and random genetic drift, and is constrained by the coevolution of the microenvironment1,2. Tumor subclones are subpopulations of tumor cells with a common set of mutations resulting from the expansion of a single cell during tumor development, and they have been observed in a substantial fraction of cancers and across multiple cancer types3. Peter Nowell has proposed that tumors evolve through sequential genetic events4, whereby one cell acquires a selective advantage so that its lineage becomes predominant. According to this traditional model, the selective advantage is conferred by a small set of driver mutations, but as the subclones that bear them successively expand, they also accumulate passenger mutations, which can be detected in sequencing experiments1. Genomes of individual tumors contain hundreds to many thousands of these genetic variants at a wide range of frequencies5,6. Because genetic drift can drive novel variants to high frequencies, it is of great interest to discern the relative importance of selection and drift in shaping the frequency distribution of variants in any given tumor.

Williams et al.7 have recently proposed a way to assess this relative importance. They have found that a simple model of tumor growth in which all novel variants are selectively neutral, that is, whose dynamics are governed entirely by drift, predicts a linear relationship between the number of mutations \(M\left( f \right)\) present in a fraction f of cells and the reciprocal of that fraction: \(M\left( f \right) \propto \frac{1}{f}\). They argue that deviation from this null model (i.e., if the R 2 of the linear fit is below the minimum observed in neutral simulations (R 2 <0.98)) indicates the presence of selection. Such selection can be tested by means of variant allele frequencies (VAFs) from which f can be derived. By applying this rationale to real cancer data from The Cancer Genome Atlas (TCGA), the test proposed by Williams et al. did not reject the null model (that is, neutrality was found) in approximately one-third of the cases, and the authors have concluded that those tumors were neutrally evolving. More recently, multiple myelomas with evidence of the proposed linear relationship have been associated with poorer prognosis8.

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Fig. 1: M(f) ~ 1/f is an uninformative test for identifying (non-)neutrality in simulated and real data.

Data availability

This study used data generated by the The Cancer Genome Atlas (TCGA, a collection of publicly available data from human tissues; http://cancergenome.nih.gov/). We ran dN/dS analyses on the data from TCGA, using published CaVeMan19,20 single-nucleotide variant calls, and ASCAT21 copy number calls, as described in Martincorena et al.13. Simulation data can be reproduced by using the R and Java scripts provided.

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Acknowledgements

This work was supported by The Francis Crick Institute, which receives its core funding from Cancer Research UK (FC001202), the UK Medical Research Council (FC001202) and the Wellcome Trust (FC001202) (M.T. and P.V.L.). M.T. is supported as a postdoctoral fellow by the European Union’s Horizon 2020 research and innovation program (Marie Skłodowska-Curie Grant agreement no. 747852-SIOMICS). P.V.L. is a Winton Group Leader in recognition of the Winton Charitable Foundation’s support toward the establishment of The Francis Crick Institute. I.M. is funded by a Cancer Research UK Career Development Fellowship (C57387/A21777). D.C.W. is funded by the Li Ka Shing Foundation. This work was supported by grant 1U24CA210957 to P.T.S.. F.M. acknowledges support from the University of Cambridge, Cancer Research UK and Hutchison Whampoa Limited. Parts of this work were funded by Cancer Research UK core grant C14303/A17197 (F.M.). This project was enabled through access to the MRC eMedLab Medical Bioinformatics infrastructure, supported by the UK Medical Research Council (grant no. MR/L016311/1) (M.T. and P.V.L.). Parts of the results published here are based on data generated by the TCGA Research Network (http://cancergenome.nih.gov/).

Author information

Author notes

  1. A list of members and affiliations appears at the end of the paper.

Authors and Affiliations

  1. The Francis Crick Institute, London, UK

    Maxime Tarabichi, Stefan C. Dentro, Clemency Jolly, Kerstin Haase, Maxime Tarabichi, Jonas Demeulemeester, Matthew Fittall, Peter Van Loo & Peter Van Loo

  2. Wellcome Trust Sanger Institute, Cambridge, UK

    Maxime Tarabichi, Iñigo Martincorena, Stefan C. Dentro, Maxime Tarabichi, David J. Adams, Peter J. Campbell, Kevin J. Dawson, Henry Lee-Six, Iñigo Martincorena, Thomas J. Mitchell & Ignacio Vázquez-García

  3. European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, UK

    Moritz Gerstung, Moritz Gerstung, Santiago Gonzalez & Lara Jerman

  4. Department of Life Sciences, Imperial College London, London, UK

    Armand M. Leroi

  5. Cancer Research UK Cambridge Institute, University of Cambridge, Cambridge, UK

    Florian Markowetz, Geoff Macintyre, Ruben M. Drews, Florian Markowetz & Ke Yuan

  6. Molecular and Medical Genetics, Oregon Health & Science University, Portland, OR, USA

    Pavana Anur, Myron Peto, Paul T. Spellman & Paul T. Spellman

  7. Donnelly Centre, University of Toronto and Vector Institute, Toronto, Ontario, Canada

    Quaid D. Morris

  8. Department of Informatics and Centre for Cancer Biomedicine, University of Oslo, Oslo, Norway

    Ole Christian Lingjærde

  9. Big Data Institute, University of Oxford, Oxford, UK

    Stefan C. Dentro, David C. Wedge & David C. Wedge

  10. Oxford NIHR Biomedical Research Centre, Oxford, UK

    David C. Wedge & David C. Wedge

  11. Department of Human Genetics, University of Leuven, Leuven, Belgium

    Peter Van Loo & Peter Van Loo

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

    Ignaty Leshchiner, Rameen Beroukhim, Gad Getz, Gavin Ha, Dimitri G. Livitz, Daniel Rosebrock & Steven Schumacher

  13. University of Toronto, Toronto, Ontario, Canada

    Jeff Wintersinger, Amit G. Deshwar, Yulia Rubanova, Paul C. Boutros, Ruian Shi, Shankar Vembu & Quaid D. Morris

  14. Vector Institute, Toronto, Ontario, Canada

    Jeff Wintersinger, Amit G. Deshwar, Yulia Rubanova & Quaid D. Morris

  15. University of Texas MD Anderson Cancer Center, Houston, TX, USA

    Kaixian Yu, Shaolong Cao, Yu Fan, Seung Jun Shin, Hongtu Zhu & Wenyi Wang

  16. Dana-Farber Cancer Institute, Boston, MA, USA

    Rameen Beroukhim

  17. Ontario Institute for Cancer Research, Toronto, Ontario, Canada

    Paul C. Boutros, Adriana Salcedo & Lincoln D. Stein

  18. Peter MacCallum Cancer Centre, Melbourne, Victoria, Australia

    David D. Bowtell, Elizabeth L. Christie & Dale W. Garsed

  19. University of Melbourne, Melbourne, Victoria, Australia

    Elizabeth L. Christie, Marek Cmero & Dale W. Garsed

  20. Walter and Eliza Hall Institute, Melbourne, Victoria, Australia

    Marek Cmero

  21. University of Cologne, Cologne, Germany

    Yupeng Cun, Martin Peifer & Tsun-Po Yang

  22. University of Leuven, Leuven, Belgium

    Jonas Demeulemeester

  23. Simon Fraser University, Burnaby, British Columbia, Canada

    Nilgun Donmez & Salem Malikic

  24. Vancouver Prostate Centre, Vancouver, British Columbia, Canada

    Nilgun Donmez, Salem Malikic & S. Cenk Sahinalp

  25. German Cancer Research Center (DKFZ), Heidelberg, Germany

    Roland Eils, Kortine Kleinheinz & Matthias Schlesner

  26. Heidelberg University, Heidelberg, Germany

    Roland Eils & Kortine Kleinheinz

  27. Massachusetts General Hospital Center for Cancer Research, Charlestown, MA, USA

    Gad Getz

  28. Massachusetts General Hospital, Department of Pathology, Boston, MA, USA

    Gad Getz

  29. Harvard Medical School, Boston, MA, USA

    Gad Getz

  30. Weill Cornell Medicine, New York, NY, USA

    Marcin Imielinski & Xiaotong Yao

  31. New York Genome Center, New York, NY, USA

    Marcin Imielinski & Xiaotong Yao

  32. University of Ljubljana, Ljubljana, Slovenia

    Lara Jerman

  33. NorthShore University HealthSystem, Evanston, IL, USA

    Yuan Ji & Subhajit Sengupta

  34. University of Chicago, Chicago, IL, USA

    Yuan Ji

  35. University of California Santa Cruz, Santa Cruz, CA, USA

    Juhee Lee

  36. University of Cambridge, Cambridge, UK

    Thomas J. Mitchell & Ignacio Vázquez-García

  37. University of Helsinki, Helsinki, Finland

    Ville Mustonen

  38. Carleton College, Northfield, MN, USA

    Layla Oesper

  39. Princeton University, Princeton, NJ, USA

    Benjamin J. Raphael

  40. Indiana University, Bloomington, IN, USA

    S. Cenk Sahinalp

  41. Korea University, Seoul, Republic of Korea

    Seung Jun Shin

  42. Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA

    David A. Wheeler

  43. University of Glasgow, Glasgow, UK

    Ke Yuan

Authors
  1. Maxime Tarabichi
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  2. Iñigo Martincorena
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  3. Moritz Gerstung
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  4. Armand M. Leroi
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  5. Florian Markowetz
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  6. Paul T. Spellman
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  7. Quaid D. Morris
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  8. Ole Christian Lingjærde
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  9. David C. Wedge
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  10. Peter Van Loo
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Consortia

The PCAWG Evolution and Heterogeneity Working Group

  • Stefan C. Dentro
  • , Ignaty Leshchiner
  • , Moritz Gerstung
  • , Clemency Jolly
  • , Kerstin Haase
  • , Maxime Tarabichi
  • , Jeff Wintersinger
  • , Amit G. Deshwar
  • , Kaixian Yu
  • , Santiago Gonzalez
  • , Yulia Rubanova
  • , Geoff Macintyre
  • , David J. Adams
  • , Pavana Anur
  • , Rameen Beroukhim
  • , Paul C. Boutros
  • , David D. Bowtell
  • , Peter J. Campbell
  • , Shaolong Cao
  • , Elizabeth L. Christie
  • , Marek Cmero
  • , Yupeng Cun
  • , Kevin J. Dawson
  • , Jonas Demeulemeester
  • , Nilgun Donmez
  • , Ruben M. Drews
  • , Roland Eils
  • , Yu Fan
  • , Matthew Fittall
  • , Dale W. Garsed
  • , Gad Getz
  • , Gavin Ha
  • , Marcin Imielinski
  • , Lara Jerman
  • , Yuan Ji
  • , Kortine Kleinheinz
  • , Juhee Lee
  • , Henry Lee-Six
  • , Dimitri G. Livitz
  • , Salem Malikic
  • , Florian Markowetz
  • , Iñigo Martincorena
  • , Thomas J. Mitchell
  • , Ville Mustonen
  • , Layla Oesper
  • , Martin Peifer
  • , Myron Peto
  • , Benjamin J. Raphael
  • , Daniel Rosebrock
  • , S. Cenk Sahinalp
  • , Adriana Salcedo
  • , Matthias Schlesner
  • , Steven Schumacher
  • , Subhajit Sengupta
  • , Ruian Shi
  • , Seung Jun Shin
  • , Lincoln D. Stein
  • , Ignacio Vázquez-García
  • , Shankar Vembu
  • , David A. Wheeler
  • , Tsun-Po Yang
  • , Xiaotong Yao
  • , Ke Yuan
  • , Hongtu Zhu
  • , Wenyi Wang
  • , Quaid D. Morris
  • , Paul T. Spellman
  • , David C. Wedge
  •  & Peter Van Loo

Contributions

M.T., I.M., M.G., A.M.L., F.M., P.T.S., Q.D.M., O.C.L., D.C.W. and P.V.L. participated in argumentation. M.T., O.C.L., D.C.W. and P.V.L. derived the deterministic equations. M.T. wrote the code and generated the figures, with input from I.M., M.G., O.C.L., D.C.W. and P.V.L.; M.T., O.C.L., D.C.W. and P.V.L. drafted the manuscript, which was revised by I.M., M.G., A.M.L., F.M., P.T.S. and Q.D.M. All authors read and approved the manuscript.

Corresponding author

Correspondence to Peter Van Loo.

Supplementary information

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Tarabichi, M., Martincorena, I., Gerstung, M. et al. Neutral tumor evolution?. Nat Genet 50, 1630–1633 (2018). https://doi.org/10.1038/s41588-018-0258-x

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