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Reply to ‘Revisiting signatures of neutral tumor evolution in the light of complexity of cancer genomic data’

Nature Genetics volume 50, pages 1628–1630 (2018)Cite this article

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Williams et al. reply — Balaparya and De1 question the applicability of the power-law neutral-evolution model to adequately describe the pattern of subclonal somatic mutations in bulk cancer sequencing data.

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Fig. 1: Signatures of neutral evolution are robust to confounding factors in the data.

Data availability

Gastric cancers from ref. 3 and colorectal cancers from ref. 4 were analyzed with our framework in our original manuscript2. The new TCGA pan-cancer analysis is based on publicly available GDC calls that can be downloaded from https://portal.gdc.cancer.gov/ (Supplementary Table 1).

References

  1. Balaparya, A. & De, S. Nat. Genet. https://doi.org/10.1038/s41588-018-0219-4 (2018).

  2. Williams, M. J., Werner, B., Barnes, C. P., Graham, T. A. & Sottoriva, A. Nat. Genet. 48, 238–244 (2016).

    Article  CAS  Google Scholar 

  3. Wang, K. et al. Nat. Genet. 46, 573–582 (2014).

    Article  CAS  Google Scholar 

  4. Sottoriva, A. et al. Nat. Genet. 47, 209–216 (2015).

    Article  CAS  Google Scholar 

  5. Aran, D., Sirota, M. & Butte, A. J. Nat. Commun. 6, 8971 (2015).

    Article  CAS  Google Scholar 

  6. Forbes, S. A. et al. Nucleic Acids Res. 45 D1, D777–D783 (2017).

    Article  Google Scholar 

  7. Sun, R. et al. Nat. Genet. 49, 1015–1024 (2017).

    Article  CAS  Google Scholar 

  8. Andor, N., Harness, J. V., Müller, S., Mewes, H. W. & Petritsch, C. Bioinformatics 30, 50–60 (2014).

    Article  CAS  Google Scholar 

  9. Williams, M. J. et al. Nat. Genet. 50, 895–903 (2018).

    Article  CAS  Google Scholar 

  10. Burrell, R. A., McGranahan, N., Bartek, J. & Swanton, C. Nature 501, 338–345 (2013).

    Article  CAS  Google Scholar 

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Acknowledgements

A.S. is supported by the Chris Rokos Fellowship in Evolution and Cancer and by Cancer Research UK (A22909). T.A.G. is supported by Cancer Research UK (A19771). C.P.B. is supported by the Wellcome Trust (097319/Z/11/Z). B.W. is supported by a Geoffrey W. Lewis Post-Doctoral Training fellowship. A.S. and T.A.G. are jointly supported by the Wellcome Trust (202778/B/16/Z and 202778/Z/16/Z, respectively). This work was also supported by Wellcome Trust funding to the Centre for Evolution and Cancer (105104/Z/14/Z).

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Authors and Affiliations

  1. Evolution and Cancer Laboratory, Barts Cancer Institute, Queen Marry University of London, London, UK

    Marc J. Williams & Trevor A. Graham

  2. Department of Cell and Developmental Biology, University College London, London, UK

    Marc J. Williams & Chris P. Barnes

  3. Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX), University College London, London, UK

    Marc J. Williams

  4. Evolutionary Genomics and Modelling Lab, Centre for Evolution and Cancer, the Institute of Cancer Research, London, UK

    Benjamin Werner, Timon Heide & Andrea Sottoriva

  5. Department of Genetics, Evolution and Environment, University College London, London, UK

    Chris P. Barnes

Authors
  1. Marc J. Williams
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Contributions

M.J.W. performed beta-binomial noise analysis. T.H. performed TCGA classification. All authors participated in the discussion and addressed the critiques. M.J.W., B.W., C.P.B., T.A.G., and A.S. wrote the manuscript.

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Correspondence to Trevor A. Graham or Andrea Sottoriva.

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The authors declare no competing interests.

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Williams, M.J., Werner, B., Heide, T. et al. Reply to ‘Revisiting signatures of neutral tumor evolution in the light of complexity of cancer genomic data’. Nat Genet 50, 1628–1630 (2018). https://doi.org/10.1038/s41588-018-0210-0

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