Abstract

The sequencing of cancer genomes may enable tailoring of therapeutics to the underlying biological abnormalities driving a particular patient's tumor. However, sequencing-based strategies rely heavily on representative sampling of tumors. To understand the subclonal structure of primary breast cancer, we applied whole-genome and targeted sequencing to multiple samples from each of 50 patients' tumors (303 samples in total). The extent of subclonal diversification varied among cases and followed spatial patterns. No strict temporal order was evident, with point mutations and rearrangements affecting the most common breast cancer genes, including PIK3CA, TP53, PTEN, BRCA2 and MYC, occurring early in some tumors and late in others. In 13 out of 50 cancers, potentially targetable mutations were subclonal. Landmarks of disease progression, such as resistance to chemotherapy and the acquisition of invasive or metastatic potential, arose within detectable subclones of antecedent lesions. These findings highlight the importance of including analyses of subclonal structure and tumor evolution in clinical trials of primary breast cancer.

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Acknowledgements

This work is supported by the Wellcome Trust. P.J.C. is a Wellcome Trust Senior Clinical Fellow (103858/Z/14/Z). L.R.Y., Y.L. and L.B.A. are funded by Wellcome Trust PhD fellowships. S.N.-Z. is funded by a Wellcome Trust Intermediate Clinical Research Fellowship (WT100183MA). P.V.L. is a postdoctoral researcher at the Research Foundation Flanders (FWO). Work within the project is supported by the Belgian Cancer Plan–Ministry of Health, the Breast Cancer Research Foundation, the Brussels Region, the Norwegian Cancer Society, the Norwegian Health Region West and the Bergen Research Foundation. Some samples referenced in this publication will be included in the Breast Cancer Genome Analyses for the International Cancer Genome Consortium (ICGC) Working Group led by the Wellcome Trust Sanger Institute. BASIS is a part of the ICGC working group and is funded by the European Community's Seventh Framework Programme (FP7/2010-2014) under grant agreement number 242006. This working group also encompasses a triple-negative breast cancer project funded by the Wellcome Trust (grant 077012/Z/05/Z) and a HER2+ breast cancer project funded by Institut National du Cancer (INCa). We thank B. Leirvaag, D. Ekse, N.K. Duong and C. Eriksen for technical assistance. Research performed at Los Alamos National Laboratory was carried out under the auspices of the National Nuclear Security Administration of the US Department of Energy.

Author information

Affiliations

  1. Cancer Genome Project, Wellcome Trust Sanger Institute, Hinxton, UK.

    • Lucy R Yates
    • , Moritz Gerstung
    • , Gunes Gundem
    • , Peter Van Loo
    • , Ludmil B Alexandrov
    • , Helen Davies
    • , Yilong Li
    • , Young Seok Ju
    • , Manasa Ramakrishna
    • , Serena Nik-Zainal
    • , Stuart McLaren
    • , Adam Butler
    • , Sancha Martin
    • , Dominic Glodzik
    • , Andrew Menzies
    • , Keiran Raine
    • , Jonathan Hinton
    • , David Jones
    • , Laura J Mudie
    • , Michael R Stratton
    • , David C Wedge
    •  & Peter J Campbell
  2. Department of Oncology, The University of Cambridge, Cambridge, UK.

    • Lucy R Yates
  3. Section of Oncology, Department of Clinical Science, University of Bergen, Bergen, Norway.

    • Stian Knappskog
    •  & Per Eystein Lønning
  4. Department of Oncology, Haukeland University Hospital, Bergen, Norway.

    • Stian Knappskog
    •  & Per Eystein Lønning
  5. Breast Cancer Translational Research Laboratory, Institut Jules Bordet, Université Libre de Bruxelles, Brussels, Belgium.

    • Christine Desmedt
    • , Denis Larsimont
    • , Delphine Vincent
    • , Pierre-Yves Adnet
    • , Marion Maetens
    • , Michail Ignatiadis
    •  & Christos Sotiriou
  6. Department of Human Genetics, University of Leuven, Leuven, Belgium.

    • Peter Van Loo
  7. Department of Surgery, Haukeland University Hospital, Bergen, Norway.

    • Turid Aas
  8. Theoretical Division, Los Alamos National Laboratory, Los Alamos, New Mexico, USA.

    • Ludmil B Alexandrov
  9. Department of Pathology, Haukeland University Hospital, Bergen, Norway.

    • Hans Kristian Haugland
    •  & Peer Kaare Lilleng
  10. The Gade Laboratory for Pathology, Department of Clinical Medicine, University of Bergen, Bergen, Norway.

    • Peer Kaare Lilleng
  11. Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

    • Bing Jiang
    • , April Greene-Colozzi
    • , Aquila Fatima
    •  & Andrea L Richardson
  12. Brigham and Women's Hospital, Harvard Medical School, Boston, Massachusetts, USA.

    • Andrea L Richardson

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Contributions

L.R.Y. and P.J.C. designed and directed the study and prepared the manuscript. L.R.Y. and M.G. performed analyses and prepared figures. S.K., T.A. and P.E.L. contributed to the study design and sample preparation for cohort 1. C.D., C.S., M.I. and M.M. contributed to the study design and sample preparation for cohort 2. D.C.W., P.V.L., G.G., H.D., Y.S.J., S. McLaren, M.R., S.N.-Z., A.B., D.G., A.M., K.R., J.H., D.J., M.R.S., Y.L. and L.B.A. contributed to analysis. S. Martin managed samples. A.L.R., D.L., H.K.H. and P.K.L. conducted histopathological assessment. P.-Y.A., D.V., B.J., A.G.-C. and A.F. performed DNA extraction. L.J.M. contributed to library preparation, PCR and gel electrophoresis.

Competing interests

P.J.C. and M.R.S. are founders, stock holders and consultants for 14M Genomics Ltd, a genomics diagnostic company.

Corresponding author

Correspondence to Peter J Campbell.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Figures 1–6, Supplementary Note

Zip files

  1. 1.

    Supplementary Source Code

    R code for mutation clustering

Excel files

  1. 1.

    Supplementary Table 1

    Patient and sample characteristics

  2. 2.

    Supplementary Table 2

    Sequencing coverage

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    Supplementary Table 3

    Annotation of potential driver genes

  4. 4.

    Supplementary Table 4

    Validation data

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    Supplementary Table 5

    Mutation clusters.

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    Supplementary Table 6

    Heterogeneity scores.

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    Supplementary Table 7

    Mutation and copy number calls from capture data.

  8. 8.

    Supplementary Table 8

    Coding mutations and oncogenic copy number events from whole genome data

About this article

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DOI

https://doi.org/10.1038/nm.3886