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Genomic architecture and evolution of clear cell renal cell carcinomas defined by multiregion sequencing

Nature Genetics 46, 225–233 (2014) | Download Citation

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Abstract

Clear cell renal carcinomas (ccRCCs) can display intratumor heterogeneity (ITH). We applied multiregion exome sequencing (M-seq) to resolve the genetic architecture and evolutionary histories of ten ccRCCs. Ultra-deep sequencing identified ITH in all cases. We found that 73–75% of identified ccRCC driver aberrations were subclonal, confounding estimates of driver mutation prevalence. ITH increased with the number of biopsies analyzed, without evidence of saturation in most tumors. Chromosome 3p loss and VHL aberrations were the only ubiquitous events. The proportion of C>T transitions at CpG sites increased during tumor progression. M-seq permits the temporal resolution of ccRCC evolution and refines mutational signatures occurring during tumor development.

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Acknowledgements

We thank the patients, the research nurses at the Royal Marsden Hospital, and Lifetech and Westminster Genomic Services at the University of Westminster, London, for their assistance with validation. C.S. and M. Gerlinger are supported by grants from Cancer Research UK Biomarkers and Imaging Discovery and Development Committee (BIDD), the Medical Research Council and the Seventh European Union Framework Programme, and C.S. is supported by the Breast Cancer Research Foundation and the Rosetrees Trust. We acknowledge the Ramón y Cajal program of the Ministerio de Economía y Competitividad, Spain, and Novartis for funding support for E-PREDICT clinical trials. This study was supported by researchers at the National Institute for Health Research Biomedical Research Centres at University College London Hospitals and at the Royal Marsden Hospital.

Author information

    • Marco Gerlinger
    • , Stuart Horswell
    • , James Larkin
    • , Andrew J Rowan
    •  & Max P Salm

    These authors contributed equally to this work.

Affiliations

  1. Translational Cancer Therapeutics Laboratory, Cancer Research UK London Research Institute, London, UK.

    • Marco Gerlinger
    • , Andrew J Rowan
    • , Nicholas McGranahan
    • , Claudio R Santos
    • , Pierre Martinez
    •  & Charles Swanton

  2. Bioinformatics and Biostatistics, Cancer Research UK London Research Institute, London, UK.

    • Stuart Horswell
    • , Max P Salm
    •  & Aengus Stewart

  3. Department of Medicine, Royal Marsden Hospital, London, UK.

    • James Larkin
    • , Rosalie Fisher
    • , Lisa Pickering
    •  & Martin Gore

  4. Instituto de Biomedicina y Biotecnología de Cantabria (CSIC-UC-Sodercan), Departamento de Biología Molecular, Universidad de Cantabria, Santander, Spain.

    • Ignacio Varela

  5. Advanced Sequencing Facility, Cancer Research UK London Research Institute, London, UK.

    • Nicholas Matthews
    • , Benjamin Phillimore
    • , Sharmin Begum
    •  & Adam Rabinowitz

  6. Experimental Histopathology, Cancer Research UK London Research Institute, London, UK.

    • Bradley Spencer-Dene
    •  & Gordon Stamp

  7. Biomolecular Modelling, Cancer Research UK London Research Institute, London, UK.

    • Sakshi Gulati
    •  & Paul A Bates

  8. Department of Urology, Royal Marsden Hospital, London, UK.

    • David L Nicol

  9. Department of Pathology, Royal Marsden Hospital, London, UK.

    • Steven Hazell

  10. Department of Genomic Medicine, MD Anderson Cancer Center, Houston, Texas, USA.

    • P Andrew Futreal

  11. University College London Cancer Institute, University College London, London, UK.

    • Charles Swanton

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Contributions

M. Gerlinger, J.L. and C.S. designed the study. R.F., L.P., M. Gore, D.L.N. and J.L. provided clinical specimens. M. Gerlinger, A.J.R. and R.F. processed the samples. G.S., B.S.-D. and S. Hazell performed histopathological analyses. N. Matthews, B.P., S.B., A.J.R. and A.R. sequenced the samples. S. Horswell, I.V., N. McGranahan, M.P.S., P.M., S.G., P.A.B., A.S. and M. Gerlinger performed bioinformatics analyses. B.S.-D. processed histological samples, which were analyzed by G.S. and S. Horswell. M. Gerlinger, N. McGranahan and C.R.S. analyzed all data. M. Gerlinger, N. McGranahan, C.R.S., P.A.F., J.L. and C.S. interpreted the data. M. Gerlinger, N. McGranahan, C.R.S. and C.S. wrote the manuscript. All authors read and approved the final manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Charles Swanton.

Integrated supplementary information

Supplementary figures

  1. 1.

    VHL bisulfite sequencing.

  2. 2.

    Observed number of nonsynonymous variants for N biopsies.

  3. 3.

    Density plots of regional VAFs.

  4. 4.

    BAP1 and PBRM1 expression signatures in tumor regions with BAP1 or PBRM1 mutations.

  5. 5.

    Regional Fuhrman grades according to BAP1 and TP53 mutation status.

  6. 6.

    SCNA (LogR) profiles by region.

  7. 7.

    Mutational and copy number driver heterogeneity are positively correlated.

  8. 8.

    Cases with copy-neutral loss of heterozygosity in chromosome 3p.

  9. 9.

    Superimposition of driver SCNAs onto phylogenetic trees generated from point mutation data.

  10. 10.

    Mutational spectrum of trunk and branch mutations across 96 trinucleotide contexts.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Tables 1, 2, 4 and 7, Supplementary Figures 1–10 and Supplementary Note

Excel files

  1. 1.

    Supplementary Table 3

    Details of nonsynonymous somatic mutations by region

  2. 2.

    Supplementary Table 5

    Variant allele frequencies by region

  3. 3.

    Supplementary Table 6

    Nonsynonymous somatic mutations by inferred subclone

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DOI

https://doi.org/10.1038/ng.2891

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