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Association of a germline copy number polymorphism of APOBEC3A and APOBEC3B with burden of putative APOBEC-dependent mutations in breast cancer

Nature Genetics volume 46, pages 487491 (2014) | Download Citation

Abstract

The somatic mutations in a cancer genome are the aggregate outcome of one or more mutational processes operative through the lifetime of the individual with cancer1,2,3. Each mutational process leaves a characteristic mutational signature determined by the mechanisms of DNA damage and repair that constitute it. A role was recently proposed for the APOBEC family of cytidine deaminases in generating particular genome-wide mutational signatures1,4 and a signature of localized hypermutation called kataegis1,4. A germline copy number polymorphism involving APOBEC3A and APOBEC3B, which effectively deletes APOBEC3B5, has been associated with modestly increased risk of breast cancer6,7,8. Here we show that breast cancers in carriers of the deletion show more mutations of the putative APOBEC-dependent genome-wide signatures than cancers in non-carriers. The results suggest that the APOBEC3A-APOBEC3B germline deletion allele confers cancer susceptibility through increased activity of APOBEC-dependent mutational processes, although the mechanism by which this increase in activity occurs remains unknown.

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Acknowledgements

We would like to thank M. Hurles and C. Anderson of the Wellcome Trust Sanger Institute for their input. We would like to thank The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC) for access to the mutation catalogs used in Alexandrov et al.9 and for access to BAM files. We would like to thank the Wellcome Trust for support (grant 098051). S.N.-Z. is a Wellcome-Beit Prize Fellow and is supported through a Wellcome Trust Intermediate Fellowship (grant WT100183MA). P.J.C. is personally funded through a Wellcome Trust Senior Clinical Research Fellowship (grant WT088340MA). N.B. is a European Hematology Association (EHA) fellow and is supported by a starter grant from the Academy of Medical Sciences. The H.L. Holmes Award from National Research Council Canada and an EMBO (European Molecular Biology Organization) Fellowship support A.S. We would also like to acknowledge funding from Breakthrough Breast Cancer Research (ICGC 08/09) and the BASIS project, funded by the European Community's Seventh Framework Programme (FP7/2010-2014) under grant agreement 242006. This study was performed within the Research Ethics Approval of 09/h0306/36.

Author information

Affiliations

  1. Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton, UK.

    • Serena Nik-Zainal
    • , David C Wedge
    • , Ludmil B Alexandrov
    • , Mia Petljak
    • , Adam P Butler
    • , Niccolo Bolli
    • , Helen R Davies
    • , Sancha Martin
    • , Elli Papaemmanuil
    • , Manasa Ramakrishna
    • , Adam Shlien
    • , Yali Xue
    • , Chris Tyler-Smith
    • , Peter J Campbell
    •  & Michael R Stratton
  2. Department of Medical Genetics, Addenbrooke's Hospital National Health Service (NHS) Trust, Cambridge, UK.

    • Serena Nik-Zainal
  3. Department of Haematology, University of Cambridge, Cambridge, UK.

    • Niccolo Bolli
    •  & Peter J Campbell
  4. Section of Oncology, Department of Clinical Science, University of Bergen, Bergen, Norway.

    • Stian Knappskog
  5. Department of Oncology, Haukeland University Hospital, Bergen, Norway.

    • Stian Knappskog
  6. Department of Genetics and Genome Biology, The Hospital for Sick Children, Toronto, Ontario, Canada.

    • Adam Shlien
  7. Regional Genetics Laboratories, Cambridge University Hospitals NHS Foundation Trust, Cambridge Biomedical Campus, Cambridge, UK.

    • Ingrid Simonic

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Contributions

S.N.-Z. and M.R.S. conceived the experiments and wrote the manuscript. S.N.-Z., D.C.W., L.B.A. and P.J.C. carried out analyses and/or statistics with assistance from M.P., A.P.B., N.B., A.S., H.R.D., M.R., E.P., S.K. and I.S. S.M. governed administrative aspects. Y.X. and C.T.-S. advised and performed analysis on selection.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Ludmil B Alexandrov or Michael R Stratton.

Supplementary information

PDF files

  1. 1.

    Supplementary Text and Figures

    Supplementary Note, Supplementary Figures 1–5 and Supplementary Table 3

Excel files

  1. 1.

    Supplementary Table 1

    (a) Summary of cancer samples used in this analysis obtained from various sequencing centers and from peer-reviewed publications. (b) Detailed background data of 2,719 whole-genome and exome sequenced cancer samples used in this analysis are included in this table. Cancer type, sample identification, type of sequencing experiment, age of cancer diagnosis, total number of mutations in each sample and numbers of mutations attributed to signatures 2 and 13 and signatures 1A and 1B, as well as the proportional contributions of each of these signatures to each cancer (determined using Non-negative Matrix Factorization (NNMF)) are presented in this table.

  2. 2.

    Supplementary Table 2

    (a) Loci used for sampling. (b) Germline APOBEC3A-APOBEC3B polymorphism status in all 2,719 patients. APOBEC3A-APOBEC3B deletion allele status column: 0 = hom, 1=het and 2 = non-carrier of deletion allele. Hypermutator column: 0 = non-hypermutator, 1 = hypermutator. (c) Concordance between tumor and normal sampling in 123 whole-genome sequenced breast cancers, 166 tumor-normal exome-sequenced cancers and 9 cancers that were genome as well as exome sequenced.

  3. 3.

    Supplementary Table 4

    An analysis of strand-coordinated mutagenesis. 123 breast cancer genomes and 1 ALL genome were analyzed for whether successive pairs of mutations were on the same or different strands. Sample = name of sample; expected same strand = expected number of successive same-strand mutations; observed same strand = observed number of successive same-strand mutations; odds ratio of strandedness = odds ratio reporting enrichment of observed to expected same-strand mutations; total variants = total number of variants in analysis; pairs within 700 bp of each other = number of pairs of successive variants that were within 700 bp of each other; same.cis = same strand in cis; same.trans = same strand in trans; diff.cis = different strand in cis; diff.trans = different strand in trans; same.other = same strand unclassified (not informative); diff.other = different strand unclassified.

  4. 4.

    Supplementary Table 5

    Expression levels.

Zip files

  1. 1.

    Supplementary Data Set 1

    Coverage counts and plots for genomes.

  2. 2.

    Supplementary Data Set 2

    Coverage counts and plots for exomes.

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DOI

https://doi.org/10.1038/ng.2955

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