Reduced local mutation density in regulatory DNA of cancer genomes is linked to DNA repair

Journal name:
Nature Biotechnology
Volume:
32,
Pages:
71–75
Year published:
DOI:
doi:10.1038/nbt.2778
Received
Accepted
Published online

Abstract

Carcinogenesis and neoplastic progression are mediated by the accumulation of somatic mutations. Here we report that the local density of somatic mutations in cancer genomes is highly reduced specifically in accessible regulatory DNA defined by DNase I hypersensitive sites. This reduction is independent of any known factors influencing somatic mutation density and is observed in diverse cancer types, suggesting a general mechanism. By analyzing individual cancer genomes1, we show that the reduced local mutation density within regulatory DNA is linked to intact global genome repair machinery, with nearly complete abrogation of the hypomutation phenomenon in individual cancers that possess mutations in components of the nucleotide excision repair system. Together, our results connect chromatin structure, gene regulation and cancer-associated somatic mutation.

At a glance

Figures

  1. Relative density of somatic mutations is reduced in DHSs of all analyzed cancer genomes (lung, melanoma, colon, multiple myeloma (MM)). Mutation density per (uniquely mappable) bp is shown for (red) DHS maxima defined as [plusmn]75 bp around the peak of DNase I hypersensitivity (marked as DHS peaks), (green) DHSs, (cyan) 1,000-bp flanking regions and (purple) overall genome. Mutation density in DHSs is substantially lower in comparison with immediate flanking regions and genome average. The effect is stronger for DHS maxima compared to overall DHSs.
    Figure 1: Relative density of somatic mutations is reduced in DHSs of all analyzed cancer genomes (lung3, melanoma2, colon13, multiple myeloma (MM)5). Mutation density per (uniquely mappable) bp is shown for (red) DHS maxima defined as ±75 bp around the peak of DNase I hypersensitivity (marked as DHS peaks), (green) DHSs, (cyan) 1,000-bp flanking regions and (purple) overall genome. Mutation density in DHSs is substantially lower in comparison with immediate flanking regions and genome average. The effect is stronger for DHS maxima compared to overall DHSs.
  2. Density of somatic C:G[rarr]T:A transition mutations in melanoma samples strongly depends on chromatin accessibility in a monotonic and continuous fashion.
    Figure 2: Density of somatic C:Gright arrowT:A transition mutations in melanoma samples strongly depends on chromatin accessibility in a monotonic and continuous fashion.

    Density of C:Gright arrowT:A transitions per C:G base-pair in 400-bp genomic intervals is shown as a function of chromatin accessibility in melanocytes measured by the density DNase I cleavages. The dependence is presented separately for introns and intergenic regions, and is equally present in both. Mutation densities are parametrically fitted to a spline function using a generalized additive model Poisson regression model18.

  3. Normalization of DHS hypomutation in melanoma genomes with mutated nucleotide excision repair pathway genes.
    Figure 3: Normalization of DHS hypomutation in melanoma genomes with mutated nucleotide excision repair pathway genes.

    Relative mutation density in DHSs of melanoma genomes is shown for samples with an intact NER system (blue) and samples with nonsynonymous mutations in NER pathway genes (red). Nonsynonymous changes in NER pathway genes significantly track relative mutation reduction in DHSs (P < 0.0237, Wilcoxon-Mann-Whitney test).

  4. Reduction of mutation density in DHSs and in transcribed regions.
    Figure 4: Reduction of mutation density in DHSs and in transcribed regions.

    Shown for individual melanoma samples (scatter plot) are nonsynonymous mutations in genes involved in NER (marked by shape and color corresponding to each gene). Roles of these genes within the NER pathway are shown by the diagram on the right. XPG, XPF and LIG1 are core repair components; CETN2 and DDB2 are specific to global genome repair and are involved in lesion recognition. CSB is specific to TCR and is involved in recruiting NER to the stalled RNA Pol II. Samples with low (or no) reduction of somatic mutations in DHSs and carrying nonsynonymous changes in genes of core NER components also show low (or no) reduction of mutation frequency in transcribed regions, suggesting that core NER genes are responsible for both effects. NER, samples with mutations in NER genes; NER+, samples with intact NER genes.

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References

  1. Berger, M.F. et al. Melanoma genome sequencing reveals frequent PREX2 mutations. Nature 485, 502506 (2012).
  2. Pleasance, E.D. et al. A comprehensive catalogue of somatic mutations from a human cancer genome. Nature 463, 191196 (2010).
  3. Pleasance, E.D. et al. A small-cell lung cancer genome with complex signatures of tobacco exposure. Nature 463, 184190 (2010).
  4. Meyerson, M., Gabriel, S. & Getz, G. Advances in understanding cancer genomes through second-generation sequencing. Nat. Rev. Genet. 11, 685696 (2010).
  5. Chapman, M.A. et al. Initial genome sequencing and analysis of multiple myeloma. Nature 471, 467472 (2011).
  6. Hanawalt, P.C. & Spivak, G. Transcription-coupled DNA repair: two decades of progress and surprises. Nat. Rev. Mol. Cell Biol. 9, 958970 (2008).
  7. Lainé, J. & Egly, J. Initiation of DNA repair mediated by a stalled RNA polymerase IIO. EMBO J. 25, 387397 (2006).
  8. Thurman, R.E. et al. The accessible chromatin landscape of the human genome. Nature 489, 7582 (2012).
  9. Gross, D.S. & Garrard, W.T. Nuclease hypersensitive sites in chromatin. Annu. Rev. Biochem. 57, 159197 (1988).
  10. Neph, S. et al. An expansive human regulatory lexicon encoded in transcription factor footprints. Nature 489, 8390 (2012).
  11. Legault, J., Tremblay, A., Ramotar, D. & Mirault, M.E. Clusters of S1 nuclease-hypersensitive sites induced in vivo by DNA damage. Mol. Cell Biol. 17, 54375452 (1997).
  12. Parker, S.C. et al. Mutational signatures of de-differentiation in functional non-coding regions of melanoma genomes. PLoS Genet. 8, e1002871 (2012).
  13. Bass, A.J. et al. Genomic sequencing of colorectal adenocarcinomas identifies a recurrent VTI1A–TCF7L2 fusion. Nat. Genet. 43, 964968 (2011).
  14. Cibulskis, K. et al. Sensitive detection of somatic point mutations in impure and heterogeneous cancer samples. Nat. Biotechnol. 31, 213219 (2013).
  15. Hodgkinson, A., Chen, Y. & Eyre-Walker, A. The large-scale distribution of somatic mutations in cancer genomes. Hum. Mutat. 33, 136143 (2012).
  16. Stamatoyannopoulos, J.A. et al. Human mutation rate associated with DNA replication timing. Nat. Genet. 41, 393395 (2009).
  17. Schuster-Bockler, B. & Lehner, B. Chromatin organization is a major influence on regional mutation rates in human cancer cells. Nature 488, 504507 (2012).
  18. Faraway, J.J. Extending the Linear Model with R: Generalized Linear, Mixed Effects and Nonparametric Regression Models (Chapman & Hall/CRC, Boca Raton, 2006).
  19. Hansen, R.S. et al. Sequencing newly replicated DNA reveals widespread plasticity in human replication timing. Proc. Natl. Acad. Sci. USA 107, 139144 (2010).
  20. King, M.C. & Wilson, A.C. Evolution at two levels in humans and chimpanzees. Science 188, 107116 (1975).
  21. Lindblad-Toh, K. et al. A high-resolution map of human evolutionary constraint using 29 mammals. Nature 478, 476482 (2011).
  22. Chen, X. et al. Nucleosomes suppress spontaneous mutations base-specifically in eukaryotes. Science 335, 12351238 (2012).
  23. Sasaki, S. et al. Chromatin-associated periodicity in genetic variation downstream of transcriptional start sites. Science 323, 401404 (2009).
  24. Cheng, K.C., Cahill, D.S., Kasai, H., Nishimura, S. & Loeb, L.A. 8-Hydroxyguanine, an abundant form of oxidative DNA damage, causes G—T and A—C substitutions. J. Biol. Chem. 267, 166172 (1992).
  25. Kawanishi, S., Hiraku, Y., Pinlaor, S. & Ma, N. Oxidative and nitrative DNA damage in animals and patients with inflammatory diseases in relation to inflammation-related carcinogenesis. Biol. Chem. 387, 365372 (2006).
  26. Hitomi, K., Iwai, S. & Tainer, J.A. The intricate structural chemistry of base excision repair machinery: implications for DNA damage recognition, removal, and repair. DNA Repair (Amst.) 6, 410428 (2007).
  27. Amouroux, R., Campalans, A., Epe, B. & Radicella, J.P. Oxidative stress triggers the preferential assembly of base excision repair complexes on open chromatin regions. Nucleic Acids Res. 38, 28782890 (2010).
  28. Friedberg, E.C. et al. DNA Repair and Mutagenesis (ASM Press, 2006).
  29. Bell, O., Tiwari, V.K., Thomä, N.H. & Schübeler, D. Determinants and dynamics of genome accessibility. Nat. Rev. Genet. 12, 554564 (2011).
  30. Thoma, F. Repair of UV lesions in nucleosomes–intrinsic properties and remodeling. DNA Repair (Amst.) 4, 855869 (2005).
  31. Aboussekhra, A. et al. Mammalian DNA nucleotide excision repair reconstituted with purified protein components. Cell 80, 859868 (1995).
  32. Yasuda, T. et al. Nucleosomal structure of undamaged DNA regions suppresses the non-specific DNA binding of the XPC complex. DNA Repair (Amst.) 4, 389395 (2005).
  33. Fei, J. et al. Regulation of nucleotide excision repair by UV-DDB: prioritization of damage recognition to internucleosomal DNA. PLoS Biol. 9, e1001183 (2011).
  34. Shuck, S.C., Short, E.A. & Turchi, J.J. Eukaryotic nucleotide excision repair: from understanding mechanisms to influencing biology. Cell Res. 18, 6472 (2008).
  35. Sugasawa, K. Xeroderma pigmentosum genes: functions inside and outside DNA repair. Carcinogenesis 29, 455465 (2008).
  36. Hanawalt, P.C., Ford, J.M. & Lloyd, D.R. Functional characterization of global genomic DNA repair and its implications for cancer. Mutat. Res. 544, 107114 (2003).
  37. Girard, P.M. & Boiteux, S. Repair of oxidized DNA bases in the yeast Saccharomyces cerevisiae. Biochimie 79, 559566 (1997).
  38. Haruta, N., Kubota, Y. & Hishida, T. Chronic low-dose ultraviolet-induced mutagenesis in nucleotide excision repair-deficient cells. Nucleic Acids Res. 40, 84068415 (2012).
  39. Nik-Zainal, S. et al. Mutational processes molding the genomes of 21 breast cancers. Cell 149, 979993 (2012).
  40. Roberts, S.A. et al. Clustered mutations in yeast and in human cancers can arise from damaged long single-strand DNA regions. Mol. Cell 46, 424435 (2012).
  41. Burns, M.B. et al. APOBEC3B is an enzymatic source of mutation in breast cancer. Nature 494, 366370 (2013).
  42. Lange, S.S., Takata, K. & Wood, R.D. DNA polymerases and cancer. Nat. Rev. Cancer 11, 96110 (2011).
  43. Kanehisa, M., Goto, S., Sato, Y., Furumichi, M. & Tanabe, M. KEGG for integration and interpretation of large-scale molecular data sets. Nucleic Acids Res. 40, D109D114 (2012).
  44. Palomera-Sanchez, Z. & Zurita, M. Open, repair and close again: chromatin dynamics and the response to UV-induced DNA damage. DNA Repair (Amst.) 10, 119125 (2011).
  45. Iyer, L.M., Zhang, D., Rogozin, I.B. & Aravind, L. Evolution of the deaminase fold and multiple origins of eukaryotic editing and mutagenic nucleic acid deaminases from bacterial toxin systems. Nucleic Acids Res. 39, 94739497 (2011).
  46. Huang, F.W. et al. Highly recurrent TERT promoter mutations in human melanoma. Science 339, 957959 (2013).
  47. Lawrence, M.S. et al. Mutational heterogeneity in cancer and the search for new cancer-associated genes. Nature 499, 214218 (2013).
  48. Neph, S. et al. BEDOPS: high-performance genomic feature operations. Bioinformatics 28, 19191920 (2012).

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Author information

  1. These authors contributed equally to this work.

    • Paz Polak &
    • Michael S Lawrence

Affiliations

  1. Division of Genetics, Department of Medicine, Brigham & Women's Hospital, Boston, Massachusetts, USA.

    • Paz Polak,
    • Nina Stoletzki &
    • Shamil R Sunyaev
  2. Harvard Medical School, Boston, Massachusetts, USA.

    • Paz Polak,
    • Nina Stoletzki,
    • Levi A Garraway &
    • Shamil R Sunyaev
  3. The Broad Institute of MIT and Harvard, Cambridge, Massachusetts, USA.

    • Paz Polak,
    • Michael S Lawrence,
    • Nina Stoletzki,
    • Petar Stojanov,
    • Levi A Garraway,
    • Gad Getz &
    • Shamil R Sunyaev
  4. Departments of Genome Sciences and Medicine (Oncology), University of Washington, Seattle, Washington, USA.

    • Eric Haugen,
    • Robert E Thurman &
    • John A Stamatoyannopoulos
  5. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

    • Levi A Garraway
  6. Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

    • Levi A Garraway
  7. Department of Biology, Tufts University, Medford, Massachusetts, USA.

    • Sergei Mirkin

Contributions

P.P., M.S.L., N.S., G.G., J.A.S. and S.R.S. conceived the study. P.P. led the analysis of sequencing data. M.S.L. and P.S. contributed to the analysis of sequencing data. R.E.T. and E.H. analyzed DHS data. L.A.G. provided melanoma sequencing data. S.M., G.G., J.A.S. and S.R.S. supervised the analysis. P.P., S.M., J.A.S. and S.R.S. wrote the manuscript.

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The authors declare no competing financial interests.

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