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High order chromatin architecture shapes the landscape of chromosomal alterations in cancer

Nature Biotechnology volume 29, pages 11091113 (2011) | Download Citation

Abstract

The accumulation of data on structural variation in cancer genomes provides an opportunity to better understand the mechanisms of genomic alterations and the forces of selection that act upon these alterations in cancer. Here we test evidence supporting the influence of two major forces, spatial chromosome structure and purifying (or negative) selection, on the landscape of somatic copy-number alterations (SCNAs) in cancer1. Using a maximum likelihood approach, we compare SCNA maps and three-dimensional genome architecture as determined by genome-wide chromosome conformation capture (HiC) and described by the proposed fractal-globule model2,3. This analysis suggests that the distribution of chromosomal alterations in cancer is spatially related to three-dimensional genomic architecture and that purifying selection, as well as positive selection, influences SCNAs during somatic evolution of cancer cells.

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References

  1. 1.

    et al. The landscape of somatic copy-number alteration across human cancers. Nature 463, 899–905 (2010).

  2. 2.

    et al. Comprehensive mapping of long-range interactions reveals folding principles of the human genome. Science 326, 289–293 (2009).

  3. 3.

    The fractal globule as a model of chromatin architecture in the cell. Chromosome Res. 19, 37–51 (2011).

  4. 4.

    et al. Patterns of somatic mutation in human cancer genomes. Nature 446, 153–158 (2007).

  5. 5.

    et al. The genomic landscapes of human breast and colorectal cancers. Science 318, 1108–1113 (2007).

  6. 6.

    et al. Assessing the significance of chromosomal aberrations in cancer: methodology and application to glioma. Proc. Natl. Acad. Sci. USA 104, 20007–20012 (2007).

  7. 7.

    The Cancer Genome Atlas Research Network. Comprehensive genomic characterization defines human glioblastoma genes and core pathways. Nature 455, 1061–1068 (2008).

  8. 8.

    et al. The genomic complexity of primary human prostate cancer. Nature 470, 214–220 (2011).

  9. 9.

    & Genome organization influences partner selection for chromosomal rearrangements. Trends Genet. 27, 63–71 (2011).

  10. 10.

    , & Spatial genome organization in the formation of chromosomal translocations. Semin. Cancer Biol. 17, 80–90 (2007).

  11. 11.

    et al. Proximity of chromosomal loci that participate in radiation-induced rearrangements in human cells. Science 290, 138–141 (2000).

  12. 12.

    & Intermingling of chromosome territories in interphase suggests role in translocations and transcription-dependent associations. PLoS Biol. 4, e138 (2006).

  13. 13.

    , & The role of topological constraints in the kinetics of collapse of macromolecules. J. Phys. 49, 2095–2100 (1988).

  14. 14.

    The clonal evolution of tumor cell populations. Science 194, 23–28 (1976).

  15. 15.

    , , & Cancer as an evolutionary and ecological process. Nat. Rev. Cancer 6, 924–935 (2006).

  16. 16.

    et al. The mutation spectrum revealed by paired genome sequences from a lung cancer patient. Nature 465, 473–477 (2010).

  17. 17.

    , , & Mechanisms of change in gene copy number. Nat. Rev. Genet. 10, 551–564 (2009).

  18. 18.

    , & Statistical Methods in Medical Research (Blackwell Science, Malden, MA, 2001).

  19. 19.

    , , & Adaptive amplification: an inducible chromosomal instability mechanism. Cell 103, 723–731 (2000).

  20. 20.

    The Statistical Processes of Evolutionary Theory (Clarendon Press, Oxford, 1962).

  21. 21.

    et al. Genome-wide translocation sequencing reveals mechanisms of chromosome breaks and rearrangements in B cells. Cell 147, 107–119 (2011).

  22. 22.

    et al. Translocation-capture sequencing reveals the extent and nature of chromosomal rearrangements in B lymphocytes. Cell 147, 95–106 (2011).

  23. 23.

    et al. Common themes and cell type specific variations of higher order chromatin arrangements in the mouse. BMC Cell Biol. 6, 44 (2005).

  24. 24.

    , , , & Spatial proximity of translocation-prone gene loci in human lymphomas. Nat. Genet. 34, 287–291 (2003).

  25. 25.

    , & The cancer genome. Nature 458, 719–724 (2009).

  26. 26.

    & Cancer: drivers and passengers. Nature 446, 145–146 (2007).

  27. 27.

    Estimating the dimension of a model. Ann. Stat. 6, 461–464 (1978).

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Acknowledgements

We thank members of the Mirny Lab for helpful conversations, in particular with C. McFarland regarding purifying selection and M. Imakaev regarding fractal globules. We thank C. Mermel for an introduction to SCNA data. We thank V. Agarwala, J. Engrietz, R. McCord and J. Dekker for helpful comments and suggestions. This work was supported by the US National Institutes of Health/National Cancer Institute Physical Sciences Oncology Center at MIT (U54CA143874). G.G. and M.M. are TCGA-funded investigators (NIH U24CA143845, U24CA144025 and U24CA143867).

Author information

Affiliations

  1. Harvard University, Program in Biophysics, Boston, Massachusetts, USA.

    • Geoff Fudenberg
  2. The Broad Institute of the Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA.

    • Gad Getz
    • , Matthew Meyerson
    •  & Leonid A Mirny
  3. Harvard Medical School, Boston, Massachusetts, USA.

    • Matthew Meyerson
  4. Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

    • Matthew Meyerson
  5. Center for Cancer Genome Discovery, Dana-Farber Cancer Institute, Boston, Massachusetts, USA.

    • Matthew Meyerson
  6. Harvard-MIT, Division of Health Sciences and Technology, Cambridge, Massachusetts, USA.

    • Leonid A Mirny
  7. Department of Physics, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.

    • Leonid A Mirny

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Contributions

G.F. designed the study, performed data analysis and wrote the paper; G.G. and M.M. provided expertise in SCNA analysis and developed the manuscript; L.A.M. designed the study, performed initial data analysis and wrote the paper.

Competing interests

The authors declare no competing financial interests.

Corresponding author

Correspondence to Leonid A Mirny.

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DOI

https://doi.org/10.1038/nbt.2049

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