Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

Principles for the post-GWAS functional characterization of cancer risk loci

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

References

  1. Hindorff, L.A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. U S A 106, 9362−9367 (2009).

    Article  CAS  Google Scholar 

  2. Easton, D.F. et al. Genome-wide association study identifies novel breast cancer susceptibility loci. Nature 447, 1087–1093 (2007).

    Article  CAS  Google Scholar 

  3. Hindorff, L.A. et al. Potential etiologic and functional implications of genome-wide association loci for human diseases and traits. Proc. Natl. Acad. Sci. USA 106, 9362–9367 (2009).

    Article  CAS  Google Scholar 

  4. Jia, L. et al. Functional enhancers at the gene-poor 8q24 cancer-linked locus. PLoS Genet. 5, e1000597 (2009).

    Article  Google Scholar 

  5. Anonymous. On beyond GWAS. Nat. Genet. 42, 551 (2010).

  6. Glazier, A.M., Nadeau, J.H. & Aitman, T.J. Finding genes that underlie complex traits. Science 298, 2345–2349 (2002).

    Article  CAS  Google Scholar 

  7. Udler, M.S. et al. FGFR2 variants and breast cancer risk: fine-scale mapping using African American studies and analysis of chromatin conformation. Hum. Mol. Genet. 18, 1692–1703 (2009).

    Article  CAS  Google Scholar 

  8. Via, M., Gignoux, C. & Burchard, E.G. The 1000 Genomes Project: new opportunities for research and social challenges. Genome Med. 2, 3 (2010).

    Article  Google Scholar 

  9. Saccone, N.L. et al. In search of causal variants: refining disease association signals using cross-population contrasts. BMC Genet. 9, 58 (2008).

    Article  Google Scholar 

  10. Heintzman, N.D. et al. Histone modifications at human enhancers reflect global cell-type-specific gene expression. Nature 459, 108–112 (2009).

    Article  CAS  Google Scholar 

  11. Visel, A. et al. ChIP-seq accurately predicts tissue-specific activity of enhancers. Nature 457, 854–858 (2009).

    Article  CAS  Google Scholar 

  12. Visel, A., Rubin, E.M. & Pennacchio, L.A. Genomic views of distant-acting enhancers. Nature 461, 199–205 (2009).

    Article  CAS  Google Scholar 

  13. Birney, E. et al. Identification and analysis of functional elements in 1% of the human genome by the ENCODE pilot project. Nature 447, 799–816 (2007).

    Article  CAS  Google Scholar 

  14. Blow, M.J. et al. ChIP-Seq identification of weakly conserved heart enhancers. Nat. Genet. 42, 806–810 (2010).

    Article  CAS  Google Scholar 

  15. Kunarso, G. et al. Transposable elements have rewired the core regulatory network of human embryonic stem cells. Nat. Genet. 42, 631–634 (2010).

    Article  CAS  Google Scholar 

  16. Coetzee, G.A. et al. A systematic approach to understand the functional consequences of non-protein coding risk regions. Cell Cycle 9, 47–51 (2010).

    Article  Google Scholar 

  17. Pomerantz, M.M. et al. The 8q24 cancer risk variant rs6983267 shows long-range interaction with MYC in colorectal cancer. Nat. Genet. 41, 882–884 (2009).

    Article  CAS  Google Scholar 

  18. Ahmadiyeh, N. et al. 8q24 prostate, breast, and colon cancer risk loci show tissue-specific long-range interaction with MYC. Proc. Natl. Acad. Sci. USA 107, 9742–9746 (2010).

    Article  CAS  Google Scholar 

  19. Wasserman, N.F., Aneas, I. & Nobrega, M.A. An 8q24 gene desert variant associated with prostate cancer risk confers differential in vivo activity to a MYC enhancer. Genome Res. 20, 1191–1197 (2010).

    Article  CAS  Google Scholar 

  20. Gupta, R.A. et al. Long non-coding RNA HOTAIR reprograms chromatin state to promote cancer metastasis. Nature 464, 1071–1076 (2010).

    Article  CAS  Google Scholar 

  21. Khalil, A.M. et al. Many human large intergenic noncoding RNAs associate with chromatin-modifying complexes and affect gene expression. Proc. Natl. Acad. Sci. USA 106, 11667–11672 (2009).

    Article  CAS  Google Scholar 

  22. Jones, P.A. & Baylin, S.B. The epigenomics of cancer. Cell 128, 683–692 (2007).

    Article  CAS  Google Scholar 

  23. Raval, A. et al. Downregulation of death-associated protein kinase 1 (DAPK1) in chronic lymphocytic leukemia. Cell 129, 879–890 (2007).

    CAS  Google Scholar 

  24. Smith, L.T. et al. Epigenetic regulation of the tumor suppressor gene TCF21 on 6q23-q24 in lung and head and neck cancer. Proc. Natl. Acad. Sci. USA 103, 982–987 (2006).

    Article  CAS  Google Scholar 

  25. Jirtle, R.L. & Skinner, M.K. Environmental epigenomics and disease susceptibility. Nat. Rev. Genet. 8, 253–262 (2007).

    Article  CAS  Google Scholar 

  26. Lister, R. et al. Human DNA methylomes at base resolution show widespread epigenomic differences. Nature 462, 315–322 (2009).

    Article  CAS  Google Scholar 

  27. Chan, T.L. et al. Heritable germline epimutation of MSH2 in a family with hereditary nonpolyposis colorectal cancer. Nat. Genet. 38, 1178–1183 (2006).

    Article  CAS  Google Scholar 

  28. Suter, C.M., Martin, D.I. & Ward, R.L. Germline epimutation of MLH1 in individuals with multiple cancers. Nat. Genet. 36, 497–501 (2004).

    Article  CAS  Google Scholar 

  29. Hesson, L.B., Hitchins, M.P. & Ward, R.L. Epimutations and cancer predisposition: importance and mechanisms. Curr. Opin. Genet. Dev. 20, 290–298 (2010).

    Article  CAS  Google Scholar 

  30. Kerkel, K. et al. Genomic surveys by methylation-sensitive SNP analysis identify sequence-dependent allele-specific DNA methylation. Nat. Genet. 40, 904–908 (2008).

    Article  CAS  Google Scholar 

  31. Pelletier, C. & Weidhaas, J.B. MicroRNA binding site polymorphisms as biomarkers of cancer risk. Expert Rev. Mol. Diagn. 10, 817–829 (2010).

    Article  CAS  Google Scholar 

  32. Gemayel, R., Vinces, M.D., Legendre, M. & Verstrepen, K.J. Variable tandem repeats accelerate evolution of coding and regulatory sequences. Annu. Rev. Genet. 44, 445–477 (2010).

    Article  CAS  Google Scholar 

  33. Zhao, Z. et al. Circular chromosome conformation capture (4C) uncovers extensive networks of epigenetically regulated intra- and interchromosomal interactions. Nat. Genet. 38, 1341–1347 (2006).

    Article  CAS  Google Scholar 

  34. Sandhu, K.S. et al. Nonallelic transvection of multiple imprinted loci is organized by the H19 imprinting control region during germline development. Genes Dev. 23, 2598–2603 (2009).

    Article  CAS  Google Scholar 

  35. Steidl, U. et al. A distal single nucleotide polymorphism alters long-range regulation of the PU.1 gene in acute myeloid leukemia. J. Clin. Invest. 117, 2611–2620 (2007).

    Article  CAS  Google Scholar 

  36. Blaydon, D.C. et al. The gene encoding R-spondin 4 (RSPO4), a secreted protein implicated in Wnt signaling, is mutated in inherited anonychia. Nat. Genet. 38, 1245–1247 (2006).

    Article  CAS  Google Scholar 

  37. Kelsell, D.P. et al. Mutations in ABCA12 underlie the severe congenital skin disease harlequin ichthyosis. Am. J. Hum. Genet. 76, 794–803 (2005).

    Article  CAS  Google Scholar 

  38. Nicolae, D.L. et al. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 6, e1000888 (2010).

    Article  Google Scholar 

  39. Moffatt, M.F. et al. Genetic variants regulating ORMDL3 expression contribute to the risk of childhood asthma. Nature 448, 470–473 (2007).

    Article  CAS  Google Scholar 

  40. Musunuru, K. et al. From noncoding variant to phenotype via SORT1 at the 1p13 cholesterol locus. Nature 466, 714–719 (2010).

    Article  CAS  Google Scholar 

  41. Zhong, H. et al. Liver and adipose expression associated SNPs are enriched for association to type 2 diabetes. PLoS Genet. 6, e1000932 (2010).

    Article  Google Scholar 

  42. Pomerantz, M.M. et al. Analysis of the 10q11 cancer risk locus implicates MSMB and NCOA4 in human prostate tumorigenesis. PLoS Genet. 6, e1001204 (2010).

    Article  Google Scholar 

  43. Monks, S.A. et al. Genetic inheritance of gene expression in human cell lines. Am. J. Hum. Genet. 75, 1094–1105 (2004).

    Article  CAS  Google Scholar 

  44. Morley, M. et al. Genetic analysis of genome-wide variation in human gene expression. Nature 430, 743–747 (2004).

    Article  CAS  Google Scholar 

  45. Stranger, B.E. et al. Genome-wide associations of gene expression variation in humans. PLoS Genet. 1, e78 (2005).

    Article  Google Scholar 

  46. Schadt, E.E. et al. Genetics of gene expression surveyed in maize, mouse and man. Nature 422, 297–302 (2003).

    Article  CAS  Google Scholar 

  47. Johnson, J.M. et al. Genome-wide survey of human alternative pre-mRNA splicing with exon junction microarrays. Science 302, 2141–2144 (2003).

    Article  CAS  Google Scholar 

  48. Rockman, M.V. & Kruglyak, L. Genetics of global gene expression. Nat. Rev. Genet. 7, 862–872 (2006).

    Article  CAS  Google Scholar 

  49. Cheung, V.G. & Spielman, R.S. Genetics of human gene expression: mapping DNA variants that influence gene expression. Nat. Rev. Genet. 10, 595–604 (2009).

    Article  CAS  Google Scholar 

  50. Cookson, W., Liang, L., Abecasis, G., Moffatt, M. & Lathrop, M. Mapping complex disease traits with global gene expression. Nat. Rev. Genet. 10, 184–194 (2009).

    Article  CAS  Google Scholar 

  51. Schadt, E.E. et al. Mapping the genetic architecture of gene expression in human liver. PLoS Biol. 6, e107 (2008).

    Article  Google Scholar 

  52. Pastinen, T. Genome-wide allele-specific analysis: insights into regulatory variation. Nat. Rev. Genet. 11, 533–538 (2010).

    Article  CAS  Google Scholar 

  53. Montgomery, S.B. et al. Transcriptome genetics using second generation sequencing in a Caucasian population. Nature 464, 773–777 (2010).

    Article  CAS  Google Scholar 

  54. Pickrell, J.K. et al. Understanding mechanisms underlying human gene expression variation with RNA sequencing. Nature 464, 768–772 (2010).

    Article  CAS  Google Scholar 

  55. Margolin, A.A. et al. ARACNE: an algorithm for the reconstruction of gene regulatory networks in a mammalian cellular context. BMC Bioinformatics 7 Suppl 1, S7 (2006).

    Article  Google Scholar 

  56. Bumgarner, R.E. & Yeung, K.Y. Methods for the inference of biological pathways and networks. Methods Mol. Biol. 541, 225–245 (2009).

    Article  CAS  Google Scholar 

  57. Furuta, S. et al. Depletion of BRCA1 impairs differentiation but enhances proliferation of mammary epithelial cells. Proc. Natl. Acad. Sci. USA 102, 9176–9181 (2005).

    Article  CAS  Google Scholar 

  58. Proia, T.A. et al. Genetic predisposition directs breast cancer phenotype by dictating progenitor cell fate. Cell Stem Cell 8, 149–163 (2010).

    Article  Google Scholar 

Download references

Acknowledgements

We would like to thank F. Bunz and all the members of the NIH Post-Genome Wide Association Initiative for helpful discussions and, in particular, I. Tomlinson (Wellcome Trust Centre for Human Genetics, Oxford). The contributing groups are supported by funding made available through the NIH Post-Genome Wide Association Initiative in response to Call (http://grants.nih.gov./grants/oer.htm). This Call sustains research across five cancer organ sites (prostate: 1U19CA148537-01; breast: 1U19CA148065-01; ovarian: 1U19CA148112-01; colorectal: 1U19CA148107-01; and lung: 1U19CA148127-01). For further information on this Initiative, please refer to the website: (http://epi.grants.cancer.gov/). In addition, this article is the product of the first attempt to engage the entire scientific community in the drafting of a scientific paper through open-access websites. We would like to thank R. Hoffmann at WikiGenes for hosting the pre-submission version of this submission (http://www.wikigenes.org/e/pub/e/84.html) and his unstinting energy and enthusiasm for this project and also Nature Precedings for hosting the same version (http://precedings.nature.com/documents/5162/version/1).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Ian G Mills.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Freedman, M., Monteiro, A., Gayther, S. et al. Principles for the post-GWAS functional characterization of cancer risk loci. Nat Genet 43, 513–518 (2011). https://doi.org/10.1038/ng.840

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ng.840

This article is cited by

Search

Quick links

Nature Briefing: Cancer

Sign up for the Nature Briefing: Cancer newsletter — what matters in cancer research, free to your inbox weekly.

Get what matters in cancer research, free to your inbox weekly. Sign up for Nature Briefing: Cancer