Tumor Biology

, Volume 35, Issue 12, pp 12607–12611 | Cite as

Expression QTL-based analyses reveal the mechanisms underlying colorectal cancer predisposition

Research Article

Abstract

Genome-wide association studies have identified many risk loci associated with colorectal cancer. Strategies integrating biological data sets with GWAS results will provide insights into the roles of risk single-nucleotide polymorphisms. We performed expression quantitative trait locus-based analyses using the information provided in The Cancer Genome Atlas. Analysis of the cis-expression quantitative trait loci (eQTLs) of 18 previously reported colorectal cancer risk loci resulted in the discovery of five variants that were significantly associated with gene expressions. Analysis of the trans-eQTLs identified three risk loci that affect the expression levels of a neighboring transcription factor, MYC. These findings provide a more comprehensive picture of gene expression determinants in colorectal cancer and insights into the underlying biology of risk loci.

Keywords

Colorectal cancer GWAS eQTL 

Notes

Acknowledgment

The authors thank Qinghua Cui and Chengxiang Qiu for the assistance on statistical analysis.

Funding source

This study was supported by the National Natural Science Foundation of China (item no. 81372291) and (item no. 81372290).

Conflicts of interest

None.

Supplementary material

13277_2014_2583_MOESM1_ESM.xls (38 kb)
Table S1 Summary of 50 colorectal cancer GWAS risk alleles obtained from the National Human Genome Research Institute (XLS 38 kb)
13277_2014_2583_MOESM2_ESM.docx (16 kb)
Table S2 Clinical and pathologic data of 146 patients from whom both colorectal tumor expression profiles and matched germline genotype data were available (DOCX 16.3 kb)
13277_2014_2583_MOESM3_ESM.xlsx (12 kb)
Table S3 From the 18 risk SNP loci, we obtained 191 unique SNP gene pairs (XLSX 11.9 kb)

Reference

  1. 1.
    Edwards SL, Beesley J, French JD, Dunning AM. Beyond GWASs: illuminating the dark road from association to function. Am J Hum Genet. 2013;93(5):779–97. doi: 10.1016/j.ajhg.2013.10.012.PubMedCentralPubMedCrossRefGoogle Scholar
  2. 2.
    Welter D, MacArthur J, Morales J, Burdett T, Hall P, Junkins H, et al. The NHGRI GWAS catalog, a curated resource of SNP-trait associations. Nucleic Acids Res. 2014;42(Database issue):D1001–6. doi: 10.1093/nar/gkt1229.PubMedCentralPubMedCrossRefGoogle Scholar
  3. 3.
    Morley M, Molony CM, Weber TM, Devlin JL, Ewens KG, Spielman RS, et al. Genetic analysis of genome-wide variation in human gene expression. Nature. 2004;430(7001):743–7. doi: 10.1038/nature02797.PubMedCentralPubMedCrossRefGoogle Scholar
  4. 4.
    Lappalainen T, Sammeth M, Friedlander MR, Hoen PA, Monlong J, Rivas MA, et al. Transcriptome and genome sequencing uncovers functional variation in humans. Nature. 2013;501(7468):506–11. doi: 10.1038/nature12531.PubMedCentralPubMedCrossRefGoogle Scholar
  5. 5.
    Maurano MT, Humbert R, Rynes E, Thurman RE, Haugen E, Wang H, et al. Systematic localization of common disease-associated variation in regulatory DNA. Science. 2012;337(6099):1190–5. doi: 10.1126/science.1222794.PubMedCentralPubMedCrossRefGoogle Scholar
  6. 6.
    Fraser HB, Xie X. Common polymorphic transcript variation in human disease. Genome Res. 2009;19(4):567–75. doi: 10.1101/gr.083477.108.PubMedCrossRefGoogle Scholar
  7. 7.
    Nicolae DL, Gamazon E, Zhang W, Duan S, Dolan ME, Cox NJ. Trait-associated SNPs are more likely to be eQTLs: annotation to enhance discovery from GWAS. PLoS Genet. 2010;6(4):e1000888. doi: 10.1371/journal.pgen.1000888.PubMedCentralPubMedCrossRefGoogle Scholar
  8. 8.
    Dimas AS, Deutsch S, Stranger BE, Montgomery SB, Borel C, Attar-Cohen H, et al. Common regulatory variation impacts gene expression in a cell type-dependent manner. Science. 2009;325(5945):1246–50. doi: 10.1126/science.1174148.PubMedCentralPubMedCrossRefGoogle Scholar
  9. 9.
    The Cancer Genome Atlas Network. Comprehensive molecular characterization of human colon and rectal cancer. Nature. 2012;487(7407):330–7. doi: 10.1038/nature11252.PubMedCentralCrossRefGoogle Scholar
  10. 10.
    Johnson AD, Handsaker RE, Pulit SL, Nizzari MM, O'Donnell CJ, de Bakker PI. SNAP: a Web-based tool for identification and annotation of proxy SNPs using HapMap. Bioinformatics. 2008;24(24):2938–9. doi: 10.1093/bioinformatics/btn564.PubMedCentralPubMedCrossRefGoogle Scholar
  11. 11.
    Mason JM, Arndt KM. Coiled coil domains: stability, specificity, and biological implications. Chembiochem: Eur J Chem Biol. 2004;5(2):170–6. doi: 10.1002/cbic.200300781.CrossRefGoogle Scholar
  12. 12.
    Fan C, Dong L, Zhu N, Xiong Y, Zhang J, Wang L, et al. Isolation of siRNA target by biotinylated siRNA reveals that human CCDC12 promotes early erythroid differentiation. Leuk Res. 2012;36(6):779–83. doi: 10.1016/j.leukres.2011.12.017.PubMedCrossRefGoogle Scholar
  13. 13.
    Pomerantz MM, Ahmadiyeh N, Jia L, Herman P, Verzi MP, Doddapaneni H, et al. The 8q24 cancer risk variant rs6983267 shows long-range interaction with MYC in colorectal cancer. Nat Genet. 2009;41(8):882–4. doi: 10.1038/ng.403.PubMedCentralPubMedCrossRefGoogle Scholar
  14. 14.
    Tuupanen S, Turunen M, Lehtonen R, Hallikas O, Vanharanta S, Kivioja T, et al. The common colorectal cancer predisposition SNP rs6983267 at chromosome 8q24 confers potential to enhanced Wnt signaling. Nat Genet. 2009;41(8):885–90. doi: 10.1038/ng.406.PubMedCrossRefGoogle Scholar
  15. 15.
    Sur IK, Hallikas O, Vaharautio A, Yan J, Turunen M, Enge M, et al. Mice lacking a Myc enhancer that includes human SNP rs6983267 are resistant to intestinal tumors. Science. 2012;338(6112):1360–3. doi: 10.1126/science.1228606.PubMedCrossRefGoogle Scholar
  16. 16.
    Li Q, Seo JH, Stranger B, McKenna A, Pe'er I, Laframboise T, et al. Integrative eQTL-based analyses reveal the biology of breast cancer risk loci. Cell. 2013;152(3):633–41. doi: 10.1016/j.cell.2012.12.034.PubMedCentralPubMedCrossRefGoogle Scholar
  17. 17.
    Brown CD, Mangravite LM, Engelhardt BE. Integrative modeling of eQTLs and cis-regulatory elements suggests mechanisms underlying cell type specificity of eQTLs. PLoS Genet. 2013;9(8):e1003649. doi: 10.1371/journal.pgen.1003649.PubMedCentralPubMedCrossRefGoogle Scholar
  18. 18.
    Loo LW CI, Tiirikainen M, Lum-Jones A, Seifried A, Dunklee LM, Church JM, et al. cis-Expression QTL analysis of established colorectal cancer risk variants in colon tumors and adjacent normal tissue. PloS one. 2012;7(2). doi: 10.1371/journal.pone.0030477.t001.

Copyright information

© International Society of Oncology and BioMarkers (ISOBM) 2014

Authors and Affiliations

  1. 1.Department of Gastroenterological SurgeryPeking University People’s HospitalBeijingPeople’s Republic of China
  2. 2.Department of General SurgeryAffiliated Hospital of QingDao UniversityQingdaoPeople’s Republic of China

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