Skip to main content

Thank you for visiting 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.

Genome-wide association study of renal cell carcinoma identifies two susceptibility loci on 2p21 and 11q13.3


We conducted a two-stage genome-wide association study of renal cell carcinoma (RCC) in 3,772 affected individuals (cases) and 8,505 controls of European background from 11 studies and followed up 6 SNPs in 3 replication studies of 2,198 cases and 4,918 controls. Two loci on the regions of 2p21 and 11q13.3 were associated with RCC susceptibility below genome-wide significance. Two correlated variants (r2 = 0.99 in controls), rs11894252 (P = 1.8 × 10−8) and rs7579899 (P = 2.3 × 10−9), map to EPAS1 on 2p21, which encodes hypoxia-inducible-factor-2 alpha, a transcription factor previously implicated in RCC. The second locus, rs7105934, at 11q13.3, contains no characterized genes (P = 7.8 × 10−14). In addition, we observed a promising association on 12q24.31 for rs4765623, which maps to SCARB1, the scavenger receptor class B, member 1 gene (P = 2.6 × 10−8). Our study reports previously unidentified genomic regions associated with RCC risk that may lead to new etiological insights.

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

Relevant articles

Open Access articles citing this article.

Access options

Buy article

Get time limited or full article access on ReadCube.


All prices are NET prices.

Figure 1: Association results, recombination and linkage disequilibrium plots for regions below genome-wide significance (2p21 and 11q13.3) and a region with a promising association (12q24.31) to RCC susceptibility.
Figure 2: Forest plots for three SNPs showing significant or promising association to RCC susceptibility.


  1. Ferlay, J., Bray, F., Pisani, P. & Parkin, D.M. GLOBOCAN 2002: Cancer Incidence, Mortality and Prevalence Worldwide. (IARC CancerBase No. 5. version 2.0, IARCPress, Lyon, France, 2004).

    Google Scholar 

  2. Scélo, G. & Brennan, P. The epidemiology of bladder and kidney cancer. Nat. Clin. Pract. Urol. 4, 205–217 (2007).

    Google Scholar 

  3. Chow, W.H., Dong, L.M. & Devesa, S.S. Epidemiology and risk factors for kidney cancer. Nat. Rev. Urol. 7, 245–257 (2010).

    Google Scholar 

  4. McLaughlin, J.K. et al. A population–based case–control study of renal cell carcinoma. J. Natl. Cancer Inst. 72, 275–284 (1984).

    Google Scholar 

  5. Schlehofer, B. et al. International renal-cell-cancer study. VI. The role of medical and family history. Int. J. Cancer 66, 723–726 (1996).

    Google Scholar 

  6. Gago-Dominguez, M., Yuan, J.M., Castelao, J.E., Ross, R.K. & Yu, M.C. Family history and risk of renal cell carcinoma. Cancer Epidemiol. Biomarkers Prev. 10, 1001–1004 (2001).

    Google Scholar 

  7. Hung, R.J. et al. Family history and the risk of kidney cancer: a multicenter case-control study in Central Europe. Cancer Epidemiol. Biomarkers Prev. 16, 1287–1290 (2007).

    Google Scholar 

  8. Linehan, W.M. et al. Hereditary kidney cancer: unique opportunity for disease-based therapy. Cancer 115, 2252–2261 (2009).

    Google Scholar 

  9. Peto, J. & Houlston, R.S. Genetics and the common cancers. Eur. J. Cancer 37 Suppl 8, S88–S96 (2001).

    Google Scholar 

  10. Wellcome Trust Case Control Consortium. Genome-wide association study of 14,000 cases of seven common diseases and 3,000 shared controls. Nature 447, 661–678 (2007).

  11. Frazer, K.A. et al. A second generation human haplotype map of over 3.1 million SNPs. Nature 449, 851–861 (2007).

    Google Scholar 

  12. Packer, B.R. et al. SNP500Cancer: a public resource for sequence validation, assay development, and frequency analysis for genetic variation in candidate genes. Nucleic Acids Res. 34, D617–D621 (2006).

    Google Scholar 

  13. 1000 Genomes Project Consortium. A map of human genome variation from population-scale sequencing. Nature 467, 1061–1073 (2010).

  14. Skol, A.D., Scott, L.J., Abecasis, G.R. & Boehnke, M. Joint analysis is more efficient than replication-based analysis for two-stage genome-wide association studies. Nat. Genet. 38, 209–213 (2006).

    Google Scholar 

  15. Higgins, J.P. et al. Gene expression patterns in renal cell carcinoma assessed by complementary DNA microarray. Am. J. Pathol. 162, 925–932 (2003).

    Google Scholar 

  16. Xia, G. et al. Regulation of vascular endothelial growth factor transcription by endothelial PAS domain protein 1 (EPAS1) and possible involvement of EPAS1 in the angiogenesis of renal cell carcinoma. Cancer 91, 1429–1436 (2001).

    Google Scholar 

  17. Sowter, H.M., Raval, R.R., Moore, J.W., Ratcliffe, P.J. & Harris, A.L. Predominant role of hypoxia-inducible transcription factor (Hif)-1alpha versus Hif-2alpha in regulation of the transcriptional response to hypoxia. Cancer Res. 63, 6130–6134 (2003).

    Google Scholar 

  18. Kondo, K., Kim, W.Y., Lechpammer, M. & Kaelin, W.G. Jr. Inhibition of HIF2alpha is sufficient to suppress pVHL-defective tumor growth. PLoS Biol. 1, E83 (2003).

    Google Scholar 

  19. Zimmer, M., Doucette, D., Siddiqui, N. & Iliopoulos, O. Inhibition of hypoxia-inducible factor is sufficient for growth suppression of VHL−/− tumors. Mol. Cancer Res. 2, 89–95 (2004).

    Google Scholar 

  20. Gunaratnam, L. & Bonventre, J.V. HIF in kidney disease and development. J. Am. Soc. Nephrol. 20, 1877–1887 (2009).

    Google Scholar 

  21. Chanock, S. High marks for GWAS. Nat. Genet. 41, 765–766 (2009).

    Google Scholar 

  22. Thomas, G. et al. Multiple loci identified in a genome-wide association study of prostate cancer. Nat. Genet. 40, 310–315 (2008).

    Google Scholar 

  23. Eeles, R.A. et al. Multiple newly identified loci associated with prostate cancer susceptibility. Nat. Genet. 40, 316–321 (2008).

    Google Scholar 

  24. Turnbull, C. et al. Genome-wide association study identifies five new breast cancer susceptibility loci. Nat. Genet. 42, 504–507 (2010).

    Google Scholar 

  25. Kozarsky, K.F. et al. Overexpression of the HDL receptor SR-BI alters plasma HDL and bile cholesterol levels. Nature 387, 414–417 (1997).

    Google Scholar 

  26. Rigotti, A. et al. A targeted mutation in the murine gene encoding the high density lipoprotein (HDL) receptor scavenger receptor class B type I reveals its key role in HDL metabolism. Proc. Natl. Acad. Sci. USA 94, 12610–12615 (1997).

    Google Scholar 

  27. Ueda, Y. et al. Lower plasma levels and accelerated clearance of high density lipoprotein (HDL) and non-HDL cholesterol in scavenger receptor class B type I transgenic mice. J. Biol. Chem. 274, 7165–7171 (1999).

    Google Scholar 

  28. Yeager, M. et al. Genome-wide association study of prostate cancer identifies a second risk locus at 8q24. Nat. Genet. 39, 645–649 (2007).

    Google Scholar 

  29. Hunter, D.J. et al. A genome-wide association study identifies alleles in FGFR2 associated with risk of sporadic postmenopausal breast cancer. Nat. Genet. 39, 870–874 (2007).

    Google Scholar 

  30. Landi, M.T. et al. A genome-wide association study of lung cancer identifies a region of chromosome 5p15 associated with risk for adenocarcinoma. Am. J. Hum. Genet. 85, 679–691 (2009).

    Google Scholar 

  31. Amundadottir, L. et al. Genome-wide association study identifies variants in the ABO locus associated with susceptibility to pancreatic cancer. Nat. Genet. 41, 986–990 (2009).

    Google Scholar 

  32. Petersen, G.M. et al. A genome-wide association study identifies pancreatic cancer susceptibility loci on chromosomes 13q22.1, 1q32.1 and 5p15.33. Nat. Genet. 42, 224–228 (2010).

    Google Scholar 

  33. Yu, K. et al. Population substructure and control selection in genome-wide association studies. PLoS ONE 3, e2551 (2008).

    Google Scholar 

  34. Falush, D., Stephens, M. & Pritchard, J.K. Inference of population structure using multilocus genotype data: dominant markers and null alleles. Mol. Ecol. Notes 7, 574–578 (2007).

    Google Scholar 

  35. Price, A.L. et al. Principal components analysis corrects for stratification in genome-wide association studies. Nat. Genet. 38, 904–909 (2006).

    Google Scholar 

  36. de Bakker, P.I. et al. Practical aspects of imputation-driven meta-analysis of genome-wide association studies. Hum. Mol. Genet. 17, R122–R128 (2008).

    Google Scholar 

  37. Aulchenko, Y.S., Struchalin, M.V. & van Duijn, C.M. ProbABEL package for genome-wide association analysis of imputed data. BMC Bioinformatics 11, 134 (2010).

    Google Scholar 

Download references


The authors thank all of the participants who took part in this research and the funders and support staff who made this study possible. Funding for the genome-wide genotyping was provided by the French Institut National du Cancer (INCa) for those studies coordinated by IARC/CNG, and by the intramural research program of the National Cancer Institute (NCI), US National Institutes of Health (NIH) for those studies coordinated by the NCI. Additional acknowledgments can be found in the Supplementary Note.

Author information

Authors and Affiliations



M.P.P., M.J., J.R.T., G.S., L.E.M., V.G., W.-H.C., J.D.M., N.R., S.J.C. and P. Brennan contributed to the design and execution of the overall study. M.P.P., M.J., J.R.T., G.S., L.E.M., L.A.K., X.W., V.G., K.B.J., J.D.M., N.R., S.J.C. and P. Brennan contributed to the statistical analyses. M.P.P., M.J., S.J.C. and P. Brennan wrote the first draft of the manuscript. D. Zelenika, E.P., L.A.K., X.W., K.B.J., S.H.V., S.L.v.d.M., Y.Y., A.M.M., E.S.B., N.N.C., M.F., D.L., I.G., S.H., H. Blanche, A.H., G.S.T., Z.W., M.Y., K.G.S., S.J.C. and M.L. supervised or conducted the genotyping. The remaining authors conducted the epidemiologic studies and contributed samples to the GWAS and/or replication studies. All authors contributed to the writing of the manuscript.

Corresponding authors

Correspondence to Stephen J Chanock or Paul Brennan.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Tables 1, 3 and 4, Supplementary Figures 1–3 and Supplementary Note (PDF 677 kb)

Supplementary Table 2

Association results for SNPs imputed on 2p21 (EPAS1), 11q13.3, and 12q24.31 (SCARB1), using data from 1000 Genomes as scaffold (XLS 7053 kb)

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Purdue, M., Johansson, M., Zelenika, D. et al. Genome-wide association study of renal cell carcinoma identifies two susceptibility loci on 2p21 and 11q13.3. Nat Genet 43, 60–65 (2011).

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI:

This article is cited by


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing