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GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer


Genome-wide association studies (GWAS) have identified four susceptibility loci for epithelial ovarian cancer (EOC), with another two suggestive loci reaching near genome-wide significance. We pooled data from a GWAS conducted in North America with another GWAS from the UK. We selected the top 24,551 SNPs for inclusion on the iCOGS custom genotyping array. We performed follow-up genotyping in 18,174 individuals with EOC (cases) and 26,134 controls from 43 studies from the Ovarian Cancer Association Consortium. We validated the two loci at 3q25 and 17q21 that were previously found to have associations close to genome-wide significance and identified three loci newly associated with risk: two loci associated with all EOC subtypes at 8q21 (rs11782652, P = 5.5 × 10−9) and 10p12 (rs1243180, P = 1.8 × 10−8) and another locus specific to the serous subtype at 17q12 (rs757210, P = 8.1 × 10−10). An integrated molecular analysis of genes and regulatory regions at these loci provided evidence for functional mechanisms underlying susceptibility and implicated CHMP4C in the pathogenesis of ovarian cancer.

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Figure 1: The associations of SNP genotypes with risk of ovarian cancer.
Figure 2: Summary of the functional analyses at the 8q21 locus.
Figure 3: Summary of the functional analysis of the 10p12 locus.
Figure 4: Summary of the functional analysis of the 17q12 locus.


  1. 1

    Lichtenstein, P. et al. Environmental and heritable factors in the causation of cancer—analyses of cohorts of twins from Sweden, Denmark and Finland. N. Engl. J. Med. 343, 78–85 (2000).

    CAS  Article  Google Scholar 

  2. 2

    Stratton, J.F., Pharoah, P., Smith, S.K., Easton, D. & Ponder, B.A. A systematic review and meta-analysis of family history and risk of ovarian cancer. Br. J. Obstet. Gynaecol. 105, 493–499 (1998).

    CAS  Article  Google Scholar 

  3. 3

    Antoniou, A.C. & Easton, D.F. Risk prediction models for familial breast cancer. Future Oncol. 2, 257–274 (2006).

    Article  Google Scholar 

  4. 4

    Song, H. et al. A genome-wide association study identifies a new ovarian cancer susceptibility l ocus on 9p22.2. Nat. Genet. 41, 996–1000 (2009).

    CAS  Article  Google Scholar 

  5. 5

    Bolton, K.L. et al. Common variants at 19p13 are associated with susceptibility to ovarian cancer. Nat. Genet. 42, 880–884 (2010).

    CAS  Article  Google Scholar 

  6. 6

    Goode, E.L. et al. A genome-wide association study identifies susceptibility loci for ovarian cancer at 2q31 and 8q24. Nat. Genet. 42, 874–879 (2010).

    CAS  Article  Google Scholar 

  7. 7

    Shen, H. et al. Epigenetic analysis leads to identification of HNF1B as a subtype-specific susceptibility gene for ovarian cancer. Nat. Comm. published online; doi:10.1038/ncomms2629 (27 March 2013).

  8. 8

    Ernst, J. et al. Mapping and analysis of chromatin state dynamics in nine human cell types. Nature 473, 43–49 (2011).

    CAS  Article  Google Scholar 

  9. 9

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

    Article  Google Scholar 

  10. 10

    Kim, M.J. et al. Functional characterization of liver enhancers that regulate drug-associated transporters. Clin. Pharmacol. Ther. 89, 571–578 (2011).

    CAS  Article  Google Scholar 

  11. 11

    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).

    CAS  Article  Google Scholar 

  12. 12

    Wright, J.B., Brown, S.J. & Cole, M.D. Upregulation of c-MYC in cis through a large chromatin loop linked to a cancer risk-associated single-nucleotide polymorphism in colorectal cancer cells. Mol. Cell Biol. 30, 1411–1420 (2010).

    CAS  Article  Google Scholar 

  13. 13

    McCullough, J., Fisher, R.D., Whitby, F.G., Sundquist, W.I. & Hill, C.P. ALIX-CHMP4 interactions in the human ESCRT pathway. Proc. Natl. Acad. Sci. USA 105, 7687–7691 (2008).

    CAS  Article  Google Scholar 

  14. 14

    Carlton, J.G., Caballe, A., Agromayor, M., Kloc, M. & Martin-Serrano, J. ESCRT-III governs the Aurora B-mediated abscission checkpoint through CHMP4C. Science 336, 220–225 (2012).

    CAS  Article  Google Scholar 

  15. 15

    Yu, X., Riley, T. & Levine, A.J. The regulation of the endosomal compartment by p53 the tumor suppressor gene. FEBS J. 276, 2201–2212 (2009).

    CAS  Article  Google Scholar 

  16. 16

    Nikolova, D.N. et al. Genome-wide gene expression profiles of ovarian carcinoma: identification of molecular targets for the treatment of ovarian carcinoma. Mol. Med. Report 2, 365–384 (2009).

    CAS  Google Scholar 

  17. 17

    Caudell, D. & Aplan, P.D. The role of CALM-AF10 gene fusion in acute leukemia. Leukemia 22, 678–685 (2008).

    CAS  Article  Google Scholar 

  18. 18

    Cóser, V.M. et al. Nebulette is the second member of the nebulin family fused to the MLL gene in infant leukemia. Cancer Genet. Cytogenet. 198, 151–154 (2010).

    Article  Google Scholar 

  19. 19

    Ram, R. & Blaxall, B.C. Nebulette mutations in cardiac remodeling: big effects from a small mechanosensor. J. Am. Coll. Cardiol. 56, 1503–1505 (2010).

    Article  Google Scholar 

  20. 20

    Salzman, J. et al. ESRRA-C11orf20 is a recurrent gene fusion in serous ovarian carcinoma. PLoS Biol. 9, e1001156 (2011).

    CAS  Article  Google Scholar 

  21. 21

    Voight, B.F. et al. Twelve type 2 diabetes susceptibility loci identified through large-scale association analysis. Nat. Genet. 42, 579–589 (2010).

    CAS  Article  Google Scholar 

  22. 22

    Spurdle, A.B. et al. Genome-wide association study identifies a common variant associated with risk of endometrial cancer. Nat. Genet. 43, 451–454 (2011).

    CAS  Article  Google Scholar 

  23. 23

    Elliott, K.S. et al. Evaluation of association of HNF1B variants with diverse cancers: collaborative analysis of data from 19 genome-wide association studies. PLoS ONE 5, e10858 (2010).

    Article  Google Scholar 

  24. 24

    Kato, N., Sasou, S. & Motoyama, T. Expression of hepatocyte nuclear factor-1β (HNF-1β) in clear cell tumors and endometriosis of the ovary. Mod. Pathol. 19, 83–89 (2006).

    CAS  Article  Google Scholar 

  25. 25

    Tsuchiya, A. et al. Expression profiling in ovarian clear cell carcinoma: identification of hepatocyte nuclear factor-1β as a molecular marker and a possible molecular target for therapy of ovarian clear cell carcinoma. Am. J. Pathol. 163, 2503–2512 (2003).

    CAS  Article  Google Scholar 

  26. 26

    Cancer Genome Atlas Research Network. Integrated genomic analyses of ovarian carcinoma. Nature 474, 609–615 (2011).

  27. 27

    Kato, N. & Motoyama, T. Hepatocyte nuclear factor-1β (HNF-1β) in human urogenital organs: its expression and role in embryogenesis and tumorigenesis. Histol. Histopathol. 24, 1479–1486 (2009).

    CAS  PubMed  Google Scholar 

  28. 28

    Hindorff, L.A., Junkins, H.A., Hall, P.A., Mehta, J.P. & Manolio, T.A. A catalogue of published genome-wide association studies. National Institutes of Health National Human Genome Research Institute. <> (2013).

  29. 29

    Antoniou, A.C. et al. A locus on 19p13 modifies risk of breast cancer in BRCA1 mutation carriers and is associated with hormone receptor-negative breast cancer in the general population. Nat. Genet. 42, 885–892 (2010).

    CAS  Article  Google Scholar 

  30. 30

    Michailidou, K. et al. Large-scale genotyping identifies 41 new breast cancer susceptibility loci. Nat. Genet. published online; doi:10.1038/ng.2563 (27 March 2013).

    CAS  Article  Google Scholar 

  31. 31

    Lawrenson, K. et al. Senescent fibroblasts promote neoplastic transformation of partially transformed ovarian epithelial cells in a three-dimensional model of early stage ovarian cancer. Neoplasia 12, 317–325 (2010).

    CAS  Article  Google Scholar 

  32. 32

    Permuth-Wey, J. et al. LIN28B polymorphisms influence susceptibility to epithelial ovarian cancer. Cancer Res. 71, 3896–3903 (2011).

    CAS  Article  Google Scholar 

  33. 33

    Kermani, B.G. Artificial intelligence and global normalization methods for genotyping. US patent 7,035,740 (2008).

  34. 34

    Teo, Y.Y. et al. A genotype calling algorithm for the Illumina BeadArray platform. Bioinformatics 23, 2741–2746 (2007).

    CAS  Article  Google Scholar 

  35. 35

    Giannoulatou, E., Yau, C., Colella, S., Ragoussis, J. & Holmes, C.C. GenoSNP: a variational Bayes within-sample SNP genotyping algorithm that does not require a reference population. Bioinformatics 24, 2209–2214 (2008).

    CAS  Article  Google Scholar 

  36. 36

    Sankararaman, S., Sridhar, S., Kimmel, G. & Halperin, E. Estimating local ancestry in admixed populations. Am. J. Hum. Genet. 82, 290–303 (2008).

    CAS  Article  Google Scholar 

  37. 37

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

    CAS  Article  Google Scholar 

  38. 38

    Xing, G., Lin, C.Y., Wooding, S.P. & Xing, C. Blindly using Wald's test can miss rare disease-causal variants in case-control association studies. Ann. Hum. Genet. 76, 168–177 (2012).

    Article  Google Scholar 

  39. 39

    Breslow, N.E. & Day, N.E. Statistical Methods in Cancer Research. Volume 1—The Analysis of Case-Control Studies (International Agency for Research on Cancer, Lyon, 1980).

    Google Scholar 

  40. 40

    Forbes, S.A. et al. COSMIC: mining complete cancer genomes in the Catalogue of Somatic Mutations in Cancer. Nucleic Acids Res. 39, D945–D950 (2011).

    CAS  Google Scholar 

  41. 41

    Mostafavi, S., Ray, D., Warde-Farley, D., Grouios, C. & Morris, Q. GeneMANIA: a real-time multiple association network integration algorithm for predicting gene function. Genome Biol. 9 (suppl. 1), S4 (2008).

    Article  Google Scholar 

  42. 42

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

    CAS  Article  Google Scholar 

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We thank all the individuals who took part in this study and all the researchers, clinicians and technical and administrative staff who made possible the many studies contributing to this work (a full list is provided in the Supplementary Note). The COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 - HEALTH-F2-2009-223175). The Ovarian Cancer Association Consortium is supported by a grant from the Ovarian Cancer Research Fund thanks to donations by the family and friends of Kathryn Sladek Smith (PPD/RPCI.07). The scientific development and funding for this project were supported in part by the Genetic Associations and Mechanisms in Oncology (GAME-ON) and a National Cancer Institute Cancer Post-GWAS Initiative (U19-CA148112). Details of the funding of individual investigators and studies are provided in the Supplementary Note. This study made use of data generated by the Wellcome Trust Case Control consortium; funding for the project was provided by the Wellcome Trust under award 076113. A full list of the investigators who contributed to the generation of the data is available from the website (see URLs). The results published here are based in part on data generated by The Cancer Genome Atlas Pilot Project established by the National Cancer Institute and National Human Genome Research Institute; information about The Cancer Genome Atlas (TCGA) and the investigators and institutions who constitute the TCGA research network can be found on the website (see URLs).

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Writing group: P.D.P.P., Y.-Y.T., C.M.P., S.J.R., J.M.S., T.A.S., B.L.F., E.L.G., A.N.A.M. and S.A.G. All authors read and approved the final manuscript. Provision of samples and data from contributing studies: K.L., M.P., J.P.T., H. Shen, R.W., R.K., M.C.L., H. Song, D.C.T., F.B., D.V., J.M.C., J.D., E. Dicks, K.K.A., H.A.-C., N.A., S.M.A., L.B., E.V.B., M.W.B., M.J.B., G.B., N.B., J.D.B., L.A.B., A.B.-W., R. Brown, R. Butzow, I.C., M.E.C., R.S.C., J.C.-C., Y.A.C., Z.C., A.D.-M., E. Despierre, J.A.D., T.D., A.d.B., M.D., D.E., R.E., A.B.E., P.A.F., D.F., J.F., Y.-T.G., M.G.-C., A.G.-M., G.G., A.G., M.G., J.G., Q.G., M.K.H., P. Harter, A.H., F.H., P. Hillemanns, M.H., E.H., C.K.H., S.H., A. Jakubowska, A. Jensen, K.R.K., B.Y.K., L.E.K., L.A.K., S.K.K., G.E.K., C.K., J.K., D.L., S.L., N.D.L., N.L., J. Lee, A.L., B.K.L., J. Lissowska, J. Lubinński, L.L., G.L., L.F.A.G.M., K.M., V.M., J.R.M., U.M., F.M., K.B.M., T.N., S.A.N., R.B.N., H. Nevanlinna, S.N., H. Noushmehr, K.O., S.O., I.O., J.P., T.P., L.M.P., J.P.-W., M.C.P., E.M.P., X.Q., H.A.R., L.R.-R., M.A.R., A.R., I.R., I.K.R., H.B.S., I.S., G.S., H. Shen, V.S., X.-O.S., W.S., M.C.S., P.S., K.T., S.-H.T., K.L.T., P.J.T., A.T., S.S.T., A.M.v.A., D.v.d.B., I.V., R.A.V., A.F.V., S.W.-G., N.W., A.S.W., E.W., B.W., Y.L.W., A.H.W., H.P.Y., W.Z., A.Z., F.Z., M.T.G., P. Hall, D.F.E., C.L.P., A.B., G.C.-T., E.I. and J.M.S. Bioinformatics and data management: J.D., E. Dicks, Z.C. and R.W. Data analysis: J.P.T., Q.G., Y.-Y.T. and B.L.F. Preparation of samples for genotyping: S.J.R. and C.M.P. Genotyping: J.M.C., D.C.T., F.B. and D.V. Functional analyses: S.A.G., M.B., A.N.A.M., B.L.F., K.L., H. Shen, E.L.G., S.J.R., Y.A.C. and M.L.C.

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Correspondence to Paul D P Pharoah.

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The authors declare no competing financial interests.

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A list of members is provided in the Supplementary Note.

A list of members is provided in the Supplementary Note.

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Supplementary Tables 1–5, Supplementary Figures 1–13 and Supplementary Note (PDF 43425 kb)

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Pharoah, P., Tsai, YY., Ramus, S. et al. GWAS meta-analysis and replication identifies three new susceptibility loci for ovarian cancer. Nat Genet 45, 362–370 (2013).

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