Evaluating the ovarian cancer gonadotropin hypothesis: A candidate gene study

AW Lee; JP Tyrer; JA Doherty; DA Stram; J Kupryjanczyk; A Dansonka-Mieszkowska; J Plisiecka-Halasa; B Spiewankiewicz; EJ Myers; G Chenevix-Trench; PA Fasching; MW Beckmann; AB Ekici; A Hein; I Vergote; E Van Nieuwenhuysen; D Lambrechts; KG Wicklund; U Eilber; S Wang-Gohrke; J Chang-Claude; A Rudolph; L Sucheston-Campbell; K Odunsi; KB Moysich; YB Shvetsov; PJ Thompson; MT Goodman; LR Wilkens; T Dörk; P Hillemanns; M Dürst; IB Runnebaum; N Bogdanova; LM Pelttari; H Nevanlinna; A Leminen; RP Edwards; JL Kelley; P Harter; I Schwaab; F Heitz; A Du Bois; S Orsulic; J Lester; C Walsh; BY Karlan; E Hogdall; SK Kjaer; A Jensen; RA Vierkant; JM Cunningham; EL Goode; BL Fridley; MC Southey; GG Giles; F Bruinsma; X Wu; MAT Hildebrandt; K Lu; D Liang; M Bisogna; DA Levine; RP Weber; JM Schildkraut; ES Iversen; A Berchuck; KL Terry; DW Cramer; SS Tworoger; EM Poole; SH Olson; I Orlow; EV Bandera; L Bjorge; IL Tangen; HB Salvesen; C Krakstad; LFAG Massuger; LA Kiemeney; KKH Aben; AM Van Altena; Y Bean; T Pejovic; M Kellar; ND Le; LS Cook; LE Kelemen; A Brooks-Wilson; J Lubinski; J Gronwald; C Cybulski; A Jakubowska; N Wentzensen; LA Brinton; J Lissowska; H Yang; L Nedergaard; L Lundvall; C Hogdall

Journal article

Evaluating the ovarian cancer gonadotropin hypothesis: A candidate gene study

AW Lee, JP Tyrer, JA Doherty, DA Stram, J Kupryjanczyk, A Dansonka-Mieszkowska, J Plisiecka-Halasa, B Spiewankiewicz, EJ Myers, G Chenevix-Trench, PA Fasching, MW Beckmann, AB Ekici, A Hein, I Vergote, E Van Nieuwenhuysen, D Lambrechts, KG Wicklund, U Eilber, S Wang-Gohrke Show all

Gynecologic Oncology | ACADEMIC PRESS INC ELSEVIER SCIENCE | Published : 2015

DOI: 10.1016/j.ygyno.2014.12.017

Abstract

Objective: Ovarian cancer is a hormone-related disease with a strong genetic basis. However, none of its high-penetrance susceptibility genes and GWAS-identified variants to date are known to be involved in hormonal pathways. Given the hypothesized etiologic role of gonadotropins, an assessment of how variability in genes involved in the gonadotropin signaling pathway impacts disease risk is warranted. Methods: Genetic data from 41 ovarian cancer study sites were pooled and unconditional logistic regression was used to evaluate whether any of the 2185 SNPs from 11 gonadotropin signaling pathway genes was associated with ovarian cancer risk. A burden test using the admixture likelihood (AML) ..

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University of Melbourne Researchers

Melissa Southey Author

Fiona Bruinsma Author

Ian Campbell Author

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Grants

Awarded by National Institutes of Health

Funding Acknowledgements

The scientific development and funding for this project were funded by the following: the US National Cancer Institute (R01-CA076016); the COGS project is funded through a European Commission's Seventh Framework Programme grant (agreement number 223175 HEALTH F2 2009-223175); the Genetic Associations and Mechanisms in Oncology (GAME-ON): a NCI Cancer Post-GWAS Initiative (U19-CA148112); 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).