Evaluating the ovarian cancer gonadotropin hypothesis: A candidate gene study

Alice W. Lee, Jonathan P. Tyrer, Jennifer A. Doherty, Douglas A. Stram, Jolanta Kupryjanczyk, Agnieszka Dansonka-Mieszkowska, Joanna Plisiecka-Halasa, Beata Spiewankiewicz, Emily J. Myers, Georgia Chenevix-Trench, Peter A. Fasching, Matthias W. Beckmann, Arif B. Ekici, Alexander Hein, Ignace Vergote, Els Van Nieuwenhuysen, Diether Lambrechts, Kristine G. Wicklund, Ursula Eilber, Shan Wang-GohrkeJenny Chang-Claude, Anja Rudolph, Lara Sucheston-Campbell, Kunle Odunsi, Kirsten B. Moysich, Yurii B. Shvetsov, Pamela J. Thompson, Marc T. Goodman, Lynne R. Wilkens, Thilo Dörk, Peter Hillemanns, Matthias Dürst, Ingo B. Runnebaum, Natalia Bogdanova, Liisa M. Pelttari, Heli Nevanlinna, Arto Leminen, Robert P. Edwards, Joseph L. Kelley, Philipp Harter, Ira Schwaab, Florian Heitz, Andreas Du Bois, Sandra Orsulic, Jenny Lester, Christine Walsh, Beth Y. Karlan, Estrid Hogdall, Susanne K. Kjaer, Allan Jensen, Robert A. Vierkant, Julie M. Cunningham, Ellen L. Goode, Brooke L. Fridley, Melissa C. Southey, Graham G. Giles, Fiona Bruinsma, Xifeng Wu, Michelle A.T. Hildebrandt, Karen Lu, Dong Liang, Maria Bisogna, Douglas A. Levine, Rachel Palmieri Weber, Joellen M. Schildkraut, Edwin S. Iversen, Andrew Berchuck, Kathryn L. Terry, Daniel W. Cramer, Shelley S. Tworoger, Elizabeth M. Poole, Sara H. Olson, Irene Orlow, Elisa V. Bandera, Line Bjorge, Ingvild L. Tangen, Helga B. Salvesen, Camilla Krakstad, Leon F.A.G. Massuger, Lambertus A. Kiemeney, Katja K.H. Aben, Anne M. Van Altena, Yukie Bean, Tanja Pejovic, Melissa Kellar, Nhu D. Le, Linda S. Cook, Linda E. Kelemen, Angela Brooks-Wilson, Jan Lubinski, Jacek Gronwald, Cezary Cybulski, Anna Jakubowska, Nicolas Wentzensen, Louise A. Brinton, Jolanta Lissowska, Hannah Yang, Lotte Nedergaard, Lene Lundvall, Claus Hogdall, Honglin Song, Ian G. Campbell, Diana Eccles, Rosalind Glasspool, Nadeem Siddiqui, Karen Carty, James Paul, Iain A. McNeish, Weiva Sieh, Valerie McGuire, Joseph H. Rothstein, Alice S. Whittemore, John R. McLaughlin, Harvey A. Risch, Catherine M. Phelan, Hoda Anton-Culver, Argyrios Ziogas, Usha Menon, Susan J. Ramus, Aleksandra Gentry-Maharaj, Patricia Harrington, Malcolm C. Pike, Francesmary Modugno, Mary Anne Rossing, Roberta B. Ness, Paul D.P. Pharoah, Daniel O. Stram, Anna H. Wu, Celeste Leigh Pearce

Research output: Contribution to journalArticle

11 Scopus citations

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) method was also used to evaluate gene-level associations. Results: We did not find any genome-wide significant associations between individual SNPs and ovarian cancer risk. However, there was some suggestion of gene-level associations for four gonadotropin signaling pathway genes: INHBB (p = 0.045, mucinous), LHCGR (p = 0.046, high-grade serous), GNRH (p = 0.041, high-grade serous), and FSHB (p = 0.036, overall invasive). There was also suggestive evidence for INHA (p = 0.060, overall invasive). Conclusions: Ovarian cancer studies have limited sample numbers, thus fewer genome-wide susceptibility alleles, with only modest associations, have been identified relative to breast and prostate cancers. We have evaluated the majority of ovarian cancer studies with biological samples, to our knowledge, leaving no opportunity for replication. Using both our understanding of biology and powerful gene-level tests, we have identified four putative ovarian cancer loci near INHBB, LHCGR, GNRH, and FSHB that warrant a second look if larger sample sizes and denser genotype chips become available.

Original languageEnglish (US)
Pages (from-to)542-548
Number of pages7
JournalGynecologic oncology
Volume136
Issue number3
DOIs
StatePublished - Mar 1 2015

Keywords

  • Gene
  • Genetic variation
  • Genetics
  • Gonadotropins
  • Ovarian cancer
  • Polymorphisms

ASJC Scopus subject areas

  • Oncology
  • Obstetrics and Gynecology

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    Lee, A. W., Tyrer, J. P., Doherty, J. A., Stram, D. A., Kupryjanczyk, J., Dansonka-Mieszkowska, A., Plisiecka-Halasa, J., Spiewankiewicz, B., Myers, E. J., Chenevix-Trench, G., Fasching, P. A., Beckmann, M. W., Ekici, A. B., Hein, A., Vergote, I., Van Nieuwenhuysen, E., Lambrechts, D., Wicklund, K. G., Eilber, U., ... Pearce, C. L. (2015). Evaluating the ovarian cancer gonadotropin hypothesis: A candidate gene study. Gynecologic oncology, 136(3), 542-548. https://doi.org/10.1016/j.ygyno.2014.12.017