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Tagging Single Nucleotide Polymorphisms in Cell Cycle Control Genes and Susceptibility to Invasive Epithelial Ovarian Cancer

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Tagging Single Nucleotide Polymorphisms in Cell Cycle Control Genes and Susceptibility to Invasive Epithelial Ovarian Cancer Research Article Tagging Single Nucleotide Polymorphisms in Cell Cycle Control Genes and Susceptibility to Invasive Epithelial Ovarian Cancer Simon A. Gayther,1 Honglin Song,2 Susan J. Ramus,1 Susan Kru¨ger Kjaer,4 Alice S. Whittemore,5 Lydia Quaye,1 Jonathan Tyrer,2 Danielle Shadforth,2 Estrid Hogdall,4 Claus Hogdall,6 Jan Blaeker,7 Richard DiCioccio,8 Valerie McGuire,5 Penelope M. Webb,9 Jonathan Beesley,9 Adele C. Green,9 David C. Whiteman,9 The Australian Ovarian Cancer Study Group,9 The Australian Cancer Study (Ovarian Cancer),20 Marc T. Goodman,10 Galina Lurie,10 Michael E. Carney,10 Francesmary Modugno,10 Roberta B. Ness,11 Robert P. Edwards,12 Kirsten B. Moysich,7 Ellen L. Goode,13 Fergus J. Couch,13 Julie M. Cunningham,13 Thomas A. Sellers,14 Anna H. Wu,15 Malcolm C. Pike,15 Edwin S. Iversen,16 Jeffrey R. Marks,16 Montserrat Garcia-Closas,17 Louise Brinton,17 Jolanta Lissowska,18 Beata Peplonska,19 Douglas F. Easton,3 Ian Jacobs,1 Bruce A.J. Ponder,2 Joellen Schildkraut,16 C. Leigh Pearce,15 Georgia Chenevix-Trench,9 Andrew Berchuck,16 Paul D.P. Pharoah,2 and on behalf of the Ovarian Cancer Association Consortium 1Translational Research Laboratories, University College London, London, United Kingdom; 2Cancer Research United Kingdom Department of Oncology and 3Cancer Research United Kingdom Genetic Epidemiology Unit, University of Cambridge, Strangeways Research Laboratory, Cambridge, United Kingdom; 4Danish Cancer Society, Copenhagen, Denmark; 5Stanford University School of Medicine, Stanford, California; 6University of Copenhagen, Copenhagen, Denmark; 7Aarhus University Hospital, Skejby, Aarhus, Denmark; 8Roswell Park Cancer Institute, Buffalo, New York; 9The Queensland Institute of Medical Research, Post Office Royal Brisbane Hospital, Australia; 10Cancer Research Center, University of Hawaii, Honolulu, Hawaii; 11Department of Epidemiology and University of Pittsburgh Cancer Institute, 12Department of Obstetrics, Gynecology and Reproductive Health, University of Pittsburgh Cancer Institute, Pittsburgh, Pennsylvania; 13Mayo Clinic College of Medicine, Rochester, Minnesota; 14H. Lee Moffitt Cancer Center and Research Institute, Tampa, Florida; 15University of Southern California, Keck School of Medicine, Los Angeles, California; 16Duke University Medical Center, Durham, North Carolina; 17Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, Maryland; 18Department of Cancer Epidemiology and Prevention, M. Sklodowska-Curie Institute of Oncology and Cancer Center, Warsaw, Poland; 19Nofer Institute of Occupational Medicine, Lodz, Poland; and 20Peter MacCallum Cancer Institute, Melbourne, Australia Abstract the minor allele of these SNPs was foundto be associated with reduced risk [OR, 0.91 (0.85–0.98) for rs3731257; and OR, High-risk susceptibility genes explain <40% of the excess risk 0.93 (0.87–0.995) for rs2066827]. In conclusion, we have of familial ovarian cancer. Therefore, other ovarian cancer foundevidencethat a single taggedSNP in both the CDKN2A susceptibility genes are likely to exist. We have useda single and CDKN1B genes may be associatedwith reducedovarian nucleotide polymorphism (SNP)–tagging approach to evaluate cancer risk. This study highlights the need for multicenter common variants in 13 genes involvedin cell cycle control— CCND1, CCND2, CCND3, CCNE1, CDK2, CDK4, CDK6, CDKN1A, collaborations for genetic association studies. [Cancer Res CDKN1B, CDKN2A, CDKN2B, CDKN2C, and CDKN2D—andrisk 2007;67(7):3027–35] of invasive epithelial ovarian cancer. We useda two-stage, multicenter, case-control study. In stage 1, 88 SNPs that tag Introduction common variation in these genes were genotypedin three Several genes have been identified that confer high-penetrance studies from the United Kingdom, United States, and Denmark f susceptibility to epithelial ovarian cancer. The main protagonists ( 1,500 cases and2,500 controls). Genotype frequencies in BRCA1 BRCA2 cases andcontrols were comparedusing logistic regression. are and . These genes are responsible for about half In stage 2, eight other studies from Australia, Poland, and the of all families containing two or more ovarian cancer cases in first- f f degree relatives and most families containing several ovarian UnitedStates ( 2,000 cases and 3,200 controls) were z genotypedfor the five most significant SNPs from stage 1. cancer cases ( 3) or in which ovarian and breast cancers occur No SNP was significant in the stage 2 data alone. Using the together (1, 2). combinedstages 1 and2 dataset, CDKN2A rs3731257 and However, the known susceptibility genes explain <40% of the CDKN1B rs2066827 were associated with disease risk (unad- excess familial ovarian cancer risk (3). If other highly penetrant justed P trend= 0.008 and0.036, respectively), but these were ovarian cancer susceptibility genes exist, they are likely to be rare. One possible explanation for the residual risks is the existence of not significant after adjusting for multiple testing. Carrying several common but only moderately or low-penetrance suscepti- bility alleles in the population (4). Note: Supplementary data for this article are available at Cancer Research Online There have been several studies that have attempted to identify (http://cancerres.aacrjournals.org/). S.A. Gayther and H. Song contributed equally to this work. common variants in genes that may be associated with increased Requests for reprints: Simon Gayther, Translational Research Laboratories, Windeyer risk of ovarian cancer. Candidate genes have usually been selected Institute, University College London, 46 Cleveland Street, London W1T 4JF, United based on biological plausibility. These include genes in pathways Kingdom. Phone: 44-20-7679-9204; Fax: 44-20-7679-9687; E-mail: [email protected]. I2007 American Association for Cancer Research. controlling steroid hormone metabolism (e.g., progesterone recep- doi:10.1158/0008-5472.CAN-06-3261 tor, androgen receptor, CYP17, prohibitin; refs. 5–14), DNA repair www.aacrjournals.org 3027 Cancer Res 2007; 67: (7). April 1, 2007 Downloaded from cancerres.aacrjournals.org on September 28, 2021. © 2007 American Association for Cancer Research. Cancer Research Table 1A. Characteristics of the 11 ovarian cancer case control studies (listed alphabetically) included in the Ovarian Cancer Association Consortium pooled study Study name Location Total Total Age Age Reference DNA source Days from Number number number range range diagnosis to of SNPs c of cases* of controls* (cases) (controls) blood draw genotyped AOCS and ACS Multiregional, 802 (71) 933 (42) 23–80 19–81 9 Blood 0–1,663(103) 5 (ovarian Australia lymphocytes cancer) FROC (Family Stanford, CA 327 (39) 429 (59) 23–64 19–66 16, 17, 21, 23 Blood 55–1,477 (281) 88 Registry for lymphocytes; Ovarian mouthwash Cancer) Study Hawaii Ovarian Hawaii 313 (241) 574 (426) 18–87 19–88 33 Blood 16–2,026 (375) 5 Cancer Study lymphocytes; mouthwash HOPE Pittsburgh 57 (1) 152 (8) 34–80 44–79 – Blood 0–280 (149) 5 (hormones lymphocytes; and ovarian mouthwash cancer prediction) study LAC-CCOC Los Angeles, CA 659 (211) 819 (198) 18–84 21–78 8 Blood 46–1,340 (252) 5 lymphocytes MALOVA Copenhagen, 446 1221 (0) 32–80 35–79 16, 17, 21, 23 Blood All preoperative 88 (Malignant Denmark lymphocytes Ovarian Cancer study) Mayo Clinic Minnesota 317 (13) 462 (35) 28–91 23–90 32 Blood 0–365 (31) 5 Rochester, lymphocytes ovarian cancer case- control study NCOCS North Carolina 610 (91) 843(156) 22–74 20–75 9 Blood 29–1,259 (187) 5 lymphocytes POCS Warsaw and 264 625 (0) 24–74 24–74 – Blood 0–525 (82) 5 Lodz lymphocytes; mouthwash SEARCH Cambridge, 731 (42) 855 (4) 21–74 39–77 16, 17, 21, 23 Blood 140–4,850 (1,231) 88 ovarian United lymphocytes cancer Kingdom *Numbers of subjects that are non-white are given in parentheses. cThe mean is given in parentheses. (e.g., BRCA1, BRCA2, RAD51, MSH2; refs. 15–17) and in putative the mechanisms that regulate cell division. In mammalian cells, cell oncogenes and tumor suppressor genes (TP53, RB1, HRAS1, STK15; division is controlled by the activity of cyclin-dependent kinases refs. 18–23). Thus far, reported positive associations include (CDK) and their essential activating coenzymes, the cyclins and an increased ovarian cancer risk for two PGR haplotypes (8); a CDK inhibitors (reviewed in refs. 24, 25). CDK activity is regulated protective effect for the PGR promoter +331A allele in endome- on several levels, including cyclin synthesis and degradation, trioid ovarian tumors (9); an increased risk of borderline ovarian phosphorylation, and dephosphorylation. The interaction between cancer associated with the Pro72Arg polymorphism in the TP53 CDKs and cyclins is tightly controlled to ensure an ordered gene (20); and an increased risk associated with the polymorphism progression through the cell cycle from G1 to S to G2. The events in the STK15 oncogene (23). However, none of these associations occurring before DNA synthesis are probably the most thoroughly are conclusive due to the small size of the initial studies, and there understood. The key event in cell cycle regulation is transversion are no reports indicating that they have been validated in of the restriction (R) point late in G1, which is crucial to the cell’s additional populations. destiny toward division, differentiation, senescence, or apoptosis. It There are no published reports describing the association is believed that once the R point has been overcome, cell cycle between variants in cell-cycle control genes and ovarian cancer
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