• Joellen M Schildkraut, Ellen L Goode, Merlise A Clyde, Edwin S Iversen, Patricia G Moorman, Andrew Berchuck, Jeffrey R Marks, Jolanta Lissowska, Louise Brinton, Beata Peplonska, Julie M Cunningham, Robert A Vierkant, David N Rider, Georgia Chenevix-Trench, Penelope M Webb, Jonathan Beesley, Xiaoqing Chen, Catherine Phelan, Rebecca Sutphen, Thomas A Sellers, Leigh Pearce, Anna H Wu, David Van Den Berg, David Conti, Christopher K Elund, Rebecca Anderson, Marc T Goodman, Galina Lurie, Michael E Carney, Pamela J Thompson, Simon A Gayther, Susan J Ramus, Ian Jacobs, Krüger KjaerSusanneS, Estrid Hogdall, Jan Blaakaer, Claus Hogdall, Douglas F Easton, Honglin Song, Paul D P Pharoah, Alice S Whittemore, Valerie McGuire, Lydia Quaye, Hoda Anton-Culver, Argyrios Ziogas, Kathryn L Terry, Daniel W Cramer, Susan E Hankinson, Shelley S Tworoger, Brian Calingaert, Stephen Chanock, Mark Sherman, Montserrat Garcia-Closas, and Australian Ovarian Cancer Study Group.
• Comprehensive Cancer Center, Department of Community and Family Medicine, Duke University Medical Center, and Department of Statistical Science, Duke University, Durham, North Carolina, USA. schil001@mc.duke.edu
• Cancer Res. 2009 Mar 15; 69 (6): 2349-57.

AbstractThe p53 protein is critical for multiple cellular functions including cell growth and DNA repair. We assessed whether polymorphisms in the region encoding TP53 were associated with risk of invasive ovarian cancer. The study population includes a total of 5,206 invasive ovarian cancer cases (2,829 of which were serous) and 8,790 controls from 13 case-control or nested case-control studies participating in the Ovarian Cancer Association Consortium (OCAC). Three of the studies performed independent discovery investigations involving genotyping of up to 23 single nucleotide polymorphisms (SNP) in the TP53 region. Significant findings from this discovery phase were followed up for replication in the other OCAC studies. Mixed effects logistic regression was used to generate posterior median per allele odds ratios (OR), 95% probability intervals (PI), and Bayes factors (BF) for genotype associations. Five SNPs showed significant associations with risk in one or more of the discovery investigations and were followed up by OCAC. Mixed effects analysis confirmed associations with serous invasive cancers for two correlated (r(2) = 0.62) SNPs: rs2287498 (median per allele OR, 1.30; 95% PI, 1.07-1.57) and rs12951053 (median per allele OR, 1.19; 95% PI, 1.01-1.38). Analyses of other histologic subtypes suggested similar associations with endometrioid but not with mucinous or clear cell cancers. This large study provides statistical evidence for a small increase in risk of ovarian cancer associated with common variants in the TP53 region.

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