Carboplatin/taxane-induced gastrointestinal toxicity: a pharmacogenomics study on the SCOTROC1 trial

Carboplatin/taxane combination is first-line therapy for ovarian cancer. However, patients can encounter treatment delays, impaired quality of life, even death because of chemotherapy-induced gastrointestinal (GI) toxicity. A candidate gene study was conducted to assess potential association of genetic variants with GI toxicity in 808 patients who received carboplatin/taxane in the Scottish Randomized Trial in Ovarian Cancer 1 (SCOTROC1). Patients were randomized into discovery and validation cohorts consisting of 404 patients each. Clinical covariates and genetic variants associated with grade III/IV GI toxicity in discovery cohort were evaluated in replication cohort. Chemotherapy-induced GI toxicity was significantly associated with seven single-nucleotide polymorphisms in the ATP7B, GSR, VEGFA and SCN10A genes. Patients with risk genotypes were at 1.53 to 18.01 higher odds to develop carboplatin/taxane-induced GI toxicity (P<0.01). Variants in the VEGF gene were marginally associated with survival time. Our data provide potential targets for modulation/inhibition of GI toxicity in ovarian cancer patients

Hip fracture risk assessment: Artificial neural network outperforms conditional logistic regression in an age- and sex-matched case control study

Copyright @ 2013 Tseng et al.; licensee BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background - Osteoporotic hip fractures with a significant morbidity and excess mortality among the elderly have imposed huge health and economic burdens on societies worldwide. In this age- and sex-matched case control study, we examined the risk factors of hip fractures and assessed the fracture risk by conditional logistic regression (CLR) and ensemble artificial neural network (ANN). The performances of these two classifiers were compared. Methods - The study population consisted of 217 pairs (149 women and 68 men) of fractures and controls with an age older than 60 years. All the participants were interviewed with the same standardized questionnaire including questions on 66 risk factors in 12 categories. Univariate CLR analysis was initially conducted to examine the unadjusted odds ratio of all potential risk factors. The significant risk factors were then tested by multivariate analyses. For fracture risk assessment, the participants were randomly divided into modeling and testing datasets for 10-fold cross validation analyses. The predicting models built by CLR and ANN in modeling datasets were applied to testing datasets for generalization study. The performances, including discrimination and calibration, were compared with non-parametric Wilcoxon tests. Results - In univariate CLR analyses, 16 variables achieved significant level, and six of them remained significant in multivariate analyses, including low T score, low BMI, low MMSE score, milk intake, walking difficulty, and significant fall at home. For discrimination, ANN outperformed CLR in both 16- and 6-variable analyses in modeling and testing datasets (p?<?0.005). For calibration, ANN outperformed CLR only in 16-variable analyses in modeling and testing datasets (p?=?0.013 and 0.047, respectively). Conclusions - The risk factors of hip fracture are more personal than environmental. With adequate model construction, ANN may outperform CLR in both discrimination and calibration. ANN seems to have not been developed to its full potential and efforts should be made to improve its performance.National Health Research Institutes in Taiwa

Comprehensive genetic assessment of the ESR1 locus identifies a risk region for endometrial cancer.

Excessive exposure to estrogen is a well-established risk factor for endometrial cancer (EC), particularly for cancers of endometrioid histology. The physiological function of estrogen is primarily mediated by estrogen receptor alpha, encoded by ESR1. Consequently, several studies have investigated whether variation at the ESR1 locus is associated with risk of EC, with conflicting results. We performed comprehensive fine-mapping analyses of 3633 genotyped and imputed single nucleotide polymorphisms (SNPs) in 6607 EC cases and 37 925 controls. There was evidence of an EC risk signal located at a potential alternative promoter of the ESR1 gene (lead SNP rs79575945, P=1.86×10(-5)), which was stronger for cancers of endometrioid subtype (P=3.76×10(-6)). Bioinformatic analysis suggests that this risk signal is in a functionally important region targeting ESR1, and eQTL analysis found that rs79575945 was associated with expression of SYNE1, a neighbouring gene. In summary, we have identified a single EC risk signal located at ESR1, at study-wide significance. Given SNPs located at this locus have been associated with risk for breast cancer, also a hormonally driven cancer, this study adds weight to the rationale for performing informed candidate fine-scale genetic studies across cancer types.This work was supported by the National Health and Medical Research Council of Australia (ID#1031333 to A B Spurdle, DF, A M Dunning, ID#39435 to ANECS, ID#552402, QIMR Controls); National Health and Medical Research Council of Australia Fellowship Scheme (to A B Spurdle); Principal Research Fellow of Cancer Research UK (to D F Easton); Joseph Mitchell Trust (to A M Dunning); Oxford Comprehensive Biomedical Research Centre (to I Tomlinson); The European Community's Seventh Framework Programme (grant agreement number 22175 (HEALTH-F2-2009-223175) (COGS); Cancer Research UK (C1287/A10118 to COGS and BCAC, C1287/A10710, C12292/A11174, C1281/A12014 to COGS and BCAC, C5047/A15007, C5047/A10692, C8197/A16565, C490/A10124 to SEARCH, CORGI - NSECG, to I Tomlinson); National Institutes of Health (CA128978, R01 CA122443 to MECS and MAY, P30 CA15083 to MECS, P50 CA136393 to MECS and MAY, CAHRES); Post-Cancer GWAS Initiative (1U19 CA148537, 1U19 CA148065, 1U19 CA148112 – the GAME-ON initiative); Department of Defence (W81XWH-10-1-0341); Canadian Institutes of Health Research (CIHR) for the CIHR Team in Familial Risks of Breast Cancer; Komen Foundation for the Cure; The Breast Cancer Research Foundation; Ovarian Cancer Research Fund (to COGS); Cancer Council Queensland (ID#4196615 to ANECS); Council Cancer Tasmania (ID#403031, #ID457636 to ANECS); Medical Research Council (G0000934 to the British 1958 Birth Cohort); Wellcome Trust (068545/Z/02, 085475 to the British 1958 Birth Cohort); Wellcome Trust Human Genetics Grant (090532/Z/09/Z to NSECG); European Union (EU FP7 CHIBCHA to NSECG); The University of Newcastle (to QIMR Controls, to NECS); Gladys M Brawn Senior Research Fellowship (QIMR Controls); The Vincent Fairfax Family Foundation (QIMR Controls); Hunter Medical Research Institute (HCS, NECS); Hunter Area Pathology Service (HCS); ELAN fund of the University of Erlangen (BECS); Verelst Foundation for endometrial cancer (LES); Fred C and Katherine B Anderson Foundation (to MECS, to MAY); Mayo Foundation (to MECS, to MAY); Ovarian Cancer Research Fund with support of the Smith family, in memory of Kathryn Sladek Smith (MECS, PPD/RPCI.07 to OCAC); Helse Vest Grant (MoMaTEC); University of Bergen (MoMaTEC); Melzer Foundation (MoMaTEC); The Norwegian Cancer Society – Harald Andersens legat (MoMaTEC); The Research Council of Norway (MoMaTEC); Haukeland University of Hospital (MoMaTEC); NBN Children's Cancer Research Group (NECS); Ms Jennie Thomas (NECS); regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet (20110222, 20110483, 20110141 and DF 07015 all to RENDOCAS, to KARBAC); The Swedish Labor Market Insurance (100069 to RENDOCAS); The Swedish Cancer Society (11 0439 to RENDOCAS); Agency for Science, Technology and Research of Singapore (CAHRES); Susan G Komen Breast Cancer Foundation (CAHRES); UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge (OCAC); Baden-Württemberg state Ministry of Science, Research and Arts (ESTHER); Federal Ministry of Family Affairs, Senior Citizens, Women and Youth (ESTHER); Federal Ministry of Education and Research (BMBF) Germany (01KW9975/5 to GENICA, 01KW9976/8 to GENICA, 01KW9977/0 to GENICA, 01KW0114 to GENICA, to ESTHER); Robert Bosch Foundation (GENICA); Deutsches Krebsforschungszentrum – DKFZ (GENICA); Institute for Prevention and Occupational Medicine of the German Social Accident Insurance, Institute of the Ruhr University Bochum, IPA (GENICA); Department of Internal Medicine, Evangelische Kliniken Bonn gGmbH, Johanniter Krankenhaus (GENICA); Deutsche Krebshilfe e.V. (70-2892-BR I to MARIE); Hamburg Cancer Society (MARIE); German Cancer Research Center (MARIE); Breast Cancer Research Foundation (MCBCS); David F. and Margaret T. Grohne Family Foundation (MCBCS); Ting Tsung and Wei Fong Chao Foundation (MCBCS); VicHealth (MCCS); Cancer Council Victoria (MCCS); Breakthrough Breast Cancer (UKBGS); Institute of Cancer Research (UKBGS); and NHS funding to the NIHR Biomedical Research Centre (UKBGS/ICR).This is the final version of the article. It first appeared from the Society for Endocrinology via http://dx.doi.org/10.1530/ERC-15-031

Assessing the genetic architecture of epithelial ovarian cancer histological subtypes.

Epithelial ovarian cancer (EOC) is one of the deadliest common cancers. The five most common types of disease are high-grade and low-grade serous, endometrioid, mucinous and clear cell carcinoma. Each of these subtypes present distinct molecular pathogeneses and sensitivities to treatments. Recent studies show that certain genetic variants confer susceptibility to all subtypes while other variants are subtype-specific. Here, we perform an extensive analysis of the genetic architecture of EOC subtypes. To this end, we used data of 10,014 invasive EOC patients and 21,233 controls from the Ovarian Cancer Association Consortium genotyped in the iCOGS array (211,155 SNPs). We estimate the array heritability (attributable to variants tagged on arrays) of each subtype and their genetic correlations. We also look for genetic overlaps with factors such as obesity, smoking behaviors, diabetes, age at menarche and height. We estimated the array heritabilities of high-grade serous disease ([Formula: see text] = 8.8 ± 1.1 %), endometrioid ([Formula: see text] = 3.2 ± 1.6 %), clear cell ([Formula: see text] = 6.7 ± 3.3 %) and all EOC ([Formula: see text] = 5.6 ± 0.6 %). Known associated loci contributed approximately 40 % of the total array heritability for each subtype. The contribution of each chromosome to the total heritability was not proportional to chromosome size. Through bivariate and cross-trait LD score regression, we found evidence of shared genetic backgrounds between the three high-grade subtypes: serous, endometrioid and undifferentiated. Finally, we found significant genetic correlations of all EOC with diabetes and obesity using a polygenic prediction approach.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 Nurses’ Health Studies would like to thank the participants and staff of the Nurses' Health Study and Nurses' Health Study II for their valuable contributions as well as the following state cancer registries for their help: AL, AZ, AR, CA, CO, CT, DE, FL, GA, ID, IL, IN, IA, KY, LA, ME, MD, MA, MI, NE, NH, NJ, NY, NC, ND, OH, OK, OR, PA, RI, SC, TN, TX, VA, WA, WY. The authors assume full responsibility for analyses and interpretation of these data. Funding of the constituent studies was provided by the California Cancer Research Program (00-01389V-20170, N01-CN25403, 2II0200); the Canadian Institutes of Health Research (MOP-86727); Cancer Australia; Cancer Council Victoria; Cancer Council Queensland; Cancer Council New South Wales; Cancer Council South Australia; Cancer Council Tasmania; Cancer Foundation of Western Australia; the Cancer Institute of New Jersey; Cancer Research UK (C490/A6187, C490/A10119, C490/A10124); the Danish Cancer Society (94-222-52); the ELAN Program of the University of Erlangen-Nuremberg; the Eve Appeal; the Helsinki University Central Hospital Research Fund; Helse Vest; the Norwegian Cancer Society; the Norwegian Research Council; the Ovarian Cancer Research Fund; Nationaal Kankerplan of Belgium; the L & S Milken Foundation; the Polish Ministry of Science and Higher Education (4 PO5C 028 14, 2 PO5A 068 27); the Roswell Park Cancer Institute Alliance Foundation; the US National Cancer Institute (K07-CA095666, K07-CA80668, K07-CA143047, K22-CA138563, N01-CN55424, N01-PC67001, N01-PC067010, N01-PC035137, P01-CA017054, P01-CA087696, P30-CA072720, P30-CA15083, P30-CA008748, P50-CA159981, P50-CA105009, P50-CA136393, R01-CA149429, R01-CA014089, R01-CA016056, R01-CA017054, R01-CA049449, R01-CA050385, R01-CA054419, R01-CA058598, R01-CA058860, R01-CA061107, R01-CA061132, R01-CA063678, R01-CA063682, R01-CA067262, R01-CA071766, R01-CA074850, R01-CA080978, R01-CA083918, R01-CA087538, R01-CA092044, R01-CA095023, R01-CA122443, R01-CA112523, R01-CA114343, R01-CA126841, R01-CA136924, R03-CA113148, R03-CA115195, U01-CA069417, U01-CA071966, UM1-CA186107, UM1-CA176726 and Intramural research funds); the NIH/National Center for Research Resources/General Clinical Research Center (MO1-RR000056); the US Army Medical Research and Material Command (DAMD17-01-1-0729, DAMD17-02-1-0666, DAMD17-02-1-0669, W81XWH-07-0449, W81XWH-10-1-02802); the US Public Health Service (PSA-042205); the National Health and Medical Research Council of Australia (199600 and 400281); the German Federal Ministry of Education and Research of Germany Programme of Clinical Biomedical Research (01GB 9401); the State of Baden-Wurttemberg through Medical Faculty of the University of Ulm (P.685); the German Cancer Research Center; the Minnesota Ovarian Cancer Alliance; the Mayo Foundation; the Fred C. and Katherine B. Andersen Foundation; the Lon V. Smith Foundation (LVS-39420); the Oak Foundation; Eve Appeal; the OHSU Foundation; the Mermaid I project; the Rudolf-Bartling Foundation; the UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge, Imperial College London, University College Hospital ‘Womens Health Theme’ and the Royal Marsden Hospital; and WorkSafeBC 14. Investigator-specific funding: G.C.P receives scholarship support from the University of Queensland and QIMR Berghofer. Y.L. was supported by the NHMRC Early Career Fellowship. G.C.T. is supported by the National Health and Medical Research Council. S.M. was supported by an ARC Future Fellowship

CYP19A1 fine-mapping and Mendelian randomization: estradiol is causal for endometrial cancer.

Candidate gene studies have reported CYP19A1 variants to be associated with endometrial cancer and with estradiol (E2) concentrations. We analyzed 2937 single nucleotide polymorphisms (SNPs) in 6608 endometrial cancer cases and 37 925 controls and report the first genome wide-significant association between endometrial cancer and a CYP19A1 SNP (rs727479 in intron 2, P=4.8×10(-11)). SNP rs727479 was also among those most strongly associated with circulating E2 concentrations in 2767 post-menopausal controls (P=7.4×10(-8)). The observed endometrial cancer odds ratio per rs727479 A-allele (1.15, CI=1.11-1.21) is compatible with that predicted by the observed effect on E2 concentrations (1.09, CI=1.03-1.21), consistent with the hypothesis that endometrial cancer risk is driven by E2. From 28 candidate-causal SNPs, 12 co-located with three putative gene-regulatory elements and their risk alleles associated with higher CYP19A1 expression in bioinformatical analyses. For both phenotypes, the associations with rs727479 were stronger among women with a higher BMI (Pinteraction=0.034 and 0.066 respectively), suggesting a biologically plausible gene-environment interaction.Fine-mapping analysis was supported by NHMRC project grant [ID#1031333] to ABS, DFE and AMD. ABS, PW, GWM, and DRN are supported by the NHMRC Fellowship scheme. AMD is supported by the Joseph Mitchell Trust. IT is supported by Cancer Research UK and the Oxford Comprehensive Biomedical Research Centre. Funding for the iCOGS infrastructure came from: the European Community's Seventh Framework Programme under grant agreement no 223175 [HEALTH-F2-2009-223175] [COGS], Cancer Research UK [C1287/A10118, C1287/A 10710, C12292/A11174, C1281/A12014, C5047/A8384, C5047/A15007, C5047/A10692, C8197/A16565], the National Institutes of Health [CA128978] and Post-Cancer GWAS initiative [1U19 CA148537, 1U19 CA148065 and 1U19 CA148112 - the GAME-ON initiative], the Department of Defence [W81XWH-10-1-0341], the Canadian Institutes of Health Research [CIHR] for the CIHR Team in Familial Risks of Breast Cancer, Komen Foundation for the Cure, the Breast Cancer Research Foundation, and the Ovarian Cancer Research Fund. ANECS recruitment was supported by project grants from the NHMRC [ID#339435], The Cancer Council Queensland [ID#4196615] and Cancer Council Tasmania [ID#403031 and ID#457636]. SEARCH recruitment was funded by a programme grant from Cancer Research UK [C490/A10124]. Stage 1 and stage 2 case genotyping was supported by the NHMRC [ID#552402, ID#1031333]. This study 647 makes use of data generated by the Wellcome Trust Case-Control Consortium (WTCCC). A full list of the investigators who contributed to the generation of the data is available from www.wtccc.org.uk. Funding for the project was provided by the Wellcome Trust under award 076113. We acknowledge use of DNA from the British 1958 Birth Cohort collection, funded by the Medical Research Council grant G0000934 and the Wellcome Trust grant 068545/Z/02 - funding for this project was provided by the Wellcome Trust under award 085475. NSECG was supported by the EU FP7 CHIBCHA grant and Wellcome Trust Centre for Human Genetics Grant 090532/Z/09Z, and CORGI by Cancer Research UK. Recruitment of the QIMR Berghofer controls was supported by the NHMRC. The University of Newcastle, the Gladys M Brawn Senior Research Fellowship scheme, The Vincent Fairfax Family Foundation, the Hunter Medical Research Institute and the Hunter Area Pathology Service all contributed towards the costs of establishing the Hunter Community Study. The Bavarian Endometrial Cancer Study (BECS) was partly funded by the ELAN fund of the University of Erlangen. The Leuven Endometrium Study (LES) was supported by the Verelst Foundation for endometrial cancer. The Mayo Endometrial Cancer Study (MECS) and Mayo controls (MAY) were supported by grants from the National Cancer Institute of United States Public Health Service [R01 CA122443, P30 CA15083, P50 CA136393, and GAME-ON the NCI Cancer Post-GWAS Initiative U19 CA148112], the Fred C and Katherine B Andersen Foundation, the Mayo Foundation, and the Ovarian Cancer Research Fund with support of the Smith family, in memory of Kathryn Sladek Smith. MoMaTEC received financial support from a Helse Vest Grant, the University of Bergen, Melzer Foundation, The Norwegian Cancer Society (Harald Andersens legat), The Research Council of Norway and Haukeland University Hospital. 672 The Newcastle Endometrial Cancer Study (NECS) acknowledges contributions from the University of Newcastle, The NBN Children’s Cancer Research Group, Ms Jennie Thomas and the Hunter Medical Research Institute. RENDOCAS was supported through the regional agreement on medical training and clinical research (ALF) between Stockholm County Council and Karolinska Institutet [numbers: 20110222, 20110483, 20110141 and DF 07015], The Swedish Labor Market Insurance [number 100069] and The Swedish Cancer Society [number 11 0439]. The Cancer Hormone Replacement Epidemiology in Sweden Study (CAHRES, formerly called The Singapore and Swedish Breast/Endometrial Cancer Study; SASBAC) was supported by funding from the Agency for Science, Technology and Research of Singapore (A*STAR), the US National Institutes of Health and the Susan G. Komen Breast Cancer Foundation. The Breast Cancer Association Consortium (BCAC) is funded by Cancer Research UK [C1287/A10118, C1287/A12014]. The Ovarian Cancer Association Consortium (OCAC) 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], and the UK National Institute for Health Research Biomedical Research Centres at the University of Cambridge. Additional funding for individual control groups is detailed in the Supplementary Information. EPIC-Norfolk was funded by research programme grant funding from Cancer Research UK and the Medical Research Council with additional support from the Stroke Association, British Heart Foundation, Department of Health, Research into Ageing and Academy of Medical Sciences. The SIBS study was supported by program grant C1287/A10118 and project grants from Cancer Research 697 UK (grant numbers C1287/8459).This is the author accepted manuscript. The final version is available from Bioscientifica via http://dx.doi.org/10.1530/ERC-15-038

Methylation of Leukocyte DNA and Ovarian Cancer: Relationships with Disease Status and Outcome

Genome-wide interrogation of DNA methylation (DNAm) in blood-derived leukocytes has become feasible with the advent of CpG genotyping arrays. In epithelial ovarian cancer (EOC), one report found substantial DNAm differences between cases and controls; however, many of these disease-associated CpGs were attributed to differences in white blood cell type distributions. We examined blood-based DNAm in 336 EOC cases and 398 controls; we included only high-quality CpG loci that did not show evidence of association with white blood cell type distributions to evaluate association with case status and overall survival

Shared genetics underlying epidemiological association between endometriosis and ovarian cancer

Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18-0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07-0.89 and 0.40, 95% CI = 0.05-0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11-0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci.Other Research Uni

Exome genotyping arrays to identify rare and low frequency variants associated with epithelial ovarian cancer risk

Rare and low frequency variants are not well covered in most germline genotyping arrays and are understudied in relation to epithelial ovarian cancer (EOC) risk. To address this gap, we used genotyping arrays targeting rarer protein-coding variation in 8,165 EOC cases and 11,619 controls from the international Ovarian Cancer Association Consortium (OCAC). Pooled association analyses were conducted at the variant and gene level for 98,543 variants directly genotyped through two exome genotyping projects. Only common variants that represent or are in strong linkage disequilibrium (LD) with previously-identified signals at established loci reached traditional thresholds for exome-wide significance (P ( )P≥5.0 ×10 (-)  (7)) were detected for rare and low-frequency variants at 16 novel loci. Four rare missense variants were identified (ACTBL2 rs73757391 (5q11.2), BTD rs200337373 (3p25.1), KRT13 rs150321809 (17q21.2) and MC2R rs104894658 (18p11.21)), but only MC2R rs104894668 had a large effect size (OR = 9.66). Genes most strongly associated with EOC risk included ACTBL2 (PAML = 3.23 × 10 (-)  (5); PSKAT-o = 9.23 × 10 (-)  (4)) and KRT13 (PAML = 1.67 × 10 (-)  (4); PSKAT-o = 1.07 × 10 (-)  (5)), reaffirming variant-level analysis. In summary, this large study identified several rare and low-frequency variants and genes that may contribute to EOC susceptibility, albeit with possible small effects. Future studies that integrate epidemiology, sequencing, and functional assays are needed to further unravel the unexplained heritability and biology of this disease

A Targeted Genetic Association Study of Epithelial Ovarian Cancer Susceptibility

BACKGROUND: Genome-wide association studies have identified several common susceptibility alleles for epithelial ovarian cancer (EOC). To further understand EOC susceptibility, we examined previously ungenotyped candidate variants, including uncommon variants and those residing within known susceptibility loci. RESULTS: At nine of eleven previously published EOC susceptibility regions (2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13), novel variants were identified that were more strongly associated with risk than previously reported variants. Beyond known susceptibility regions, no variants were found to be associated with EOC risk at genome-wide statistical significance (p \u3c5x10(-8)), nor were any significant after Bonferroni correction for 17,000 variants (p\u3c 3x10-6). METHODS: A customized genotyping array was used to assess over 17,000 variants in coding, non-coding, regulatory, and known susceptibility regions in 4,973 EOC cases and 5,640 controls from 13 independent studies. Susceptibility for EOC overall and for select histotypes was evaluated using logistic regression adjusted for age, study site, and population substructure. CONCLUSION: Given the novel variants identified within the 2q31, 3q25, 5p15, 8q21, 8q24, 10p12, 17q12, 17q21.31, and 19p13 regions, larger follow-up genotyping studies, using imputation where necessary, are needed for fine-mapping and confirmation of low frequency variants that fall below statistical significance