Iversen, Edwin S.

PURPOSE The emergence of large real-world clinical databases and tools to mine electronic medical records has allowed for an unprecedented look at large data sets with clinical and epidemiologic correlates. In clinical cancer genetics, real-world databases allow for the investigation of prevalence and effectiveness of prevention strategies and targeted treatments and for the identification of barriers to better outcomes. However, real-world data sets have inherent biases and problems (eg, selection bias, incomplete data, measurement error) that may hamper adequate analysis and affect statistical power. METHODS Here, we leverage a real-world clinical data set from a large health network for patients with breast cancer tested for variants in BRCA1 and BRCA2 (N = 12,423). We conducted data cleaning and harmonization, cross-referenced with publicly available databases, performed variant reassessment and functional assays, and used functional data to inform a variant's clinical significance applying American College of Medical Geneticists and the Association of Molecular Pathology guidelines. RESULTS In the cohort, White and Black patients were over-represented, whereas non-White Hispanic and Asian patients were under-represented. Incorrect or missing variant designations were the most significant contributor to data loss. While manual curation corrected many incorrect designations, a sizable fraction of patient carriers remained with incorrect or missing variant designations. Despite the large number of patients with clinical significance not reported, original reported clinical significance assessments were accurate. Reassessment of variants in which clinical significance was not reported led to a marked improvement in data quality. CONCLUSION We identify the most common issues with BRCA1 and BRCA2 testing data entry and suggest approaches to minimize data loss and keep interpretation of clinical significance of variants up to date.

Abstract Background: Germline genetic testing of individuals with a diagnosis of triple negative breast cancer, young age at diagnosis, or a family history of breast and/or ovarian cancer has led to the identification of many unique BRCA2 missense variants of uncertain significance (VUS). VUS in BRCA2 are predominantly missense mutations that have unclear relevance to breast, ovarian, and other cancers. Thus, patients found to have a germline BRCA2 VUS do not know if the variant is associated with high risks of these cancers similar to truncating mutations, intermediate risks more similar to CHEK2 mutations, or low risks of no clinical significance. Furthermore, it is unclear if germline BRCA2 VUS, or somatic VUS identified by tumor sequencing, are associated with hypersensitivity to selected DNA damaging and cross-linking agents. Methods: We have used a homology directed repair (HDR) cell-based assay to characterize missense variants in the DNA binding domain (DBD) of BRCA2. The method has been validated using known pathogenic and known non-pathogenic BRCA2 missense variants and has 100% sensitivity (95% confidence interval (CI): 75.3%–100%) and 100% specificity (95% CI: 81.5%–100%) for pathogenic BRCA2 variants. A classifier of variant pathogenicity based on the mean and variances of the distributions of the HDR results of the known pathogenic and neutral variants has been established. We have also developed PARP inhibitor and cisplatin drug response assays for BRCA2 missense variants. Results: Assessment of 207 BRCA2 missense variants, identified in public databases such as BRCA exchange and ClinVar, by the HDR assay identified 71 deleterious variants with >99% probability of pathogenicity, 116 neutral variants with >99% probability of neutrality, and 20 with hypomorphic activity and potentially intermediate risk. A combination of the functional data and sequence-based predictors of protein activity in a Bayesian prediction model resulted in classification of the deleterious variants as pathogenic cancer predisposing variants and the neutral variants as non-pathogenic with low clinical significance. The influence of the deleterious/pathogenic variants on PARPi and cisplatin response was also assessed. Conclusion: The HDR assay is effective for characterization of BRCA2 VUS. The combination of functional data and in silico prediction models provides a robust tool for clinical annotation of BRCA2 VUS. HDR function of BRCA2 missense variants is strongly correlated with response to targeted therapy. Citation Format: Couch FJ, Shimelis H, Hart SN, Moore RM, Thomas A, Lipton GB, Iversen E. Cancer risks and response to targeted therapy associated with BRCA2 variants of uncertain significance [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr GS4-06.

Abstract Approximately 15% of genetic screens for mutations in BRCA1 and BRCA2 identify Variants of Uncertain Significance (VUS). Primarily missense mutations, VUS are often difficult to interpret, leading to either uncertainty in how to properly counsel a patient or an unnecessary prophylactic surgery. Given the paucity of data for which missenses are classified as truly pathogenic, computational deleterious missense prediction (DMP) algorithms are used to predict whether a mutation is likely deleterious or neutral. Accuracy of DMPs can vary considerably and have only been calibrated on a relatively small number of missense mutations of demonstrable effect on protein function. In this study, the performance of 41 different DMPs was compared to functional data from 455 functionally characterized missense variants in BRCA1 and BRCA2. New optimized thresholds for classifying missense mutations as deleterious are presented for several existing models as well as a newly derived naïve voting method (NVM). The areas under the curve estimates for the NVM approach are between 0.889-0.922, much higher than previous methods. We estimate that the overall pathogenic potential of missense variants to be 6.8% for BRCA1 and 3.2% of BRCA2, but can be as high as 50% depending on protein location. Overall these results provide key insights into how to predict deleterious missense mutations in BRCA1 and BRCA2. Citation Format: Hart SN, Hoskin T, Shimelis H, Feng B, Lindor NM, Monteiro A, Iversen E, Goldgar DE, Suman V, Couch FJ. Optimized prediction of deleterious missense mutations in BRCA1 and BRCA2 genes [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-02-03.

Abstract Panel-based germline genetic testing of established breast and ovarian cancer predisposition genes is widely used in high-risk clinics to inform on risks of breast and ovarian cancer. While most protein truncating mutations identified in predisposition genes are associated with moderate to high risks of these cancers, variants of uncertain significance (VUS), in the form of missense and intronic variants, have an undefined relevance to cancer. Many hundreds of VUS in BRCA1 and BRCA2 identified by clinical genetic testing over the last 20 years still have uncertain clinical relevance. In addition, VUS in other known predisposition genes are being identified by current panel-testing in up to 10% of individuals without BRCA1 or BRCA2 mutations. These VUS cause problems in cancer risk estimation and clinical management of patients undergoing clinical genetic testing. In an effort to evaluate the clinical significance of VUS in cancer predisposition genes we have developed functional assays that characterize the impact of the variants on the functions of the proteins encoded by the predisposition genes. In particular, a homology directed repair reporter assay providing a quantitative measure of homologous recombination repair of DNA double strand breaks has been developed for characterization of VUS in homologous recombination associated genes. When applied to 13 known pathogenic and 30 known neutral variants from the DNA binding domain of BRCA2, this assay exhibits 100% specificity and 100% sensitivity. Based on these results a model estimating the probability of pathogenicity of each BRCA2 VUS was developed. The HDR assay and probability model has now been applied to 230 BRCA2 VUS identified through genetic testing. Here we identify 80 BRCA2 variants that are deficient in HDR activity. We further combined these results with prior probabilities of pathogenicity derived from the sequence based Align GVGD in silico prediction model to estimate the posterior probability of pathogenicity for each VUS. Our results suggest that in the absence of family based segregation information, results from the HDR functional assay and in silico prediction models can be used to predict the pathogenicity of BRCA2 VUS. The assay has also been used to characterize VUS in the PALB2 and RAD51C predisposition genes, leading to identification of a subset of missense variants that are deficient in HDR repair activity and may be associated with increased risk of breast and ovarian cancer. These results will prove useful for improved risk assessment of carriers of these BRCA2, PALB2 and RAD51C variants and their family members and for validation of other approaches to mutation classification. Citation Format: Fergus J. Couch, Hermela Shimelis, Andreas Schroeder, Chunling Hu, Emily Hallberg, Gary Lipton, Edwin Iversen, Noralane M. Lindor. Characterization of variants of uncertain significance (VUS) in breast and ovarian cancer predisposition genes. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4685. doi:10.1158/1538-7445.AM2015-4685

Abstract Background: Recent bioinformatic analyses and high-throughput sequencing efforts have revealed that RNA editing is a widespread post-transcriptional modification that affects non-coding repetitive elements throughout the genome. This modification, which involves the conversion of adenosine into inosine, is mediated by the action of the adenosine deaminases acting on RNA (ADAR) family of enzymes. Based on reports of dysfunctional ADAR expression in epithelial ovarian cancers (EOC), we hypothesized that single nucleotide polymorphisms (SNPs) in five ADAR genes (ADAD1, ADAR1, ADAR2, ADAR3, SND1) may contribute to EOC susceptibility, potentially by altering the expression of corresponding genes in ovarian tissues. Methods: Using directly genotyped and imputed data from 10,891 invasive EOC cases and 21,693 healthy controls of European ancestry represented in the international Collaborative Oncological Gene-environment Study, we evaluated the frequency of 7,133 SNPs in 5 RNA editing genes. Unconditional logistic regression was used to estimate odds ratios (OR) and 95% confidence intervals (CI) between genotypes and case status under a log-additive genetic model, with adjustment for the first five principal components representing European ancestry. Subgroup analysis was conducted for the four main histologic sub-types of EOC. We also aggregated SNP-level data and conducted gene-level analyses using the Admixture Maximum Likelihood (AML) test and the Sequence-Kernel Association test for the combined effect of common and rare variants (SKAT-CR). Results: Association analysis revealed a top risk-associated SNP (OR (95% CI) = 1.39 (1.17-1.64)) in ADAR3 with P = 1.3 x10−4, 17 additional SNPs in ADAR1, ADAR3, or SND1 with P = 10−4, and 51 SNPs with P = 10−3; this observed number of statistically-significant SNPs was greater than expected. When restricting to the 6,500 invasive serous adenocarcinomas, the magnitude of association strengthened for numerous SNPs. Exploratory analysis for the less common histologic subtypes (endometrioid (n = 1,439), mucinous (n = 696), and clear cell (n = 660)) revealed SNP-level associations (P<10−3) unique to each sub-type. Gene-level analyses based on AML and SKAT-CR revealed that ADAR1 was globally associated (P<0.10) with susceptibility to invasive EOC, with P = 0.024 and P = 0.023, respectively. Expression quantitative trait locus analysis is underway to evaluate associations between genotype and gene expression in EOC and precursor tissues using data from The Cancer Genome Atlas Project and other sources. Conclusions: Preliminary data from this large-scale collaboration suggest that germline variation involving RNA editing genes may influence susceptibility to EOC. This novel finding warrants further investigation, as inherited and acquired alterations affecting RNA editing may serve as important biological mechanisms that promote the development of EOC and possibly other malignancies. Citation Format: Jennifer Permuth-Wey, Brett M. Reid, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen Goode, Edwin Iversen, Leigh Pearce, Paul D. P. Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Inherited variants affecting RNA editing may contribute to ovarian cancer susceptibility. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4635. doi:10.1158/1538-7445.AM2015-4635

Abstract Background: Cell-type-specific super enhancers, or large clusters of mediator-rich enhancers, are highly transcribed regions of the genome with key functions in the maintenance of cell identity and control. These regulatory elements are easily perturbed and enriched for disease-associated sequence variation. Identification of disease-associated super-enhancers and investigation of their sequence variants may help identify important, biologically relevant associations previously overlooked by genome-wide studies. Thus, we sought to identify variants within ovarian tissue specific super-enhancers and investigate their association with epithelial ovarian cancer (EOC) susceptibility. Methods: We utilized genotype data from a European population of ∼11,000 invasive EOC cases and 22,000 healthy controls from the Ovarian Cancer Association Consortium. A public catalog of 478 super-enhancers, identified by peak histone H3K27ac ChIP-seq signal in ovarian tissue, was used to identify 72,116 variants located within 344 super-enhancer regions. Unconditional logistic regression (log-additive model) was used to assess individual SNP-EOC risk associations. Additionally, we reviewed associations within 500 kb of super-enhancer regions to identify proximal associated variants. When LD structure indicated, we employed conditional analysis to determine independence of the super-enhancer signal. Gene-EOC risk associations were assessed with the Admixture Maximum Likelihood (AML) test and Sequence-Kernel Association Test (SKAT) for the combined effect of common and rare (MAF<0.01) variants. Models were adjusted for population stratification using the first five principal components. To adjust for multiple comparisons, a false discovery rate of 10% was used. Results: The most significant SNP observed was rs147487657 (p = 7.7×10−6) on locus 2q37.3 in the HDAC4 gene and there were an additional 12 SNPs with p<1.0×10−4, although not significant at 10% FDR. Gene-level analyses identified two super-enhancers significantly associated with EOC risk. An enhancer at the previously reported 2q31 locus, containing HOXD8 and HOXD-AS2, associated (SKAT p = 4.3×10−5; AML p<0.001) with the top SNP located within the 5′UTR of HOXD8 transcription factor (rs847163 (T>C); p<2.08×10−5). Conditional analysis did not identify an independent association within the super-enhancer region. The second EOC-associated super-enhancer identified was at locus 1q32 (SKAT p = 0.00052, AML p = 0.001) containing the CSRP1 gene. There were 6 SNPs with p<0.001 and 16 SNPs with p<0.01, all were inversely associated with risk and consistent with the top hit at rs927901 T>C (OR = 0.94; 95% CI: 0.90-0.97; p = 2.1×10−4). Associations varied by histologic subtype, possibly due to variance in disease relevant super-enhancer cell-type.Conclusion: These findings suggest germline variation within super-enhancer regions may contribute to EOC susceptibility Citation Format: Brett M. Reid, Jennifer Permuth-Wey, Y. Ann Chen, Hui-Yi Lin, Alvaro Monteiro, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Leigh Pearce, Paul Pharoah, Catherine Phelan, Susan Ramus, Mary Anne Rossing, Joellen Schildkraut, Thomas Sellers, on behalf of the Ovarian Cancer Association Consortium. Variants within super-enhancer regulatory elements associate with epithelial ovarian cancer risk. [abstract]. In: Proceedings of the 106th Annual Meeting of the American Association for Cancer Research; 2015 Apr 18-22; Philadelphia, PA. Philadelphia (PA): AACR; Cancer Res 2015;75(15 Suppl):Abstract nr 4634. doi:10.1158/1538-7445.AM2015-4634

Abstract Background: Common genetic variants identified by genome-wide association studies and follow-up genotyping initiatives only explain a small proportion of the heritability of epithelial ovarian cancer (EOC). We hypothesized that some of the missing heritability may be explained by rare (minor allele frequency (MAF) <0.5%) and low-frequency (MAF 0.5-5%) protein-coding variants that are not well captured by genotyping arrays that focus on common variants. Methods: To examine the association between uncommon variants and EOC susceptibility, we genotyped 7,060 EOC cases and 6,712 controls from the Ovarian Cancer Association Consortium using the Affymetrix Axiom Exome Genotyping Array. This platform contains 300,785 putative functional coding variants selected from exome sequences of 12,000+ individuals representing multiple ethnicities and complex traits. After performing quality control (QC), we used unconditional logistic regression treating the number of minor alleles carried as an ordinal variable (log-additive model) to evaluate SNP-EOC risk associations. Genotype cluster plots were visually inspected for top-ranking variants to determine assay success, and allele frequencies of samples from the 1000 Genomes Project and other cohorts were evaluated for QC purposes. Results: A total of 13,318 samples (97%) passed QC, and 12,779 eligible samples (6,293 invasive serous and endometrioid cases and 6,486 controls) were included in the analyses. 280,737 (93%) of the 300,785 attempted markers were successfully genotyped and had call rates >90%. After removing 31,436 monomorphic markers, the 249,301 remaining markers were included in association analyses. We confirmed variants at previously reported EOC susceptibility loci (9p22, 3q25, 17cen-q21.3, and 8q24), with p-values between 10-5 and 10-11. Several correlated low-frequency non-synonymous variants (MAF=5%) residing in a novel EOC susceptibility gene at 3q25.31 were risk-associated. The most significant variant at 3q25.31 had an OR=1.36 and p = 5.58x10-8. Also noteworthy is a rare variant at 15q15.1-q21.1 (MAF=0.5%) that introduces a stop codon in a gene belonging to the tyrosine kinase family (OR=0.39, CI=0.26-0.58, p = 4.52x10-6). We also identified a more common synonymous coding variant in a phosphatase at 6q21.3 that was associated with increased risk (OR=1.22, CI=1.13-1.33, p = 1.84x10-6, MAF=9.6%). Population stratification and gene-based analyses are underway to further examine the impact of the newly-identified variants on EOC risk. A meta-analysis to include data from an additional 2104 EOC cases and 2516 controls genotyped with Illumina's HumanExome Beadchip rare variant array is also underway. Functional analysis of the most promising variants will follow. Conclusions: Preliminary data from this large-scale study reveals novel rare and low-frequency variants that may influence susceptibility to epithelial ovarian cancer. Citation Format: Jennifer Permuth-Wey, Y. Ann Chen, Zhihua Chen, Andrew Berchuck, Georgia Chenevix-Trench, Jennifer Doherty, Simon Gayther, Ellen L. Goode, Edwin Iversen, Alvaro N.A. Monteiro, Leigh Pearce, Paul D.P. Pharoah, Catherine M. Phelan, Ailith Pirie, Susan Ramus, Mary Ann Rossing, Joellen M. Schildkraut, Thomas A. Sellers, on behalf of the Ovarian Cancer Association Consortium. Exome genotyping array identifies rare and low-frequency variants that may be associated with ovarian cancer risk. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 946. doi:10.1158/1538-7445.AM2014-946

Abstract Background. Transmembrane transport (GO:0055085) is the process whereby a solute/hormone/ion/iron is transported from one side of a membrane to the other. Disruption of these processes leads to defects in homeostasis which contributes to cancer risk. We hypothesized that germline single nucleotide polymorphisms (SNPs) in the cellular transport genes are associated with EOC risk and histopathology subtype. Methods. We genotyped 305 SNPs from 120 cellular transport related genes in 14,525 cases and 23,448 controls of European ancestry, 387 African, and 2,388 Asian ancestries from 43 studies in the Ovarian Cancer Association Consortium (OCAC). A custom Illumina iSelect designed for the Collaborative Oncological Gene-environment Study (COGS) was used. For women of European ancestry, both invasive cancers combined and the four main histological subtypes (serous (n=8,369), mucinous (n=943), endometroid (n=2,067) and clear cell (n=1,024) carcinoma) were analyzed, while for women of African and Asian ancestry only the serous subtype was analyzed adjusting for study site and first 5 principal components. Odds ratios and 95% confidence intervals were calculated using unconditional logistic regression. We fitted a log-additive genetic model. Results. In women of European ancestry, the strongest evidence of an association for all invasive EOCs was the iron transport gene, HEPH rs17216603 (OR=0.85, 95%CI=0.78-0.93, P=2.8x10−4), which was also the most significant association for serous histological subtype (OR=0.81, 95%CI=0.73-0.91, P=2.0x10−4). For endometrioid EOC, the strongest association was observed in the glucuronidation gene, UGT1A5 rs11563251 (OR=0.82, 95%CI=0.73-0.92, P=6.6x10−4). For clear cell and mucinous EOC, the thyroid hormone transport protein, SERPINA7 rs1804495 showed the strongest associations (OR=1.06, 95%CI=1.06-1.38, P=0.0041) and (OR=0.85, 95%CI=0.73-0.98, P=0.0407), respectively. For women of African ancestry, the strongest association for serous EOC was the glutathione conjugation gene, MGST rs6488840 (OR=0.55, 95%CI=0.37-0.82, P=0.0035). This SNP was not significant in women of European or Asian ancestry. In women of Asian ancestry, the HEPH rs17216603 (OR=1.45, 95%CI=1.15-1.83, P=0.0019) demonstrated the strongest association, although the directionality of risk was reversed compared to European women. Conclusions. Our results suggest that variation in transmembrane transport genes may influence EOC risk and histopathologic subtype in women of European, African and Asian ancestries, highlighting the differences in the disease etiology across populations. Additional epidemiological and functional studies are warranted to elucidate translational and clinical utility of these associations. Citation Format: Ganna Chornokur, Jonathan Tyrer, Hui-Yi Lin, Gang Han, Xiaotao Qu, Chen Zhihua, Ya-Yu Tsai, Ellen L. Goode, Julie M. Cunningham, Edwin Iversen, Susan J. Ramus, Andrew Berchuk, Joellen M. Schildkraut, Alvaro Monteiro, Simon A. Gayther, Steven A. Narod, Paul Pharoah, Thomas A. Sellers, Catherine M. Phelan. Variation in transmembrane transport genes influence epithelial ovarian cancer risk and histopathologic subtype. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 3644. doi:10.1158/1538-7445.AM2013-3644

Abstract Population stratification in case-control studies can result from differences in ancestral make-up between cases and controls due to sampling variation. Ancestry is therefore routinely estimated and controlled for in these studies. Although less common, it is also possible for ancestry to truly be associated to the disease of interest. Controlling for ancestry can then compromise the power to detect variants that underlie both ancestry and disease. Using data from a multi-center case-control study of epithelial ovarian cancer (OC) among women of European-American ethnicity in which case-control samples were drawn from four geographically distinct North-American sites, we developed a three-step method to investigate whether the stratification observed across the four sites is due to chance or to a non-spurious association between European ancestry and OC. First, we collapsed genome-wide data into two principal components (PCs) that represent the major axes of European ancestral variation, which correspond to north-south and to west-east geographical clines. Next, we determined the discriminant function based on these two PCs that best separates cases and controls for each individual study site and we used the largest angle between the four discriminant function vectors as a measure of similarity ranging from 0 degrees, where all four vectors are exactly the same, to 180 degrees where two of the vectors face exactly opposite directions. If stratification is due to sampling, it is unlikely that the four sites will present similar discriminant functions by chance alone. We then gauged significance of similarity by permuting the case control status across individuals within each site and recalculating the maximum angle between the discriminant function vectors, thus obtaining a null distribution for the statistic. We found that all four sites present the greatest separation between cases and controls on the west-east axis of ancestral variation, with a higher proportion of ovarian cancer cases presenting western ancestry. The largest angle between the four discriminant function vectors observed was of 36.5 degrees. Permutation testing showed this level of similarity between the functions to have a p-value < 0.01 and suggests that OC risk is somehow tied to European ancestry. It remains to be seen whether shared culture or other exposures such as parity or oral contraceptive use explain this connection or whether genetic variants underlie it and are potentially being missed due to routine ancestry control in association testing. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1678. doi:1538-7445.AM2012-1678

Abstract DNA copy number variations (CNVs) are a significant and ubiquitous source of human genetic variation. However, the influence of CNVs on cancer susceptibility remains poorly understood. Out of 83 genome-wide association studies (GWAS) on cancer to date, only a few studies found significant associations on germline CNVs and cancer. Here we analyzed data from our ongoing two-stage GWAS of four North American case-control studies to test the hypothesis that CNVs in germline DNA from peripheral blood lymphocytes may serve as risk factors for epithelial ovarian cancer (EOC). To reduce disease heterogeneity, we focused on the subset of cases with serous histology. The analysis was therefore based on 942 serous ovarian cancer patients and 1,682 healthy controls who were genotyped using the Illumina 610K quad array. Subjects with extreme noise and genomic waviness in log R ratio (LR) were excluded prior to segmentation; principal component analysis was performed to adjust for batch effects. CNV segmentation was performed on LR data from 22 autosomes using circular binary segmentation embedded in the Copy Number Analysis Module from Golden Helix SNP Variation Suite version 7. Copy number segment covariates were discretized based on the thresholds that signify a transition between copy number states (deletion/no deletion; duplication/no duplication) after the segmentation. Unconditional logistic regression on a log-additive model was used to evaluate the association between copy number states and serous EOC risk after adjusting for study sites. By comparing single marker copy number states at 388,958 SNPs on 22 autosomes, we observed a total of 134 SNPs significantly associated with risk of serous EOC with a p value below 10−6. Associations with deletion polymorphisms were observed on chromosomes 7, 8, 14, and 18 when controlling for false discovery rate at 1%; no duplication polymorphisms were significant. We observed a large deletion at chromosome 14 that occurred in 8.9% of cases but in only 3.9% of controls, with a p value of 5.59×10−8 (Odds Ratio (OR): 2.56, 95% confidence interval (CI): 1.82-3.60). Another common deletion on chromosome 7 occurred in 8.8% of cases and only 4.3% of controls (p=3.83×10−6; OR: 2.23, 95% CI: 1.60-3.10). Two additional regions on chromosomes 8 and 18 with deletion events less than 5% were also identified. Women who harbored the deletion on chromosome 8 were at lower risk of developing serous ovarian cancer (p=4.83×10−8; OR: 0.04, 95% CI: 0.01-0.30). Women who carried the deletion on chromosome 18 had an increased risk for serous EOC (p=9.04×10−7; OR: 7.26, 95% CI: 2.94-17.97). Further validation of these four regions using independent data sets is currently underway. In summary, this is the largest reported genome-wide study of CNVs and serous EOC risk. These preliminary results suggested that germline CNVs may play an important role in ovarian cancer susceptibility. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 1649. doi:1538-7445.AM2012-1649