Ya-Yu Tsai

Meta-analysis of 8q24 for seven cancers reveals a locus between NOV and ENPP2 associated with cancer development

BackgroundHuman chromosomal region 8q24 contains several genes which could be functionally related to cancer, including the proto-oncogene c-MYC. However, the abundance of associations around 128 Mb on chromosome 8 could mask the appearance of a weaker, but important, association elsewhere on 8q24.MethodsIn this study, we completed a meta-analysis of results from nine genome-wide association studies for seven types of solid-tumor cancers (breast, prostate, pancreatic, lung, ovarian, colon, and glioma) to identify additional associations that were not apparent in any individual study.ResultsFifteen SNPs in the 8q24 region had meta-analysis p-values < 1E-04. In particular, the region consisting of 120,576,000-120,627,000 bp contained 7 SNPs with p-values < 1.0E-4, including rs6993464 (p = 1.25E-07). This association lies in the region between two genes, NOV and ENPP2, which have been shown to play a role in tumor development and motility. An additional region consisting of 5 markers from 128,478,000 bp - 128,524,000 (around gene POU5F1B) had p-values < 1E-04, including rs6983267, which had the smallest p-value (p = 6.34E-08). This result replicates previous reports of association between rs6983267 and prostate and colon cancer.ConclusionsFurther research in this area is warranted as these results demonstrate that the chromosomal region 8q24 may contain a locus that influences general cancer susceptibility between 120,576 and 120,630 kb.

TRM: a powerful two-stage machine learning approach for identifying SNP-SNP interactions.

Studies have shown that interactions of single nucleotide polymorphisms (SNPs) may play an important role in understanding the causes of complex disease. We have proposed an integrated machine learning method that combines two machine‐learning methods—Random Forests (RF) and Multivariate Adaptive Regression Splines (MARS)—to identify a subset of important SNPs and detect interaction patterns more effectively and efficiently. In this two‐stage RF‐MARS (TRM) approach, RF is first applied to detect a predictive subset of SNPs, and then MARS is used to identify the interaction patterns. We evaluated the TRM performances in four models. RF variable selection was based on out‐of‐bag classification error rate (OOB) and variable important spectrum (IS). Our results support that RFOOB had better performance than MARS and RFIS in detecting important variables. This study demonstrates that TRMOOB, which is RFOOB plus MARS, has combined the strengths of RF and MARS in identifying SNP‐SNP interactions in a scenario of 100 candidate SNPs. TRMOOB had greater true positive rate and lower false positive rate compared with MARS, particularly for searching interactions with a strong association with the outcome. Therefore, the use of TRMOOB is favored for exploring SNP‐SNP interactions in a large‐scale genetic variation study.

Gene Set Analysis of Survival Following Ovarian Cancer Implicates Macrolide Binding and Intracellular Signaling Genes

Background: Genome-wide association studies (GWAS) for epithelial ovarian cancer (EOC), the most lethal gynecologic malignancy, have identified novel susceptibility loci. GWAS for survival after EOC have had more limited success. The association of each single-nucleotide polymorphism (SNP) individually may not be well suited to detect small effects of multiple SNPs, such as those operating within the same biologic pathway. Gene set analysis (GSA) overcomes this limitation by assessing overall evidence for association of a phenotype with all measured variation in a set of genes. Methods: To determine gene sets associated with EOC overall survival, we conducted GSA using data from two large GWAS (N cases = 2,813, N deaths = 1,116), with a novel Principal Component-Gamma GSA method. Analysis was completed for all cases and then separately for high-grade serous histologic subtype. Results: Analysis of the high-grade serous subjects resulted in 43 gene sets with P < 0.005 (1.7%); of these, 21 gene sets had P < 0.10 in both GWAS, including intracellular signaling pathway (P = 7.3 × 10−5) and macrolide binding (P = 6.2 × 10−4) gene sets. The top gene sets in analysis of all cases were meiotic mismatch repair (P = 6.3 × 10−4) and macrolide binding (P = 1.0 × 10−3). Of 18 gene sets with P < 0.005 (0.7%), eight had P < 0.10 in both GWAS. Conclusion: This research detected novel gene sets associated with EOC survival. Impact: Novel gene sets associated with EOC survival might lead to new insights and avenues for development of novel therapies for EOC and pharmacogenomic studies. Cancer Epidemiol Biomarkers Prev; 21(3); 529–36. ©2012 AACR.

Polymorphisms in stromal genes and susceptibility to serous epithelial ovarian cancer: a report from the ovarian cancer association consortium

Alterations in stromal tissue components can inhibit or promote epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) show reduced stromal expression in serous epithelial ovarian cancer (sEOC). We hypothesized that common variants in these genes associate with risk. Associations with sEOC among Caucasians were estimated with odds ratios (OR) among 397 cases and 920 controls in two U.S.-based studies (discovery set), 436 cases and 1,098 controls in Australia (replication set 1) and a consortium of 15 studies comprising 1,668 cases and 4,249 controls (replication set 2). The discovery set and replication set 1 (833 cases and 2,013 controls) showed statistically homogeneous (Pheterogeneity≥0.48) decreased risks of sEOC at four variants: DCN rs3138165, rs13312816 and rs516115, and LUM rs17018765 (OR = 0.6 to 0.9; Ptrend = 0.001 to 0.03). Results from replication set 2 were statistically homogeneous (Pheterogeneity≥0.13) and associated with increased risks at DCN rs3138165 and rs13312816, and LUM rs17018765: all ORs = 1.2; Ptrend≤0.02. The ORs at the four variants were statistically heterogeneous across all 18 studies (Pheterogeneity≤0.03), which precluded combining. In post-hoc analyses, interactions were observed between each variant and recruitment period (Pinteraction≤0.003), age at diagnosis (Pinteraction = 0.04), and year of diagnosis (Pinteraction = 0.05) in the five studies with available information (1,044 cases, 2,469 controls). We conclude that variants in DCN and LUM are not directly associated with sEOC, and that confirmation of possible effect modification of the variants by non-genetic factors is required.

Abstract 2615: Genetic variations in angiogenesis-related genes in prostate cancer recurrence

Proceedings: AACR 103rd Annual Meeting 2012‐‐ Mar 31‐Apr 4, 2012; Chicago, IL Introduction: Prostate cancer is the most common cancer and the second leading cause of cancer death in American men. Among patients who have a radical prostatectomy, ∼30% will have disease recurrence. Currently, the level of prostate specific antigen (PSA), clinical stage (TNM) and tumor grade (Gleason score) are used to estimate prognosis and inform treatment modalities. Although these are extremely useful, additional biomarkers are needed to better predict outcome. Angiogenesis has been associated with Gleason score, tumor stage, progression, metastasis and survival in prostate cancer. We hypothesized that single nucleotide polymorphisms (SNPs) in genes in the angiogenesis pathway may be associated with prostate cancer recurrence. Methods: In a historical cohort of 1061 prostatectomy cases treated at the Moffitt Cancer Center from 1986 to 2003, we identified 311 recurrent cases and 750 non-recurrent cases. A recurrent case was defined by either an elevated PSA level after surgical treatment, clinical metastasis or disease specific death. All other patients were categorized as non-recurrent. We compared genotype frequencies of 2,981 SNPs in 547 angiogenesis genes between the two groups. Genotyping was performed using the Illumina GoldenGate assay and associations between recurrence-free survival and individual SNPs were evaluated using competing Cox regression models to estimate hazard ratios (HR) and 95% confidence intervals (95%CI) under three inheritance models (dominant, recessive and log-additive model). For each SNP, the minimum P-value among all tested inheritance models was selected. We calculated q-values to estimate false discovery rates. Results: The mean age at diagnosis of the study subjects was 59.7 (SD=7.5) years. The recurrence rate was 29.3% with a median recurrence-free survival of 200.8 (range=179.0-241.9) months. A total of 91 SNPs in 56 angiogenesis genes had raw P-values less than 0.01 and q-values less than 3%. We found associations for several families of genes that have been previously associated with aggressiveness and/or survival of prostate cancer, such as cadherins (CDH,11 SNPs), fibroblast growth factor and its receptor (FGF/FGFR, 6 SNPs), insulin-like growth factor and its receptor (IGF/IGFR, 3 SNPs), interleukins (IL, 5 SNPs), metalloproteinases (MMP, 3 SNPs) and thrombospondin (THBS, 4 SNPs). The most significant association was observed for [rs889730][1] in CDH13 (HR= 0.69, 95%CI=0.58-0.83, P=0.000057, additive model). CDH13 contributes to promotion of tumor neovascularization, but down regulation has been associated with a poor outcome in prostate cancer. Conclusion: Data from this comprehensive study of angiogenesis genes and prostate cancer suggests that variants in angiogenesis-related genes may influence prostate cancer recurrence after radical prostatectomy. Further studies are warranted to confirm these preliminary findings. 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 2615. doi:1538-7445.AM2012-2615 [1]: /lookup/external-ref?link_type=GEN&access_num=rs889730&atom=%2Fcanres%2F72%2F8_Supplement%2F2615.atom

Abstract 3285: Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition

An ovarian cancer Genome Wide Association Study (GWAS) identified 9p22.2 as a novel susceptibility locus with the most statistically significant single nucleotide polymorphisms (SNPs) located in an intergenic region near the Basonuclin 2 (BNC2) gene, which codes for a putative transcription regulator containing three pairs of zinc finger (ZF) domains. The minor alleles are protective in terms of ovarian cancer susceptibility. However, the molecular mechanisms by which these SNPs modify susceptibility remain largely unknown. The significant SNPs in the 9p22.2 locus lie in non-coding regions and therefore are hypothesized to affect the activity of regulatory elements and modify the expression of a target gene(s). In order to test this hypothesis we conducted fine mapping for the locus which delimited a ∼74kb region containing SNPs with a p-value less than 10-8. FAIRE-Seq and ChIP-Seq experiments for histone markers conducted in immortalized ovarian surface epithelial cells (IOSE) and fallopian tube epithelial cells (IFTE) were used to prioritize functional SNP candidates which overlap with regulatory elements. Luciferase assays tested the ability of these regulatory elements to activate transcription. Chromosome conformation capture (3C) experiments demonstrate a physical interaction between the BNC2 promoter and candidate regulatory elements containing risk-associated SNPs. Methylation Quantification at Trait Loci (mQTL) revealed an association between decreased methylation at the BNC2 promoter and the protective minor alleles. Expression analysis shows decreased expression of BNC2 in cancer versus normal tissue implicating tumor suppressor function of BNC2. Therefore the protective minor allele likely increases expression of BNC2 which in turn contains tumor suppressing properties that decrease ovarian cancer risk. BNC2 protein is in complex with transcriptional regulatory proteins, in particular the NURD complex components. Moreover, BNC2 acts as a transcriptional repressor in in vitro transfection assays indicating that it functions in transcriptional repression. We then used protein binding microarrays and CHIP-Seq experiments to identify its putative DNA binding motifs and its downstream target genes. Analysis of this data suggests that BNC2 functions in a regulatory transcription network that impacts on genes implicated in ovarian cancer with enrichment for genes in the TGF-beta response pathway. Citation Format: Melissa A. Buckley, Howard C. Shen, Gustavo A. Mendoza-Fandino, Nicholas T. Woods, Anxhela Gjyshi, Juliet French, Kate Lawrenson, Honglin Song, Jonathan Tyrer, Renato S. Carvalho, Alexandra Valle, Ann Chen, Sean Yoder, Gregory Bloom, Ya-Yu Tsai, Ally Yang, Timothy R. Hughes, Xiaotao Qu, Mine Cicek, Melissa Larson, Ellen Goode, Brooke Fridley, Susan Ramus, Georgia Chenevix-Trench, Paul Pharoah, Thomas A. Sellers, Simon Gayther, Alvaro N.A. Monteiro, Ovarian Cancer Association Consortium. Functional analysis of the 9p22 locus implicates the transcriptional regulation of BNC2 as a mechanism in ovarian cancer predisposition. [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 3285. doi:10.1158/1538-7445.AM2014-3285

Abstract 4579: Variants in long non-coding RNAs are associated with epithelial ovarian cancer risk in a pooled analysis of three genome-wide association studies.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Since most GWAS hits fall in non-coding regions of the genome and long non-coding RNAs (lncRNAs) are emerging as drivers of carcinogenesis, we hypothesized that SNPs in lncRNAs influence epithelial ovarian cancer (EOC) risk. A comprehensive lncRNA database (lncRNA db) that contained 104 human lncRNAs when downloaded in November 2011 was used to identify 1,737 variants in 63 unique lncRNAs that were represented in three genome-wide association studies from North America, the United Kingdom, and Poland (3,995 EOC cases and 3,277 controls of European background). SNPs with MAF C) (minor allele frequency= 36%, odds ratio (OR) = 0.91, CI: 0.84-0.97, p = 0.008). Among serous cases, rs3809061 was also protective (OR = 0.92, p = 0.04). These findings were replicated by a correlated SNP rs2301250 (r2 = 0.84) evaluated in COGS among serous cases (OR = 0.94, CI: 0.90-0.99, p = 0.009) and less significant among all histologies (OR = 0.96, CI: 0.93-1.00, p = 0.054). We further interrogated its functional role by performing an expression quantitative trait locus analysis on WTI-AS mRNA expression using the Cancer Genome Atlas (TCGA) data (N = 462 serous cases). WT1-AS expression was significantly higher among carriers of the variant allele (compared to TT homozygotes) using the Mann-Whitney U test (p = 0.001). WT1-AS is the antisense and possible regulator of WT1, a tumor suppressor gene reported to be prognostic in advanced EOC. These findings implicate germline lncRNA variants associated with EOC risk that merit further investigation. Citation Format: Yian Ann Chen, Zhihua Chen, Jennifer Permuth-Wey, Ya-Yu Tsai, Hui-Yi Lin, Xiaotao Qu, Kate Lawrenson, David Fenstermacher, Catherine M. Phelan, Alvaro Monteiro, Simon A. Gayther, Steven A. Narod, Rebecca Sutphen, Michael J. Birrer, Nicolas Wentzensen, Joellen M. Schildkraut, Ellen L. Goode, Paul Pharoah, Thomas Sellers. Variants in long non-coding RNAs are associated with epithelial ovarian cancer risk in a pooled analysis of three genome-wide association studies. [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 4579. doi:10.1158/1538-7445.AM2013-4579 [1]: /lookup/external-ref?link_type=GEN&access_num=AK082072&atom=%2Fcanres%2F73%2F8_Supplement%2F4579.atom

Abstract 4850: Variation in circadian rhythm genes influence epithelial ovarian cancer risk and invasiveness.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Background: Circadian rhythms of biological processes are regulated by endogenous clock genes and clock-controlled genes. Aberrant expression of circadian clock genes may have important consequences on the transactivation of downstream targets that control the cell cycle and cellular proliferation potentially promoting carcinogenesis. Animal models indicate that several circadian rhythm genes are expressed in the ovaries, where they influence and are influenced by estrous cycles. The goal of the current study was to examine the association of circadian gene variants and epithelial ovarian cancer (EOC) risk. Methods: Thirty-one SNPs from five circadian genes (i.e., ARNTL, CRY2, KLF10, NPAS2, PER3, TIMELESS) were genotyped in 14,736 cases and 23,448 control women of European ancestry from 43 studies in the Ovarian Cancer Association Consortium (OCAC), on a custom Illumina iSelect designed for the Collaborative Oncological Gene-Environment Study (COGS). Both invasive cancers combined and the four main histological subtypes (serous [n=8,372], endometroid [n=2,068], clear cell [n=1,025] and mucinous [n=943] were analyzed, SNP analyses were conducted using unconditional logistic regression under a log-additive model. All analyses were adjusted for study site and population substructure. Results: Eleven SNPs were found to be associated with ovarian cancer risk. The SNPs most associated with serous cancer risk were KLF10 rs2513928 (OR=.95 p=6.1x10−3), rs2513927 (OR=1.05 p=6.1x10−3), rs2511703 (OR=1.05 p=9.8x10−3), rs3191333 (OR=1.05, p=1.5x10−2) and NPAS2 rs13012930 (OR=.95, p=3.5x10−2). Endometroid cancer risk was significantly associated with ARNTL SNPs rs10732458 (OR=1.3, p=1.0x10−2) and rs7117836 (OR=1.2, p=4.6x10−2), while clear cell cancer risk was associated with ARNTL rs1562438 (OR=.88, p=1.5x10−2), rs1026071 (OR=.89, p=1.8x10−2), and rs3816360 (OR=.91, p=4.8x10−2) and KLF10 rs2388232 (OR=1.1, p=3.3x10−2). No variants were significantly associated with mucinous cancer risk. Four SNPs in KLF10 were associated with cancer invasiveness; they were rs2513928 (OR=.95, p=1.8x10−3), rs3191333 (OR=1.04, p=1.4x10−2), rs2513927 (OR=1.04, p=1.9x10−2), and rs2511703 (OR=1.03, p=2.8x10−2). Conclusions: Data from the current study suggest that polymorphisms in circadian genes ARNTL, KLF10, and NPAS2 are significantly associated with ovarian cancer histopathologic subtypes and invasiveness. These findings merit further investigation and replication. Funding: R01 [CA149429][1] Citation Format: Heather Jim, Jonathan Tyrer, Hui-Yi Lin, Gang Han, Xiaotao Qu, Ellen L. Goode, Zhihua Chen, Ya-Yu Tsai, Julie M. Cunningham, Edward Iversen, Susan Ramus, Andrew Berchuck, Joellen Schildkraut, Alvaro Monteiro, Simon Gayther, Steven A. Narod, Thomas A. Sellers, Paul Pharoah, Catherine M. Phelan. Variation in circadian rhythm genes influence epithelial ovarian cancer risk and invasiveness. [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 4850. doi:10.1158/1538-7445.AM2013-4850 Note: This abstract was not presented at the AACR Annual Meeting 2013 because the presenter was unable to attend. [1]: /lookup/external-ref?link_type=GEN&access_num=CA149429&atom=%2Fcanres%2F73%2F8_Supplement%2F4850.atom

Abstract 4839: SNP-SNP interactions in mitochondria-related pathways are associated with invasive Epithelial Ovarian Cancer (EOC) risk .

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC Background: Variation in mitochondrial genes in cancer cells alters the mitochondrial bioenergetic and biosynthetic state, which mediates cross-talk between mitochondria and the nucleus to modulate many cellular processes. The objective of this study was to comprehensively evaluate mitochondria-nuclear cross-talk in terms of SNP-SNP interactions associated with invasive epithelial ovarian cancer (EOC) risk, which may play an important role in unveiling the underlying mechanism of this complex lethal disease. Methods: Our analyses were based on 1,938 invasive EOC cases and 2,009 controls with greater than 80% European ancestry from five case-control studies genotyped using the Illumina 610quad chip. We evaluated 2,488 SNPs in over 1,500 genes in eight mitochondria-related pathways (apoptosis, oxidation-reduction, epithelial-mesenchymal transition, immunomoduation, transmembrane transport, small GTPases, BRCA1-interactors and circadian rhythm). SNPs with strong linkage disequilibrium of r2 > 0.8 were excluded. We examined 2-way SNP-SNP interactions associated with invasive EOC risk using the two-stage Random Forests plus Multivariate Adaptive Regression Splines (TRM) approach. Bootstrapping was further performed to select important variables and reduce false positive findings. Based on the scree plot using 1,000 bootstrap samples, the factors with more than 4% of bootstrap frequency were defined as significant factors. We then included each identified factors separately in model adjusting for study site and first principal component representing European ancestry. Results: Five significant SNP-SNP interactions were observed: (rs2270799 in IQSEC3 (12p13.33) + [rs933305][1] in CUX2 (12q24.3), (p= 6.3x10−5); rs6063251 in PREX1 (20q13.3) + rs9705 in SLC39A8 (4q22-q24), (p= 3.5x10−5); [rs933305][1] in CUX2 (12q24.3) + rs1712957 in ARHGAP15 (2q22.2-q22.3), (p=4.2x10−7), rs2861828 in SLIT1 (10q23.3-q24) + rs6063251 in PREX1 (20q13.3), (p=2.5x10−7); rs10954593 in SEMA3C (7q21-q31) + [rs933305][1] in CUX2 (12q24.3), (p=2.8x10−3). Four of the five interactions involved SNPs from genes in the small GTPases pathway (IQSEC3; PREX1 (twice) and ARHGAP15). In addition, three of the five interaction pairs involved the CUX2 gene. This gene encodes a protein which contains three CUT domains and a homeodomain, which are DNA-binding motifs. The main mitochondrial SNP-SNP interaction involved the nuclear mitochondria gene SLC39A8. Conclusions: Our results suggest that genetic variation in mitochondrial-related pathways may be associated with invasive EOC risk. These findings highlight important genes/pathways that may interact as a network to influence invasive EOC risk and may generate novel therapeutic targets. External validation will be done using other independent studies for future analyses. Citation Format: Hui-Yi Lin, Ya-Yu Tsai, Y. Ann Chen, Zhihua Chen, Xiaotao Qu, Ellen L. Goode, Joellen Schildkraut, Edwin Iversen, Steven A. Narod, Thomas A. Sellers, Catherine M. Phelan. SNP-SNP interactions in mitochondria-related pathways are associated with invasive Epithelial Ovarian Cancer (EOC) risk . [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 4839. doi:10.1158/1538-7445.AM2013-4839 [1]: /lookup/external-ref?link_type=GEN&access_num=rs933305&atom=%2Fcanres%2F73%2F8_Supplement%2F4839.atom

Abstract 3644: Variation in transmembrane transport genes influence epithelial ovarian cancer risk and histopathologic subtype.

Proceedings: AACR 104th Annual Meeting 2013; Apr 6-10, 2013; Washington, DC 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