Citations

Abstract Defective microRNA (miRNA) biogenesis contributes to the development and progression of epithelial ovarian cancer (EOC). In this study, we examined the hypothesis that single nucleotide polymorphisms (SNP) in miRNA biogenesis genes may influence EOC risk. In an initial investigation, 318 SNPs in 18 genes were evaluated among 1,815 EOC cases and 1,900 controls, followed up by a replicative joint meta-analysis of data from an additional 2,172 cases and 3,052 controls. Of 23 SNPs from 9 genes associated with risk (empirical P < 0.05) in the initial investigation, the meta-analysis replicated 6 SNPs from the DROSHA, FMR1, LIN28, and LIN28B genes, including rs12194974 (G>A), an SNP in a putative transcription factor binding site in the LIN28B promoter region (summary OR = 0.90, 95% CI: 0.82–0.98; P = 0.015) which has been recently implicated in age of menarche and other phenotypes. Consistent with reports that LIN28B overexpression in EOC contributes to tumorigenesis by repressing tumor suppressor let-7 expression, we provide data from luciferase reporter assays and quantitative RT-PCR to suggest that the inverse association among rs12194974 A allele carriers may be because of reduced LIN28B expression. Our findings suggest that variants in LIN28B and possibly other miRNA biogenesis genes may influence EOC susceptibility. Cancer Res; 71(11); 3896–903. ©2011 AACR.

Abstract Recent GWAS have identified and confirmed associations between several SNPs in the gene desert located on chromosome 8q24 with risk of cancers of the breast, prostate, glioma, bladder and colorectum. Evidence supporting an association with ovarian cancer is limited and inconsistent. Here we evaluate preliminary results in the 8q24 region from stage I of an ongoing invasive epithelial ovarian cancer GWAS among 1864 cases (1096 serous cases) and 1912 controls. All subjects were self-reported non-Hispanic non-Jewish Caucasian, and were genotyped with the Illumina 610quad Chip. Samples and SNPs with call rates less than 95% were excluded (9.6% and 9.9%, respectively) as well as 128 subjects with ambiguous gender, unresolved identical genotypes and less than 80% European ancestry were also excluded. Our most significant hit in the region was rs6651252 located at 8q24.21 with p = 0.000125 for all ovarian cancer, and 1.02*10−5 for serous cases only. This region is located approximately 849 kb downstream of the previous 8q24.21 findings on other cancers, and was not in linkage disequilibrium with any of the haplotype blocks reported previously. We further examined the block structure of this region with eight genotyped SNPs located within 129.61 to 129.64 MB (rs10088218, rs1516973, rs1516975, rs16903097, rs10098821, rs6651252, rs1561928, and rs1561927) and performed haplotype analysis to evaluate the association with ovarian cancer risk. One haplotype (AAGCAGGG, estimated frequency=0.11) was significantly associated with decreased ovarian cancer risk with an odds ratio of 0.67 (all cases, 95% CI: 0.78-0.91, p=0.0026, empirical p= 0.0020). This region contains no known genes, but it is located upstream and overlaps with a known copy number variation (CNV) reported by Redon et al. (2006). Previous published literature on array CGH and CNV results from TCGA (The Cancer Genome Atlas) also indicate that the 8q24.21 region is associated with frequent gains/amplification in ovarian tumors. Combined analysis of SNPs and CNV identified in this region is underway to elucidate the joint effect of these two types of genetic variation on ovarian cancer risk. Our result indicates a novel locus on 8q24.21 is associated with epithelial ovarian cancer susceptibility. Haplotype analysis reveals one specific haplotype that is associated with decreased ovarian cancer risk compared to the most common haplotype. Given previous 8q24 findings from other cancers and evidence from publicly available resources, fine-mapping and resequencing of this region is warranted. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4724.

Abstract Background: We previously identified a panel of genes associated with outcome of ovarian cancer. The purpose of the current study was to assess whether variants in these genes correlated with ovarian cancer risk. Methods and Findings: Women with and without invasive ovarian cancer (749 cases, 1,041 controls) were genotyped at 136 single nucleotide polymorphisms (SNPs) within 13 candidate genes. Risk was estimated for each SNP and for overall variation within each gene. At the gene-level, variation within MSL1 (male-specific lethal-1 homolog) was associated with risk of serous cancer (p=0.03); haplotypes within PRPF31 (PRP31 pre-mRNA processing factor 31 homolog) were associated with risk of invasive disease (p=0.03). MSL1 rs7211770 was associated with decreased risk of serous disease (OR 0.81, 95% CI 0.66-0.98; p=0.03). SNPs in MFSD7, BTN3A3, ZNF200, PTPRS, and CCND1A were inversely associated with risk (p<0.05), and there was increased risk at HEXIM1 rs1053578 (p=0.04, OR 1.40, 95% CI 1.02-1.91). Conclusions: Tumor studies can reveal novel genes worthy of follow-up for cancer susceptibility. Here, we found that inherited markers in the gene encoding MSL1, part of a complex that modifies the histone H4, may decrease risk of invasive serous ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 4718.

Abstract Introduction: Alterations in components of the stromal tissue that underlie the epithelium can initiate, promote or inhibit epithelial tumorigenesis. Decorin (DCN) and lumican (LUM) are stromal genes with reduced expression in serous ovarian cancer. We hypothesized that single nucleotide polymorphisms (SNPs) in these genes may influence susceptibility to serous ovarian cancer. Methods: To test this hypothesis, we compared genotype frequencies of 11 tagSNPs in DCN and LUM between 397 Caucasian cases with primary serous ovarian cancer and 920 Caucasian controls in two studies conducted at Mayo Clinic and Duke University (discovery set). Associations were evaluated further in a third Caucasian population of 436 cases and 1,098 controls in Australia (replication set). TagSNPs were selected from unrelated Caucasian samples within HapMap based on the following criteria: (i) minor allele frequency ≥ 0.05, (ii) pairwise linkage disequilibrium (LD) of r2 ≥ 0.8, and (iii) location within, and 5kb upstream and downstream of, each gene region. Genotyping was performed using the Illumina GoldenGate™ assay and associations between SNPs and serous cancer were evaluated using unconditional logistic regression to estimate per allele odds ratios (OR) and 95% confidence intervals (95%CI). Untyped genotypes for DCN rs13312816 in the discovery set, and for DCN rs3138165 and LUM rs17018765 in the replication set, were imputed using the MACH software. Results: In the discovery set, we observed inverse associations between DCN rs3138165 (OR=0.7; 95%CI=0.5-1.0), DCN rs13312816 (OR=0.7; 95%CI=0.5-1.0), DCN rs516115 (OR=0.8; 95%CI=0.7-1.0) and LUM rs17018765 (OR=0.7; 95%CI=0.5-1.0) and risk of serous ovarian cancers (all Ptrend=0.06). Associations were confirmed in the replication set for DCN rs3138165 (OR=0.6; 95%CI=0.4-0.9; Ptrend=0.009), DCN rs13312816 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.01) and LUM rs17018765 (OR=0.6; 95%CI=0.4-0.9; Ptrend=0.008), but not for DCN rs516115 (Ptrend=0.20). To increase statistical power, data from the discovery and replication sets were combined (833 cases and 2,013 controls) following confirmation of no statistical heterogeneity in the ORs between study sites. In the combined sample, associations were strengthened for DCN rs3138165 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.002), DCN rs13312816 (OR=0.7; 95%CI=0.5-0.9; Ptrend=0.002), DCN rs516115 (OR=0.9; 95%CI=0.8-1.0; Ptrend=0.03) and LUM rs17018765 (OR=0.6; 95%CI=0.5-0.8; Ptrend=0.001). All four SNPs were in the same LD block on chromosome 12, suggesting that serous ovarian cancer susceptibility may be driven by a single, correlated variant in the region. Conclusion: The findings of this study suggest that genetic variation in DCN and LUM may influence susceptibility to serous ovarian cancer and contribute to the mounting evidence that supports the role of the stroma in epithelial ovarian cancer. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 2854.

Abstract Aberrant glycosylation is a well-described hallmark of cancer. In a previous ovarian cancer case control study that examined polymorphisms in 26 glycosylation-associated genes, we found strong statistical evidence (P = 0.00017) that women who inherited two copies of a single-nucleotide polymorphism in the UDP-N-acetylgalactosamine:polypeptide N-acetylgalactosaminyltransferase, GALNT1, had decreased ovarian cancer risk. The current study attempted to replicate this observation. The GALNT1 single-nucleotide polymorphism rs17647532 was genotyped in 6,965 cases and 8,377 controls from 14 studies forming the Ovarian Cancer Association Consortium. The fixed effects estimate per rs17647532 allele was null (odds ratio, 0.99; 95% confidence interval, 0.92-1.07). When a recessive model was fit, the results were unchanged. Test for hetero geneity of the odds ratios revealed consistency across the 14 replication sites but significant differences compared with the original study population (P = 0.03). This study underscores the need for replication of putative findings in genetic association studies. Cancer Epidemiol Biomarkers Prev; 19(2); 600–4

Abstract The 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 (r2 = 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. [Cancer Res 2009;69(6):2349–57]

AbstractOver 22,000 cases of ovarian cancer were diagnosed in 2007 in the United States, but only a fraction of them can be attributed to mutations in highly penetrant genes such as BRCA1. To determine whether low-penetrance genetic variants contribute to ovarian cancer risk, we genotyped 1,536 single nucleotide polymorphisms (SNP) in several candidate gene pathways in 848 epithelial ovarian cancer cases and 798 controls in the North Carolina Ovarian Cancer Study (NCO) using a customized Illumina array. The inflammation gene interleukin-18 (IL18) showed the strongest evidence for association with epithelial ovarian cancer in a gene-by-gene analysis (P = 0.002) with a <25% chance of being a false-positive finding (q value = 0.240). Using a multivariate model search algorithm over 11 IL18 tagging SNPs, we found that the association was best modeled by rs1834481. Further, this SNP uniquely tagged a significantly associated IL18 haplotype and there was an increased risk of epithelial ovarian cancer per rs1834481 allele (odds ratio, 1.24; 95% confidence interval, 1.06-1.45). In a replication stage, 12 independent studies from the Ovarian Cancer Association Consortium (OCAC) genotyped rs1834481 in an additional 5,877 cases and 7,791 controls. The fixed effects estimate per rs1834481 allele was null (odds ratio, 0.99; 95% confidence interval, 0.94-1.05) when data from the 12 OCAC studies were combined. The effect estimate remained unchanged with the addition of the initial North Carolina Ovarian Cancer Study data. This analysis shows the importance of consortia, like the OCAC, in either confirming or refuting the validity of putative findings in studies with smaller sample sizes. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3567–72)

Abstract Studies suggest that underglycosylation of the cell membrane mucin MUC1 may be associated with epithelial ovarian cancer. We identified 26 genes involved in glycosylation and examined 93 single nucleotide polymorphisms (SNP) with a minor allele frequency of ≥0.05 in relation to incident ovarian cancer. Cases were ascertained at the Mayo Clinic, Rochester, MN (n = 396) or a 48-county region in North Carolina (Duke University; n = 534). Ovarian cancer–free controls (n = 1,037) were frequency matched to the cases on age, race, and residence. Subjects were interviewed to obtain data on risk factors and a sample of blood for DNA and genotyped using the Illumina GoldenGate assay. We excluded subjects and individual SNPs with genotype call rates of <90%. Data were analyzed using logistic regression, with adjustment for age and residence. We fitted dominant, log additive, and recessive genetic models. Among Caucasians, nine SNPs in eight genes were associated with risk at P < 0.05 under at least one genetic model before adjusting for multiple testing. A SNP in GALNT1 (rs17647532) was the only one that remained statistically significant after Bonferroni adjustment for multiple testing but was not statistically significant in Hardy-Weinberg equilibrium among controls. Haplotype analyses revealed a global association of GALNT1 with risk (P = 0.038, under a recessive genetic model), which largely reflected a decreased risk of one haplotype (0.10 frequency; odds ratio, 0.07; P = 0.01) compared with the most common haplotype (0.39 frequency). These results suggest that genetic polymorphisms in the glycoslyation process may be novel risk factors for ovarian cancer. (Cancer Epidemiol Biomarkers Prev 2008;17(2):397–404)

Abstract High-risk susceptibility genes explain <40% of the excess risk of familial ovarian cancer. Therefore, other ovarian cancer susceptibility genes are likely to exist. We have used a single nucleotide polymorphism (SNP)–tagging approach to evaluate common variants in 13 genes involved in cell cycle control—CCND1, CCND2, CCND3, CCNE1, CDK2, CDK4, CDK6, CDKN1A, CDKN1B, CDKN2A, CDKN2B, CDKN2C, and CDKN2D—and risk of invasive epithelial ovarian cancer. We used a two-stage, multicenter, case-control study. In stage 1, 88 SNPs that tag common variation in these genes were genotyped in three studies from the United Kingdom, United States, and Denmark (∼1,500 cases and 2,500 controls). Genotype frequencies in cases and controls were compared using logistic regression. In stage 2, eight other studies from Australia, Poland, and the United States (∼2,000 cases and ∼3,200 controls) were genotyped for the five most significant SNPs from stage 1. No SNP was significant in the stage 2 data alone. Using the combined stages 1 and 2 data set, CDKN2A rs3731257 and CDKN1B rs2066827 were associated with disease risk (unadjusted P trend = 0.008 and 0.036, respectively), but these were not significant after adjusting for multiple testing. Carrying the minor allele of these SNPs was found to be associated with reduced risk [OR, 0.91 (0.85–0.98) for rs3731257; and OR, 0.93 (0.87–0.995) for rs2066827]. In conclusion, we have found evidence that a single tagged SNP in both the CDKN2A and CDKN1B genes may be associated with reduced ovarian cancer risk. This study highlights the need for multicenter collaborations for genetic association studies. [Cancer Res 2007;67(7):3027–35]