Schildkraut, Joellen M.

Abstract Dysfunction in enzymes involved in one-carbon (1-C) metabolism can lead to increased chromosomal strand breaking and abnormal methylation patterns, which are both associated with cancer risk. Availability of 1-C units may modify risk. We investigated the association of single-nucleotide polymorphisms (SNP) in 21 genes in the 1-C transfer pathway among 829 Caucasian cases with primary epithelial ovarian cancer and 941 frequency-matched unaffected controls enrolled at Mayo Clinic (Rochester, MN) and Duke University (Durham, NC) and examined risk modification by multivitamin supplement use. Multivariable-adjusted SNP-specific logistic regression and haplotype analyses were done for 180 SNPs and false positive report probabilities (FPRP) were calculated. Each copy of the minor allele in SHMT1 intron 5 A>G (rs9909104) was associated with epithelial ovarian cancer [odds ratio (OR), 1.2; 95% confidence interval (95% CI), 1.0–1.4; P trend = 0.02; FPRP = 0.16] and a 5-SNP SHMT1 haplotype was associated with decreased risk (P = 0.01; FPRP = 0.09). Three SNPs in DNMT3A were associated with risk among multivitamin supplement users: 3′ untranslated region (UTR) C>G (rs13420827: OR, 0.8; 95% CI, 0.6–1.0; P interaction = 0.006; FPRP = 0.54), intron 6 G>A (rs11887120: OR, 0.8; 95% CI, 0.7–1.0; P interaction = 0.007; FPRP = 0.57), and intron 22 A>T (rs11695471: OR, 1.2; 95% CI, 1.0–1.5; P interaction = 0.01; FPRP = 0.66). These data extend previous findings from other cancers of a role for SHMT1 in ovarian cancer, and provide evidence that SNPs in methylation and DNA synthesis reactions are associated with risk of ovarian cancer. Interventions with modifiable factors such as multivitamin intake may reduce risk. [Cancer Res 2008;68(7):2498–506]

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]

Abstract Recent experimental evidence has shown that catechol estrogens can be activated through metabolism to form depurinating DNA adducts and thereby initiate cancer. Limited data are available regarding this pathway in epithelial ovarian cancer. We conducted a case-control study of 503 incident epithelial ovarian cancer cases at the Mayo Clinic in Rochester, MN, and Jacksonville, FL, and a 48-county region in North Carolina. Six hundred nine cancer-free controls were frequency matched to the cases on age, race, and residence. After an interview to obtain data on risk factors, a sample of blood was collected for DNA isolation. Subjects were genotyped for seven common single nucleotide polymorphisms in four genes involved in catechol estrogen formation (CYP1A1 and CYP1B1) or conjugation (COMT and SULT1A1). Data were analyzed using logistic regression, stratified by race, and with adjustment for design factors and potential confounders. None of the individual genotypes were significantly associated with ovarian cancer risk. However, an oligogenic model that considered the joint effects of the four candidate genes provided evidence for an association between combinations of these genes and ovarian cancer status (P = 0.015). Although preliminary, this study provides some support for the hypothesis that low-penetrance susceptibility alleles may influence risk of epithelial ovarian cancer.