Sellers, Thomas A.

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 Background: Early adolescent weight may affect the risk of postmenopausal breast cancer, and this association may be modified by a family history of breast or ovarian cancer in a first-degree relative, and/or estrogen (ER) and progesterone (PR) receptor status of the disease. Methods: Relative weight at age 12 years (above, below, or average weight compared with peers) and family history were ascertained using a mailed questionnaire in 1986, in the Iowa Women's Health Study, a prospective cohort study of postmenopausal women. Incident breast cancer cases (including ER and PR status) were identified using the Iowa Surveillance, Epidemiology, and End Results Cancer Registry. Relative risks (RR) and 95% confidence intervals (95% CI) were estimated using Cox proportional hazards regression, and were adjusted for breast cancer risk factors, including body mass index at age 18 years and body mass index at study baseline. Results: Through 2003, 2,503 cases of postmenopausal breast cancer were identified among 35,941 women in the analytic cohort. Compared with women with average weight at age 12 years, there was no association of below average weight with risk of breast cancer (RR, 1.02; 95% CI, 0.92-1.13), whereas women with above average weight had a lower risk (RR, 0.85; 95% CI, 0.74-0.98). There was no evidence of an interaction between weight at age 12 years and family history (P = 0.44). The inverse association of above average weight with risk of breast cancer was strongest for PR− tumors (RR, 0.62; 95% CI, 0.43-0.89), intermediate for ER+ (RR, 0.80; 95% CI, 0.67-0.96) and ER− (RR, 0.77; 95% CI, 0.50-1.19) tumors, and weakest for PR+ tumors (RR, 0.90; 95% CI, 0.74-1.09). These associations were not modified by a family history (all P > 0.18). In a joint ER/PR analyses, the strongest inverse association with above average weight at age 12 years was seen for ER+/PR− (RR, 0.49; 95% CI, 0.29-0.85). Conclusion: Above average weight at age 12 years was inversely associated with risk of postmenopausal breast cancer, and was not modified by a family history of the disease. The inverse association was strongest for ER+/PR− tumors. (Cancer Epidemiol Biomarkers Prev 2008;17(2):374–8)

Abstract Increased mammographic density (MD), the proportion of dense tissue visible on a mammogram, is a strong risk factor for breast cancer, common in the population and clusters in families. We conducted the first genome-wide linkage scan to identify genes influencing MD. DNA was obtained from 889 relatives (756 women, 133 men) from 89 families. Percent MD was estimated on 618 (82%) female family members using a validated computer-assisted thresholding method. The genome-wide scan included 403 microsatellite DNA markers with an average spacing of 9 cM. Fine mapping of a region of chromosome 5p (5p13.1-5p15.1) was done using 21 additional closely spaced DNA markers. Linkage analyses were conducted to quantify the evidence for a gene responsible for MD across the genome. The maximum log odds for linkage (LOD) score from the genome-wide scan was on chromosome 5p (LOD = 2.9, supporting linkage by a factor of 102.9 or 794 to 1) with a 1-LOD interval spanning 28.6 cM. Two suggestive regions for linkage were also identified on chromosome 12 (LOD = 2.6, 1-LOD interval of 14.8 cM; and LOD = 2.5, 1-LOD interval of 17.2 cM). Finer mapping of the region surrounding the maximum LOD on chromosome 5p resulted in stronger and statistically significant evidence for linkage (LOD = 4.2) and a narrowed 1-LOD interval (13.4 cM). The putative locus on chromosome 5p is likely to account for up to 22% of variation in MD. Hence, 1 or more of the 45 candidate genes in this region could explain a large proportion of MD and, potentially, breast cancer. [Cancer Res 2007;67(17):8412–8]

AbstractThe AURKA oncogene is associated with abnormal chromosome segregation and aneuploidy and predisposition to cancer. Amplification of AURKA has been detected at higher frequency in tumors from BRCA1 and BRCA2 mutation carriers than in sporadic breast tumors, suggesting that overexpression of AURKA and inactivation of BRCA1 and BRCA2 cooperate during tumor development and progression. The F31I polymorphism in AURKA has been associated with breast cancer risk in the homozygous state in prior studies. We evaluated whether the AURKA F31I polymorphism modifies breast cancer risk in BRCA1 and BRCA2 mutation carriers from the Consortium of Investigators of Modifiers of BRCA1/2. Consortium of Investigators of Modifiers of BRCA1/2 was established to provide sufficient statistical power through increased numbers of mutation carriers to identify polymorphisms that act as modifiers of cancer risk and can refine breast cancer risk estimates in BRCA1 and BRCA2 mutation carriers. A total of 4,935 BRCA1 and 2,241 BRCA2 mutation carriers and 11 individuals carrying both BRCA1 and BRCA2 mutations was genotyped for F31I. Overall, homozygosity for the 31I allele was not significantly associated with breast cancer risk in BRCA1 and BRCA2 carriers combined [hazard ratio (HR), 0.91; 95% confidence interval (95% CI), 0.77-1.06]. Similarly, no significant association was seen in BRCA1 (HR, 0.90; 95% CI, 0.75-1.08) or BRCA2 carriers (HR, 0.93; 95% CI, 0.67-1.29) or when assessing the modifying effects of either bilateral prophylactic oophorectomy or menopausal status of BRCA1 and BRCA2 carriers. In summary, the F31I polymorphism in AURKA is not associated with a modified risk of breast cancer in BRCA1 and BRCA2 carriers. (Cancer Epidemiol Biomarkers Prev 2007;16(7):1416–21)

Purpose Atypical hyperplasia is a well-recognized risk factor for breast cancer, conveying an approximately four-fold increased risk. Data regarding long-term absolute risk and factors for risk stratification are needed. Patients and Methods Women with atypical hyperplasia in the Mayo Benign Breast Disease Cohort were identified through pathology review. Subsequent breast cancers were identified via medical records and a questionnaire. Relative risks (RRs) were estimated using standardized incidence ratios, comparing the observed number of breast cancers with those expected based on Iowa Surveillance, Epidemiology, and End Results (SEER) data. Age, histologic factors, and family history were evaluated as risk modifiers. Plots of cumulative breast cancer incidence provided estimates of risk over time. Results With mean follow-up of 13.7 years, 66 breast cancers (19.9%) occurred among 331 women with atypia. RR of breast cancer with atypia was 3.88 (95% CI, 3.00 to 4.94). Marked elevations in risk were seen with multifocal atypia (eg, three or more foci with calcifications [RR, 10.35; 95% CI, 6.13 to 16.4]). RR was higher for younger women (< 45; RR, 6.76; 95% CI, 3.24 to 12.4). Risk was similar for atypical ductal and atypical lobular hyperplasia, and family history added no significant risk. Breast cancer risk remained elevated over 20 years, and the cumulative incidence approached 35% at 30 years. Conclusion Among women with atypical hyperplasia, multiple foci of atypia and the presence of histologic calcifications may indicate “very high risk” status (> 50% risk at 20 years). A positive family history does not further increase risk in women with atypia.

Abstract Background: Mammographic density is a strong risk factor for breast cancer. However, whether changes in mammographic density are associated with risk remains unclear. Materials and Methods: A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Controls were matched on age, exam date, residence, menopause, interval between, and number of mammograms. All serial craniocaudal mammograms 10 years before ascertainment were digitized, and quantitative measures of percent density (PD) were estimated using a thresholding method. Data on potential confounders were abstracted from medical records. Logistic regression models with generalized estimating equations were used to evaluate the interactions among PD at earliest mammogram, time from earliest to each serial mammogram, and absolute change in PD between the earliest and subsequent mammograms. Analyses were done separately for PD measures from the ipsilateral and contralateral breast and also by use of hormone therapy (HT). Results: Subjects had an average of five mammograms available, were primarily postmenopausal (83%), and averaged 61 years at the earliest mammogram. Mean PD at earliest mammogram was higher for cases (31%) than controls (27%; ipsilateral side). There was no evidence of an association between change in PD and breast cancer risk by time. Compared with no change, an overall reduction of 10% PD (lowest quartile of change) was associated with an odds ratio of 0.9997 and an increase of 6.5% PD (highest quartile of change) with an odds ratio of 1.002. The same results held within the group of 220 cases and 340 controls never using HT. Among the 124 cases and 337 controls known to use HT during the interval, there was a statistically significant interaction between change in PD and time since the earliest mammogram (P = 0.01). However, in all groups, the risk associated with the earliest PD remained a stronger predictor of risk than change in PD. Conclusion: We observed no association between change in PD with breast cancer risk among all women and those never using HT. However, the interaction between change in PD and time should be evaluated in other populations. (Cancer Epidemiol Biomarkers Prev 2007;16(5):921–8)

Abstract High-risk susceptibility genes explain &lt;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 Mammographic breast density is a strong risk factor for breast cancer but whether breast density is a general marker of susceptibility or is specific to the location of the eventual cancer is unknown. A study of 372 incident breast cancer cases and 713 matched controls was conducted within the Mayo Clinic mammography screening practice. Mammograms on average 7 years before breast cancer were digitized, and quantitative measures of percentage density and dense area from each side and view were estimated. A regional density estimate accounting for overall percentage density was calculated from both mammogram views. Location of breast cancer and potential confounders were abstracted from medical records. Conditional logistic regression was used to estimate associations, and C-statistics were used to evaluate the strength of risk prediction. There were increasing trends in breast cancer risk with increasing quartiles of percentage density and dense area, irrespective of the side of the breast with cancer (Ptrends &lt; 0.001). Percentage density from the ipsilateral side [craniocaudal (CC): odds ratios (ORs), 1.0 (ref), 1.7, 3.1, and 3.1; mediolateral oblique (MLO): ORs, 1.0 (ref), 1.5, 2.2, and 2.8] and the contralateral side [CC: ORs, 1.0 (ref), 1.8, 2.2, and 3.7; MLO: ORs, 1.0 (ref), 1.6, 1.9, and 2.5] similarly predicted case-control status (C-statistics, 0.64-65). Accounting for overall percentage density, density in the region where the cancer subsequently developed was not a significant risk factor [CC: 1.0 (ref), 1.3, 1.0, and 1.2; MLO: 1.0 (ref), 1.1, 1.0, and 1.1 for increasing quartiles]. Results did not change when examining mammograms 3 years on average before the cancer. Overall mammographic density seems to represent a general marker of breast cancer risk that is not specific to breast side or location of the eventual cancer. (Cancer Epidemiol Biomarkers Prev 2007;16(1):43–9)