Sellers, Thomas A.

AbstractMammographic percent density (PD) is a strong risk factor for breast cancer, but there has been relatively little systematic evaluation of other features in mammographic images that might additionally predict breast cancer risk. We evaluated the association of a large number of image texture features with risk of breast cancer using a clinic-based case-control study of digitized film mammograms, all with screening mammograms before breast cancer diagnosis. The sample was split into training (123 cases and 258 controls) and validation (123 cases and 264 controls) data sets. Age-adjusted and body mass index (BMI)–adjusted odds ratios (OR) per SD change in the feature, 95% confidence intervals, and the area under the receiver operator characteristic curve (AUC) were obtained using logistic regression. A bootstrap approach was used to identify the strongest features in the training data set, and results for features that validated in the second half of the sample were reported using the full data set. The mean age at mammography was 64.0 ± 10.2 years, and the mean time from mammography to breast cancer was 3.7 ± 1.0 (range, 2.0-5.9 years). PD was associated with breast cancer risk (OR, 1.49; 95% confidence interval, 1.25-1.78). The strongest features that validated from each of several classes (Markovian, run length, Laws, wavelet, and Fourier) showed similar ORs as PD and predicted breast cancer at a similar magnitude (AUC = 0.58-0.60) as PD (AUC = 0.58). All of these features were automatically calculated (unlike PD) and measure texture at a coarse scale. These features were moderately correlated with PD (r = 0.39-0.76), and after adjustment for PD, each of the features attenuated only slightly and retained statistical significance. However, simultaneous inclusion of these features in a model with PD did not significantly improve the ability to predict breast cancer. (Cancer Epidemiol Biomarkers Prev 2009;18(3):837–45)

Abstract Introduction: Tissue microarrays (TMA) enable rapid analysis of biomarkers in large-scale studies involving archival tumor specimens, however, their utility in heterogeneous tumors such as ovarian cancer is limited. Methods: In this study, immunohistochemical analysis was done on TMAs comprised of epithelial ovarian cancer (EOC) to estimate the prevalence of loss of expression of three mismatch repair proteins. TMAs were initially created using cores sampled from the center of donor tissue blocks from 59 EOC cases. Full sections were subsequently created and levels of expression were compared between tissues sampled from the central portion versus the periphery. Follow-up analyses were done by obtaining cores from the periphery of up to five additional donor blocks per case. A linear mixed model for each protein was used to investigate differences between results from the initial and follow-up blocks. Results: In the original TMAs created using centrally sampled cores, loss of mismatch repair expression was noted in 17 (29%) of the 59 cases. By comparison, analyses from peripherally sampled cores revealed loss of expression in only 6 of these 17 cases. For each protein, significant differences (P < 0.05) were detected between results from the initial donor block and the majority of the follow-up blocks. Conclusions: Our investigations, based on EOC, suggest that sampling variability in protein expression may result when TMAs are used. Thus, at least for EOC, it is important to preferentially sample from the periphery of tumor blocks where exposure to tissue fixatives is optimal. (Cancer Epidemiol Biomarkers Prev 2009;18(1):28–34)

Abstract Breast density is a strong risk factor for breast cancer; however, no standard assessment method exists. An automated breast density method was modified and compared with a semi-automated, user-assisted thresholding method (Cumulus method) and the Breast Imaging Reporting and Data System four-category tissue composition measure for their ability to predict future breast cancer risk. The three estimation methods were evaluated in a matched breast cancer case-control (n = 372 and n = 713, respectively) study at the Mayo Clinic using digitized film mammograms. Mammograms from the craniocaudal view of the noncancerous breast were acquired on average 7 years before diagnosis. Two controls with no previous history of breast cancer from the screening practice were matched to each case on age, number of previous screening mammograms, final screening exam date, menopausal status at this date, interval between earliest and latest available mammograms, and residence. Both Pearson linear correlation (R) and Spearman rank correlation (r) coefficients were used for comparing the three methods as appropriate. Conditional logistic regression was used to estimate the risk for breast cancer (odds ratios and 95% confidence intervals) associated with the quartiles of percent breast density (automated breast density method, Cumulus method) or Breast Imaging Reporting and Data System categories. The area under the receiver operator characteristic curve was estimated and used to compare the discriminatory capabilities of each approach. The continuous measures (automated breast density method and Cumulus method) were highly correlated with each other (R = 0.70) but less with Breast Imaging Reporting and Data System (r = 0.49 for automated breast density method and r = 0.57 for Cumulus method). Risk estimates associated with the lowest to highest quartiles of automated breast density method were greater in magnitude [odds ratios: 1.0 (reference), 2.3, 3.0, 5.2; P trend < 0.001] than the corresponding quartiles for the Cumulus method [odds ratios: 1.0 (reference), 1.7, 2.1, and 3.8; P trend < 0.001] and Breast Imaging Reporting and Data System [odds ratios: 1.0 (reference), 1.6, 1.5, 2.6; P trend < 0.001] method. However, all methods similarly discriminated between case and control status; areas under the receiver operator characteristic curve were 0.64, 0.63, and 0.61 for automated breast density method, Cumulus method, and Breast Imaging Reporting and Data System, respectively. The automated breast density method is a viable option for quantitatively assessing breast density from digitized film mammograms. (Cancer Epidemiol Biomarkers Prev 2008;17(11):3090–7)

Abstract Catechol O-methyltransferase (COMT)-catalyzed methylation of catecholestrogens has been proposed to play a protective role in estrogen-induced genotoxic carcinogenesis. We have taken a comprehensive approach to test the hypothesis that genetic variation in COMT might influence breast cancer risk. Fifteen COMT single nucleotide polymorphisms (SNPs) selected on the basis of in-depth resequencing of the COMT gene were genotyped in 1,482 DNA samples from a Mayo Clinic breast cancer case control study. Two common SNPs in the distal promoter for membrane-bound (MB) COMT, rs2020917 and rs737865, were associated with breast cancer risk reduction in premenopausal women in the Mayo Clinic study, with allele-specific odds ratios (OR) of 0.70 [95% confidence interval (CI), 0.52–0.95] and 0.68 (95% CI, 0.51–0.92), respectively. These two SNPs were then subjected to functional genomic analysis and were genotyped in an additional 3,683 DNA samples from two independent case control studies (GENICA and GESBC). Functional genomic experiments showed that these SNPs could up-regulate transcription and that they altered DNA-protein binding patterns. Furthermore, substrate kinetic and exon array analyses suggested a role for MB-COMT in catecholestrogen inactivation. The GENICA results were similar to the Mayo case control observations, with ORs of 0.85 (95% CI, 0.72–1.00) and 0.85 (95% CI, 0.72–1.01) for the two SNPs. No significant effect was observed in the GESBC study. These studies showed that two SNPs in the COMT distal promoter were associated with breast cancer risk reduction in two of three case control studies, compatible with the results of functional genomic experiments, suggesting a role for MB-COMT in breast cancer risk. [Cancer Res 2008;68(14):5997–6005]

Abstract Whole genome amplification (WGA) offers a means to enrich DNA quantities for epidemiologic studies. We used an ovarian cancer study of 1,536 single nucleotide polymorphisms (SNPs) and 2,368 samples to assess performance of multiple displacement amplification (MDA) WGA using an Illumina GoldenGate BeadArray. Initial screening revealed successful genotyping for 93.4% of WGA samples and 99.3% of genomic samples, and 93.2% of SNPs for WGA samples and 96.3% of SNPs for genomic samples. SNP failure was predicted by Illumina-provided designability rank, %GC (P ≤ 0.002), and for WGA only, distance to telomere and Illumina-provided SNP score (P ≤ 0.002). Distance to telomere and %GC were highly correlated; adjustment for %GC removed the association between distance to telomere and SNP failure. Although universally high, per-SNP call rates were related to designability rank, SNP score, %GC, minor allele frequency, distance to telomere (P ≤ 0.01), and, for WGA only, Illumina-provided validation class (P < 0.001). We found excellent concordance generally (>99.0%) among 124 WGA:genomic replicates, 15 WGA replicates, 88 replicate aliquots of the same WGA preparation, and 25 genomic replicates. Where there was discordance, it was across WGA:genomic replicates but limited to only a few samples among other replicates suggesting the introduction of error. Designability rank and SNP score correlated with WGA:genomic concordance (P < 0.001). In summary, use of MDA WGA DNA is feasible; however, caution is warranted regarding SNP selection and analysis. We recommend that biological SNP characteristics, notably distance to telomere and GC content (<50% GC recommended), as well as Illumina-provided metrics be considered in the creation of GoldenGate assays using MDA WGA DNA. (Cancer Epidemiol Biomarkers Prev 2008;17(7):1781–9)

Abstract Aim: To examine the use of complementary and alternative medicine (CAM) by women with varying levels of familial and perceived risk of breast cancer with the goal of preventing breast cancer. Methods: Cross-sectional data on CAM use were collected on 2,198 women (mean age, 63 years) personally unaffected by breast cancer in the Minnesota Breast Cancer Family Study. CAM use was compared across women at high, moderate, or average risk based on family history, as well as across categories of perceived risk of breast cancer. CAM use was also examined in relation to screening and general health behaviors, worry about breast cancer, and optimism. Results: Half (49.5%) of the women reported using at least one CAM modality with the intent of preventing breast cancer. Univariate analyses indicated that greater overall CAM use was related to greater perceived risk (P = 0.018), more general health behaviors (P < 0.0001), more breast cancer screening behaviors (P = 0.0002), greater optimism (P = 0.0002), and higher educational attainment (P < 0.0001). Multivariate analysis revealed that general health behaviors (P < 0.0001), education (P = 0.0027), and optimism (P = 0.037) were significant predictors of CAM use when in the same model with perceived risk and breast cancer screening behaviors. Conclusions: Many women use CAM with the goal of preventing breast cancer. General health-promoting behaviors, education, and optimism predict CAM use. Evidence-based guidance is needed for the public and health care providers on the potential and limitations of specific CAM approaches to affect cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(6):1527–34)

Objective: Mother-daughter communication may be a potential pathway between family history and cancer prevention behavior. We examined the degree to which mothers reported providing advice on breast cancer prevention to their daughters, the content of such advice, and correlates of providing such advice. Methods: Data were collected via a mailed questionnaire to 1773 women from 355 families in the Minnesota Breast Cancer Family Study. Women were asked whether or not they had provided advice to their daughters on what they should do to prevent breast cancer. An additional open-ended question asked them to describe the types of advice they had provided. Results: Nine hundred seventy-six (55%) of the women reported providing breast cancer prevention advice to their daughters. The most frequent types of advice were to have a mammogram (51%), perform breast self-examination (BSE) (39%), have a clinical breast examination (CBE) (30%), and maintain a healthy lifestyle (21%). From multivariate logistic regression, older age ( p < 0.001), having a personal history of breast cancer ( p < 0.001), higher degree of breast cancer worry/concern ( p < 0.001), engaging in a higher number of health-promoting behaviors ( p < 0.001), and ever performing a BSE ( p = 0.04) were factors independently associated with the provision of advice. Analyses accounting for sample nonindependence did not change our results. Conclusions: Breast cancer prevention behaviors were associated with providing advice. By better understanding the pathways through which breast cancer family history is associated with screening mammography and other prevention behaviors, researchers can develop more effective, tailored prevention interventions at the family level.

AbstractBackground: Limited studies have examined the associations between mammographic density and subsequent breast tumor characteristics.Methods: Eligible women were part of a case-control study of postmenopausal breast cancer, were 40 years or older and had a routine mammogram 4 years or more before their diagnosis. Mammographic density (percent density, dense area, and nondense area) was estimated using a computer-assisted thresholding program. At the time of cancer diagnosis, cases were classified as asymptomatic or symptomatic based on medical record review and breast imaging workup. Pathologic review was done blinded to the density status. Linear regression models and tests for trend examined the association between pathologic characteristics of the breast tumor and the components of density for all participants, and stratified by symptom status at diagnosis.Results: Of the 286 eligible cases, 77% were 60 years or older and mean percent density was 29.5% (SD, 14.6%). Density was not significantly associated with tumor size (P = 0.22), histologic type (P = 0.77), estrogen receptor (P = 0.11) or progesterone receptor (P = 0.37) status, mitotic activity (P = 0.12), or nuclear pleomorphism (P = 0.09; P values for percent density). An inverse association was suggested between tumor grade and percent density (32.0%, 30.3%, 26.7% for grades 1-3; P = 0.06 for trend). The inverse association with tumor grade and its components (nuclear pleomorphism and tubular differentiation) was only evident among the 97 symptomatic women; positive associations of estrogen receptor (P = 0.009) and progesterone receptor (P = 0.04) were also seen with percent density only in this subgroup.Conclusions: The inverse association between tumor grade and percent density in the symptomatic population could inform the biology of the association between mammographic density and breast cancer risk. (Cancer Epidemiol Biomarkers Prev 2008;17(4):872–9)

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&gt;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&gt;G (rs13420827: OR, 0.8; 95% CI, 0.6–1.0; P interaction = 0.006; FPRP = 0.54), intron 6 G&gt;A (rs11887120: OR, 0.8; 95% CI, 0.7–1.0; P interaction = 0.007; FPRP = 0.57), and intron 22 A&gt;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]