Biomarkers Of Breast Cancer Risk Research Articles

Abstract P5-12-03: Initial report of a randomized trial of letrozole in high risk women taking hormone replacement therapy

Abstract Background: On the basis of positive results in a pilot study, we initiated a randomized, double-blind, placebo-controlled trial of the aromatase inhibitor letrozole in post-menopausal women at high risk for development of breast cancer who were taking hormone replacement therapy (HRT). The objective was to determine if risk biomarkers for breast cancer in benign breast tissue sampled by random peri-areolar aspiration (RPFNA) could be favorably modulated. Methods Women who exhibited cytologic hyperplasia +/- atypia and Ki-67 immunocytochemistry staining ≥1.5% on screening RPFNA were eligible to be randomized 1:1 between placebo and letrozole (2.5. mg daily) for six months, followed by repeat RPFNA. Women were then given the option to receive open-label letrozole for a second six months, and a third RPFNA. The primary analysis was a difference between the two groups for the change in Ki-67 between baseline and 6 months. The initial accrual goal was 108 subjects, with the expectation of 96 subjects evaluable for the baseline∼6 months comparison. Results 55 subjects were enrolled between March 2007 and March 2014, when accrual was closed. From the time of our successful pilot study to present, there had been a steady decline in the use of HRT by women in our high risk cohort, both in frequency of women using as well as the type and strength of HRT. The result was fewer potential subjects for screening and fewer still that satisfied the 1.5% Ki-67 criterion. Thus, the trial was closed early. Of 55 enrolled subjects, two dropped out prior to 6 months; 52 completed 6 months and provided evaluable RPFNA specimens for analysis, with one subject scheduled for repeat aspiration in September. Six subjects went off study between 6 and 12 months; 42 have completed the entire 12 month schedule, and 5 are still on trial. At baseline, 18 women displayed hyperplasia (Masood score 13-15) and 37 had hyperplasia with atypia (Masood score 14-17). Median Ki-67 was 3.0%, with a range from 1.6 – 15.4%. For 52 comparisons between baseline and 6 months, 8 women had no change by Masood score, 8 had an increase and 36 exhibited a decrease, i.e., less abnormality. Two women had no change in Ki-67 staining, 13 exhibited increased Ki-67 and 37 showed a decrease; median at 6 months 1.7%, median change -1.4%. For 42 comparisons between baseline and 12 months, 11 women had no change by Massod score, 9 increased, and 22 decreased. One woman had no change in Ki-67 staining, 10 exhibited increased Ki-67 and 31 showed a decrease. The decreases in Masood score and Ki-67 between baseline and 12 months (when all subjects had received letrozole, either for 6 or 12 months) were statistically significant (p<0.005, Wilcoxon signed rank test). When 6-month data are available for the final subject, the randomization will be unblinded by the statistician and the primary study question will be addressed. Conclusion While pending final analysis of the primary (blinded) endpoint, preliminary analysis indicates favorable modulation of cytomorphology and proliferation by the aromatase inhibitor letrozole in high risk post-menopausal women taking hormone replacement therapy. Funding: NIH RO1 CA122577; Novartis Pharmaceuticals Corp. Citation Format: Carol J Fabian, Bruce F Kimler, Jennifer L Nydegger, Trina Metheny, Carola M Zalles, Brian K Petroff, Hung-wen Yeh, Michael D Alvarado. Initial report of a randomized trial of letrozole in high risk women taking hormone replacement therapy [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P5-12-03.

Abstract P1-01-07: Quantitative assessment of early- and delayed DCE-MRI background parenchymal enhancement in breast cancer risk prediction

Abstract Purpose Background parenchymal enhancement (BPE) estimated from breast dynamic contrast enhanced MRI (DCE-MRI) has been correlated with breast cancer risk. Multiple time-point post-contrast-subtracted sequences are acquired in typical clinical breast DCE-MRI protocols. We quantitatively assessed BPE using fully automated computer algorithms and investigated the relationship between BPE quantified from three time-point post-contrast sequences and breast cancer risk prediction. Materials and Methods A retrospective case-control study was performed using breast DCE-MRI scans from 102 patients (mean 47.2±7.3 YO) who underwent either open surgical biopsy or core biopsy from 2009-2011: 51 women had unilateral breast cancer and 51 were age- and date-of-MRI matched controls with a unilateral biopsy-proven benign. For each MRI scan, three post-contrast-subtracted sequences (i.e., SUB 1, SUB 2 and SUB 3) acquired over a total of 7 minutes were analyzed. BPE was quantified from each of the sequences using fully automated computer algorithms on the breasts contralateral to the cancers and the contralateral (negative) breasts of the controls. For each sequence, two quantitative BPE measures were generated: the absolute BPE volume (|BPE|) and its relative amount over the whole breast volume (BPE%). Volumetric absolute and relative amounts of fibroglandular tissue (|FGT| and FGT%) were also automatically quantified, from the pre-contrast sequence. BI-RADS breast density assessment was retrieved from the mammography report (< 6 months) prior to cancer diagnosis (for cases) or MRI (for controls). Multivariable conditional logistic regression was performed to assess BPE measures, quantified respectively from SUB 1, SUB 2, and SUB 3, as predictors of breast cancer risk. Results Breast cancer risk odds ratios (ORs) were reported by |BPE| and BPE% (Table 1), after adjustment for breast density, |FGT|, and FGT%. Breast density did not correlate with risk for breast cancer in this study cohort: OR for BI-RADS density alone was 0.75 (95% CI: 0.35, 1.59; p=0.5). OR was 1.14 (95% CI: 0. 72, 1.81; p=0.6) for |FGT| alone and 0.70 (95% CI: 0.19, 2.52; p=0.6) for FGT% alone. Table 1: Breast cancer risk odds ratios (ORs) with 95% confidence intervals [CIs] for BPE quantified from SUB 1, SUB 2, and SUB 3, respectively. BPE from SUB1BPE from SUB2BPE from SUB3|BPE|2.0 (95% CI: 1.1-3.7; p=0.02)2.0 (95% CI: 1.2-3.3; p=0.01)1.7 (95% CI: 1.1-2.7; p=0.02)BPE%3.6 (95% CI: 1.3-10.1; p=0.01)2.8 (95% CI: 1.3-6.2; p=0.01)2.4 (95% CI: 1.2-5.0; p=0.02) Conclusions Increased BPE quantified from DCE-MRI are predictive of breast cancer risk, independent of measures of breast density and FGT. BPE estimated from three time-point SUB sequences has a similar predictive effect of breast cancer risk, while an early sequence (e.g., SUB 1) appears to have a larger magnitude of effect than that of a delayed sequence (e.g., SUB 3). Clinical Relevance Quantified BPE in breast DCE-MRI has potential for use as a biomarker of breast cancer risk and may be included to improve breast cancer risk prediction. A single post-contrast sequence (i.e., SUB 1) may be adequate for use to estimate breast cancer risk using breast MRI in the context of breast cancer screening for high-risk women. Citation Format: Shandong Wu, Wendie A Berg, Margarita L Zuley, Brenda F Kurland, Rachel C Jankowitz, Jules Sumkin, Robert M Nishikawa, David Gur. Quantitative assessment of early- and delayed DCE-MRI background parenchymal enhancement in breast cancer risk prediction [abstract]. In: Proceedings of the Thirty-Seventh Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2014 Dec 9-13; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2015;75(9 Suppl):Abstract nr P1-01-07.

Highlights of This Issue

Nonsteroidal anti-inflammatory drugs (NSAID) may decrease lung cancer risk; however, any protective effect appears to be most evident in men. Baik and colleagues evaluated the associations between NSAID use and lung cancer incidence in postmenopausal women in the Women's Health Initiative. Compared to non-use, regular NSAID use was not associated with overall lung cancer incidence in postmenopausal women. Future studies will need to take into account the various molecular subtypes of non–small cell lung cancer to further elucidate the role of NSAIDS in lung cancer in women.Human papillomavirus (HPV) self-sampling might be a promising tool to increase the effectiveness of HPV screening programs when offered to program non-attendees. However, the effectiveness could decrease if regular program attendees “switch” to self-sampling, since self-sampling test characteristics may be inferior. Rozemeijer and colleagues examined the conditions in which the harms of HPV self-sampling outweigh the benefits. The authors report that offering self-sampling will gain health effects if the relative CIN2+ sensitivity is ≥0.95, unscreened attendees are recruited, and the total attendance increases by ≥6 percentage points. Otherwise, switching of regular attendees may decrease the total effectiveness of the program.Marinac and colleagues examined associations of nighttime fasting duration with biomarkers of breast cancer risk among women in the 2009–2010 U.S. National Health and Nutrition Examination Survey. Each 3-hour increase in nighttime fasting was associated with a 4% lower 2-hour glucose measurement. Randomized trials are needed to confirm whether prolonged nighttime fasting could improve biomarkers of glucose control, thereby reducing breast cancer risk.Mammographic density (MD) is a strong breast cancer risk factor and to provide insight into this association, Bertrand and colleagues examined the percent MD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes. Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA was associated with increased breast cancer and NDA was associated with decreased risk across all ages and invasive tumor characteristics. DA and NDA are important to consider when developing age- and subtype-specific risk models.

Prolonged Nightly Fasting and Breast Cancer Risk: Findings from NHANES (2009-2010).

A novel line of research has emerged, suggesting that daily feeding-fasting schedules that are synchronized with sleep-wake cycles have metabolic implications that are highly relevant to breast cancer. We examined associations of nighttime fasting duration with biomarkers of breast cancer risk among women in the 2009-2010 U.S. National Health and Nutrition Examination Survey. Dietary, anthropometric, and HbA1c data were available for 2,212 women, and 2-hour postprandial glucose concentrations were available for 1,066 women. Nighttime fasting duration was calculated using 24-hour food records. Separate linear regression models examined associations of nighttime fasting with HbA1c and 2-hour glucose concentrations. Logistic regression modeled associations of nighttime fasting with elevated HbA1c (HbA1c ≥ 39 mmol/mol or 5.7%) and elevated 2-hour glucose (glucose ≥ 140 mg/dL). All models adjusted for age, education, race/ethnicity, body mass index, total kcal intake, evening kcal intake, and the number of eating episodes per day. Each 3-hour increase in nighttime fasting (roughly 1 SD) was associated with a 4% lower 2-hour glucose measurement [β, 0.96; 95% confidence interval (CI), 0.93-1.00; P < 0.05], and a nonstatistically significant decrease in HbA1c. Logistic regression models indicate that each 3-hour increase in nighttime fasting duration was associated with roughly a 20% reduced odds of elevated HbA1c (OR, 0.81; 95% CI, 0.68-0.97; P < 0.05) and nonsignificantly reduced odds of elevated 2-hour glucose. A longer nighttime duration was significantly associated with improved glycemic regulation. Randomized trials are needed to confirm whether prolonged nighttime fasting could improve biomarkers of glucose control, thereby reducing breast cancer risk.

Long-term exposure to air pollution and mammographic density in the Danish Diet, Cancer and Health cohort.

BackgroundGrowing evidence suggests that air pollution may be a risk factor for breast cancer, but the biological mechanism remains unknown. High mammographic density (MD) is one of the strongest predictors and biomarkers of breast cancer risk, but it has yet to be linked to air pollution. We investigated the association between long-term exposure to traffic-related air pollution and MD in a prospective cohort of women 50 years and older.MethodsFor the 4,769 women (3,930 postmenopausal) participants in the Danish Diet, Cancer and Health cohort (1993–1997) who attended mammographic screening in Copenhagen (1993–2001), we used MD assessed at the first screening after cohort entry. MD was defined as mixed/dense or fatty. Traffic-related air pollution at residence was assessed by modeled levels of nitrogen oxides (NOx) and nitrogen dioxide (NO2). The association between mean NOx and NO2 levels since 1971 until cohort baseline (1993–97) and MD was analyzed using logistic regression, adjusting for confounders, and separately by menopause, smoking status, and obesity.ResultsWe found inverse, statistically borderline significant associations between long-term exposure to air pollution and having mixed/dense MD in our fully adjusted model (OR; 95% CI: 0.96; 0.93-1.01 per 20 μg/m3 of NOx and 0.89; 0.80- 0.98 per 10 μg/m3 of NO2). There was no interaction with menopause, smoking, or obesity.ConclusionTraffic-related air pollution exposure does not increase MD, indicating that if air pollution increases breast cancer risk, it is not via MD.Electronic supplementary materialThe online version of this article (doi:10.1186/s12940-015-0017-8) contains supplementary material, which is available to authorized users.

Factors associated with participation in a prevention trial aimed at reducing biomarkers of breast cancer risk

ObjectivesPoor enrollment into prevention trials is a major obstacle to the conduct of clinical investigations. This study focuses on cognitive and affective influences on the decision to participate in a clinical trial aimed at reducing biomarkers of breast cancer risk. MethodsFollowing a decision to participate or not in a clinical trial focused on reduction of breast cancer risk, women were recruited into the present study. Data were gathered via telephone survey. ResultsOne hundred healthy women took part in the current study, 72 of whom had participated in the clinical trial, and 28 of whom had declined participation. Women who decided to enroll perceived more benefits and fewer costs, and they experienced more positive emotions and fewer negative emotions. They also made the decision more quickly, more easily, were more satisfied with it, and had fewer regrets than women who declined participation in the clinical trial. ConclusionsParticipants to this clinical trial differed from nonparticipants in terms of antecedents, process, and outcomes of the decision to enroll. Practice implicationsAlthough obstacles exist, accrual might be improved by greater emphasis on the practical and psychosocial benefits to participants.

Promoter Hypermethylation in White Blood Cell DNA and Breast Cancer Risk.

The role of gene-specific methylation in white blood cells (WBC) as a marker of breast cancer risk is currently unclear. We determined whether promoter hypermethylation in blood DNA of candidate tumor suppressor genes frequently methylated in breast tumors can be used as a surrogate biomarker for breast cancer risk. Promoter methylation of BRCA1, CDH1 and RARβ was analyzed in WBC DNA from a population-based sample of 1,021 breast cancer patients and 1,036 controls by the MethyLight assay. Gene-specific promoter methylation in the DNA of 569 tumor tissue samples was also analyzed to determine the correlation of methylation levels with blood from the same individual. Hypermethylation of BRCA1 (OR: 1.31; 95% CI: 0.98-1.75) in WBC was associated with an increased risk of breast cancer when positive methylation was defined as ≥0.1% methylated. There was lack of concordance between tumor tissue and paired WBC DNA methylation. These results provide limited support that hypermethylation of BRCA1 in WBC DNA may be useful for determination of breast cancer risk. Additional studies with larger numbers of genes are needed to fully understand the relationship between WBC methylation and breast cancer risk.

Modulation of Breast Cancer Risk Biomarkers by High-Dose Omega-3 Fatty Acids: Phase II Pilot Study in Postmenopausal Women

Modulation of Breast Cancer Risk Biomarkers by High-Dose Omega-3 Fatty Acids: Phase II Pilot Study in Postmenopausal Women

Genetic polymorphisms in inflammatory response genes and their associations with breast cancer risk

AimTo explore the association of NFKB1 c.-798_-795delATTG (rs28362491), NFKBIA c.-949C>T (rs2233406), IL-8 c.-352A>T (rs4073), IL-10 c.-854T>C (rs1800871), TNF c.-418G>A (rs361525), and TNF c.-488G>A (rs1800629) polymorphisms with breast cancer risk in an East Chinese population.MethodsWe conducted a case-control study including 975 study participants (474 breast cancer patients and 501 female controls without cancer) and genotyped the polymorphisms employing polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP). Logistic regression was used to assess the association of the polymorphisms with breast cancer risk.ResultsWe found that the ins/del and del/del genotypes of NFKB1 polymorphism and TT genotype of IL-10 polymorphism significantly increased breast cancer risk (NFKB1 ins/del odds ratio [OR] 1.69, 95% [CI] 1.23-2.33, P = 0.001; NFKB1 del/del OR 2.42, 95% CI 1.72-3.42, P < 0.001; IL-10 TT OR 2.36, 95% CI 1.58-3.52, P < 0.001). On the other hand, the TT genotype of IL-8 polymorphism, GA and AA genotypes of TNF c.-418G>A polymorphism, and GA genotype of TNF c.-488G>A polymorphism significantly reduced breast cancer risk (IL-8 TT OR 0.48, 95% CI 0.33-0.72, P < 0.001; TNF c.-418 GA OR 0.58, 95% CI 0.41-0.80, P = 0.001; TNF c.-418 AA OR 0.38, 95% CI 0.14-0.98, P = 0.044; TNF c.-488 GA OR 0.68, 95% CI 0.48-0.96, P = 0.029). When stratified by menopausal status, the CT genotype of NFKBIA polymorphism significantly reduced the risk among pre-menopausal women (OR 0.63, 95% CI 0.40-0.99, P = ,043), but not among post-menopausal women.ConclusionsNFKB1, NFKBIA, IL-8, IL-10, and TNF polymorphisms could serve as useful predictive biomarkers for breast cancer risk among women in East China.

Benign breast tissue composition in breast cancer patients: association with risk factors, clinical variables, and gene expression.

Breast tissue composition (epithelium, non-fatty stroma, and adipose) changes qualitatively and quantitatively throughout the lifespan, and may mediate relationships between risk factors and breast cancer initiation. We sought to identify relationships between tissue composition, risk factors, tumor characteristics, and gene expression. Participants were 146 patients from the Polish Breast Cancer Study, with data on risk factor and clinicopathological characteristics. Benign breast tissue composition was evaluated using digital image analysis of histologic sections. Whole-genome microarrays were performed on the same tissue blocks. Mean epithelial, non-fatty stromal, and adipose proportions were 8.4% (SD = 4.9%), 27.7% (SD = 24.0%), and 64.0% (SD = 24.0%), respectively. Among women <50 years old, stroma proportion decreased and adipose proportion increased with age, with approximately 2% difference per year (P < 0.01). The variation in epithelial proportion with age was modest (0.1% per year). Higher epithelial proportion was associated with obesity (7.6% in nonobese vs. 10.1% in obese; P = 0.02) and with poorly differentiated tumors (7.8% in well/moderate vs. 9.9% in poor; P = 0.05). Gene expression signatures associated with epithelial and stromal proportion were identified and validated. Stroma-associated genes were in metabolism and stem cell maintenance pathways, whereas epithelial genes were enriched for cytokine and immune response pathways. Breast tissue composition was associated with age, body mass index, and tumor grade, with consequences for breast gene expression. Breast tissue morphologic factors may influence breast cancer etiology. Composition and gene expression may act as biomarkers of breast cancer risk and progression.

Hormone metabolism pathway genes and mammographic density change after quitting estrogen and progestin combined hormone therapy in the California Teachers Study.

IntroductionMammographic density (MD) is a strong biomarker of breast cancer risk. MD increases after women start estrogen plus progestin therapy (EPT) and decreases after women quit EPT. A large interindividual variation in EPT-associated MD change has been observed, but few studies have investigated genetic predictors of the EPT-associated MD change. Here, we evaluate the association between polymorphisms in hormone metabolism pathway genes and MD changes when women quit EPT.MethodsWe collected mammograms before and after women quit EPT and genotyped 405 tagging single nucleotide polymorphisms (SNPs) in 30 hormone metabolism pathway genes in 284 non-Hispanic white participants of the California Teachers Study (CTS). Participants were ages 49 to 71 years at time of mammography taken after quitting EPT. We assessed percent MD using a computer-assisted method. MD change was calculated by subtracting MD of an ‘off-EPT’ mammogram from MD of an ‘on-EPT’ (that is baseline) mammogram. Linear regression analysis was used to investigate the SNP-MD change association, adjusting for the baseline ‘on-EPT’ MD, age and BMI at time of baseline mammogram, and time interval and BMI change between the two mammograms. An overall pathway and gene-level summary was obtained using the adaptive rank truncated product (ARTP) test. We calculated ‘P values adjusted for correlated tests (PACT)’ to account for multiple testing within a gene.ResultsThe strongest associations were observed for rs7489119 in SLCO1B1, and rs5933863 in ARSC. SLCO1B1 and ARSC are involved in excretion and activation of estrogen metabolites of EPT, respectively. MD change after quitting was 4.2% smaller per minor allele of rs7489119 (P = 0.0008; PACT = 0.018) and 1.9% larger per minor allele of rs5933863 (P = 0.013; PACT = 0.025). These individual SNP associations did not reach statistical significance when we further used Bonferroni correction to consider the number of tested genes. The pathway level summary ARTP P value was not statistically significant.ConclusionsData from this longitudinal study of EPT quitters suggest that genetic variation in two hormone metabolism pathway genes, SLCO1B1 and ARSC, may be associated with change in MD after women stop using EPT. Larger longitudinal studies are needed to confirm our findings.Electronic supplementary materialThe online version of this article (doi:10.1186/s13058-014-0477-8) contains supplementary material, which is available to authorized users.

Abstract 3249: Differential impact of body mass index (BMI) on absolute and percent breast density; implications regarding their use as breast cancer risk (BCR) biomarkers

Abstract Percent breast density (PBD) is a commonly used biomarker of BCR. However, its use is greatly confounded by the strong influence of non-dense breast tissue on its measurement and factors, such as BMI, which have a direct impact on this non-dense tissue. Consequently, BMI, a potent BCR factor, is actually negatively correlated with PBD. We propose that absolute breast density (ABD), a more direct determinant of BCR which can be easily and accurately measured on a routine basis, is a more accurate and valid biomarker of BCR. To address this issue, we compared the correlation between PBD and ABD with baseline demographics (e.g., age, BMI, waist:hip ratio, reproductive parameters, family history of BC and personal history of breast biopsies) and dietary and physical activity variables (measured using a modified version of the NCI Diet History Questionnaire and the International Physical Activity Questionnaire, respectively) in a group of 169 healthy postmenopausal women enrolled in a chemoprevention trial testing the individual and combined effects of the antiestrogen Raloxifene and the omega-3 preparation Lovaza on BD used as a biomarker of BCR (NCT00723398). A volumetric breast density software (Volpara, Matakina, Wellington, New Zealand) was used for determination of ABD and PBD since it may be superior to the two-dimensional method in predicting BCR. As observed previously, a strong negative correlation between PBD and BMI was observed (Rho = -0.5, P&amp;lt;5e-12) due to the strong positive correlation of BMI with non-dense breast. However, we also observed a strong positive correlation of BMI with ABD (Rho = 0.41, P&amp;lt;2.5e-8), a relationship which is not well established in the literature and supports the use of ABD as a more accurate indicator of BCR. We also observed that correction of PBD by BMI did not frequently provide the same information as ABD, thus further indicating that the latter should be the gold standard for BD measurement. The strong positive association between BMI and ABD implies that even a modest change in BMI (as can be expected with dietary and physical activity manipulations) is likely to obscure the independent effect of an intervention on ABD. We indeed observed that many correlations between dietary variables and ABD did not emerge until adjustment was made for BMI. Our data support the following conclusions: 1) ABD instead of PBD (even after adjustment for BMI) should be used for assessment of BD; 2) based on our novel observation of the strong positive correlation between BMI and ABD, ABD should be adjusted for BMI when testing the influence of an intervention on BD as a biomarker of BCR. (Supported by grant KG081632 from Susan G. Komen for the Cure.) Citation Format: Susann Schetter, Terryl Hartman, Jason Liao, John P. Richie, Bogdan Prokopczyk, Cynthia Dubrock, Carina Signori, Christopher Hamilton, Laurence M. Demers, Karam El-Bayoumy, Andrea Manni. Differential impact of body mass index (BMI) on absolute and percent breast density; implications regarding their use as breast cancer risk (BCR) biomarkers. [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 3249. doi:10.1158/1538-7445.AM2014-3249

Validation of six genetic determinants of susceptibility to estrogen-induced mammary cancer in the rat and assessment of their relevance to breast cancer risk in humans.

When treated with 17β-estradiol, female ACI rats (Rattus norvegicus) rapidly develop mammary cancers that share multiple phenotypes with luminal breast cancers. Seven distinct quantitative trait loci that harbor genetic determinants of susceptibility to 17β-estradiol−induced mammary cancer have been mapped in reciprocal intercrosses between susceptible ACI rats and resistant Brown Norway (BN) rats. A panel of unique congenic rat strains has now been generated and characterized to confirm the existence of these quantitative trait loci, designated Emca3 through Emca9, and to quantify their individual effects on susceptibility to 17β-estradiol−induced mammary cancer. Each congenic strain carries BN alleles spanning an individual Emca locus, introgressed onto the ACI genetic background. Data presented herein indicate that BN alleles at Emca3, Emca4, Emca5, Emca6, and Emca9 reduce susceptibility to 17β-estradiol−induced mammary cancer, whereas BN alleles at Emca7 increase susceptibility, thereby confirming the previous interval mapping data. All of these Emca loci are orthologous to regions of the human genome that have been demonstrated in genome-wide association studies to harbor genetic variants that influence breast cancer risk. Moreover, four of the Emca loci are orthologous to loci in humans that have been associated with mammographic breast density, a biomarker of breast cancer risk. This study further establishes the relevance of the ACI and derived congenic rat models of 17β-estradiol−induced mammary cancer for defining the genetic bases of breast cancer susceptibility and elucidating the mechanisms through which 17β-estradiol contributes to breast cancer development.

Associations of change in television viewing time with biomarkers of postmenopausal breast cancer risk: the Australian Diabetes, Obesity and Lifestyle Study.

Sedentary behavior has been previously shown, in a cross-sectional study, to have deleterious associations with biomarkers of postmenopausal breast cancer risk. We examined the associations of change in sedentary behavior [daily television (TV) viewing time, h/day] over a 5-year period with putative markers of postmenopausal breast cancer risk. The analytic cohort consisted of 1,001 postmenopausal women from the Australian Diabetes, Obesity and Lifestyle (AusDiab) study (1999-2005). Multivariate linear regression models were used to examine associations of change in TV viewing time with biomarkers of the following risk mechanisms: adiposity (body mass index [BMI], waist circumference); metabolic dysfunction (fasting plasma glucose, 2-h plasma glucose, fasting insulin, insulin resistance [homeostasis model assessment of insulin resistance (HOMA-IR)]); and inflammation (high-sensitivity C-reactive protein (hs-CRP)). All analyses were adjusted for age, baseline TV viewing, and potential confounders. Hourly increments of change in TV viewing time were positively associated with BMI (β = 0.50, 95% CI 0.20, 0.81; p = 0.001), waist circumference (β = 1.18, 95% CI 0.49, 1.87; p = 0.001), fasting insulin (β = 38.13%, 95% CI 37.08, 39.20; p = 0.01) and HOMA-IR (β = 37.93%, 95% CI 36.92, 38.98; p = 0.03) in fully adjusted models. Significant associations with BMI, waist circumference, fasting insulin and HOMA-IR were also present in analyses using categories of change in TV viewing time (reduced, same, increased). The findings suggest that increasing habitual sedentary behavior over time could increase breast cancer risk among postmenopausal women. Further investigation into the role of sedentary behavior in breast cancer etiology is warranted.

Differential impact of body mass index on absolute and percent breast density: implications regarding their use as breast cancer risk biomarkers.

Percent breast density (PBD), a commonly used biomarker of breast cancer risk (BCR), is confounded by the influence of non-dense breast tissue on its measurement and factors, such as BMI, which have an impact on non-dense tissue. Consequently, BMI, a potent BCR factor, is, paradoxically, negatively correlated with PBD. We propose that absolute breast density (ABD) is a more accurate biomarker of BCR. We used a volumetric method to compare the correlation between PBD and ABD with baseline demographics and dietary and physical activity variables in a group of 169 postmenopausal women enrolled in a clinical trial prior to any intervention. As expected, a strong negative correlation between PBD and BMI was observed (Rho = -0.5, p < 5e(-12)). In contrast, we observed a strong, previously not well established, positive correlation of BMI with ABD (Rho = 0.41, p < 2.5e(-8)), which supports the use of ABD as a more accurate indicator of BCR. Correction of PBD by BMI did not frequently provide the same information as ABD. In addition, because of the strong influence of BMI on ABD, many correlations between dietary variables and ABD did not emerge, until adjustment was made for BMI. ABD corrected by BMI should be the gold standard BD measurement. These findings identify the optimal measurement of BD when testing the influence of an intervention on BD as a biomarker of BCR.

Melanocytic nevi as biomarkers of breast cancer risk.

report on their number of moles using qualitative categories as follows: ‘‘none,’’ ‘‘a few,’’ ‘‘many,’’ or ‘‘very many.’’ The cohort was followed through 2008; a total of 5,956 incident breast cancer cases were ascertained over nearly 1.4 million personyears. In age-adjusted models, women reporting the most nevi were observed to have 13% higher breast cancer risk than their counterparts without nevi (p for trend=0.04). This association was attenuated and the trend no longer significant when investigators adjusted for benign breast disease or family history of breast cancer. A non-statistically significant increase in breast cancer risk of 8% was observed after adjusting for established breast cancer risk factors and measures of ultraviolet radiation exposure. While their findings are broadly consistent, subgroup findings in the two studies were different. Kvaskoff and colleagues found no significant association in postmenopausal women, but observed that, among premenopausal women, those who had reported ‘‘very many’’ nevi were 34% more likely to be diagnosed with breast cancer compared to counterparts who reported ‘‘none’’ even after adjustment for all potential confounders (p for trend=0.03, p for heterogeneity=0.04). In contrast, Han and colleagues found no significant modification of the risk association by menopausal status. The association between nevi and breast cancer risk is unlikely to be causal. Both melanocytic nevi and melanoma are derived from melanin-producing cells in dermal or epidermal tissues [5]; in contrast, most breast cancers are thought to arise from epithelial cells of ductal or lobular origin [6]. Given their

Global methylation levels in peripheral blood leukocyte DNA by LUMA and breast cancer: a case-control study in Japanese women.

Background:Global hypomethylation has been suggested to cause genomic instability and lead to an increased risk of cancer. We examined the association between the global methylation level of peripheral blood leukocyte DNA and breast cancer among Japanese women.Methods:We conducted a hospital-based case–control study of 384 patients aged 20–74 years with newly diagnosed, histologically confirmed invasive breast cancer, and 384 matched controls from medical checkup examinees in Nagano, Japan. Global methylation levels in leukocyte DNA were measured by LUminometric Methylation Assay. Odds ratios (ORs) and 95% confidence intervals (CIs) for the associations between global hypomethylation and breast cancer were estimated using a logistic regression model.Results:Compared with women in the highest tertile of global methylation level, ORs for the second and lowest tertiles were 1.87 (95% CI=1.20–2.91) and 2.86 (95% CI=1.85–4.44), respectively. Global methylation levels were significantly lower in cases than controls, regardless of the hormone receptor status of the cancer (all P values for trend <0.05).Interpretation:These findings suggest that the global methylation level of peripheral blood leukocyte DNA is low in patients with breast cancer and may be a potential biomarker for breast cancer risk.

Changes in mammographic density over time in breast cancer cases and women at high risk for breast cancer

High mammographic breast density is one of the strongest intermediate markers of breast cancer risk, and decreases in density over time have been associated with decreases in breast cancer risk. Using repeated measures of mammographic density in a cohort of high-risk women, the Women at Risk (WAR) cohort at Columbia University Medical Center (N = 2670), we examined whether changes in prediagnostic mammographic density differed among 85 prospectively-ascertained breast cancer cases and 85 age-matched controls, using a nested case–control design. Median age at first mammogram was 51 years (range, 29–77 years), with a median of 4 years between first and second prediagnostic mammogram (range, 1–15 years). Using linear regression with change in percent density as the outcome, we found that in women who did not go on to be diagnosed with breast cancer, change in percent density decreased as time between first and second mammogram increased (β = −1.62% per year, p = 0.004). However, in women who did go on to be diagnosed with breast cancer, there was no overall change in percent density associated with time between first and second mammogram (β = 0.29% per year, p = 0.61); the change over time was statistically significantly different between cases versus controls (p <0.009). If replicated in larger cohorts, these results suggest that within-individual changes in mammographic density as measured by percent density may be a useful biomarker of breast cancer risk.

Metabolomic characterization of nipple aspirate fluid by (1)H NMR spectroscopy and GC-MS.

Nipple aspirate fluid (NAF) is a noninvasively obtained biofluid from the duct openings of the breast. NAF components are constantly secreted, metabolized, and reabsorbed by the epithelial lining of the lactiferous ducts of the breast. NAF has been studied as a potential breast tissue surrogate for the discovery of novel breast cancer risk, early detection, and treatment response biomarkers. We report the first unsupervised metabolite characterization of nipple aspirate fluid using NMR and GC-MS using convenience samples previously collected from four premenopausal and four postmenopausal women. A total of 38 metabolites were identified using the two analytical techniques, including amino acids, organic acids, fatty acids, and carbohydrates. Analytical reproducibility of metabolites in NAF by GC-MS was high across different extraction and analysis days. Overall, 31 metabolites had a coefficient of variation below 20%. By GC-MS, there were eight metabolites unique to NAF, 19 unique to plasma, and 24 shared metabolites. Correlative analysis of shared metabolites between matched NAF and plasma samples from pre- and postmenopausal women shows almost no correlations, with the exception being lactic acid, which was significantly negatively correlated (R(2) = 0.57; P = 0.03). These results suggest that NAF is metabolically distinct from plasma and that the application of metabolomic strategies may be useful for future studies investigating breast cancer risk and intervention response biomarkers.

Using breast milk to assess breast cancer risk: the role of mass spectrometry-based proteomics.

Although mammography and treatment advances have led to declines in breast cancer mortality in the United States, breast cancer remains a major cause of morbidity and mortality. Breast cancer in young women is associated with increased mortality and current methods of detecting breast cancers in this group of women have known limitations. Tools for accurately assessing personal breast cancer risk in young women are needed to identify those women who would benefit the most from earlier intervention. Proteomic analysis of breast milk could identify biomarkers of breast cancer risk and provide a tool for identifying women at increased risk. A preliminary analysis of milk from four women provides a proof of concept for using breast milk to assess breast cancer risk.