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High mammographic density (MD) is a strong risk factor for breast cancer; however, data on the association between MD and breast cancer subtypes has been inconsistent and most studies have been conducted using data from Western women. Studies have shown that Asian women, who in general have denser breasts compared with Western women, were more likely to develop luminal B and HER2-enriched tumors. We previously reported that higher MD, assessed using Breast Imaging Reporting and Data System (BI-RADS) categories, was associated with HER2-enriched tumors among Chinese breast cancer patients, which may at least partially explain the higher incidence of HER2-enriched tumors observed in Asian women. Since BI-RADS MD measurement is categorical and known to be subjective, in this study, we aimed to re-evaluate the MD-subtype association using an automated quantitative density metric. The analysis included 1,549 women with invasive breast cancer who were diagnosed and treated in a tertiary hospital in Beijing, China. Subtypes were defined as Luminal A (n=606): ER+ and PR+, HER2-, and low Ki-67 ( Citation Format: Xiaohong R Yang, Yuan Tian, Jennifer Guida, Hela Koka, Ariane Chan, Changyuan Guo, Erni Li, Eric Tang, Hyuna Sung, Ning Lu, Nan Hu, Gretchen Gierach, Jing Li. Association between quantitative mammographic density and breast cancer subtypes among Chinese breast cancer patients [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P5-08-20.

Introduction: Mammographic density and family history of breast cancer (FHBC) are independent risk factors for breast cancer. Women with dense breasts have a 4-6-fold increased risk of breast cancer and women with FHBC have a 1.5-3-fold increased risk of breast cancer. However, there is little data on the associations of FHBC with mammographic density, especially in premenopausal women. To address this, we investigated the associations of FHBC in first-degree relatives with mammographic density in premenopausal women. Methods: We used data from 375 cancer-free premenopausal women who were during routine screening mammography at Washington University in St. Louis in 2016. We used Volpara to measure volumetric measures of density including volumetric percent density, dense volume, and non-dense volume. We collected data on first-degree relatives (mother, sister) and numbers of first degree relatives (0, 1, ≥2) with a positive FHBC. We used multivariable linear regression model, adjusted for age, BMI, parity, race, age at menarche, and alcohol consumption, to determine the associations of FHBC and log-transformed volumetric percent density, dense volume, and non-dense volume. Beta coefficients (β) were evaluated and back transformed for easier interpretation. Results: The mean age of participants was 47.5 years (range=32-58). The mean BMI was 30.8 kg/m2 (range =17.9-63.1). Volumetric percent density was 25% (p-value Table 1.Associations of family history of breast cancer (FHBC) and volumetric percent density (VPD), and dense volume (DV) in 375 premenopausal women*.FHBCNVPD (%) DV (cm3 ) Beta (95% CI)P-valueBeta (95% CI)P-valueNo275Ref Ref Yes871.25 (1.12,1.41) Conclusions: Premenopausal women with a first-degree FHBC have higher volumetric percent density. Our findings could help identify high-risk women who may benefit from targeted screening. Citation Format: Han Y, Zong X, Colditz GA, Toriola AT. Family history of breast cancer and mammographic density in premenopausal women [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr P4-10-08.

Background: Increased mammographic breast density decreases the sensitivity and the specificity of mammography screening and is associated with a significant risk factor for breast cancer. No studies were identified that examined the impact of supplemental screening on breast cancer recurrence rates or mortality for women with dense breasts. The aim of this study is to examine factors associating with breast density in Japanese women. Data sources and methods: We used mammography check-up participants (n=5159, women aged 40 years or older) between Apr 2014 and Mar 2017 as our baseline data. Using a self-administered questionnaire, data of life style were collected. Logistic regression was used to estimate the odds of having dense breasts by age, body mass index (BMI), alcohol consumption, smoking, parity, menopausal status, dysmenorrhea, hormone replacement therapy (HRT), family history of breast cancer, physical exercise, fried foods intake, brightly colored vegetables intake, coffee intake, tea intake and bone mineral density. Breast densities were divided into four categories based on BI-RADS classification. BI-RADS 3 and 4 were defined as dense breast. All statistical tests were two-sided. Results: Dense breast accounted for 62.3% of mammography screening participants. Dense breast at an early age was more frequent as 78.0% in the 40's. Alcohol intake (20 g or more a day, OR=1.62, 0.026) in post-menopausal women showed statistically significant positive interaction with dense breast. Weak positive interaction was seen in bone mineral density>80% (OR=0.63, 0.086, n=775). On the other, age (OR=0.97, Conclusion: Dense breast accounted for 62.3% of all participants. Dense breast was more frequent at early age as 78.0% in their 40's. Alcohol consumption and bone mineral density in post-menopausal women were positive interaction with mammographic breast density. On the contrary, age, BMI, number of live birth and post-menopause were negative interaction with mammographic breast density. Citation Format: Uchida K, Ohashi H, Hiroko N, Mimoto R. Factors associated with mammographic density in Japanese women [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P3-10-18.

Background: Women with high breast density have a 4-6 fold increased risk of breast cancer compared to women with low breast density. There is a strong inverse association between body mass index (BMI) and breast density, so we hypothesized that some of the racial/ethnic variation in mammographic density may reflect differences in the prevalence of high BMI or the strength of the association between BMI and mammographic density by race/ethnicity. Methods: We leveraged data from the Utah Population Database (UPDB) mammography cohort, including 140,200 non-Hispanic White (NHW) women, 703 non-Hispanic Black (NHB) women, 15,560 Hispanic women, 713 American Indian/Alaskan Native (AIAN) women, 2,525 Asian women, and 434 Native Hawaiian/Pacific Islander (NHPI) women with a screening mammogram obtained 2005-2019. We estimated the association between BMI and binary mammographic density (BI-RADS A & B versus C & D) using logistic regression adjusted for age, education, and parity in Utah. Menopausal status was not available, so we used age 55 as a proxy. We considered effect modification by running stratified analyses and conducting a likelihood ratio test of models with and without an interaction between BMI and race/ethnicity. We also calculated population attributable risks (PAR%). Results: The prevalence of high BMI differed by race/ethnicity with the highest BMI among NHPI women (29.4% overweight and 52.2% obese) and lowest BMI among Asian women (17.9% overweight and 5.7% obese). Results from multivariable models were consistent with a strong inverse association between BMI and mammographic density (ORBMI>30v≤25=0.21, 95% CI=0.21-0.22, p-trend Discussion: We observed the strongest evidence of racial/ethnic differences in BMI when comparing the two groups most commonly studied together: Asians and NHPIs. While we present only limited evidence to suggest that BMI is differentially associated with breast density by race/ethnicity, differences in the prevalence of high BMI were substantial. Overall, our findings suggest that risk factor prevalence should not be overlooked when evaluating potential contributors to cancer disparities. Citation Format: Mollie E. Barnard, Tarun Martheswaran, Karen Curtin, Jennifer A. Doherty. Body mass index and mammographic density by race and ethnicity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 32.

Introduction: Interval breast cancers present with clinical symptoms following a normal screening mammogram. They are associated with unfavorable biological features and with dense breasts. Models predictive of aggressive phenotypes may facilitate tailored screening for women at elevated risk of interval cancers. Polygenic risk scores (PRS) represent the cumulative effects of multiple single nucleotide polymorphisms (SNPs) and can be used to risk-stratify women. In prior reports, PRS is preferentially associated with screen-detected rather than interval cancers. We investigated methods to refine the PRS to preferentially predict interval cancers, and tested the performance of the PRS in joint models with mammographic breast density (MBD). Methods: We used data from 1058 breast cancer cases from The Cancer Genome Atlas (TCGA) as the discovery set for our PRS. We selected 107 SNPs from genomewide association studies of breast cancer risk for testing against tumor status at last follow-up in TCGA. Presence of tumor indicated recurrence, progression, or positive margins after resection. Women with tumor present at Results: Of 107 SNPs, 23 had suggestive associations with presence of tumor at last follow-up in TCGA. The 23-SNP PRS discriminated between women with interval cancers and controls, with AUROC 0.57 (95% CI 0.51-0.63). With the inclusion of MBD in the model, the AUROC was 0.68 (95% CI 0.62-0.74). Women in the highest PRS quintile had an unadjusted 2.07-fold odds (95% CI 1.05-4.07) of developing interval cancers compared with women in the lowest quintile; adjustment for MBD did not change the point estimate. The PRS also discriminated between women with interval and screen-detected cancers, although the findings did not reach statistical significance (AUROC 0.55, 95% CI 0.48-0.61). With the inclusion of MBD in the model, the AUROC was 0.63 (95% CI 0.57-0.69). Discussion: A PRS associated with presence of tumor at last follow-up was independently predictive of interval cancers relative to controls. Models with PRS and MBD discriminated between interval and screen-detected cancers, although MBD provided most of the predictive power. Our findings are limited by the size and low number of recurrences in TCGA. It is possible that tumor status largely reflects treatment received, and may only partially represent the biological pathways of interval cancers. Our results suggest that SNPs may potentially identify women at risk for developing interval breast cancer, although further validation is required. Citation Format: Shieh Y, Hu D, Huntsman S, Ma L, Gard CC, Leung JWT, Tice JA, Cummings SR, Kerlikowske K, Ziv E. A model with polygenic risk score and mammographic density predicts interval cancers [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P5-09-05.

Background: Incresed mammographic density is a significant risk factor for breast cancer and decreses the sensitivity of mammography screening. The aim of this study is to examine the factors affecting breast density in Japanese women. Data sources and methods: Between Apr. 2014 and Mar. 2016, 3492 women were received mammography screening. According to the results of mammography, breast density was categorized as non-dense(BI-RADS 1 and 2, n=1670) and dense(BI-RADS 3 and 4, n=2222) . Logistic regression was used to estimate the odds of having dense breasts by age, body mass index(BMI), alcohol consumption, smoking, parity, menopausal status, dysmenorrhea, hormone use, family history of breast cancer, physical activity, fried foods intake, brightly colored vegetables intake, coffee intake and tea or green tea intake. All statistical tests were two-sided. Results: There was a statistically significant negative interaction of age(OR=0.97, Results of analysis of factors influencing breast density among all study participants Odds ratio95% CIPAgeContinuoous variables0.970.95-0.98 Results of analysis of factors influencing breast density in women aged ≥55 years (n=1382) Odds ratio95% CIPBMI Conclusion: Alcohol consumption increase mammographic breast density in women aged ≥55 years. As both of increased breast density and alcohol consumption have been suggested to increase risk of breast cancer, more cautious mammographic screening should be considered for those women aged ≥55 years. Citation Format: Uchida K, Ohashi H, Kitano N, Tsunoda K, Nagamatsu T, Sekine C, Imawari Y, Nogi H, Takeyama H. Alcohol consumption increases mammographic density in women aged ≥55 years [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-07-16.

Introduction Mammographic density (MD), created predominantly by increased stromal tissue, is a major risk factor for breast cancer, though little is known about the biological mechanisms mediating it. Tamoxifen prevents breast cancer in a subset of high-risk women via mechanisms that appear dependent on reduction of MD. Animal models suggest tamoxifen remodels the mammary stroma to a tumour-inhibitory phenotype. This study aims to analyse the effect of tamoxifen on human breast fibroblast function and identify pro-tumourigenic pathways contributing to the density-associated risk. Methods Primary human breast fibroblasts from normal, high risk or breast cancer patients were treated with hydroxytamoxifen (100nM-5uM), the active metabolite of tamoxifen. Fibroblast function was analysed by measuring: proliferation, expression of stromal proteins fibronectin and collagen 1; effects on TGF-β signalling via SMAD phosphorylation and upregulation of the myofibroblast marker SMA. Genome wide analysis was performed using RNA-Seq. Significantly deregulated pathways were validated by quantitative real time PCR, western blotting and mass spectrometry. Results Fibroblasts from 25 patients were treated with hydroxytamoxifen. All patients showed reduced proliferation with treatment. 62% of patients showed reduced fibronectin expression. Collagen 1 expression and TGF-β-mediated upregulation of SMA and fibronectin were consistently inhibited by tamoxifen. RNA-Seq analysis revealed downregulation of Wnt signalling, an established pro-fibrogenic and pro-tumourigenic pathway, and other stromal signalling pathways including matrix/receptor interaction, focal adhesion signalling and collagen formation. Intriguingly, there was significant modulation of many metabolic pathways, including components of the microsomal anti-oestrogen binding site (AEBS). Binding of tamoxifen to the AEBS inhibits cholesterol epoxide hydrolase (ChEH) enzyme activity, promoting an anti-tumourigenic phenotype. The effects of tamoxifen on fibroblasts could be replicated using tesmilifene, a commercially available inhibitor of ChEH. Mass spectrometry analysis confirmed an altered cholesterol metabolite profile in the tamoxifen treated fibroblasts. Conclusion These data indicate that tamoxifen can directly remodel the mammary stromal microenvironment, generating a less 'reactive' stroma. Thus, tamoxifen impacts on multiple pathways, many independent of the oestrogen receptor, to create a tumour-inhibitory microenvironment. This offers exciting potential for patient monitoring and alternative breast cancer prevention strategies.Introduction Mammographic density (MD), created predominantly by increased stromal tissue, is a major risk factor for breast cancer, though little is known about the biological mechanisms mediating it. Tamoxifen prevents breast cancer in a subset of high-risk women via mechanisms that appear dependent on reduction of MD. Animal models suggest tamoxifen remodels the mammary stroma to a tumour-inhibitory phenotype. This study aims to analyse the effect of tamoxifen on human breast fibroblast function and identify pro-tumourigenic pathways contributing to the density-associated risk. Methods Primary human breast fibroblasts from normal, high risk or breast cancer patients were treated with hydroxytamoxifen (100nM-5uM), the active metabolite of tamoxifen. Fibroblast function was analysed by measuring: proliferation, expression of stromal proteins fibronectin and collagen 1; effects on TGF-β signalling via SMAD phosphorylation and upregulation of the myofibroblast marker SMA. Genome wide analysis was performed using RNA-Seq. Significantly deregulated pathways were validated by quantitative real time PCR, western blotting and mass spectrometry. Results Fibroblasts from 25 patients were treated with hydroxytamoxifen. All patients showed reduced proliferation with treatment. 62% of patients showed reduced fibronectin expression. Collagen 1 expression and TGF-β-mediated upregulation of SMA and fibronectin were consistently inhibited by tamoxifen. RNA-Seq analysis revealed downregulation of Wnt signalling, an established pro-fibrogenic and pro-tumourigenic pathway, and other stromal signalling pathways including matrix/receptor interaction, focal adhesion signalling and collagen formation. Intriguingly, there was significant modulation of many metabolic pathways, including components of the microsomal anti-oestrogen binding site (AEBS). Binding of tamoxifen to the AEBS inhibits cholesterol epoxide hydrolase (ChEH) enzyme activity, promoting an anti-tumourigenic phenotype. The effects of tamoxifen on fibroblasts could be replicated using tesmilifene, a commercially available inhibitor of ChEH. Mass spectrometry analysis confirmed an altered cholesterol metabolite profile in the tamoxifen treated fibroblasts. Conclusion These data indicate that tamoxifen can directly remodel the mammary stromal microenvironment, generating a less 'reactive' stroma. Thus, tamoxifen impacts on multiple pathways, many independent of the oestrogen receptor, to create a tumour-inhibitory microenvironment. This offers exciting potential for patient monitoring and alternative breast cancer prevention strategies. Citation Format: Ironside A, Hawkesford K, Gomm J, Haywood L, Goulding I, Wang J, Lamaziere A, Poirot M, Silvente-Poirot S, Chelala C, Jones JL. Molecular mediators of mammographic density [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P4-15-04.

Background: Stratified breast cancer (BC) prevention is a major option for the future but requires clinically meaningful internationally validated risk models. Non parametric models may be alternate methods for modeling in very large cohorts. We have previously shown that a non-parametric similarity-based k-nearest neighbors' (kNN) model performs better than the BCRAT/Gail model to on 65 000 women of the E3N French national cohort (Dartois et al 2015). We used this method to develop and validate a mammographic density-based model in larger general screening populations (pops). Methods: A modified version of a data-mining based algorithm, the kNN method, was implemented and adapted as previously described [ref Dartois]. Core concept of kNN algorithm is to gather similar profiles using a distance computation. We developed a BC risk prediction model on 629 229 women (wn) from the US Breast Cancer Research Consortium (BCSC), with 5 times random selection of learning and validation sets (75/25 %) within the cohort. 5 parameters were included: age, family history, previous breast biopsy, mammographic density and race. The model's performances (discrimination using c-stat (AUC) and calibration using E/0 ratio) were evaluated and compared to the parametric model developed on the same pop (param/BCSC)(Tice et al 2008). This kNN/BCSC model was then tested on two French screening pops after adjustment on French BC incidence: an urban area (Paris suburbs, N=316 775) and a rural area (Côte d'Or, N=32 930). Its performances were compared to those of a model directly developed (same methods) on the Paris cohort (kNN/Paris). Levels of individual risks assessed by the models were assigned into 4 risk categories. The sensitivity of the models was defined as the number of wn who had BC whose 5 yrs-risk category was intermediate (median risk at 50-yrs - 1.66%), high (> 1.66%) or very high (> 20% lifetime) divided by the total number of wn who had BC. Results: The performances of the different models are shown in Table 1. The kNN model developed on BCSC performed well (c-stat 0.653 and E/0 1.001). It had equivalent performances as the parametric model developed previously on the same pop. This kNN/BCSC had a good discrimination on French pops, although slightly lower than that on US pops. This is expected since French screening starts at 50 (vs 40 in BCSC) and French parameters do not include race. The calibration of such model was excellent on Paris, while it overestimated the risk on Côte d'Or, in which BC incidence is lower. It performed as well as the kNN/Paris model directly developed on Paris' pop. The sensitivity of the kNN/BCSC on US and French pops was good. Conclusions: A new non parametric kNN breast cancer risk model developed on an American screening cohort (BCSC) was successfully validated on two French screening cohorts. This new international model could allow stratified prevention. Performances of the models Param/BCSC on BCSCParam/BCSC on PariskNN/BCSC on BCSCkNN/BCSC on PariskNN/BCSC on Cote d'OrkNN/Paris on ParisN629 229313 817629 229313 81732 930313 817c-statistic0.6580.6020.6530.6020.5930.605E/0 global1.031.071.0011.061.521.00Sensitivity--76.18%72.87%72.58%- Citation Format: Ragusa S, Gauthier E, Dartois L, Tice J, Dancourt V, Arveux P, Brixi Z, Bernoux A, Soyer P, Delattre H, Brechenade S, Catajar N, Kaufmanis A, Hélin VM, Clavel F, Kerlikowske K, Miglioretti D, Delaloge S. Development and validation of a new non-parametric breast cancer risk assessment model on US and European screening populations [abstract]. In: Proceedings of the 2016 San Antonio Breast Cancer Symposium; 2016 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2017;77(4 Suppl):Abstract nr P2-06-05.

It is now possible to prevent many breast cancers inhigh-risk women using anti-estrogen hormonal drugs. Several Phase III breast cancer preventiontrials demonstrated that hormonal drugs such as the “selective estrogenreceptor modulators” tamoxifen and raloxifene, and aromatase inhibitors preventthe development of 50% of ER-positive breast cancers in women. However, mostwomen at high risk of breast cancer do not use these cancer preventive drugsdue to concerns about their side effects. To overcome this problem, recent studies havefocused on testing novel approaches for the prevention of breast cancer. Results of preclinical and clinical studiestesting targeted drugs and vaccines for breast cancer prevention show that itis possible to prevent breast cancer with reduced toxicity. Studies seeking to prevent all forms ofbreast cancer, including ER-positive, HER2-positive, and “triple-negative”breast cancer, will be presented and discussed. Novel approaches testing targeted therapies including signalinginhibitors, combinations of preventive agents, and vaccines, will be presented. Many of these interventions prevent breastcancer in animal models, and are now being tested in human clinicaltrials. Results from studies testing novel drugdelivery approaches will also be discussed. Topical gels containing anti-estrogen drugs are being used to reducebreast cell growth and mammographic density in Phase II clinical trials. This topical approach has the potential toprevent ER-positive breast cancers without the toxicity of oral hormonaldrugs. All of these novel preventive measuresoffer great promise to effectively prevent all forms of breast cancer withminimal toxicity. Citation Format: P Brown. Beyond Hormones: Newer Pharmacologic Approaches [abstract]. In: Proceedings of the 2020 San Antonio Breast Cancer Virtual Symposium; 2020 Dec 8-11; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2021;81(4 Suppl):Abstract nr SP020.

Background: Mammographic density (MD) is an independent risk factor for breast cancer, but whether chemoprevention can modify this risk biomarker is unknown. MD naturally declines with age, particularly after menopause. Prior studies have shown a significant decrease in MD with tamoxifen correlated with decreased breast cancer incidence, however, other anti-estrogens, such as aromatase inhibitors (AIs) and raloxifene, have not shown significant effect. No studies have examined the long-term effects (>24 months) of chemoprevention on MD. Methods: We conducted a retrospective cohort study of high-risk women seen at an academic breast center. Patients were considered to be at high risk for breast cancer and eligible for chemoprevention if they had a 5-year predicted breast cancer risk according to the Gail model of ≥1.67%, atypical ductal or lobular hyperplasia, history of ductal or lobular carcinoma in situ, and/or BRCA mutation. We collected demographic, breast cancer risk factor, and clinical data, including prior or current anti-estrogen use, type of anti-estrogen, and duration of use, from a self-administered questionnaire and medical chart review. We dichotomized anti-estrogen use as ever/never. One reader measured MD from digital images using a semiautomated computer-assisted technique with Cumulus software. MD was determined for a baseline mammogram (within 6 months of starting an anti-estrogen), a short-term follow-up (12-24 months) and/or a long-term follow-up (48-60 months) mammogram. We conducted multivariable logistic regression models to assess the association between change in MD over time with and without anti-estrogen use for chemoprevention. Results: Of 190 evaluable women, 86 (45%) women took an anti-estrogen (53 tamoxifen, 25 raloxifene, 4 AI, 4 multiple anti-estrogens) and 104 (55%) did not. Compared to women who did not take an anti-estrogen, those who took chemoprevention were more likely to be older (age 56 vs. 53 years), postmenopausal (65% vs. 51%), have a higher body mass index [BMI] (28.2 vs. 26.8 kg/m2), and had a lower mean baseline MD (12.7% vs. 15.9%). Comparing high-risk women who initiated anti-estrogens to those who did not, mean absolute short-term change in MD (SD) was -0.249% (SD 6.22) vs .057% (10.16) and mean long-term change in MD was -3.25% (8.25) vs. -4.19% (11.98), respectively. There was no significant short-term change in breast density with chemoprevention; however, women who took chemoprevention were 4 times more likely to have at least a 5% decrease in breast density compared to those who did not take chemoprevention after adjustment for age, menopausal status, and baseline MD (OR=4.14, 95% CI=1.03-16.73). Discussion: Among high-risk women who initiated anti-estrogens, we did not observe a significant short-term change in MD, but chemoprevention uptake was associated with a significant decrease in MD with long-term follow-up. Our data suggests that short-term changes in MD with chemoprevention may be too small to be detected by current methods, therefore other risk biomarkers may be needed to assess short-term response to anti-estrogens. Citation Format: Namburi S, Coe AM, Thomas P, Hershman D, Sandoval R, Maria A, Crew KD. Effect of chemoprevention uptake on mammographic density over time in women at high risk for breast cancer. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-10-09.

Introduction Elevated mammographic density (MD) is a strong and independent risk factor for breast cancer, though underlying mechanisms are unclear. Prior studies have suggested that increased cumulative exposure to sex-steroid hormones and growth factors may impact both MD and MD-related breast cancer risk; however, most studies have only evaluated individual hormones. In this study, we simultaneously explored the relationship between 29 circulating hormones and growth factors with MD among postmenopausal women undergoing diagnostic breast biopsy. Methods We used data from 89 postmenopausal women, aged 44-65, who had complete measurements of 29 serum hormones from a single pre-biopsy blood draw (i.e., sex-steroid hormones: 15 estrogen/estrogen metabolites, 7 progesterone/progesterone metabolites; and non-sex hormones: insulin-like growth factor I and binding proteins (IGFBPs) 2-7). Volumetric MD (% fibroglandular volume) was assessed in pre-biopsy digital mammograms using single X-ray absorptiometry. Sufficient dimension reduction methods were used to compute a composite marker score that accommodates correlations among hormones and their relationship to MD. Backward elimination was applied to select log-transformed hormones contributing to the score at α=0.05; multivariable linear regression was used to further examine associations between selected hormones and MD within a single model, adjusting for age and BMI. Results Pearson correlations between hormones were moderate-to-strong. Dimension reduction methods identified 6 hormones as associated with MD (pmedian vs. ≤median); BMI was consistently identified as the most significant predictor of MD (P Conclusions We identified 6 out of 29 correlated hormones that were significantly associated with MD among postmenopausal women. For several, the directions of their associations with MD were comparable to those observed in prior studies that have separately evaluated these hormones in relation to breast cancer risk. We plan to further explore how circulating hormones concurrently affect MD in premenopausal women, accounting for menstrual cycle phase. Incorporation of dimension reduction methods in studies of multiple correlated hormones can help uncover new etiologic insights into the role of hormones and growth factors in MD and breast carcinogenesis and inform strategies for prevention. Citation Format: Shaoqi Fan, Ruth M. Pfeiffer, Manila Hada, Roni T. Falk, Maeve Mullooly, Hannah Oh, Berta Geller, Pamela Vacek, Donald Weave, John Shepherd, Jeff Wang, Sally Herschorn, Louise A. Brinton, Xia Xu, Mark E. Sherman, Britton Trabert, Gretchen L. Gierach. Associations of circulating hormones with mammographic density in postmenopausal women referred to diagnostic breast biopsy [abstract]. In: Proceedings of the Annual Meeting of the American Association for Cancer Research 2020; 2020 Apr 27-28 and Jun 22-24. Philadelphia (PA): AACR; Cancer Res 2020;80(16 Suppl):Abstract nr 3488.

Introduction: Mammographic density (MD) has been reported to be associated with increased risk of breast cancer development. In addition, the association of MD with breast cancer subtypes has been proposed in Caucasian breast cancer patients but this has remained virtually unknown in Asian patients. Therefore, in this study, we retrospectively examined the subtypes and clinical prognosis in Japanese cancer patients according to their MD. Method: We retrospectively examined 781 mammograms of breast cancer patients from March 2013 to March 2016 at Nahanishi Clinic, Okinawa, Japan. In this study, MD was tentatively classified according to the recommendation of the Japanese Central Organization on Quality Assurance of Breast Cancer Screening, based on the proportion of fat area as follows; (a) extremely high dense:10-20%, (b) heterogeneously dense:40-50%, (c) scattered fatty:70-90%, (d) fatty: almost all the breast fat. “Dense breast” includes extremely high and heterogeneous dense. We also evaluated the rates of recurrence and breast cancer specific death according to MD defined as above. The status of breast cancer subtypes was also compared between dense and non-dense breasts, and between pre-menopausal and post-menopausal women. Result: Among 781 cases examined, 365 were classified as dense breasts and 416 as non-dense breasts. The median age of all the patients examined was 57 years old. The age was significantly younger (50.4 vs 63.4 years old P Citation Format: Naoko Takigami, Kentaro Tamaki, Yoshihiko Kamada, Kano Uehara, Seiko Tsuchiya, Shigeharu Terukina, Takanori Ishida, Minoru Miyashita, Keely May McNamara, Hironobu Sasano, Nobumitsu Tamaki. A study of clinical outcome and biomarker profiles of Japanese breast cancer patients according to mammographic density [abstract]. In: Proceedings of the 2019 San Antonio Breast Cancer Symposium; 2019 Dec 10-14; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2020;80(4 Suppl):Abstract nr P6-01-01.

There are increasing attempts to try to stratify cancer risks to enable more targeted early detection and prevention strategies and in particular to balance the risks and benefits of population screening for breast cancer. An increasing number of common genetic variants called Single Nucleotide Polymorphisms (SNPs) have been identified which alter breast cancer risk. Although individually their effect sizes are small they can be used multiplicatively to provide a polygenic risk score (PRS) that accurately predicts risk in both the familial and population setting. Although the first 18 SNPs produce a highly calibrated PRS that is ready for use there are now PRSs of 143 or even 313 SNPs that increase risk stratification although with some loss of calibration. Using data from 9362 women in the Predicting the Risk Of Cancer At Screening (PROCAS) study (500 prospective cancers) and 2000 women in the FH-Risk familial cohort (500 prospective cancers) we have validated the PRS alongside mammographic density (density residual-DR) and standard risk factors to assess future risk of different types of breast cancer. The combined score accurately predicts breast cancers rates with 18-21% of women being predicted in the moderate or high risk categories (≥5% 10 year risk) that developed 41.5-45% of the stage 2+ cancers. In contrast SNP143 is able to identify alongside density and standard risk factors 21% of the general population at Conclusions: A combined approach using Tyrer-Cuzick, mammographic density and a PRS provides accurate risk stratification not only overall but also for worse prognosis cancers. This provides support for reducing screening intervals in the high and increasing them in the low risk groups. It is high time these highly informative tests were used in risk stratification Citation Format: Evans D. Polygenic risk scores for breast cancer: Ready or not? [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr CS1-1.

Background: While mammographic density is linked to increased breast cancer risk, limited yet conflicting data exists on an association between density and developing specific molecular subtypes of breast cancer. Methods: Eligible patients were enrolled in a larger study on breast density, diagnosed with cancer between 2003-2013, and had pathology and films available for review. Density was classified qualitatively from existing radiology reports according to Breast Imaging Reporting and Data System (BIRADS) classification and quantitatively by volumetric breast density measurements using Volpara SolutionsTM software. Subtype was assigned by hormone receptor status, tumor grade and mitotic score (MS). Subtype categories included: Luminal A (ER/PR + & grade 1; ER/PR + & grade 2 & MS=1; ER+/PR- & grade 1); Luminal B (ER+ & grade 3 or MS=3; ER+/PR- & grade 2; ER/PR + & grade 2 & MS=2); Her-2 + (ER+ or ER - & Her-2 +); Triple Negative (ER/PR-, Her-2 -). Relevant pre-cancer factors including patient age, race, BMI, family history of breast cancer, and biopsy showing LCIS were included in analysis. Results: Of 604 patients with invasive cancer, 457 had sufficient information for analysis. Among these, 233 (51%) had Luminal A, 79 (17%) Luminal B, 59 (13%) Her-2 +, and 86 (19%) Triple Negative tumors. Younger women and those with denser breasts based on quantitative measurements were more likely to have Her-2+ tumors (Table 1); this association was not seen using the standard BIRADS classification. Triple Negative tumors were less common in patients with LCIS and more common in African Americans. A multinomial logistic regression model controlling for pre-cancer patient factors demonstrated that while quantitative breast density does not significantly differentiate between all molecular subtypes (p=0.140), the association between Her-2+ tumors and denser breasts using continuous quantitative measurements is significant (p=0.035). Conclusion: Women with denser breasts by continuous-scaled quantitative measurements are at higher risk for Her-2+ tumors; an association not delineated using standard BIRADS density classification. Delineating risk factors specific to molecular breast cancer subtype may promote individualized risk prediction models and prevention strategies. Table 1. Association between patient factors and molecular breast cancer subtype Molecular SubtypeVariableLuminal ALuminal BHer-2+Triple NegativeP value (n=233)(n=79)(n=59)(n=86) Age (median,IQR)61 (54,70)58 (50,67)54 (46,70)59 (48,67)0.006BMI (median,IQR)27.1 (22.9,30.5)25.7 (23.0,30.0)26.0 (22.7,32.6)28.1 (24.3,32.6)0.173Volpara density (median,IQR)7.18 (4.74,11.25)8.68 (5.68,14.34)10.25 (5.96,16.51)7.00 (4.97,11.89)0.002BIRADS density (n,%)0.183 Fatty42 (18.0%)15 (19.0%)5 (8.5%)16 (18.6%) Scattered103 (44.2%)27 (34.2%)20 (33.9%)36 (41.9%) Heterogeneous74 (31.8%)30 (38.0%)25 (42.4%)26 *30.2%) Extreme14 (6.0%)6 (7.6%)9 (15.2%)7 (8.1%) Unspecified01 (1.2%)01 (1.2%) Race (n,%)0.002 Caucasian202 (86.7%)65 (82.3%)51 (86.4%)61 (70.9%) African American23 (9.9%)13 (16.5%)6 (10.2%)23 (26.7%) Other2 (0.9%)02 (3.4%)0 Unspecified6 (2.6%)1 (1.2%)02 (2.3%) LCIS (n,%)48 (20.6%)8 (10.1%)8 (13.6%)5 (5.8%)0.004Family history of breast cancer (n,%)107 (45.9%)34 (43.0%)21 (35.6%)39 (45.35%)0.625 Citation Format: Brandy L Edwards, Kristen A Atkins, George J Stukenborg, Wendy M Novicoff, Krista N Larson, Wendy F Cohn, Jennifer A Harvey, Anneke T Schroen. Association of mammographic density and molecular breast cancer subtype [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 P2-04-04.

Background: A reduction in mammographic density(MD) has been associated with the reduction in breast cancer risk among those taking tamoxifen. Aromatase inhibitors (AIs) show promise for breast cancer prevention in postmenopausal women. We are conducting a phase II trial of exemestane in women at increased risk for breast cancer. The primary endpoint for this study is change in MD. Methods: Subjects were screened and enrolled at two sites: Center for Cancer Research, National Cancer Institute and Lombardi Comprehensive Cancer Center, Georgetown University Hospital. Eligible participants are at increased risk for breast cancer by virtue of: Gail model risk ≥1. 7% over 5 years; high risk pathological lesion (e.g. lobular neoplasia, ductal carcinoma in situ); known BRCA1/2 deleterious mutation or prior stage I/II breast cancer at least 2 years from breast cancer treatment and not treated with AIs. Women were excluded if AP spine T-score was Results:For the 22 subjects included in this analysis 15 were eligible due to a high risk pathological lesion, 4 by Gail Model and 3 by prior breast cancers. 18 had film screen mammograms at baseline and 12 months, 4 had film screen mammograms at baseline and digital mammogram at 12 months. Mammographic density declined 7% (p=0.0006, 95% CI −11% to −3%) at one year. The change in MD ranged from −26% to +14% and the standard deviation was 9%. In regard to the four subjects who had film screen mammograms at baseline and digital at follow up, the baseline percent dense areas were slightly higher than average but this did not reach statistical significance (p=0.32 by the Wilcoxon rank sum test). The 12 month MD comparison was similar to the 18 subjects with film images (p=0.90). Conclusions: Exemestane use was associated with a statistically significant decrease in MD at one year. Prior evaluations of AI therapy in high risk women have not shown a significant decline in MD, however time on treatment was shorter and other third generation AIs were used. Although the number of subjects is small, MD did not differ significantly between film screen and digital mammograms. We will further evaluate change in MD in the entire cohort at 1 and 2 years and between film screen and digital mammography. Phase III trials are on-going to evaluate the effect of exemestane on breast cancer prevention. Citation Information: Cancer Res 2010;70(24 Suppl):Abstract nr P1-07-03.

Background: Higher mammographic breast density is a strong risk factor for breast cancer. Early-life factors may influence breast development and subsequent breast density in adulthood. Although childhood adiposity is inversely associated with breast cancer risk, the association of childhood adiposity with mammographic breast density in premenopausal women has not been adequately studied. This knowledge could provide insight into pathways linking mammographic density and breast cancer risk. We investigated the associations between adiposity at age 10 and mammographic density. Methods: We collected data from 370 premenopausal women during their routine screening mammograms at Washington University in St. Louis, MO from December 2015 to October 2016. Body size at age 10 was self-reported using the Stunkard 9-figure Somatotype pictogram. For these analyses, the Stunkard pictogram was collapsed into 4 groups: (i) body size 1 or 2, (ii) body size 3 or 4, (iii) body size 5, (iv) body size 6 or higher. Body mass index (BMI) at age 10 was imputed using BMI and Stunkard data from the Growing Up Today Study. Trained personnel collected womens' height and weight, which were used to calculate current BMI. We used the Volpara software to evaluate the following volumetric mammographic density measures: volumetric percent density (VPD), dense volume (DV) and non-dense volume (NDV). Age-adjusted Pearson correlations and multivariable linear regression models (adjusted for age, age at each given birth, family history, race, education, oral contraceptive use, and breast feeding history) were used to evaluate the associations between adiposity at age 10 and volumetric mammographic density measures. Results: The mean age at the time of screening mammogram was 47.1 years. The majority of the women (43.8%) reported having body size 1 or 2, followed by body size 3 or 4 (34.9%), body size 5 (13.8%) and body size 6 (7.6%) at age 10. We observed a negative correlation between BMI at age 10 (r= -0.28, p-value Conclusions: Our findings of an inverse association between adiposity at age 10 and percent density suggest that adiposity at age 10 could impact breast cancer development via its effect on mammographic density. Mechanistic studies to understand how childhood adiposity reduces mammographic density and breast cancer development in premenopausal women are needed. Citation Format: Alimujiang A, Imm KR, Appleton CM, Colditz GA, Berkey CS, Toriola AT. Adiposity at age 10 and mammographic density among premenopausal women [abstract]. In: Proceedings of the 2017 San Antonio Breast Cancer Symposium; 2017 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2018;78(4 Suppl):Abstract nr P4-01-01.

Background: High percent mammographic density (MD), which reflects the relative fibroglandular tissue content of the breast, is one of the strongest breast cancer risk factors; however, the pathologic mediators of this risk are unknown. We hypothesize that analysis of breast tissue sections using deep learning approaches may characterize histologic features that underpin risk associated with high MD. Methods: Non-targeted H&E stained breast tissue sections of diagnostic image-guided breast biopsies were evaluated among 588 women enrolled following an abnormal mammogram in the Breast Radiology Evaluation and Study of Tissues (BREAST) Stamp Project (2007-2010). Overall volumetric percent MD for the biopsied breast and localized volumetric percent MD surrounding the biopsy site were determined for each participant. A deep convolutional neural network (CNN) model was trained to identify and quantitatively assess breast epithelial, stroma and fat tissue and their organizational and spatial arrangements. Least absolute shrinkage and selection operator (Lasso) regression was used to determine relationships between MD measures and pathological features. To ensure reliability of the model, a cross-validation strategy was employed to build and assess the performance of the fitted model. Finally, Spearman correlation coefficients were estimated to test the association between the predicted density values by each model (predicting overall or localized MD) and the actual MD measurements. We report the average and standard deviation (SD) of the correlation coefficients. Results: In an independent validation set, the CNN model was 95.5% accurate in classifying epithelial, stromal and fat tissue. The mean (SD) correlations between the predicted model and the actual measurements for overall and localized MD were 0.70 (0.06) and 0.65 (0.06) respectively. The amount of stroma identified (normalized to tissue area) had the highest selection probability (P-value) by the Lasso model and thus the strongest positive relationship with MD (P-value >0.9 for each MD measurement). In contrast, the amount of normalized epithelial tissue was not related to MD (P-value=0.01 for each MD measurement). No association was observed for the total normalized fat area with MD (P-value Conclusions: These results show that greater stromal tissue amount and spatial distribution patterns of epithelial regions, rather than total epithelial amounts, had the strongest relationships with elevated MD. Future work will determine the relationship of these MD features with biopsy diagnosis. Citation Format: Maeve Mullooly, Babak Ehteshami Bejnordi, Maya Palakal, Pamela M. Vacek, Donald L. Weaver, John A. Shepherd, Bo Fan, Amir Pasha Mahmoudzadeh, Jeff Wang, Jason M. Johnson, Sally D. Herschorn, Brian L. Sprague, Ruth M. Pfeiffer, Louise A. Brinton, Mark E. Sherman, Andrew Beck, Gretchen L. Gierach. Application of convolutional neural networks to breast biopsies to uncover tissue correlates of mammographic breast density [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4235. doi:10.1158/1538-7445.AM2017-4235

Background: Body mass index (BMI) is inversely associated with mammographic density among postmenopausal women, but few studies have evaluated this in premenopausal women. Further, there is limited data on the associations of weight change during adulthood with mammographic density. To address these, we investigated the associations of current adiposity measures, BMI at ages 18, 30, and changes in BMI at these age periods with volumetric mammographic density measures in 314 premenopausal women who underwent screening mammogram at the Breast Health Center, Washington University in St. Louis, MO. Methods: Study participants completed a questionnaire with information on breast cancer risk factors. Weight at ages 18 and 30 were self-reported. Current weight, height, waist, and body fat percent (%), were assessed by trained research personnel. BMIs were calculated as weight at each age/current height squared (kg/m2). We calculated weight change from; (i) age 18 to 30, (ii) age 18 to current age, (iii) age 30 to current age. Volpara was used to determine volumetric mammographic density measures. We investigated age-adjusted correlations between adiposity measures and mammographic density measures using Pearson correlation coefficients. We used multivariable linear regression models (adjusted for age, age at menarche, parity, age at each birth, family history of breast cancer, race, and education) to evaluate the associations of adiposity measures with mammographic density measures. Results: All adiposity and weight change measures were significantly inversely associated with percent density (PD), and positively associated with breast volume (BV). The strongest inverse correlations with PD were observed for body fat % (r= -0.68, P25kg to those who had stable weight (gained between 0-5kg) during this period. Conclusions: Weight gain in early adulthood is associated with reductions in PD and increases in BV in premenopausal women. Our findings highlight the need for mechanistic studies focusing on early adulthood to provide a better understanding of how adiposity relates to mammographic density, and possibly breast cancer development in premenopausal women. Citation Format: Aliya Alimujiang, Graham Colditz, Catherine Appleton, Adetunji T. Toriola. Adiposity, change in adiposity during adulthood and mammographic density in premenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr 4248. doi:10.1158/1538-7445.AM2017-4248

Percent mammographic density (PMD) is a risk factor for estrogen receptor (ER)-positive and ER-negative invasive breast cancer (BC). Gene expression profiling has identified molecular signatures that classify invasive BC into distinct subtypes that vary in their clinical behavior, response to treatment and likely, etiology. Immunohistochemical (IHC) staining of tumor sections using antibody panels can be used to classify these ‘intrinsic’ molecular subtypes. We evaluated whether density measures [PMD, absolute dense area (DA) and non-dense area (NDA)], are associated equally with all ‘intrinsic’ molecular subtypes. Pooled analysis of six cohort or case-control studies included 3492 women with invasive BC and 10,148 without, who underwent screening mammography a median 4 years prior to diagnosis (for cases). PMD, DA, and NDA were assessed from digitized film-screen mammograms using a computer-assisted thresholding technique, and categorized as 0-10%, 11-25%, 26-50% and 51%+ (PMD) or into quartiles (DA and NDA). Receptor status was abstracted from pathology records and supplemented by IHC staining. We classified tumors as Luminal A (ER+ and/or PR+ and HER2- and grade 1 or 2), Luminal B (ER+ and/or PR+ and HER2+ or Luminal A and grade 3), HER2 expressing (HER2+/ER-/PR-) and triple negative (TN) (ER-/PR-/HER2-). For TN, we also differentiated basal-like tumors (positive for EGFR and/or CK 5/6) from unclassified (negative on both markers). We used polytomous logistic regression to calculate the odds ratio (OR) of each ‘intrinsic’ subtype of BC by categories of PMD, DA or NDA, adjusting for age, body mass index and study. We tested for statistical heterogeneity of associations by subtype. Of 3492 invasive BC cases, 2217 (63%) were classified as Luminal A, 747 (21%) as Luminal B, 159 (5%) as HER2 expressing, and 369 (11%) as TN. Of TN, 203 were evaluated for CK 5/6 and EGFR, with 167 (82%) classified as basal-like and 36 (18%) unclassified. PMD was associated with BC risk across all subtypes. For Luminal A, compared to women with 11-25% PMD (reference), women with 0-10% had a reduced risk of BC (OR = 0.63 [95% confidence interval: 0.55, 0.74]) while women with 26-50% had an OR = 1.5 [1.3, 1.7] and women with 51%+ had the highest risk, OR = 2.3 [2.0, 2.7]. Similar BC associations were seen across PMD categories when comparing the five subtypes (P-heterogeneity = 0.63). Similar trends were seen for DA and BC across the five subtypes (P-het = 0.25). NDA was inversely associated with BC across subtypes, and there was suggestion of a stronger inverse trend among HER2-expressing BC compared to other subtypes (P-het = 0.09). Our results suggest mammographic density measures are associated with all ‘intrinsic’ molecular subtypes. However, NDA may be more strongly inversely associated with HER2-expressing than other subtypes. Understanding the importance of density measures for BC subtypes has significance for subtype-specific risk models. Citation Format: Aaron D. Norman, Rulla M. Tamimi, Christopher G. Scott, Kimberly A. Bertrand, Matthew R. Jensen, Daniel W. Visscher, Fergus J. Couch, John Shepherd, Bo Fan, Yunn-Yi Chen, Lin Ma, Andrew Beck, Vernon S. Pankratz, Karla Kerlikowske, Celine M. Vachon. Association of mammographic density measures and breast cancer ‘intrinsic’ molecular subtypes. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2593.

Mammographic density is one of the strongest risk factors for breast cancer. The most widely used measure of mammographic density is based on the percentage of dense tissue on a mammogram (percent mammographic density). However, there is additional information in mammographic images not captured by current mammographic density measurements including heterogeneity in patterns of breast density, often referred to as ‘texture’. More recent research suggests that textural features on a mammogram are associated with breast cancer risk independent of percent mammographic density. Therefore, we evaluated an automated measure called V, which measures the grayscale variation within a mammogram, in relation to subsequent breast cancer risk in 834 breast cancer cases (426 premenopausal and 408 postmenopausal) and 1805 controls (978 premenopausal and 827 postmenopausal) from a nested case-control study of breast cancer in the Nurses’ Health Studies (NHS). Among all women, V was modestly correlated with percent mammographic density (r = 0.48, p Citation Format: Megan Rice, Kimberly Bertrand, John Heine, Bernard Rosner, Rulla Tamimi. Texture variation on a mammogram and risk of breast cancer. [abstract]. In: Proceedings of the 107th Annual Meeting of the American Association for Cancer Research; 2016 Apr 16-20; New Orleans, LA. Philadelphia (PA): AACR; Cancer Res 2016;76(14 Suppl):Abstract nr 2595.

Introduction: mammographic density is a strong risk factor for breast cancer and an essential determinant of screening sensitivity, but the breast density of Japanese women has yet to be objectively examined. Single mammographic examination fails to detect approximately half of breast cancers in women with dense breasts. We objectively evaluated mammographic density to clarify the relation between breast density and incidence of breast cancer in Japanese women. Method: We enrolled 269 patients diagnosed with breast cancer and 397 healthy controls, who participated in screening mammography at Showa University Hospital. Breast density was measured using Volpara (a software application which analyses breast composition volumetrically). Results: The average age of both control and breast cancer groups was 55. Of the control group, 308 (78%) were characterized as having dense breasts, being defined as volumetric density grade (VDG) 3 or 4. More than 50% of the total population (all ages) had dense breasts (VDG 3 or 4) and more than 20% were extremely dense (VDG:4). Of the breast cancer patients, 232 (87%) were VDG 3 or 4. 52 (23%) of those with dense breasts showed negative results in single mammography examination. In primary breast cancer patients with dense breasts, 30% of those under age 70, but only 13% of those over age 70, showed no abnormal findings from mammographic examination. Conclusion and Discussion: In comparison of our present results and other papers, In the Japanese control group, 72% of patients had dense breasts (VDG 3 or 4) at age 50 or greater, but in Holland, for example, only 36% of women had breasts classed as dense. 87% of Japanese women with breast cancer had dense breasts, approximately the same ratio (88%) as found in Korea. For Japanese and other Asians, women under 70 years old with dense breasts may warrant additional screening. Citation Format: Sawada T, Ikeda M, Kuwayama T, Akashi ST, Nakamura S. Digital measurement of mammographic density and the risk of overlooking cancer in Japanese women. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P4-01-03.

There is some evidence that women with a higher number of CAG repeat lengths on the androgen receptor (AR) gene have increased breast cancer risk. We evaluated the association between AR-CAG repeat length and mammographic density, a strong breast cancer risk factor, in 404 African-American and Caucasian breast cancer patients. In postmenopausal estrogen progestin therapy users, carriers of the less active AR-CAG had statistically significantly higher mean percentage of density (41.4%) than carriers of the more active AR-CAG (25.7%; P = 0.04). Our results raise the question of whether the number of AR-CAG repeats predicts breast cancer risk in estrogen progestin therapy users.

Several options are now becoming available for preventive therapy in women at increased risk for breast cancer. A major challenge is to determine which women are at sufficiently high risk to warrant treatment, and who will benefit from such treatment. Standard risk factors have been combined in several models to develop a risk score, and the spread in 10-year risk associated with these models will be examined. Two new features which offer improved prognostic discrimination are breast density and SNP profiles. The former can be routinely read visually, but there is a substantial inter-reader variability, and a goal is to develop automated testing which is reproducible and highly prognostic for risk. SNP profiles consist of panels (now over 70) of low risk but common genes that individually are not useful, but as a panel may add useful information. A discussion of the relative amount of information in classic models, mammographic density, and SNP scores will be presented along with initial estimates of their combined utility. Lastly we look at markers which may be able to predict response to endocrine prophylactic treatment. Currently change in breast density offers the most promise in this arena. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr ES02-2.

Background: Mammography density reflects the number of stromal and epithelial and one of strongest risk of BC. Estrogen plays an important role in the occurrence of breast cancer through a mechanism of proliferation and genotoxic effects. Action of estrogen on breast tissue by binding to estrogen receptors. The main estrogen receptor α is coded as ESR1 gene. The most studied variants in this gene are the PvuII and XbaI polymorphisms, which have been associated to lower sensitivity to estrogen. Objective: To determine the proportion of genetic variation ESR1 XbaI and PvuII in Javanese ethnic woman in Yogyakarta, Indonesia and to study the correlation between genetic variations in these genes with mammogram density based on quantitative methods. This reaserch to be used as preventive measures for the development of genetic marker breast cancer risk associated with the density of mammography for younger women who have not entered the age to undergo mammography and can be useful as a reference for evaluation of anti estrogen therapy. Method: Conducted digitizer mammogram density assessment using quantitative rating system based on computer-assisted methods of measurement with cumulus program based on interactive thresholding. Polymorphism identification ESR1 XbaI and PvuII RFLP obtained through PCR process. The numbers of genotyped cases and controls for each marker were 50 cases and 58. Mean of density and frequencies of SNPs were compared between cases and controls to identify SNPs associated with cancer susceptibility. Using anova, independent t-test, cruskal wallis and mann whitney u test we calculated significant different between SNP genotype group. Results: The mean of mammographic density is higher in cases (52%) than in controls (0,41%) (p < 0,05). Means of mammographic density were compared by ESR1 genotypes and haplotypes. The percentage density was higher in women with one or two copies of the PvuII p allele (means for CT/Pp and TT/pp are 49 % and 48 %, respectively) than in those with the CC/PP genotype (39%), TT VS CC (P >0,05). Women with one or two copies of the XbaI × allele had higher mean percentage density (AG/Xx and AA/xx, 49% and 47%, respectively) than those with the GG/XX genotype (32%,), AAVGG P < 0,05. Persentage of TT genotype and mean of density is higher in cases (30%, 52%) than controls (10,2%, 40%). Conclusion: Haplotype 2 (TG/PX) was associated with lower sensitivity to estrogen and reflects as decrease of mammographic density. The findings of this study support the view that ESR1 polymorphisms may affect breast cancer risk through differences in breast density. Keywords: Breast Cancer, Mammogram Digitizer, DNA polymorphism ESR 1 PvuII, ESR1 XbaI, PCR RFLP Citation Information: Cancer Res 2012;72(24 Suppl):Abstract nr P3-01-08.

Background Assess the relation between the presence of PVUII and XBAI polymorphisms in the estrogen receptor alpha gene and mammographic density in postmenopausal women. Methods For the present analysis, 189 postmenopausal women who had never used hormonal therapy and who did not have clinical or mammographic features were selected. Based on the ACR-BIRADSâ 2003 classification, the mammographic density was determined by three independent readers (two subjective ratings and one computerized - Adobe Photoshop â 7.0 software). Blood samples were available to extract DNA according to KIT GFX â protocol. PCR-RFLP (Polymerase Chain Reaction - Restriction Fragment Length Polymorphism) was then used to identify the polymorphisms. Results There was a high degree of agreement among the three readers to determine the mammographic density (Kappa>0.75). Sixty women (32%) had dense breasts and 129 (68%) had non-dense breasts. The PVUII polymorphism was found in 132 (69.8%) of 189 women, while the XBAI was found in 135 (71.4%) of women. Parity (p=0.02) and body mass index (p Conclusions There was no significant association of the PVUII polymorphism in the estrogen receptor alpha gene with mammographic density (p=0.34). However, the XBAI polymorphism was observed at a higher mutated homozygous frequency in women with dense breasts and there was an increased frequency of wild-type homozygous and heterozygous women with fat-replaced breasts (p=0.01). Citation Information: Cancer Res 2011;71(24 Suppl):Abstract nr P4-02-10.

While studies have shown that the use of post-menopausal hormone therapy increases mammographic density, certain aspects of this association remain unclear. We examined whether mammographic density differs according to the type of hormone therapy used, dose, duration of use, time since last use, as well as whether the effects are modified by age and body mass index (BMI). We used a cross-sectional design and recruited 2265 post-menopausal women, aged 50-69 who participated in the Norwegian Breast Cancer Screening Program in 2004. Mammographic density was assessed with the computer-assisted method (Madena), and we estimated mean percent mammographic density, controlling for possible confounding factors. Statistical analyzes were performed for all women combined and by age and BMI. Mammographic density was higher among current hormone therapy users (percent density: 20.8%; 95% CI: 19.6-21.9%), than among former (18.7%; 18.1-19.3%) or never HT users (16.7%; 15.8-17.6%). Ever users of combined estrogen-progestogen therapy (EPT) had higher percent density (20.0%; 19.1-20.9%) than estrogen-only (ET) users (18.3%, 17.7-18.9%) and never users (16.7%, 15.8-17.6%), and the highest density was seen in current EPT users (21.4%; 20.1-22.6%). Time since last use was significantly associated with density, with women who quit more than 3 years ago having density similar to never users. Mammographic density declined with increasing age and BMI. In analyses stratified by BMI, we found higher densities with EPT use in all categories, with somewhat smaller differences between ever and never EPT users in women with BMI of 26 and higher. When stratifying analyses by age, mammographic density was similar in EPT users and never users in women aged 55 and below. However, this was not true in leaner women (BMI of 23 or less). Among these young women (55 or less) with low BMI (23 or less), EPT users had higher percent density than never users. The percent density was 26.8% (23.7-29.8%) in never users, and 31.7% (28.0-35.4%) in ever users. No statistically significant difference in density was found in women older than 62 years old with a BMI of 26 and above, with percent density of 6.8% (5.3-8.3%), and 9.3% (6.9-11.6%) in never and ever users, respectively. Higher mammographic density was seen in ever users of estradiol and norethisterone acetate regimens (Activelle and Kliogest) compared to other EPT. Mammographic density was higher in women using high rather than low doses of estradiol and progestogen. In conclusion, the highest mammographic density was found in EPT users compared to ET and never users, particularly in users of the norethisterone acetate regimens. This increase was bigger in women taking high rather than low EPT doses. The association between EPT use and mammographic density was modified by age and BMI. These results have important implications and should be considered when, for example, deciding on which type and dose of hormones to prescribe. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 3726. doi:10.1158/1538-7445.AM2011-3726

Breast tissue homoeostasis depends on the complex regulation of biochemical and biophysical factors present in the extra cellular matrix (ECM). Tumor tissue in mouse and human breast is characteristically stiffer than normal tissue, and changes to the ECM contribute to this phenotype. Breast density is associated with elevated collagen content, while increased deposition of collagen is known to augment ECM stiffness. Mammographic density imaging provides a qualitative description of breast density, and high mammographic density is associated with increased risk to malignancy. However, little is known about the correlation between ECM stiffness and the density in the breast image. Previously, we have used atomic force microscopy (AFM) to characterize the changes in breast tissue stiffness with cancer progression (Levental et al., Cell 2009). We hypothesized that mammographically dense breasts would be stiffer. To further understand the biophysical regulation of breast stiffness, we investigated whether mammographic density is a predictor of ECM stiffness. Towards this goal, we studied tissue samples from prophylactic mastectomies, from women with low versus high mammographic density. Tissue samples were obtained from the peripheral quadrants as well as from the retroareolar (nipple) regions, which are known to be of higher mammographic density. We performed AFM force mapping to characterize the ECM stiffness in the different regions. Our preliminary data indicate a heterogeneous pattern of stiffness within the breast. Moreover, we found that the peripheral terminal ductal lobuli have the most compliant ECM. By contrast, the stroma stiffness in the retroareolar region was 2-fold higher than in the peripheral quadrants. This work demonstrates the technical feasibility of measuring the mechanical properties as well as defined histological characteristics within the same patient specimen. The data suggest that ECM stiffness may be greater in breast tissue of high mammographic density. The correlation between mammographic density and ECM stiffness may reveal the role of collagen status in the risk to malignancy. (supported by W81XWH-05-1-0330 and R01 CA138818-01A1 to VMW, 1U01 ES019458-01 to VMW and ZW, and P50 CA 58207 to JG, VW, SH and LC.) Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 416. doi:10.1158/1538-7445.AM2011-416

Background: Women with benign breast disease are at elevated breast cancer risk. In order to accurately predict a woman's individual risk of breast cancer, a breast cancer risk-prediction model is needed that incorporates significant breast cancer risk factors. This report describes two factors: tissue based assessment of lobular involution, and radiological marker- mammographic density (MD). Lobular involution, or physiologic atrophy of the breast glandular epithelium, is inversely associated with breast cancer risk. MD is a strong positive risk factor for breast cancer. With increasing age, the extent of lobular involution increases while MD decreases. However, it is unclear whether involution and MD represent independent breast cancer risk factors. We examined breast cancer risk associated with lobular involution and MD in women with benign breast disease (BBD) to determine whether these features are independently associated with breast cancer risk.Methods: Using the Mayo Clinic Surgical and Pathology Indices, 9376 women ages 18 to 85 with benign excisional breast biopsy between January 1, 1967 and December 31, 1991 were identified and formed the Mayo BBD cohort. We studied a sub-cohort of women diagnosed with BBD between 1985 and 1991 (when MD was clinically assessed and recorded) who had a mammogram within 6 months of the BBD diagnosis. Breast cancer outcomes were determined through the Mayo medical records and a study-specific questionnaire. Lobular involution extent was assessed in background tissue as 'none' (0% lobules involuted), 'partial' (1-74% lobules involuted) or 'complete' (≥75% lobules involuted). MD was classified as Wolfe's parenchymal pattern (PP) as N1/ fatty; P1; P2; and DY/ homogenously dense. Hazard ratios and confidence intervals were calculated using Cox regression analyses, adjusting for confounders: age, parity, BMI, BBD histology, menopausal status, family history, PP and involution extent.Results: A total of 2666 women in the Mayo BBD cohort, with biopsies between 1985 and 1991, had a mammogram within 6 months of the breast biopsy. The mean age at biopsy was 54.6 years. After a mean follow-up of 13.3 years, 172 (6.5%) women developed breast cancer. After adjustment for PP and other confounders, women with no or partial involution had elevated risk compared to women with complete involution (HR 2.62 [95% CI 1.39, 4.94] for no involution and 1.61 [95% CI 1.03, 2.53] for partial involution; complete involution as reference group; p for trend 0.003). Moreover, women with dense breasts were at greater risk compared to women with nondense breasts (HR 1.67 [95% CI 1.0, 2.73] for DY pattern, 1.96 [95% CI 1.2 – 3.21] for P2, 1.23 [95% CI 0.67, 2.26] for P1; N1 category as reference group; p for trend 0.02). Multivariate analyses also showed that women with the combination of no involution and dense breasts had greater risk compared to those with complete involution and nondense breasts (HR 4.08 [95% CI 1.72, 9.68]).Conclusion: Lobular involution and MD are both risk factors for breast cancer; this report is the first to demonstrate that each provides unique information about breast cancer risk. These findings emphasize the potential for inclusion of both these factors in future breast cancer risk-prediction models. Citation Information: Cancer Res 2009;69(24 Suppl):Abstract nr 6064.

Abstract #4082 Background: Past studies have indicated that mammographic density is associated with not only breast cancer risk but also breast cancer risk factors in women living in western nations. However, to data, no such association has been shown among native Chinese women. The aim of this cross-sectional study was to investigate the effects of age, body mass index (BMI), age at menarche, parity, and menopausal status on mammographic patterns in women from a province of Northern China. Methods: Seven hundred and two women's mammograms and information of the breast cancer risk factors were obtained from Shanxi province cancer hospital in Northern China. Mammograms were assessed according to the Wolfe classification. Results: Age, BMI, parity, and menopause were inversely and independently related to high-risk mammographic parenchymal patterns. However, there was no statistically significant association between age at menarche and high mammographic density. Relative to subjects aged less than or equal to 35 years, subjects aged greater than 55 years had reduced 62% (OR = 0.38, 95% CI: 0.14 – 1.00) odds of having a high-risk pattern. In comparison to women whose BMI was less than or equal to 25, there was a 51% and 72% reduction in the odds of having high-risk mammographic patterns for those with BMI 25 to 30 and larger than or equal to 30 respectively (OR = 0.49, 95% CI: 0.32 - 0.74; OR = 0.28, 95% CI: 0.12 - 0.68 respectively). Women with more than three children had decreased 68% risk to have high mammographic density compared to those who were nulliparous (OR = 0.32, 95% CI: 0.1 – 1.0). Premenopausal women were more than four times likely to have a high-risk pattern than postmenopausal women (OR = 4.12, 95% CI: 2.17 – 7.87). Conclusion: Our findings demonstrated that mammographic parenchymal patterns are also associated with some risk factors of breast cancer in native Chinese women. This is consistent with most studies carried out in Western countries. Further studies are needed to determine the relationship between quantitative percentage density and breast cancer risk factors. Citation Information: Cancer Res 2009;69(2 Suppl):Abstract nr 4082.