Adiposity, breast density, and breast cancer risk: epidemiological and biological considerations

Mammary adipocytes promote breast tumor cell invasion and angiogenesis in the context of menopause and obesity

The mechanism(s) underlying obesity-related postmenopausal (PM) breast cancer (BC) are not clearly understood. We hypothesized that the increased local presence of 'obese' mammary adipocytes within the BC microenvironment promotes the acquisition of an invasive and angiogenic BC cell phenotype and accelerates tumor proliferation and progression. BC cells, treated with primary mammary adipocyte secretome from premenopausal (Pre-M) and PM obese women (ObAdCM; obese adipocyte conditioned-media) upregulated the expression of several pro-tumorigenic factors including VEGF, lipocalin-2 and IL-6. Both Pre-M and PM ObAdCM stimulated endothelial cell recruitment and proliferation and significantly stimulated BC cell proliferation, migration and invasion. IL-6 and LCN2 induced STAT3/Akt signaling in BC cells and STAT3 inhibition abrogated the ObAdCM-stimulated BC cell proliferation and migration. Expression of proangiogenic regulators including VEGF, NRP1, NRP2, IL8RB, TGFβ2, and TSP-1 were found to be differentially regulated in mammary adipocytes from obese PM women. Comparative RNAseq indicated an upregulation of PI3K/Akt signaling, ECM-receptor interactions and lipid/fatty acid metabolism in PM versus Pre-M mammary adipocytes. Our results demonstrate that irrespective of menopausal status, cross-talk between obese mammary adipocytes and BC cells promotes tumor aggressiveness and suggest that targeting the LCN2/IL-6/STAT3 signaling axis may be a useful strategy in obesity-driven breast tumorigenesis.

Associations between breast cancer risk factors and mammographic breast density in a large cross-section of Korean women

BACKGROUND

We investigated the association between established risk factors for breast cancer and mammographic breast density in Korean women.

METHODS

This large cross-sectional study included 8 460 928 women aged >40 years, who were screened for breast cancer between 2009 and 2018. Breast density was assessed using the Breast Imaging Reporting and Data System. This study used multiple logistic regression analyses of age, BMI, age at menarche, menopausal status, menopausal age, parity, breastfeeding status, oral contraceptive use, family history of breast cancer, physical activity, smoking, drinking and hormone replacement therapy use to investigate their associations with mammographic breast density. Analyses were performed using SAS software.

RESULTS

Of 8 460 928 women, 4 139 869 (48.9%) had nondense breasts and 4 321 059 (51.1%) had dense breasts. Factors associated with dense breasts were: earlier age at menarche [<15 vs. ≥15; adjusted odds ratio (aOR), 1.18; 95% confidence interval (CI), 1.17-1.18], premenopausal status (aOR, 2.01; 95% CI, 2.00-2.02), later age at menopause (≥52 vs. <52; aOR, 1.23; 95% CI, 1.22-1.23), nulliparity (aOR, 1.64; 95% CI, 1.63-1.65), never breastfed (aOR, 1.23; 95% CI, 1.23-1.24) and use of hormone replacement therapy (aOR, 1.29; 95% CI, 1.28-1.29). Women with a higher BMI and the use of oral contraceptives were more likely to have nondense breasts.

CONCLUSION

Lower BMI, reproductive health and behavioral factors were associated with dense breasts in Korean women. Additional research should investigate the relationship between mammographic breast density, breast cancer risk factors and breast cancer risk.

Mammographic features differ with body composition in women with breast cancer

OBJECTIVES

There are several breast cancer (BC) risk factors-many related to body composition, hormonal status, and fertility patterns. However, it is not known if risk factors in healthy women are associated with specific mammographic features at the time of BC diagnosis. Our aim was to assess the potential association between pre-diagnostic body composition and mammographic features in the diagnostic BC image.

MATERIALS AND METHODS

The prospective Malmö Diet and Cancer Study includes women with invasive BC from 1991 to 2014 (n = 1116). BC risk factors at baseline were registered (anthropometric measures, menopausal status, and parity) along with mammography data from BC diagnosis (breast density, mammographic tumor appearance, and mode of detection). We investigated associations between anthropometric measures and mammographic features via logistic regression analyses, yielding odds ratios (OR) with 95% confidence intervals (CI).

RESULTS

There was an association between high body mass index (BMI) (≥ 30) at baseline and spiculated tumor appearance (OR 1.370 (95% CI: 0.941-2.010)), primarily in women with clinically detected cancers (OR 2.240 (95% CI: 1.280-3.940)), and in postmenopausal women (OR 1.580 (95% CI: 1.030-2.440)). Furthermore, an inverse association between high BMI (≥ 30) and high breast density (OR 0.270 (95% CI: 0.166-0.438)) was found.

CONCLUSION

This study demonstrated an association between obesity and a spiculated mass on mammography-especially in women with clinically detected cancers and in postmenopausal women. These findings offer insights on the relationship between risk factors in healthy women and related mammographic features in subsequent BC.

CLINICAL RELEVANCE STATEMENT

With increasing numbers of both BC incidence and women with obesity, it is important to highlight mammographic findings in women with an unhealthy weight.

KEY POINTS

Women with obesity and BC may present with certain mammographic features. Spiculated masses were more common in women with obesity, especially postmenopausal women, and those with clinically detected BCs. Insights on the relationship between obesity and related mammographic features will aid mammographic interpretation.

An analysis of the association between breast density and body mass index with breast cancer molecular subtypes in early breast cancer: data from a Spanish population

PURPOSE

Breast cancer is an important health problem, like obesity and dyslipidemia, with a strong association between body mass index (BMI) and breast cancer incidence and mortality. The risk of breast cancer is also high in women with high mammographic breast density (MBD). The purpose of this study was to analyze the association between BMI and MBD according to breast cancer molecular subtypes.

METHODS

This transversal, descriptive, multicenter study was conducted at three Spanish breast cancer units from November 2019 to October 2020 in women with a recent diagnosis of early breast cancer. Data were collected at the time of diagnosis.

RESULTS

The study included 162 women with a recent diagnosis of early breast cancer. The median age was 52 years and 49.1% were postmenopausal; 52% had normal weight, 32% overweight, and 16% obesity. There was no association between BMI and molecular subtype but, according to menopausal status, BMI was significantly higher in postmenopausal patients with luminal A (p = 0.011) and HER2-positive (p = 0.027) subtypes. There was no association between MBD and molecular subtype, but there were significant differences between BMI and MBD (p < 0.001), with lower BMI in patients with higher MBD. Patients with higher BMI had lower HDL-cholesterol (p < 0.001) and higher insulin (p < 0.001) levels, but there were no significant differences in total cholesterol or vitamin D.

CONCLUSIONS

This study showed higher BMI in luminal A and HER2-positive postmenopausal patients, and higher BMI in patients with low MBD regardless of menopausal status.

Temporal changes in mammographic breast density and breast cancer risk among women with benign breast disease

INTRODUCTION

Benign breast disease (BBD) and high mammographic breast density (MBD) are prevalent and independent risk factors for invasive breast cancer. It has been suggested that temporal changes in MBD may impact future invasive breast cancer risk, but this has not been studied among women with BBD.

METHODS

We undertook a nested case-control study within a cohort of 15,395 women with BBD in Kaiser Permanente Northwest (KPNW; 1970-2012, followed through mid-2015). Cases (n = 261) developed invasive breast cancer > 1 year after BBD diagnosis, whereas controls (n = 249) did not have breast cancer by the case diagnosis date. Cases and controls were individually matched on BBD diagnosis age and plan membership duration. Standardized %MBD change (per 2 years), categorized as stable/any increase (≥ 0%), minimal decrease of less than 5% or a decrease greater than or equal to 5%, was determined from baseline and follow-up mammograms. Associations between MBD change and breast cancer risk were examined using adjusted unconditional logistic regression.

RESULTS

Overall, 64.5% (n = 329) of BBD patients had non-proliferative and 35.5% (n = 181) had proliferative disease with/without atypia. Women with an MBD decrease (≤ - 5%) were less likely to develop breast cancer (Odds Ratio (OR) 0.64; 95% Confidence Interval (CI) 0.38, 1.07) compared with women with minimal decreases. Associations were stronger among women ≥ 50 years at BBD diagnosis (OR 0.48; 95% CI 0.25, 0.92) and with proliferative BBD (OR 0.32; 95% CI 0.11, 0.99).

DISCUSSION

Assessment of temporal MBD changes may inform risk monitoring among women with BBD, and strategies to actively reduce MBD may help decrease future breast cancer risk.

Cigarette smoking and mammographic breast density in post-menopausal women from the EPIC Florence cohort

Introduction

Cigarette smoking has been recognized as a risk factor for breast cancer (BC) also if the biological mechanism remains poorly understood. High mammographic breast density (MBD) is associated with BC risk and many BC risk factors, such as genetic, anthropometric, reproductive and lifestyle factors and age, are also able to modulate MBD. The aim of the present study was to prospectively explore, in post-menopausal women, the association between smoking habits and MBD, assessed using an automated software, considering duration and intensity of smoking.

Methods

The analysis was carried out in 3,774 women enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) Florence cohort in 1993-98, participating in the 2004-06 follow up (FU) and with at least one full-field digital mammography (FFDM) performed after FU. For each woman, detailed information on smoking habits, anthropometry, lifestyle and reproductive history was collected at enrollment and at FU. Smoking information at baseline and at FU was integrated. The fully automated Volpara™ software was used to obtain total breast volume (cm3), absolute breast dense volume (DV, cm3) and volumetric percent density (VPD, %) from the first available FFDM (average 5.3 years from FU). Multivariable linear regression models were applied to evaluate the associations between smoking habits and VPD or DV.

Results

An inverse association between smoking exposure and VPD emerged (Diff% -7.96%, p <0.0001 for current smokers and -3.92%, p 0.01 for former smokers, compared with non-smokers). An inverse dose-response relationship with number of cigarettes/day, years of smoking duration and lifetime smoking exposure (pack-years) and a direct association with time since smoking cessation among former smokers emerged. Similar associations, with an attenuated effect, emerged when DV was considered as the outcome variable.

Discussion

This longitudinal study confirms the inverse association between active smoking, a known risk factor for BC, and MBD among post-menopausal women. The inclusion of smoking habits in the existing BC risk prediction models could be evaluated in future studies.

Physical Activity and Mammographic Density in Japanese Women

BACKGROUND

Dense breast is one of the strong risk factors for breast cancer among women. While it has been established that physical activity is associated with decreased risk for breast cancer, results have been inconsistent in terms of mammographic density. Thus, we examined physical activity in relation to mammographic density among Japanese women in Tokyo.

METHODS

We used 123,026 records from 33,698 Japanese women without a history of breast cancer who got mammograms at St. Luke's International Hospital in Tokyo, Japan from 2004 to 2019. Mammographic density was classified according to the Breast Imaging Reporting and Data System (BI-RADS), and women self-reported their physical activity level over the past year. ORs were estimated using logistic generalized estimating equations after adjusting for age, body mass index, menopausal status, parity, family history of breast or ovarian cancer, hormone therapy use, smoking status, alcohol consumption, and year.

RESULTS

We observed inverse associations of physical activity with dense breasts. Adjusted ORs were 0.96 (95% confidence interval: 0.91-1.00) for women with physical exercise for 1-2 days per week, 0.94 (0.88-0.99) for those with physical exercise for 3-5 days per week, and 0.91 (0.84-0.99) for those with daily physical exercise when compared with those reported seldom physical exercise.

CONCLUSIONS

Higher levels of physical activity may be associated with decreased mammographic density levels in Japanese women.

IMPACT

Increasing physical activity may serve as a reasonable intervention to reduce mammographic density, and thereby, to mitigate the risk of breast cancer in Asian women.

Mammographic breast density and cardiovascular disease risk in women

AIMS

We aimed to determine the predictive role of mammographic breast density in addition to the Framingham Risk Score (FRS) on subsequent CVD events in women.

METHODS AND RESULTS

This cohort study included 4,268,579 women aged ≥40 years who underwent mammography screening between 2009 and 2010 with follow-up until 2020. Breast density was reported following the Breast Imaging Reporting and Data System. Primary outcomes included coronary heart disease, cerebrovascular disease, peripheral arterial disease, and heart failure. The incremental predictive ability of breast density added to the FRS model was assessed using the ROC and net reclassification index (NRI) among all women and strata based on FRS risk categories (<5% as low-risk, 5%-10% as moderate-risk, and ≥10% as high-risk). In total, 135,475 CVD events were recorded after a median follow-up of 10.9 years. A lower category of breast density was associated with a higher risk of CVD. Compared to the extremely dense breast group, the hazard ratios (95% CI) for CVDs were 1.12 (1.09-1.14), 1.19 (1.17-1.22), and 1.29 (1.26-1.32) in women with heterogeneously dense, scattered fibroglandular densities, and almost entirely fat breast density, respectively. Adding breast density to the FRS showed a slight improvement in AUROC but a modest improvement in NRI; the C-statistic difference was 0.083% (95% CI 0.069-0.096) with a 7.15% (6.85-7.69) increase in NRI, with the strongest improvement observed in the low-risk group.

CONCLUSIONS

Mammographic breast density is an independent predictor of incident CVD among women. The addition of mammographic breast density to FRS improves the prediction of CVDs, especially in low-risk individuals.

Development and evaluation of a method to assess breast cancer risk using a longitudinal history of mammographic density: a cohort study

BACKGROUND

Women with dense breasts have an increased risk of breast cancer. However, breast density is measured with variability, which may reduce the reliability and accuracy of its association with breast cancer risk. This is particularly relevant when visually assessing breast density due to variation in inter- and intra-reader assessments. To address this issue, we developed a longitudinal breast density measure which uses an individual woman's entire history of mammographic density, and we evaluated its association with breast cancer risk as well as its predictive ability.

METHODS

In total, 132,439 women, aged 40-73 yr, who were enrolled in Kaiser Permanente Washington and had multiple screening mammograms taken between 1996 and 2013 were followed up for invasive breast cancer through 2014. Breast Imaging Reporting and Data System (BI-RADS) density was assessed at each screen. Continuous and derived categorical longitudinal density measures were developed using a linear mixed model that allowed for longitudinal density to be updated at each screen. Predictive ability was assessed using (1) age and body mass index-adjusted hazard ratios (HR) for breast density (time-varying covariate), (2) likelihood-ratio statistics (ΔLR-χ2) and (3) concordance indices.

RESULTS

In total, 2704 invasive breast cancers were diagnosed during follow-up (median = 5.2 yr; median mammograms per woman = 3). When compared with an age- and body mass index-only model, the gain in statistical information provided by the continuous longitudinal density measure was 23% greater than that provided by BI-RADS density (follow-up after baseline mammogram: ΔLR-χ2 = 379.6 (degrees of freedom (df) = 2) vs. 307.7 (df = 3)), which increased to 35% (ΔLR-χ2 = 251.2 vs. 186.7) for follow-up after three mammograms (n = 76,313, 2169 cancers). There was a sixfold difference in observed risk between densest and fattiest eight-category longitudinal density (HR = 6.3, 95% CI 4.7-8.7), versus a fourfold difference with BI-RADS density (HR = 4.3, 95% CI 3.4-5.5). Discriminatory accuracy was marginally greater for longitudinal versus BI-RADS density (c-index = 0.64 vs. 0.63, mean difference = 0.008, 95% CI 0.003-0.012).

CONCLUSIONS

Estimating mammographic density using a woman's history of breast density is likely to be more reliable than using the most recent observation only, which may lead to more reliable and accurate estimates of individual breast cancer risk. Longitudinal breast density has the potential to improve personal breast cancer risk estimation in women attending mammography screening.

Adipose-enriched peri-tumoral stroma, in contrast to myofibroblast-enriched stroma, prognosticates poorer survival in breast cancers

Despite our understanding of the genetic basis of intra-tumoral heterogeneity, the role of stromal heterogeneity arising from an altered tumor microenvironment in affecting tumorigenesis is poorly understood. In particular, extensive study on the peri-tumoral stroma in the morphologically normal tissues surrounding the tumor is lacking. Here, we examine the heterogeneity in tumors and peri-tumoral stroma from 8 ER+/PR+/HER2- invasive breast carcinomas, through multi-region transcriptomic profiling by microarray. We describe the regional heterogeneity observed at the intrinsic molecular subtype, pathway enrichment, and cell type composition levels within each tumor and its peri-tumoral region, up to 7 cm from the tumor margins. Moreover, we identify a pro-inflammatory adipose-enriched peri-tumoral subtype which was significantly associated with poorer overall survival in breast cancer patients, in contrast to an adaptive immune cell- and myofibroblast-enriched subtype. These data together suggest that peri-tumoral heterogeneity may be an important determinant of the evolution and treatment of breast cancers.

Prenatal airborne polycyclic aromatic hydrocarbon exposure, altered regulation of peroxisome proliferator-activated receptor gamma (Ppar)γ, and links with mammary cancer

Environmental exposure to polycyclic aromatic hydrocarbons (PAH) has been shown to be associated with chronic disease outcomes through multiple mechanisms including altered regulation of the transcription factor peroxisome proliferator-activated receptor gamma (Ppar) γ. Because PAH exposure and Pparγ each have been associated with mammary cancer, we asked whether PAH would induce altered regulation of Pparγ in mammary tissue, and whether this association may underlie the association between PAH and mammary cancer. Pregnant mice were exposed to aerosolized PAH at proportions that mimic equivalent human exposures in New York City air. We hypothesized that prenatal PAH exposure would alter Pparγ DNA methylation and gene expression and induce the epithelial to mesenchymal transition (EMT) in mammary tissue of offspring (F1) and grandoffspring (F2) mice. We also hypothesized that altered regulation of Pparγ in mammary tissue would associate with biomarkers of EMT, and examined associations with whole body weight. We found that prenatal PAH exposure lowered Pparγ mammary tissue methylation among grandoffspring mice at postnatal day (PND) 28. However, PAH exposure did not associate with altered Pparγ gene expression or consistently with biomarkers of EMT. Finally, lower Pparγ methylation, but not gene expression, was associated with higher body weight among offspring and grandoffspring mice at PND28 and PND60. Findings suggest additional evidence of multi-generational adverse epigenetic effects of prenatal PAH exposure among grandoffspring mice.

Studying the association between longitudinal mammographic density measurements and breast cancer risk: a joint modelling approach

BACKGROUND

Researchers have suggested that longitudinal trajectories of mammographic breast density (MD) can be used to understand changes in breast cancer (BC) risk over a woman's lifetime. Some have suggested, based on biological arguments, that the cumulative trajectory of MD encapsulates the risk of BC across time. Others have tried to connect changes in MD to the risk of BC.

METHODS

To summarize the MD-BC association, we jointly model longitudinal trajectories of MD and time to diagnosis using data from a large ([Formula: see text]) mammography cohort of Swedish women aged 40-80 years. Five hundred eighteen women were diagnosed with BC during follow-up. We fitted three joint models (JMs) with different association structures; Cumulative, current value and slope, and current value association structures.

RESULTS

All models showed evidence of an association between MD trajectory and BC risk ([Formula: see text] for current value of MD, [Formula: see text] and [Formula: see text] for current value and slope of MD respectively, and [Formula: see text] for cumulative value of MD). Models with cumulative association structure and with current value and slope association structure had better goodness of fit than a model based only on current value. The JM with current value and slope structure suggested that a decrease in MD may be associated with an increased (instantaneous) BC risk. It is possible that this is because of increased screening sensitivity rather than being related to biology.

CONCLUSION

We argue that a JM with a cumulative association structure may be the most appropriate/biologically relevant model in this context.

Lifetime changes in body fatness and breast density in postmenopausal women: the FEDRA study

BACKGROUND

High mammographic breast density (MBD) is an established risk factor for breast cancer (BC). Body fatness conveys an increased BC risk in postmenopause but is associated with less dense breasts. Here, we studied the relationship between body fatness and breast composition within the FEDRA (Florence-EPIC Digital mammographic density and breast cancer Risk Assessment) longitudinal study.

METHODS

Repeated anthropometric data and MBD parameters (obtained through an automated software on BC screening digital mammograms) were available for all participants, as well as information on other BC risk factors. Multivariate linear regression and functional data analysis were used to longitudinally evaluate the association of body fatness, and changes thereof over time, with dense (DV) and non-dense (NDV) breast volumes and volumetric percent density (VPD).

RESULTS

A total of 5,262 women were included, with anthropometric data available at 20 and 40 years of age, at EPIC baseline (mean 49.0 years), and an average of 9.4 years thereafter. The mean number of mammograms per woman was 3.3 (SD 1.6). Body fatness (and increases thereof) at any age was positively associated with DV and NDV (the association being consistently stronger for the latter), and inversely associated with VPD. For instance, an increase by 1 kg/year between the age of 40 years and EPIC baseline was significantly associated with 1.97% higher DV, 8.85% higher NDV, and 5.82% lower VPD.

CONCLUSION

Body fatness and its increase from young adulthood until midlife are inversely associated with volumetric percent density, but positively associated with dense and non-dense breast volumes in postmenopausal women.

Association of Longitudinal Mammographic Breast Density Changes with Subsequent Breast Cancer Risk

Background Although Breast Imaging Reporting and Data System (BI-RADS) density classification has been used to assess future breast cancer risk, its reliability and validity are still debated in literature. Purpose To determine the association between overall longitudinal changes in mammographic breast density and breast cancer risk stratified by menopausal status. Materials and Methods In a retrospective cohort study using the Korean National Health Insurance Service database, women aged at least 40 years without a history of cancer who underwent three consecutive biennial mammographic screenings in 2009-2014 were followed up through December 2020. Participants were divided according to baseline breast density: fatty (BI-RADS categories a, b) versus dense (BI-RADS categories c, d) and then into subgroups on the basis of changes from the first to second and from second to third screenings. Women without change in breast density were used as the reference group. Main outcomes were incident breast cancer events, both invasive breast cancer and ductal carcinoma in situ. Cox proportion hazard regression was used to calculate the hazard ratio (HR) with adjustment for other covariables. Results Among 2 253 963 women (mean age, 59 years ± 9) there were 22 439 detected breast cancers. Premenopausal women with fatty breasts at the first screening had a higher risk of breast cancer as density increased in the second and third screenings (fatty-to-dense HR, 1.45 [95% CI: 1.27, 1.65]; dense-to-fatty HR, 1.53 [95% CI: 1.34, 1.74]; dense-to-dense HR, 1.93 [95% CI: 1.75, 2.13]). In premenopausal women with dense breasts at baseline, those in whom density continuously decreased had a 0.62-fold lower risk (95% CI: 0.56, 0.69). Similar results were observed in postmenopausal women, remaining significant after adjustment for baseline breast density or changes in body mass index (fatty-to-dense HR, 1.50 [95% CI: 1.39, 1.62]; dense-to-fatty HR, 1.42 [95% CI: 1.31, 1.53]; dense-to-dense HR, 1.62 [95% CI: 1.51, 1.75]). Conclusion In both premenopausal and postmenopausal women undergoing three consecutive biennial mammographic screenings, a consecutive increase in breast density augmented the future breast cancer risk whereas a continuous decrease was associated with a lower risk. © RSNA, 2022 Online supplemental material is available for this article. See also the editorial by Kataoka et al in this issue.

Effects of aromatase inhibitor therapy on visceral adipose tissue area and cardiometabolic health in postmenopausal women with early and locally advanced breast cancer

OBJECTIVE

Aromatase inhibitor (AI) therapy provides oncological benefits in postmenopausal women with oestrogen receptor-positive breast cancer. However, AI treatment has been associated with increased cardiovascular risk. In nonbreast cancer populations, experimentally induced low oestrogen states and natural transition to menopause have been associated with increases in visceral adipose tissue (VAT), a known surrogate marker for cardiometabolic risk. Given that AI treatment blocks oestradiol production, we hypothesized that AI treatment would increase VAT.

METHODS

We conducted a prospective 12-month cohort study of 52 postmenopausal women newly initiating AI treatment (median age: 64.5 years) and 52 women with breast pathology not requiring endocrine therapy (median age: 63.5 years). VAT area and other body composition parameters were measured at baseline, 6 months and 12 months using dual X-ray absorptiometry. Other risk markers of cardiometabolic health were also assessed.

RESULTS

In women initiating AI treatment, there was no statistically significant difference in VAT area after 12 months when compared to controls, with a mean adjusted difference of -5.00 cm² (-16.9, 6.91), p = .55. Moreover, changes in total fat mass, lean mass, subcutaneous adipose tissue area, hepatic steatosis and measures in endothelial function were also not statistically different between groups after 12 months. Findings were similar after adjustments for activity levels and coronavirus disease 2019 lockdown duration.

CONCLUSIONS

These data provide reassurance that over the initial 12 months of AI therapy, AI treatment is not associated with metabolically adverse changes in body composition, hepatic steatosis or vascular reactivity. The impact of extended AI therapy on cardiometabolic health requires further study.

Association of body composition fat parameters and breast density in mammography by menopausal status

We investigated the relationship between body fat-driven obesity and breast fat density in mammography according to menopausal status. We retrospectively analyzed 8537 women (premenopausal, n = 4351; postmenopausal, n = 4186). Body fat parameters included BMI (body mass index), waist circumference (WC), waist-hip ratio (WHR), fat mass index (FMI), Percentage of body fat (PBF), and visceral fat area (VFA). Body fat-driven obesity was defined as follows: overall obesity, BMI ≥ 25 kg/m²; central obesity, WC > 85 cm; abdominal obesity, WHR > 0.85; excessive FMI, the highest quartile (Q4) of FMI; excessive PBF, the highest quartile (Q4) of VFA; visceral obesity, and the highest quartile (Q4) of VFA). Breast density was classified according to BI-RADS (grade a, b, c, and d), which defined as an ordinal scale (grade a = 1, grade b = 2, grade c = 3, and grade d = 4). All body fat-driven obesity parameters were negatively associated with the grade of breast density in both groups of women (p < 0.001): The more fatty parameters are, the less dense breast is. In multivariable binary logistic regression, all body fat-driven obesity parameters also showed a negative association with grade d density (vs. grade a, b, or c). In premenopausal women, BMI was a more associated parameter with grade d density than those of the other fat-driven parameters (OR 0.265, CI 0.204-0.344). In postmenopausal women, WC was more associated with grade d density than the others (OR 0.315, CI 0.239-0.416). We found that BMI, WC, WHR, FMI, PBF and VFA were negatively correlated with dense breast, and the association degree pattern between body fat-driven obesity and dense breast differs according to menopausal status.

Body Mass Index Is Inversely Associated with Risk of Postmenopausal Interval Breast Cancer: Results from the Women’s Health Initiative

Interval breast cancer refers to cancer diagnosed after a negative screening mammogram and before the next scheduled screening mammogram. Interval breast cancer has worse prognosis than screening-detected cancer. Body mass index (BMI) influences the accuracy of mammography and overall postmenopausal breast cancer risk, yet how is obesity associated with postmenopausal interval breast cancer incidence is unclear. The current study included cancer-free postmenopausal women aged 50–79 years at enrollment in the Women’s Health Initiative who were diagnosed with breast cancer during follow-up. Analyses include 324 interval breast cancer cases diagnosed within one year after the participant’s last negative screening mammogram and 1969 screening-detected breast cancer patients. Obesity (BMI ≥ 30 kg/m2) was measured at baseline. Associations between obesity and incidence of interval cancer were determined by sequential logistic regression analyses. In multivariable-adjusted models, obesity was inversely associated with interval breast cancer risk [OR (95% CI) = 0.65 (0.46, 0.92)]. The inverse association persisted after excluding women diagnosed within 2 years [OR (95% CI) = 0.60 (0.42, 0.87)] or 4 years [OR (95% CI) = 0.56 (0.37, 0.86)] of enrollment, suggesting consistency of the association regardless of screening practices prior to trial entry. These findings warrant confirmation in studies with body composition measures.

Utility of U-Net for the objective segmentation of the fibroglandular tissue region on clinical digital mammograms

This study investigates the equivalence or compatibility between U-Net and visual segmentations of fibroglandular tissue regions by mammography experts for calculating the breast density and mean glandular dose (MGD). A total of 703 mediolateral oblique-view mammograms were used for segmentation. Two region types were set as the ground truth (determined visually): (1) one type included only the region where fibroglandular tissue was identifiable (called the 'dense region'); (2) the other type included the region where the fibroglandular tissue may have existed in the past, provided that apparent adipose-only parts, such as the retromammary space, are excluded (the 'diffuse region'). U-Net was trained to segment the fibroglandular tissue region with an adaptive moment estimation optimiser, five-fold cross-validated with 400 training and 100 validation mammograms, and tested with 203 mammograms. The breast density and MGD were calculated using the van Engeland and Dance formulas, respectively, and compared between U-Net and the ground truth with the Dice similarity coefficient and Bland-Altman analysis. Dice similarity coefficients between U-Net and the ground truth were 0.895 and 0.939 for the dense and diffuse regions, respectively. In the Bland-Altman analysis, no proportional or fixed errors were discovered in either the dense or diffuse region for breast density, whereas a slight proportional error was discovered in both regions for the MGD (the slopes of the regression lines were -0.0299 and -0.0443 for the dense and diffuse regions, respectively). Consequently, the U-Net and ground truth were deemed equivalent (interchangeable) for breast density and compatible (interchangeable following four simple arithmetic operations) for MGD. U-Net-based segmentation of the fibroglandular tissue region was satisfactory for both regions, providing reliable segmentation for breast density and MGD calculations. U-Net will be useful in developing a reliable individualised screening-mammography programme, instead of relying on the visual judgement of mammography experts.

Mammographic breast density, body mass index and risk of breast cancer in Korean women aged 75 years and older

Mammographic breast density and body mass index (BMI) are strong risk factors of breast cancer, but few studies have investigated these factors in older women. Our study assessed the association between breast density, BMI and the breast cancer risk among women aged ≥75 years. We included women who underwent breast cancer screening between 2009 and 2014 and were followed up until 2020. Breast density was measured using Breast Imaging Reporting and Data System. BMI was classified into three groups: <23, 23 to <25 and ≥25. Cox proportional hazards models were used to estimate the association of breast density and BMI with breast cancer risk. In 483 564 women, 1885 developed breast cancer. The 5-year incidence increased with an increase in breast density and BMI. Increase in breast density was associated with an increased breast cancer risk in all BMI categories: among women with BMI <23, those with heterogeneous/extreme density had a 2.98-fold (95% CI: 2.23-3.80) increased risk of breast cancer compared to those with entirely fatty breasts. An increase in BMI was associated with increased breast cancer risk in women with the same breast density in all density categories. When the combined associations of breast density and BMI on the risk of breast cancer were considered, women with a BMI ≥25 and heterogeneous/extreme breast density had a 5.35-fold (95% CI: 4.26-6.72) increased risk of breast cancer compared to women with a BMI <23 and fatty breasts. Women aged ≥75 years, with dense breasts, regardless of BMI status, might benefit from a tailored screening strategy for early detection of breast cancer.

1,2,3-Triazole derivatives with anti-breast cancer potential

Abstract:

Breast cancer is one of the most prevalent malignant diseases and one of the main mortality causes among women across the world. Despite advances in chemotherapy, drug resistance remains major clinical concerns, creating an urgent need to explore novel anti-breast cancer drugs. 1,2,3-Triazole is a privileged moiety, and its derivatives could inhibit cancer cell proliferation, and induce the cell cycle arrest and apoptosis. Accordingly, 1,2,3-triazole derivatives possess profound activity against various cancers including breast cancer. This review summarizes the latest progresses related to the anti-breast cancer potential of 1,2,3-triazole derivatives, covering articles published from January 2017 to December 2021. The mechanisms of action and structure-activity relationships (SARs) are also discussed for further rational design of more effective candidates.

Obesity in Postmenopausal Breast Cancer Patients: It Is Time to Improve Actions for a Healthier Lifestyle. The Results of a Comparison Between Two Italian Regions With Different "Presumed" Lifestyles

Background

Adult body fatness is a convincing risk factor for postmenopausal breast cancer. With the aim to compare the different breast cancer (BC) features in Northern and Southern Italy, we investigated the relationship between BMI and BC characteristic in two groups of patients referred in the Modena and Lecce breast units.

Materials and Methods

A retrospective analysis of a continuous series of BC patients referred to the Città di Lecce Hospital and the Modena Cancer Center, from January 2019 to December 2020 was performed. We identified four groups of BMI at BC diagnosis: underweight, BMI <18.5 kg/m²; normal weight, BMI ≥ 18.5–24.9 kg/m²; overweight, BMI ≥ 25.0–29.9 kg/m²; obese, BMI ≥30.0 kg/m². BC characteristics and clinical outcomes were analyzed by the Kolmogorov-Smirnov test and Mann-Whitney U test; categorical data were compared using Pearson’s chi-square test, and dicotomic data were compared by odds ratio.

Results

Nine hundred seventy-seven BC patients were included in the analysis. Overall, 470 were from Modena and 507 from Lecce. No differences were observed in the mean age of BC patients of Modena (61,42) and Lecce (62,08). No statistical differences between the two populations were shown in terms of tumor characteristics and pathological stage. Conversely, a statistical difference of BMI between the BC patients coming from Modena and Lecce (25.87 and 27.81, respectively; p = 0.000001) was found. BC patients diagnosed in Lecce at age ≥70 years had higher median BMI compared with the ones from Modena (p = 0.000002). The increased BMI in this aged population was also associated to larger tumor size (p = 0.040).

Conclusion

The rate of overweight and obesity was higher in BC women living in Southern Italy, despite the presumed nutrition according to the so-called Mediterranean type dietary pattern. Unexpectedly, an increased BMI rate and a relationship with larger tumor size were found in Southern BC patients aged ≥70 years. Our findings strongly support the need for promoting a healthier lifestyle model in Italy, with the aim of reducing the rate of the obesity and, consequently, the increased risk of BC.

Association of the Interaction Between Mammographic Breast Density, Body Mass Index, and Menopausal Status With Breast Cancer Risk Among Korean Women

IMPORTANCE

Evidence suggests that breast density and body mass index (BMI) are strong breast cancer risk factors; however, their interactive associations are unknown. Elucidation of these interactive associations may help to increase understanding of the causes of breast cancer and find effective interventions for susceptible subgroups.

OBJECTIVE

To explore the association of the interaction of mammographic breast density and BMI with breast cancer risks among premenopausal and postmenopausal women.

DESIGN, SETTING, AND PARTICIPANTS

This prospective observational cohort study used population-based data of the Korean National Cancer Screening Program embedded in the National Health Insurance Service database to evaluate the breast cancer risk of 3 248 941 premenopausal cancer-free women and 4 373 473 postmenopausal cancer-free women aged 40 years or older who underwent mammographic screening between January 1, 2009, and December 31, 2013, and were followed up until December 31, 2018. Statistical analysis was performed from June 1 to July 15, 2021.

EXPOSURES

Breast Imaging Reporting and Data System (BI-RADS)-defined breast density (with a scale from 1 to 4, where 1 indicates almost entirely fat, 2 indicates scattered fibroglandular densities, 3 indicates heterogeneously dense tissue, and 4 indicates extremely dense tissue) and BMI levels classified according to the World Health Organization Asia-Pacific Region classification.

MAIN OUTCOMES AND MEASURES

Adjusted relative risk (aRR) of breast cancer during the follow-up period and interactions in additive and multiplicative scales. The study end point was the development of breast cancer.

RESULTS

Of 3 248 941 premenopausal women (mean [SD] age, 44.6 [4.3] years) and 4 373 473 postmenopausal women (mean [SD] age, 59.6 [8.4] years) aged 40 years or older, 34 466 cases of breast cancer were identified among the premenopausal women, and 30 816 cases of breast cancer were identified among the postmenopausal women. Increased breast density was associated with an increased risk of breast cancer in both premenopausal and postmenopausal women across the BMI categories. Among premenopausal women, those in BI-RADS category 4 had an approximately 2-fold higher risk of breast cancer irrespective of BMI (all women: aRR, 2.36 [95% CI, 2.24-2.49]; underweight: aRR, 1.80 [95% CI, 1.25-2.59]; normal weight: aRR, 2.10 [95% CI, 1.93-2.28]; overweight: aRR, 2.47 [95% CI, 2.27-2.68]; obese: aRR, 2.87 [95% CI, 2.49-3.32]) than those with underweight status and in BI-RADS category 1. However, an association between BMI and the risk of breast cancer was found only in the postmenopausal women in all breast density categories compared with underweight women with BI-RADS category 1 (BI-RADS category 4, all women: aRR, 2.91 [95% CI, 2.78-3.04]; underweight: aRR, 2.74 [95% CI, 1.89-3.98]; normal weight: aRR, 3.05 [95% CI, 2.82-3.30]; overweight: aRR, 2.85 [95% CI, 2.67-3.04]; obese: aRR, 2.52 [95% CI, 2.22-2.88]). When the combined associations of breast density and BMI with the risk of breast cancer were considered, a high breast density and high BMI had a significant positive interaction on the additive scale for both premenopausal and postmenopausal women, especially the latter (premenopausal women: adjusted relative excess risk due to interaction, 0.53 [95% CI, 0.35-0.71]; postmenopausal women: adjusted relative excess risk due to interaction, 1.68 [95% CI, 1.26-2.10]).

CONCLUSIONS AND RELEVANCE

This study suggests that breast density and BMI interact synergistically to augment breast cancer risk, with a stronger association found among postmenopausal women. Both factors should be incorporated into risk stratification in a population-based screening for public health significance. Women with overweight or obesity and dense breast tissue might benefit from tailored early screening strategies to detect breast cancer.

Fatty liver disease and changes in dense breasts in pre- and postmenopausal women: the Kangbuk Samsung Health Study

PURPOSE

While increased breast density is a risk factor for breast cancer, the effect of fatty liver disease on breast density is unknown. We investigated whether fatty liver is a risk factor for changes in breast density over ~ 4 years of follow-up in pre- and postmenopausal women.

METHODS

This study included 74,781 middle-aged Korean women with mammographically determined dense breasts at baseline. Changes in dense breasts were identified by more screening mammograms during follow-up. Hepatic steatosis (HS) was measured using ultrasonography. Flexible parametric proportional hazards models were used to determine the adjusted hazard ratios (aHRs) and 95% confidence intervals (CIs), and a Weibull accelerated failure time model (AFT) was used to determine the time ratios (TRs) and 95% CIs.

RESULTS

During a median follow-up of 4.1 years, 4022 women experienced resolution of the dense breasts. The association between HS and dense breast resolution differed by the menopause status (P for interaction < 0.001). After adjusting for body mass index and other covariates, the aHRs (95% CI) for dense breast resolution comparing HS to non-HS were 0.81 (0.70-0.93) in postmenopausal women, while the association was converse in premenopausal women with the corresponding HRs of 1.30 (1.18-1.43). As an alternative approach, the multivariable-adjusted TR (95% CI) for dense breast survival comparing HS to non-HS were 0.81 (0.75-0.87) and 1.19 (1.06-1.33) in premenopausal and postmenopausal women, respectively.

CONCLUSION

The association between HS and changes in dense breasts differed with the menopause status. HS increased persistent dense breast survival in postmenopausal women but decreased it in premenopausal women.

Quantitative Breast Density in Contrast-Enhanced Mammography

Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.

Influential factors and prediction model of mammographic density among Chinese women

To evaluate the characteristics and influential factors of breast density and establish a new model for predicting breast density in Chinese women, so as to provide a basis for breast cancer screening techniques and duration.A total of 9412 women who were selected from screening and intervention techniques for Breast and Cervical Cancer Project between April 2018 and June 2019 were enrolled in this study. Selected women were randomly assigned to training and validation sets in a ratio of 1:1. Univariable and multivariable analyzes were performed by Logistic regression model. Nomogram was generated according to the results of multivariate analysis. Calibration, area under curve (AUC) and akaike information criterion (AIC) were used for measuring accuracy of prediction model.There were 377 (4.0%) women in breast imaging reporting and data system (BI-RADS) A category, 2164 (23.0%) in B category, 5749 (61.1%) in C category and 1122 (11.9%) in D category. Age duration, educational attainment, history of benign diseases, breastfeeding history, menopausal status, and body mass index (BMI) were imputed as independent influential factors for breast density in multivariable analysis. The AUC and AIC of training and validation set were 0.7158, 0.7139, and 4915.378, 4998.665, respectively.This study indicated that age, educational attainment, history of benign breast disease, breastfeeding history, menopausal status and BMI were independent influential factors of breast density. Nomogram generated on the basis of these factors could relatively predict breast density, which in turn could be used for recommendations of breast cancer screening techniques.

The evolution of perennially enlarged breasts in women: a critical review and a novel hypothesis

The possession of permanent, adipose breasts in women is a uniquely human trait that develops during puberty, well in advance of the first pregnancy. The adaptive role and developmental pattern of this breast morphology, unusual among primates, remains an unresolved conundrum. The evolutionary origins of this trait have been the focus of many hypotheses, which variously suggest that breasts are a product of sexual selection or of natural selection due to their putative role in assisting in nursing or as a thermoregulatory organ. Alternative hypotheses assume that permanent breasts are a by-product of other evolutionary changes. We review and evaluate these hypotheses in the light of recent literature on breast morphology, physiology, phylogeny, ontogeny, sex differences, and genetics in order to highlight their strengths and flaws and to propose a coherent perspective and a new hypothesis on the evolutionary origins of perennially enlarged breasts in women. We propose that breasts appeared as early as Homo ergaster, originally as a by-product of other coincident evolutionary processes of adaptive significance. These included an increase in subcutaneous fat tissue (SFT) in response to the demands of thermoregulatory and energy storage, and of the ontogenetic development of the evolving brain. An increase in SFT triggered an increase in oestradiol levels (E2). An increase in meat in the diet of early Homo allowed for further hormonal changes, such as greater dehydroepiandrosterone (DHEA/S) synthesis, which were crucial for brain evolution. DHEA/S is also easily converted to E2 in E2-sensitive body parts, such as breasts and gluteofemoral regions, causing fat accumulation in these regions, enabling the evolution of perennially enlarged breasts. Furthermore, it is also plausible that after enlarged breasts appeared, they were co-opted for other functions, such as attracting mates and indicating biological condition. Finally, we argue that the multifold adaptive benefits of SFT increase and hormonal changes outweighed the possible costs of perennially enlarged breasts, enabling their further development.

Engineering Breast Cancer On-chip-Moving Toward Subtype Specific Models

Breast cancer is the second leading cause of death among women worldwide, and while hormone receptor positive subtypes have a clear and effective treatment strategy, other subtypes, such as triple negative breast cancers, do not. Development of new drugs, antibodies, or immune targets requires significant re-consideration of current preclinical models, which frequently fail to mimic the nuances of patient-specific breast cancer subtypes. Each subtype, together with the expression of different markers, genetic and epigenetic profiles, presents a unique tumor microenvironment, which promotes tumor development and progression. For this reason, personalized treatments targeting components of the tumor microenvironment have been proposed to mitigate breast cancer progression, particularly for aggressive triple negative subtypes. To-date, animal models remain the gold standard for examining new therapeutic targets; however, there is room for in vitro tools to bridge the biological gap with humans. Tumor-on-chip technologies allow for precise control and examination of the tumor microenvironment and may add to the toolbox of current preclinical models. These new models include key aspects of the tumor microenvironment (stroma, vasculature and immune cells) which have been employed to understand metastases, multi-organ interactions, and, importantly, to evaluate drug efficacy and toxicity in humanized physiologic systems. This review provides insight into advanced in vitro tumor models specific to breast cancer, and discusses their potential and limitations for use as future preclinical patient-specific tools.

Prediagnostic circulating metabolites in female breast cancer cases with low and high mammographic breast density

Mammographic breast density (MBD) is a strong independent risk factor for breast cancer (BC). We designed a matched case-case study in the EPIC Florence cohort, to evaluate possible associations between the pre-diagnostic metabolomic profile and the risk of BC in high- versus low-MBD women who developed BC during the follow-up. A case-case design with 100 low-MBD (MBD ≤ 25%) and 100 high-MDB BC cases (MBD > 50%) was performed. Matching variables included age, year and type of mammographic examination. ¹H NMR metabolomic spectra were available for 87 complete case-case sets. The conditional logistic analyses showed an inverse association between serum levels of alanine, leucine, tyrosine, valine, lactic acid, pyruvic acid, triglycerides lipid main fraction and 11 VLDL lipid subfractions and high-MBD cases. Acetic acid was directly associated with high-MBD cases. In models adjusted for confounding variables, tyrosine remained inversely associated with high-MBD cases while 3 VLDL subfractions of free cholesterol emerged as directly associated with high-MBD cases. A pathway analysis showed that the "phenylalanine, tyrosine and tryptophan pathway" emerged and persisted after applying the FDR procedure. The supervised OPLS-DA analysis revealed a slight but significant separation between high- and low-MBD cases. This case-case study suggested a possible role for pre-diagnostic levels of tyrosine in modulating the risk of BC in high- versus low-MBD women. Moreover, some differences emerged in the pre-diagnostic concentration of other metabolites as well in the metabolomic fingerprints among the two groups of patients.

Association of mammographic density with blood DNA methylation

Background: Altered DNA methylation may be an intermediate phenotype between breast cancer risk factors and disease. Mammographic density is a strong risk factor for breast cancer. However, no studies to date have identified an epigenetic signature of mammographic density. We performed an epigenome-wide association study of mammographic density.

Methods: White blood cell DNA methylation was measured for 385 postmenopausal women using the Illumina Infinium MethylationEPIC BeadChip array. Differential methylation was assessed using genome-wide, probe-level, and regional analyses. We implemented a resampling-based approach to improve the stability of our findings.

Results: On average, women with elevated mammographic density exhibited DNA hypermethylation within CpG islands and gene promoters compared to women with lower mammographic density. We identified 250 CpG sites for which DNA methylation was significantly associated with mammographic density. The top sites were located within genes associated with cancer, including HDLBP, TGFB2, CCT4, and PAX8, and were more likely to be located in regulatory regions of the genome. We also identified differential DNA methylation in 37 regions, including within the promoters of PAX8 and PF4, a gene involved in the regulation of angiogenesis. Overall, our results paint a picture of epigenetic dysregulation associated with mammographic density.

Conclusion: Mammographic density is associated with differential DNA methylation throughout the genome, including within genes associated with cancer. Our results suggest the potential involvement of several genes in the biological mechanisms behind differences in breast density between women. Further studies are warranted to explore these potential mechanisms and potential links to breast cancer risk.

Gut microbiome, body weight, and mammographic breast density in healthy postmenopausal women

PURPOSE

We examined gut microbiome (GM) profiles in relation to mammographic breast density (BD) and body mass index (BMI) in healthy postmenopausal women.

METHODS

Eligible women were postmenopausal, had a BMI ≤ 35 kg/m², and had not recently taken oral/IV antibiotics. All women provided a fecal sample and information on breast cancer risk factors. Mammographic BD was classified with the American College of Radiology's BI-RADS BD classification system. Bacterial DNA was isolated from fecal samples and the V1-V2 hypervariable regions of 16S rRNA were sequenced on the Illumina MiSeq platform. We examined associations of GM with indices of within-sample (alpha) diversity and the ratio of the two main phyla (Firmicutes and Bacteroidetes; F/B ratio) with BD and BMI.

RESULTS

Among 69 women with BD data, 39 had low BD (BI-RADS I/II) and 30 had high BD (BI-RADS III/IV). BMI was inversely associated with BD (mean BMI = 23.8 and 28.0 in women with high and low BD, respectively, p = 1.07 × 10^-5). Similar levels of GM diversity were found across weight groups according to Shannon (p = 0.83); Inverse Simpson (p = 0.97); and Chao1 (p = 0.31) indices. F/B ratio and microbiota diversity were suggestively greater in women with high vs. low BD (p = 0.35, 0.14, 0.15, and 0.17 for F/B ratio, Shannon, Inverse Simpson and Chao1, respectively).

CONCLUSION

Suggestive differences observed in women with high and low BD with respect to GM alpha diversity and prevalence of specific GM taxa need to be confirmed in larger studies.

Polycyclic Aromatic Hydrocarbons and Mammary Cancer Risk: Does Obesity Matter too?

Breast cancer risk remains incompletely explained, and higher incidence rates of breast cancer over recent times and in urban and industrialized areas suggest environmental causes. Polycyclic aromatic hydrocarbons (PAH) are ubiquitous in the environment and epidemiological and rodent studies have shown associations between exposure to PAH and breast cancer incidence as well as mammary tumorigenesis. In addition, in vitro and rodent studies have implicated alterations in estrogen receptor alpha (Erα) signaling pathways following PAH exposure in limited experimental studies. However, our understanding of these mechanisms is incomplete. Sahay et al. addressed this gap by examining the effect of PAH exposure on epigenetic and transcriptional regulation of genes in the Erα pathway in a mouse cohort exposed to aerosolized PAH at proportions measured in urban air. In addition to alterations in the Erα signaling pathway in the pregnant mice and in their offspring and grandoffspring, the investigators observed higher body weights in mice exposed to PAH compared to the control. Given that associations between mammary tissue adiposity, systemic adiposity, and breast cancer risk have been observed previously, the finding of higher body weight in the PAH exposure group raises the possibility that body weight might influence the association between PAH exposure and breast cancer risk. Along with new analyses, we discuss the possibility that body weight may modify the association between PAH exposure, mammary cellular proliferation, and mammary gland ductal hyperplasia in offspring and grandoffspring mice and future research that may be needed to delineate these associations.

Visceral Adiposity Index in Breast Cancer Survivors: A Case-Control Study

BACKGROUND

Breast cancer (BC) is the first cause of cancer morbidity and mortality in women. This disease has been linked to obesity; however, it is not clear how fat accumulation affects women who survive breast cancer. Although the visceral adiposity index (VAI) is a marker of cardiometabolic risk and adipose tissue dysfunction, it is not clear how it changes in breast cancer survivors. The aim of this investigation was to compare VAI in women with and without breast cancer.

METHODS

A case-control cross-sectional study was conducted on women who were BC survivors and women without the history of BC (control group). Body composition was assessed using electrical bioimpedance while VAI by means of waist circumference (WC), body mass index (BMI), triacylglycerols (TG), and high-density lipoprotein cholesterol (HDL-C).

RESULTS

49 women in the BC survivor group and 50 in the control group. WC was wider in the survivor group as regards control (93.65 ± 10.48 vs. 88.52 ± 9.61 cm) (p=0.025); at once, TG and VAI were significantly higher for the survivor group (243.55 ± 199.84 vs. 159.84 ± 75.77) (p=0.007) and (11.03 ± 11.15 vs. 6.41 ± 3.66) (p < 0.005), respectively. Body composition parameters were similar in both groups.

CONCLUSIONS

VAI is higher in women who are BC survivors in comparison with controls matched by age and bodyweight.

Relationship between formulaic breast volume and risk of breast cancer based on linear measurements

BACKGROUND

Whether breast volume is a risk factor for breast cancer is controversial. This study aimed to evaluate whether a significant association between breast volume and risk of breast cancer, based on linear measurements, was present by applying propensity score matching (PSM).

METHODS

The study was designed as a hospital-based case-control study. Between March 2018 and May 2019, 208 cases and 340 controls were retrospectively reviewed. Information on menarche, smoking, feeding mode, oral contraceptives, reproductive history and family history was obtained through a structured questionnaire. Breast volume was calculated using a formula based on linear measurements of breast parameters. Cox regression and PSM were used to estimate odds ratios and 95% confidence intervals for breast cancer using risk factors adjusted for potential confounders.

RESULTS

There was a significant difference in breast volume between the two groups before propensity score matching (P = 0.014). Binary logistic regression showed that the risk of breast cancer was slightly higher in the case group with larger breast volumes than in the control group(P = 0.009, OR = 1.002, 95%CI:1.000 ~ 1.003). However, there was no significant statistical difference between the two groups using an independent sample Mann-Whitney U test (P = 0.438) or conditional logistic regression (P = 0.446).

CONCLUSIONS

After PSM for potential confounding factors, there is no significant difference in breast volume estimated by BREAST-V formula between the case group and the control group. The risk of breast cancer may not be related to breast volume in Chinese women.

Menopausal Transition, Body Mass Index, and Prevalence of Mammographic Dense Breasts in Middle-Aged Women

The interrelationship between menopausal stage, excessive adiposity and dense breasts remains unclear. We aimed to investigate the relationship between menopausal stage and dense-breast prevalence in midlife women while considering a possible effect modification of being overweight. The present cross-sectional study comprised 82,677 Korean women, aged 35–65 years, who attended a screening exam. Menopausal stages were categorized based on the Stages of Reproductive Aging Workshop (STRAW + 10) criteria. Mammographic breast density was categorized according to Breast Imaging Reporting and Data System (BI-RADS). Dense breasts were defined as BI-RADS Breast Density category D (extremely dense). The prevalence of dense breasts decreased as menopausal stage increased (p-trend < 0.001), and this pattern was pronounced in overweight women than non-overweight women (p-interaction = 0.016). Compared with pre-menopause, the multivariable-adjusted prevalence ratios (and 95% confidence intervals) for dense breasts were 0.98 (0.96–1.00) in early transition, 0.89 (0.86–0.92) in late transition, and 0.55 (0.52–0.59) in post-menopause, among non-overweight women, while corresponding prevalence ratios were 0.92 (0.87–0.98), 0.83 (0.77–0.90) and 0.36 (0.31–0.41) among overweight women. The prevalence of dense breasts was inversely associated with increasing menopausal stages and significantly decreased from the late menopausal transition, with stronger declines among overweight women.

The Mechanical Microenvironment in Breast Cancer

Mechanotransduction is the interpretation of physical cues by cells through mechanosensation mechanisms that elegantly translate mechanical stimuli into biochemical signaling pathways. While mechanical stress and their resulting cellular responses occur in normal physiologic contexts, there are a variety of cancer-associated physical cues present in the tumor microenvironment that are pathological in breast cancer. Mechanistic in vitro data and in vivo evidence currently support three mechanical stressors as mechanical modifiers in breast cancer that will be the focus of this review: stiffness, interstitial fluid pressure, and solid stress. Increases in stiffness, interstitial fluid pressure, and solid stress are thought to promote malignant phenotypes in normal breast epithelial cells, as well as exacerbate malignant phenotypes in breast cancer cells.

Obesity and Breast Cancer: The Role of Crown-Like Structures in Breast Adipose Tissue in Tumor Progression, Prognosis, and Therapy

Obesity is associated with increased risk and aggressiveness of many types of cancer. Women with obesity and breast cancer are more likely to be diagnosed with larger and higher-grade tumors and have higher incidence of metastases than lean individuals. Increasing evidence indicates that obesity includes systemic, chronic low-grade inflammation, and that adipose tissue can act as an important endocrine site, secreting a variety of substances that may regulate inflammation, immune response, and cancer predisposition. Obesity-associated inflammation appears to be initially mediated by macrophage infiltration into adipose tissue. Macrophages can surround damaged or necrotic adipocytes, forming "crown-like" structures (CLS). CLS are increased in breast adipose tissue from breast cancer patients and are more abundant in patients with obesity conditions. Moreover, the CLS index-ratio from individuals with obesity seems to influence breast cancer recurrence rates and survival. In this review, we discuss the most recent cellular and molecular mechanisms involved in CLS establishment in the white adipose tissue of women with obesity and their implications for breast cancer biology. We also explain how CLS influence the tumor microenvironment and affect breast cancer behavior. Targeting breast adipose tissue CLS can be a crucial therapeutic tool in cancer treatment, especially in patients with obesity.

Hormone Replacement Therapy, Breast Cancer Risk Factors, and Breast Cancer Risk: A Nationwide Population-Based Cohort

BACKGROUND

Hormone replacement therapy (HRT) increases the risk of breast cancer, but the association may vary according to patient factors. We investigated the association between HRT and breast cancer in a nationwide cohort with risk stratification according to risk factors for breast cancer.

METHODS

Using the Korean National Health Insurance Service database, 4,558,376 postmenopausal women who underwent breast cancer screening and regular health checkups from 2009 to 2014 were analyzed.

RESULTS

A total of 696,084 (15.3%) women reported current or previous HRT use. Breast cancer was newly diagnosed in 26,797 (0.6%) women during a median follow-up of 5.35 years. The HR of the risk of breast cancer in HRT users was 1.25 [95% confidence interval (CI), 1.22-1.29] compared with HRT nonusers. The risk of breast cancer increased according to HRT duration [adjusted HR = 1.08; 95% CI, 1.04-1.12, for <2 years; adjusted HR = 1.33; 95% CI, 1.25-1.40, for 2 to <5 years; and adjusted HR = 1.72; 95% CI, 1.63-1.82, for ≥5 years). The effects of HRT on breast cancer risk applied to both invasive and in situ cancer. The HRT-related risk of breast cancer was higher in women who were leaner and those who had dense breasts.

CONCLUSIONS

This nationwide population-based study confirms the association between HRT use and breast cancer risk. The risk increased proportionally with duration of HRT and differed according to body weight and breast density.

IMPACTS

Risk stratification would be useful when deciding whether to apply HRT for relief of menopausal symptoms.

Do Body Mass Index and Breast Density Impact Cancer Risk Among Women with Lobular Carcinoma In Situ?

PURPOSE

Both body mass index (BMI) and breast density impact breast cancer risk in the general population. Whether obesity and density represent additive risk factors in women with lobular carcinoma in situ (LCIS) is unknown.

METHODS

Patients diagnosed with LCIS from 1988 to 2017 were identified from a prospectively maintained database. BMI was categorized by World Health Organization classification. Density was captured as the mammographic Breast Imaging Reporting and Data System (BIRADS) value. Other covariates included age at LCIS diagnosis, menopausal status, family history, chemoprevention, and prophylactic mastectomy. Cancer-free probability was estimated using the Kaplan-Meier method, and Cox regression models were used for univariable and multivariable analyses.

RESULTS

A total of 1222 women with LCIS were identified. At a median follow-up of 7 years, 179 women developed breast cancer (121 invasive, 58 ductal carcinoma in situ); 5- and 10-year cumulative incidences of breast cancer were 10% and 17%, respectively. In multivariable analysis, increased breast density (BIRADS C/D vs. A/B) was significantly associated with increased hazard of breast cancer (hazard ratio [HR] 2.42, 95% confidence interval [CI] 1.52-3.88), whereas BMI was not. On multivariable analysis, chemoprevention use was associated with a significantly decreased hazard of breast cancer (HR 0.49, 95% CI 0.29-0.84). Exploratory analyses did not demonstrate significant interaction between BMI and menopausal status, BMI and breast density, BMI and chemoprevention use, or breast density and chemoprevention.

CONCLUSIONS

Breast cancer risk among women with LCIS is impacted by breast density. These results aid in personalizing risk assessment among women with LCIS and highlight the importance of chemoprevention counseling for risk reduction.

Association of Omentin-1 with Oxidative Stress and Clinical Significances in Patients with Breast Cancer

Purpose: Breast cancer (BC) is globally the main reason of cancer-related deaths in women. Omentin-1, an anti-inflammatory and antioxidant adipokine, plays different roles in tumorigenesis and anti-oncogenic pathways. In present study, we investigated the association of omentin-1 with oxidative stress and clinical significances in healthy controls and BC patients to assess the prognostic and diagnostic value of omentin-1 in this cancer.

Methods: This case-control study included 88 BC patients and 86 healthy controls. The serum levels of omentin-1 were assessed by enzyme-linked immunosorbent assays methods. Also, total antioxidant capacity (TAC), total oxidant status (TOS) and malondialdehyde (MDA) serum levels were measured by spectrophotometer. quantitative real-time polymerase chain reaction (qRT-PCR) was applied to the measurement of gene expression of omentin-1.

Results: the serum levels of omentin-1 were significantly lower in the BC patients compared to the healthy controls (P<0.001). Moreover, gene expression of omentin-1was significantly downregulated in the BC tissues compared to the adjacent normal tissues (P<0.001). Gene expression of omentin-1and its serum levels were significantly higher in grade I compared with grade II and III (P=0.001, P<0.001, respectively). Additionally, the serum levels of omentin-1 in the p53-positive BC patients were significantly higher than the p53-negative BC patients (P=0.001). There was an inverse correlation between the serum levels of MDA and TOS with the serum levels of omentin-1 (r=-0.436, r=-461, respectively).

Conclusion: We conclude that omentin-1 may have a good prognostic and diagnostic roles in the BC patients and decreases oxidative stress in these patients.

Combined effect of volumetric breast density and body mass index on breast cancer risk

BACKGROUND

Breast density and body mass index (BMI) are used for breast cancer risk stratification. We evaluate whether the positive association between volumetric breast density and breast cancer risk is strengthened with increasing BMI.

METHODS

The San Francisco Mammography Registry and Mayo Clinic Rochester identified 781 premenopausal and 1850 postmenopausal women with breast cancer diagnosed between 2007 and 2015 that had a screening digital mammogram at least 6 months prior to diagnosis. Up to three controls (N = 3535) were matched per case on age, race, date, mammography machine, and state. Volumetric percent density (VPD) and dense volume (DV) were measured with Volpara™. Breast cancer risk was assessed with logistic regression stratified by menopause status. Multiplicative interaction tests assessed whether the association of density measures was differential by BMI categories.

RESULTS

The increased risk of breast cancer associated with VPD was strengthened with higher BMI for both premenopausal (p_interaction = 0.01) and postmenopausal (p_interaction = 0.0003) women. For BMI < 25, 25-30, and ≥ 30 kg/m², ORs for breast cancer for a 1 SD increase in VPD were 1.24, 1.65, and 1.97 for premenopausal, and 1.20, 1.55, and 2.25 for postmenopausal women, respectively. ORs for breast cancer for a 1 SD increase in DV were 1.39, 1.33, and 1.51 for premenopausal (p_interaction = 0.58), and 1.31, 1.34, and 1.65 (p_interaction = 0.03) for postmenopausal women for BMI < 25, 25-30 and ≥ 30 kg/m², respectively.

CONCLUSIONS

The effect of volumetric percent density on breast cancer risk is strongest in overweight and obese women. These associations have clinical relevance for informing prevention strategies.

Adjusting for BMI in analyses of volumetric mammographic density and breast cancer risk

BACKGROUND

Fully automated assessment of mammographic density (MD), a biomarker of breast cancer risk, is being increasingly performed in screening settings. However, data on body mass index (BMI), a confounder of the MD-risk association, are not routinely collected at screening. We investigated whether the amount of fat in the breast, as captured by the amount of mammographic non-dense tissue seen on the mammographic image, can be used as a proxy for BMI when data on the latter are unavailable.

METHODS

Data from a UK case control study (numbers of cases/controls: 414/685) and a Norwegian cohort study (numbers of cases/non-cases: 657/61059), both with volumetric MD measurements (dense volume (DV), non-dense volume (NDV) and percent density (%MD)) from screening-age women, were analysed. BMI (self-reported) and NDV were taken as measures of adiposity. Correlations between BMI and NDV, %MD and DV were examined after log-transformation and adjustment for age, menopausal status and parity. Logistic regression models were fitted to the UK study, and Cox regression models to the Norwegian study, to assess associations between MD and breast cancer risk, expressed as odds/hazard ratios per adjusted standard deviation (OPERA). Adjustments were first made for standard risk factors except BMI (minimally adjusted models) and then also for BMI or NDV. OPERA pooled relative risks (RRs) were estimated by fixed-effect models, and between-study heterogeneity was assessed by the I2 statistics.

RESULTS

BMI was positively correlated with NDV (adjusted r = 0.74 in the UK study and r = 0.72 in the Norwegian study) and with DV (r = 0.33 and r = 0.25, respectively). Both %MD and DV were positively associated with breast cancer risk in minimally adjusted models (pooled OPERA RR (95% confidence interval): 1.34 (1.25, 1.43) and 1.46 (1.36, 1.56), respectively; I2 = 0%, P >0.48 for both). Further adjustment for BMI or NDV strengthened the %MD-risk association (1.51 (1.41, 1.61); I2 = 0%, P = 0.33 and 1.51 (1.41, 1.61); I2 = 0%, P = 0.32, respectively). Adjusting for BMI or NDV marginally affected the magnitude of the DV-risk association (1.44 (1.34, 1.54); I2 = 0%, P = 0.87 and 1.49 (1.40, 1.60); I2 = 0%, P = 0.36, respectively).

CONCLUSIONS

When volumetric MD-breast cancer risk associations are investigated, NDV can be used as a measure of adiposity when BMI data are unavailable.

Can Dietary and Physical Activity Modifications Reduce Breast Density in Postmenopausal Women? The DAMA Study, a Randomized Intervention Trial in Italy

BACKGROUND

Few randomized trials have been carried out to evaluate the effect of lifestyle modifications on mammographic breast density (MBD). The randomized 2 × 2 factorial Diet, physical Activity and MAmmography trial aimed to evaluate whether MBD can be reduced in postmenopausal women with high baseline MBD by a 24-month dietary and/or physical activity (PA) interventions.

METHODS

We randomized healthy postmenopausal women, attending the Florence (Italy) mammographic screening program, ages 50 to 69 years, nonsmokers, with MBD > 50% and no recent hormone therapy, to (i) a dietary intervention focused on plant foods, with a low glycemic load, low in saturated fats and alcohol; (ii) a PA intervention combining daily moderate intensity activities and one weekly supervised session of more strenuous activity; (iii) both interventions; (iv) general recommendations. We evaluated changes in MBD based on Volpara estimates comparing baseline and follow-up digital mammograms by an intention-to-treat-analysis.

RESULTS

MBD measures were available for 226 participants. An interaction emerged between treatments and thus we run analyses by arms. A decrease in volumetric percent density emerged for women in the dietary intervention (ratio 0.91; 95% CI, 0.86-0.97; P = 0.002) and in the PA intervention arm (0.93; 95% CI, 0.87-0.98; P = 0.01) in comparison with controls. No clear effect emerged in the double intervention arm.

CONCLUSIONS

This intervention trial suggests that a 24-month dietary or PA intervention may reduce MBD in postmenopausal women.

IMPACT

A modification of dietary habits or an increase in PA in postmenopausal women may reduce MBD. Further studies are needed to confirm these findings for planning breast cancer preventive strategies.

Vaginal estrogen and mammogram results: case series and review of literature on treatment of genitourinary syndrome of menopause (GSM) in breast cancer survivors

OBJECTIVE

To examine mammographic density before and after at least 1 year of vaginal estrogen use in a small cohort of healthy postmenopausal women and women with a personal history of breast cancer.

METHODS

We extracted data via chart review of patients from a single practitioner's menopause specialty clinic in Baltimore, MD. Mammographic change was primarily determined via the Bi-RADS scoring system, including the Bi-RADS density score. In addition, we conduct a narrative review of the current literature on the usage of local estrogen therapy, and systemic and local alternatives in the treatment of genitourinary syndrome of menopause (GSM) in breast cancer survivors.

RESULTS

Twenty healthy postmenopausal women and three breast cancer survivors fit our inclusion criteria. Amongst these two groups, we did not find an increase in mammographic density after at least 1 year and up to 18 years of local vaginal estrogen. Ospemifene use in one patient did not appear to be associated with any change in Bi-RADS score. Our narrative review found little data on the effects of vaginal estrogen therapy or newer alternative systemic therapies such as ospemifene on mammographic density.

CONCLUSIONS

Low-dose vaginal estrogen use for 1 or more years in a small cohort of women with GSM did not appear to be associated with any changes in breast density or Bi-RADS breast cancer risk scores in the majority of study participants, including three breast cancer survivors. Larger long-term controlled clinical trials should be conducted to examine the effects of low-dose vaginal estrogen on mammographic density in women with and without a personal history of breast cancer. Furthermore, relative efficacy and risk of vaginal estrogen compared with other forms of treatment for GSM should also be studied in long-term trials.