Breast fat and breast cancer

The Associations between Intakes of One-Carbon Metabolism-Related Vitamins and Breast Density among Young Women

BACKGROUND

Folate is the primary methyl donor and B vitamins are cofactors for one-carbon metabolism that maintain DNA integrity and epigenetic signatures implicated in carcinogenesis. Breast tissue is particularly susceptible to stimuli in early life. Only limited data are available on associations of one-carbon metabolism-related vitamin intake during youth and young adulthood with breast density, a strong risk factor for breast cancer.

METHODS

Over 18 years in the DISC and DISC06 Follow-up Study, diets of 182 young women were assessed by three 24-hour recalls on five occasions at ages 8 to 18 years and once at 25 to 29 years. Multivariable-adjusted linear mixed-effects regression was used to examine associations of intakes of one-carbon metabolism-related vitamins with MRI-measured percent dense breast volume (%DBV) and absolute dense breast volume (ADBV) at ages 25 to 29 years.

RESULTS

Folate intake in youth was inversely associated with %DBV (Ptrend = 0.006) and ADBV (Ptrend = 0.02). These inverse associations were observed with intake during post-, though not premenarche. In contrast, premenarche vitamin B2 intake was positively associated with ADBV (Ptrend < 0.001). Young adult folate and vitamin B6 intakes were inversely associated with %DBV (all Ptrend ≤ 0.04), whereas vitamins B6 and B12 were inversely associated with ADBV (all Ptrend ≤ 0.04).

CONCLUSIONS

Among these DISC participants intakes of one-carbon metabolism-related vitamins were associated with breast density. Larger prospective studies among diverse populations are needed to replicate these findings.

IMPACT

Our results suggest the importance of one-carbon metabolism-related vitamin intakes early in life with development of breast density and thereby potentially breast cancer risk later in life.

Genetic architecture of mammographic density as a risk factor for breast cancer: a systematic review

BACKGROUND

Mammography Density (MD) is a potential risk marker that is influenced by genetic polymorphisms and can subsequently modulate the risk of breast cancer. This qualitative systematic review summarizes the genes and biological pathways involved in breast density and discusses the potential clinical implications in view of the genetic risk profile for breast density.

METHODS

The terms related to "Common genetic variations" and "Breast density" were searched in Scopus, PubMed, and Web of Science databases. Gene pathways analysis and assessment of protein interactions were also performed.

RESULTS

Eighty-six studies including 111 genes, reported a significant association between mammographic density in different populations. ESR1, IGF1, IGFBP3, and ZNF365 were the most prevalent genes. Moreover, estrogen metabolism, signal transduction, and prolactin signaling pathways were significantly related to the associated genes. Mammography density was an associated phenotype, and eight out of 111 genes, including COMT, CYP19A1, CYP1B1, ESR1, IGF1, IGFBP1, IGFBP3, and LSP1, were modifiers of this trait.

CONCLUSION

Genes involved in developmental processes and the evolution of secondary sexual traits play an important role in determining mammographic density. Due to the effect of breast tissue density on the risk of breast cancer, these genes may also be associated with breast cancer risk.

Deciphering how early life adiposity influences breast cancer risk using Mendelian randomization

Studies suggest that adiposity in childhood may reduce the risk of breast cancer in later life. The biological mechanism underlying this effect is unclear but is likely to be independent of body size in adulthood. Using a Mendelian randomization framework, we investigate 18 hypothesised mediators of the protective effect of childhood adiposity on later-life breast cancer, including hormonal, reproductive, physical, and glycaemic traits. Our results indicate that, while most of the hypothesised mediators are affected by childhood adiposity, only IGF-1 (OR: 1.08 [1.03: 1.15]), testosterone (total/free/bioavailable ~ OR: 1.12 [1.05: 1.20]), age at menopause (OR: 1.05 [1.03: 1.07]), and age at menarche (OR: 0.92 [0.86: 0.99], direct effect) influence breast cancer risk. However, multivariable Mendelian randomization analysis shows that the protective effect of childhood body size remains unaffected when accounting for these traits (ORs: 0.59-0.67). This suggests that none of the investigated potential mediators strongly contribute to the protective effect of childhood adiposity on breast cancer risk individually. It is plausible, however, that several related traits could collectively mediate the effect when analysed together, and this work provides a compelling foundation for investigating other mediating pathways in future studies.

Crown-Like Structures in Breast Adipose Tissue: Early Evidence and Current Issues in Breast Cancer

Obesity is an established risk factor for postmenopausal breast cancer and has been linked to worse breast cancer prognosis, most clearly for hormone receptor-positive breast cancers. The underlying mechanisms of the obesity-breast cancer association are not fully understood, but growing evidence points to the breast adipose tissue microenvironment playing an important role. Obesity-induced adipose tissue dysfunction can result in a chronic state of low-grade inflammation. Crown-like structures of the breast (CLS-B) were recently identified as a histologic marker of local inflammation. In this review, we evaluate the early evidence of CLS-B in breast cancer. Data from preclinical and clinical studies show that these inflammatory lesions within the breast are associated with local NF-κB activation, increased aromatase activity, and elevation of pro-inflammatory mediators (TNFα, IL-1β, IL-6, and COX-2-derived PGE2)-factors involved in multiple pathways of breast cancer development and progression. There is also substantial evidence from epidemiologic studies that CLS-B are associated with greater adiposity among breast cancer patients. However, there is insufficient evidence that CLS-B impact breast cancer risk or prognosis. Comparisons across studies of prognosis were complicated by differences in CLS-B evaluation and deficiencies in study design, which future studies should take into consideration. Breast adipose tissue inflammation provides a plausible explanation for the obesity-breast cancer association, but further study is needed to establish its role and whether markers such as CLS-B are clinically useful.

Molecular insights into the interplay between adiposity, breast cancer and bone metastasis

Cancer is a complex disease, with various pre-existing health ailments enhancing its pathology. In cancer, the extracellular environment contains various intrinsic physiological factors whose levels are altered with aging and pre-existing conditions. In obesity, the tumor microenvironment and metastases are enriched with factors that are both derived locally, and from other physiological compartments. Similarly, in obesity, the cancer cell environment both at the site of origin and at the secondary site i.e., metastatic niche, contains significantly more phenotypically-altered adipocytes than that of un-obese cancer patients. Indeed, obesity has been linked with cancer progression, metastasis, and therapy resistance. Adipocytes not only interact with tumor cells, but also with adjacent stromal cells at primary and metastatic sites. This review emphasizes the importance of bidirectional interactions between adipocytes and breast tumor cells in breast cancer progression and its bone metastases. This paper not only chronicles the role of various adipocyte-derived factors in tumor growth, but also describes the significance of adipocyte-derived bone metastatic factors in the development of bone metastasis of breast cancer. It provides a molecular view of the interplay between the adipocytes and tumor cells involved in breast cancer bone metastasis. However, more research is needed to determine if targeting cancer-associated adipocytes holds promise as a potential therapeutic approach for breast cancer bone metastasis treatment. Interplay between adipocytes and breast cancer cells at primary cancer site and metastatic bone microenvironment. AMSC Adipose-derived mesenchymal stem cell, CAA Cancer associated adipocytes, CAF Cancer associated fibroblast, BMSC Bone marrow derived mesenchymal stem cell, BMA Bone marrow adipocyte.

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.

In utero DDT exposure and breast density before age 50

Prior studies in the Child Health and Development Studies (CHDS) found in utero exposure to the pesticide, dichlorodiphenyltrichloroethane (DDT), increased breast cancer risk by age 52. Mammographic density is considered a primary risk factor for breast cancer. We conducted a study of 309 daughters from the CHDS to examine in utero DDT exposure and mammographic density in midlife. Among daughters with high (>75th percentile) exposure to p,p'-Dichlorodiphenyldichloroethylene (DDE), p,p'-DDT was significantly correlated with increased dense area and percent density regardless of her body mass in midlife. In the subset of women with lower (<75th percentile) p,p-DDE, p,p'-DDT was associated with increased non-dense breast area. This was explained by adjustment for midlife BMI suggesting that p,p'-DDT may be obesogenic. In aggregate our findings indicate that early life p,p'-DDT exposure impacts breast density in a complex way that depends on the hosts biological ability to sequester and process DDT and levels of exposure.

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.

Association between mammographic density and tumor marker-defined breast cancer subtypes: a case-control study

High mammographic density (MD) is the most important risk factor for breast cancer. This study aimed to clarify the relationship between MD and breast cancer subtypes defined by tumor markers. We enrolled 642 women with breast cancer (69% premenopausal) and 1241 controls matched for age and menopausal status. Absolute mammographic dense area (ADA), percent mammographic dense area (PDA), and nondense area were assessed using a computer-assisted thresholding technique. We classified breast cancer cases into four subtypes using information on tumor marker expression such as estrogen receptor (ER), progesterone receptor (PR), and Cerb2 receptor (HER2); luminal A (ER+ and/or PR+, HER2-), luminal B (ER+ and/or PR+, HER2+), HER2-overexpressing (ER-, PR-, and HER2+), and triple-negative (ER-, PR-, and HER2-). Analysis was carried out using a conditional logistic regression model with adjustment for covariates. ADA and PDA were associated positively with the risk of breast cancer overall. Both ADA and PDA tended to have a positive association with breast cancer with any ER, any PR, or HER2-, but not for HER2+. The risk of luminal A breast cancer increased significantly 1.11 times (95% confidence interval: 1.01-1.23) for ADA and 1.12 times (95% confidence interval: 1.01-1.24) for PDA, estimated per 1 SD of the age and BMI-adjusted MD. However, the risk of breast cancer with luminal B, HER2-overexpressing, and triple-negative subtypes did not differ (P>0.10). Differential associations between MD measures and breast cancer by tumor marker status or tumor marker-defined subtypes were not detected. These findings suggested that the association between MD and breast cancer subtype may be because of other causal pathways.

Obesity-Linked Cancers: Current Knowledge, Challenges and Limitations in Mechanistic Studies and Rodent Models

The worldwide prevalence of obesity has doubled during the last 50 years, and according to the World Obesity Federation, one third of the people on Earth will be obese by the year 2025. Obesity is described as a chronic, relapsing and multifactorial disease that causes metabolic, biomechanical, and psychosocial health consequences. Growing evidence suggests that obesity is a risk factor for multiple cancer types and rivals smoking as the leading preventable cause for cancer incidence and mortality. The epidemic of obesity will likely generate a new wave of obesity-related cancers with high aggressiveness and shortened latency. Observational studies have shown that from cancer risk to disease prognosis, an individual with obesity is consistently ranked worse compared to their lean counterpart. Mechanistic studies identified similar sets of abnormalities under obesity that may lead to cancer development, including ectopic fat storage, altered adipokine profiles, hormone fluctuations and meta-inflammation, but could not explain how these common mechanisms produce over 13 different cancer types. A major hurdle in the mechanistic underpinning of obesity-related cancer is the lack of suitable pre-clinical models that spontaneously develop obesity-linked cancers like humans. Current approaches and animal models fall short when discerning the confounders that often coexist in obesity. In this mini-review, we will briefly survey advances in the different obesity-linked cancers and discuss the challenges and limitations in the rodent models employed to study their relationship. We will also provide our perspectives on the future of obesity-linked cancer research.

Association of Body Mass Index and Age With Subsequent Breast Cancer Risk in Premenopausal Women

Importance

The association between increasing body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) and risk of breast cancer is unique in cancer epidemiology in that a crossover effect exists, with risk reduction before and risk increase after menopause. The inverse association with premenopausal breast cancer risk is poorly characterized but might be important in the understanding of breast cancer causation.

Objective

To investigate the association of BMI with premenopausal breast cancer risk, in particular by age at BMI, attained age, risk factors for breast cancer, and tumor characteristics.

Design, Setting, and Participants

This multicenter analysis used pooled individual-level data from 758 592 premenopausal women from 19 prospective cohorts to estimate hazard ratios (HRs) of premenopausal breast cancer in association with BMI from ages 18 through 54 years using Cox proportional hazards regression analysis. Median follow-up was 9.3 years (interquartile range, 4.9-13.5 years) per participant, with 13 082 incident cases of breast cancer. Participants were recruited from January 1, 1963, through December 31, 2013, and data were analyzed from September 1, 2013, through December 31, 2017.

Exposures

Body mass index at ages 18 to 24, 25 to 34, 35 to 44, and 45 to 54 years.

Main Outcomes and Measures

Invasive or in situ premenopausal breast cancer.

Results

Among the 758 592 premenopausal women (median age, 40.6 years; interquartile range, 35.2-45.5 years) included in the analysis, inverse linear associations of BMI with breast cancer risk were found that were stronger for BMI at ages 18 to 24 years (HR per 5 kg/m2 [5.0-U] difference, 0.77; 95% CI, 0.73-0.80) than for BMI at ages 45 to 54 years (HR per 5.0-U difference, 0.88; 95% CI, 0.86-0.91). The inverse associations were observed even among nonoverweight women. There was a 4.2-fold risk gradient between the highest and lowest BMI categories (BMI≥35.0 vs <17.0) at ages 18 to 24 years (HR, 0.24; 95% CI, 0.14-0.40). Hazard ratios did not appreciably vary by attained age or between strata of other breast cancer risk factors. Associations were stronger for estrogen receptor-positive and/or progesterone receptor-positive than for hormone receptor-negative breast cancer for BMI at every age group (eg, for BMI at age 18 to 24 years: HR per 5.0-U difference for estrogen receptor-positive and progesterone receptor-positive tumors, 0.76 [95% CI, 0.70-0.81] vs hormone receptor-negative tumors, 0.85 [95% CI: 0.76-0.95]); BMI at ages 25 to 54 years was not consistently associated with triple-negative or hormone receptor-negative breast cancer overall.

Conclusions and Relevance

The results of this study suggest that increased adiposity is associated with a reduced risk of premenopausal breast cancer at a greater magnitude than previously shown and across the entire distribution of BMI. The strongest associations of risk were observed for BMI in early adulthood. Understanding the biological mechanisms underlying these associations could have important preventive potential.

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

Excess total body fat and abdominal adipose tissue are recognized risk factors for metabolic diseases but also for some types of cancers, including breast cancer. Several biological mechanisms in connection with local and systemic effects of adiposity are believed to be implicated in breast cancer development, and may involve breast fat. Breast adipose tissue can be studied through mammography by looking at breast density features such as the nondense area mainly composed of fat, or the percent breast density, which is the proportion of fibroglandular tissue in relation to fat. The relation between adiposity, breast density features, and breast cancer is complex. Studies suggest a paradoxical association as adiposity and absolute nondense area correlate positively with each other, but in contrast to adiposity, absolute nondense area seems to be associated negatively with breast cancer risk. As breast density is one of the strongest risk factors for breast cancer, it is therefore critical to understand how these factors interrelate. In this review, we discuss these relations by first presenting how adiposity measurements and breast density features are linked to breast cancer risk. Then, we used a systematic approach to capture the literature to review the relation between adiposity and breast density features. Finally, the role of adipose tissue in carcinogenesis is discussed briefly from a biological perspective.

Mammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study

BACKGROUND

Risk of screen-detected breast cancer mostly reflects inherent risk, while risk of interval cancer reflects inherent risk and risk of masking (risk of the tumor not being detected due to increased dense tissue). Therefore the predictors of whether a breast cancer is interval or screen-detected include those that predict masking. Our aim was to investigate the associations between mammographic measures and (1) inherent risk, and (2) masking.

METHODS

We conducted a case-control study nested within the Melbourne collaborative cohort study of 244 screen-detected cases (192 small tumors (<2 cm)) matched to 700 controls and 148 interval cases (76 small tumors) matched to 446 controls. Dense area (DA), percent dense area (PDA), and non-dense area (NDA) were measured using the Cumulus software. Conditional and unconditional logistic regression were applied as appropriate to estimate the odds per adjusted standard deviation (OPERA) adjusted for age and body mass index (BMI), allowing for the association with BMI to be a function of age at diagnosis. Tests of fit were performed using the Bayesian information criterion (BIC) and the area under the receiver operating characteristic curve.

RESULTS

For screen-detected cancer, the association with BMI had a marginally significant dependence on age at diagnosis, and after adjustment both DA and PDA were associated with risk (OPERA approximately 1.2) and gave a similar fit. NDA was not associated with risk. For interval cancer, the BMI risk association was not dependent on age at diagnosis and the best fitting model was PDA alone (OPERA = 2.24, 95 % confidence interval 1.75, 2.86). Prediction of interval versus screen-detected cancer was best achieved by PDA alone (OPERA = 1.76, 95 % confidence interval 1.39, 2.22) with no association with BMI. When the analysis was restricted to small tumors to reduce the influence of tumor growth, we obtained similar results.

CONCLUSIONS

Inherent breast cancer risk is predicted by BMI and DA or PDA, but not NDA. Masking is predicted by PDA, and not by BMI. Understanding risk and masking could help tailor mammographic screening.

Anthropometric factors, adult weight gain, and mammographic features

PURPOSE

To evaluate the association between anthropometric factors, weight gain during adulthood, and mammographic features among 1,435 women recruited at screening mammography.

METHODS

Spearman's partial coefficients were used to evaluate the correlation of anthropometric factors with mammographic features (percent density, absolute dense area, and non-dense area). Multivariate generalized linear models were used to evaluate the associations between weight change categories and mammographic features.

RESULTS

Body mass index was inversely correlated with percent density (r = -0.49, p < 0.0001) or absolute dense area (r = -0.21, p < 0.0001) and positively correlated with absolute non-dense area (r = 0.69, p < 0.0001). However, body mass index was positively correlated with absolute dense area when adjusting for absolute non-dense area (r = 0.16, p < 0.0001). Similar results were observed for weight, waist circumference, and waist-to-hip ratio with mammographic features. Within increasing categories of weight change, percent density (p trend < 0.0001) and absolute dense area (p trend = 0.025) increased, while absolute non-dense area decreased (p trend < 0.0001). After stratification by the median of non-dense area, the positive association between weight gain and absolute dense area remained only among women with higher non-dense area.

CONCLUSIONS

Adiposity seems positively associated with both dense and non-dense areas following adjustment for each other. Our findings suggest a higher breast dense area among women who gained weight and that a minimum of breast fat may be needed to promote the proliferation of this fibroglandular tissue.

Postmenopausal mammographic breast density and subsequent breast cancer risk according to selected tissue markers

BACKGROUND

This study aimed to determine if associations of pre-diagnostic percent breast density, absolute dense area, and non-dense area with subsequent breast cancer risk differ by the tumour's molecular marker status.

METHODS

We included 1010 postmenopausal women with breast cancer and 2077 matched controls from the Nurses' Health Study (NHS) and the Nurses' Health Study II (NHS II) cohorts. Breast density was estimated from digitised film mammograms using computer-assisted thresholding techniques. Information on breast cancer risk factors was obtained prospectively from biennial questionnaires. Polychotomous logistic regression was used to assess associations of breast density measures with tumour subtypes by the status of selected tissue markers. All tests of statistical significance were two sided.

RESULTS

The association of percent density with breast cancer risk appeared to be stronger in ER- as compared with ER+ tumours, but the difference did not reach statistical significance (density ⩾50% vs <10% odds ratio (OR)=3.06, 95% confidence interval (CI) 2.17-4.32 for ER+; OR=4.61, 95% CI 2.36-9.03 for ER-, Pheterogeneity=0.08). Stronger positive associations were found for absolute dense area and CK5/6- and EGFR- as compared with respective marker-positive tumours (Pheterogeneity=0.002 and 0.001, respectively). Stronger inverse associations of non-dense area with breast cancer risk were found for ER- as compared with ER+ tumours (Pheterogeneity=0.0001) and for AR+, CK5/6+, and EGFR+ as compared with respective marker-negative tumours (Pheterogeneity=0.03, 0.005, and 0.009, respectively). The associations of density measures with breast cancer did not differ by progesterone receptor and human epidermal growth factor receptor 2 status.

CONCLUSIONS

Breast density influences the risk of breast cancer subtypes by potentially different mechanisms.

Dense and nondense mammographic area and risk of breast cancer by age and tumor characteristics

BACKGROUND

Mammographic density (MD) is a strong breast cancer risk factor. We previously reported associations of percent mammographic density (PMD) with larger and node-positive tumors across all ages, and estrogen receptor (ER)-negative status among women ages <55 years. To provide insight into these associations, we examined the components of PMD [dense area (DA) and nondense area (NDA)] with breast cancer subtypes.

METHODS

Data were pooled from six studies including 4,095 breast cancers and 8,558 controls. DA and NDA were assessed from digitized film-screen mammograms and standardized across studies. Breast cancer odds by density phenotypes and age according to histopathologic characteristics and receptor status were calculated using polytomous logistic regression.

RESULTS

DA was associated with increased breast cancer risk [OR for quartiles: 0.65, 1.00 (Ref), 1.22, 1.55; P(trend) <0.001] and NDA was associated with decreased risk [ORs for quartiles: 1.39, 1.00 (Ref), 0.88, 0.72; P(trend) <0.001] across all ages and invasive tumor characteristics. There were significant trends in the magnitude of associations of both DA and NDA with breast cancer by increasing tumor size (P(trend) < 0.001) but no differences by nodal status. Among women <55 years, DA was more strongly associated with increased risk of ER(+) versus ER(-) tumors (P(het) = 0.02), while NDA was more strongly associated with decreased risk of ER(-) versus ER(+) tumors (P(het) = 0.03).

CONCLUSIONS

DA and NDA have differential associations with ER(+) versus ER(-) tumors that vary by age.

IMPACT

DA and NDA are important to consider when developing age- and subtype-specific risk models.

Mammographic density phenotypes and risk of breast cancer: a meta-analysis

BACKGROUND

Fibroglandular breast tissue appears dense on mammogram, whereas fat appears nondense. It is unclear whether absolute or percentage dense area more strongly predicts breast cancer risk and whether absolute nondense area is independently associated with risk.

METHODS

We conducted a meta-analysis of 13 case-control studies providing results from logistic regressions for associations between one standard deviation (SD) increments in mammographic density phenotypes and breast cancer risk. We used random-effects models to calculate pooled odds ratios and 95% confidence intervals (CIs). All tests were two-sided with P less than .05 considered to be statistically significant.

RESULTS

Among premenopausal women (n = 1776 case patients; n = 2834 control subjects), summary odds ratios were 1.37 (95% CI = 1.29 to 1.47) for absolute dense area, 0.78 (95% CI = 0.71 to 0.86) for absolute nondense area, and 1.52 (95% CI = 1.39 to 1.66) for percentage dense area when pooling estimates adjusted for age, body mass index, and parity. Corresponding odds ratios among postmenopausal women (n = 6643 case patients; n = 11187 control subjects) were 1.38 (95% CI = 1.31 to 1.44), 0.79 (95% CI = 0.73 to 0.85), and 1.53 (95% CI = 1.44 to 1.64). After additional adjustment for absolute dense area, associations between absolute nondense area and breast cancer became attenuated or null in several studies and summary odds ratios became 0.82 (95% CI = 0.71 to 0.94; P heterogeneity = .02) for premenopausal and 0.85 (95% CI = 0.75 to 0.96; P heterogeneity < .01) for postmenopausal women.

CONCLUSIONS

The results suggest that percentage dense area is a stronger breast cancer risk factor than absolute dense area. Absolute nondense area was inversely associated with breast cancer risk, but it is unclear whether the association is independent of absolute dense area.

Associations of mammographic dense and nondense areas and body mass index with risk of breast cancer

Mammographic density measurements are associated with risk of breast cancer. Few studies have investigated the concurrent associations of mammographic dense and nondense areas, body mass index (weight (kg)/height (m)(2)), and ages at mammogram and diagnosis with breast cancer risk. We conducted a matched, case-control study nested within the Melbourne Collaborative Cohort Study (cohort recruitment in 1990-1994 and follow-up until 2007) to estimate the associations between these factors and breast cancer risk under alternative causal models. Mammographic dense area was positively associated with risk, and the strength of this association was only slightly influenced by the choice of the causal model (relative risk per 1 standard deviation = 1.50, 95% confidence interval: 1.32, 1.70). Mammographic nondense area was inversely associated with risk under the assumption that fat in the body and fat in the breast cause breast cancer through independent mechanisms (relative risk per 1 standard deviation = 0.75, 95% confidence interval: 0.65, 0.86), whereas it was not associated with risk under the assumption that they are both proxies of adiposity. Knowledge about the biological mechanisms regulating the role played by mammographic nondense area and body fat on breast cancer risk is essential to better estimate their impacts on individual risk.

Body size throughout the life course and mammographic density in Mexican women

Mammographic density (MD) is a strong risk factor for breast cancer, but the biological mechanism underlying this association is not clear. Current adult body mass index (BMI) is inversely associated with percent MD; however, few studies have included Hispanic women or evaluated associations with measures of body fatness earlier in life. ESMaestras was established in 2006, when 28,345 women ages ≥35 responded to a detailed questionnaire that assessed possible disease risk factors, including body fatness in childhood, adolescence, and young adulthood. In 2007, 2084 ESMaestras participants underwent a clinical examination, which included measurements of weight, height, and sitting height and a mammogram. We measured percent MD using a computer-assisted method. The current analysis includes 972 premenopausal and 559 postmenopausal women. We used multivariable linear regression to evaluate associations between measures of body size and MD, independent of current BMI. Among pre- and postmenopausal women, we observed no significant associations between body fatness during childhood, adolescence, or young adulthood and percent MD. Among postmenopausal women, we observed a modest positive association between body fatness immediately before first pregnancy and between ages 25 and 35 after adjustment for current BMI, with differences of 4.9 and 3.6 % points, respectively, in percent MD between the heaviest and leanest women (p-trend = 0.02). There were no significant associations between height, sitting height, and percent MD among pre- or postmenopausal women in multivariable models adjusting for BMI. In general, we found no clear associations between measures of body size in early life, current sitting height, or current height, and percent MD, after adjusting for current BMI, in this population of Mexican women. Our observation of a positive association between early adult body fatness (i.e., before first pregnancy and ages 25-35) and percent MD among postmenopausal women is inconsistent with prior research and requires confirmation in other studies.