Environmental exposures during windows of susceptibility for breast cancer: a framework for prevention research.

BackgroundThe long time from exposure to potentially harmful chemicals until breast cancer occurrence poses challenges for designing etiologic studies and for implementing successful prevention programs. Growing evidence from animal and human studies indicates that distinct time periods of heightened susceptibility to endocrine disruptors exist throughout the life course. The influence of environmental chemicals on breast cancer risk may be greater during several windows of susceptibility (WOS) in a woman's life, including prenatal development, puberty, pregnancy, and the menopausal transition. These time windows are considered as specific periods of susceptibility for breast cancer because significant structural and functional changes occur in the mammary gland, as well as alterations in the mammary micro-environment and hormone signaling that may influence risk. Breast cancer research focused on these breast cancer WOS will accelerate understanding of disease etiology and prevention.Main textDespite the plausible heightened mechanistic influences of environmental chemicals on breast cancer risk during time periods of change in the mammary gland's structure and function, most human studies of environmental chemicals are not focused on specific WOS. This article reviews studies conducted over the past few decades that have specifically addressed the effect of environmental chemicals and metals on breast cancer risk during at least one of these WOS. In addition to summarizing the broader evidence-base specific to WOS, we include discussion of the NIH-funded Breast Cancer and the Environment Research Program (BCERP) which included population-based and basic science research focused on specific WOS to evaluate associations between breast cancer risk and particular classes of endocrine-disrupting chemicals-including polycyclic aromatic hydrocarbons, perfluorinated compounds, polybrominated diphenyl ethers, and phenols-and metals. We outline ways in which ongoing transdisciplinary BCERP projects incorporate animal research and human epidemiologic studies in close partnership with community organizations and communication scientists to identify research priorities and effectively translate evidence-based findings to the public and policy makers.ConclusionsAn integrative model of breast cancer research is needed to determine the impact and mechanisms of action of endocrine disruptors at different WOS. By focusing on environmental chemical exposure during specific WOS, scientists and their community partners may identify when prevention efforts are likely to be most effective

Tibolone and Breast Tissue: a Review

The safety profile of hormone replacement therapy (HRT) on breast is still controversial. Tibolone is an option of treatment for climacteric syndrome of postmenopausal women. Its risk profile on breast is debated. This is an updated narrative review focusing on the impact of tibolone on breast. Particularly, we will report data from major preclinical and clinical studies regarding the effects of the use of this compound on breast tissue and breast density. Moreover, we will analyze and discuss the most relevant findings of the principal studies evaluating the relationship between tibolone and breast cancer risk. Our purpose is making all clinicians who are particularly involved in women’s health more aware of the effects of this compound on breast and, thus, more experienced in the management of menopausal symptoms with this drug. According to the available literature, tibolone seems to be characterized by an interesting safety profile on breast tissue

Inflammation and Breast Cancer Risk

Mammographic density is one of the strongest risk factors for breast cancer. Exactly how breast density increases breast cancer risk is unknown, although it is believed that dense breast areas may reflect exposure to estrogen. Breast cancer incidence is highest in postmenopause, when most estrogens are produced in non-ovarian tissues. Cyclooxygenase (COX)-2 and the cytokine tumor necrosis factor (TNF)-alpha may play a role in regulating estrogen synthesis in postmenopausal women. The aim of the present study was to explore the association between inflammation and breast cancer risk in two populations of postmenopausal women. Different exposures associated with inflammation (non-steroidal anti-inflammatory drug (NSAID) use, circulating receptors for TNF-alpha, and a polymorphism in the TNF receptor-II gene) were measured and tested for their association with incident breast cancer or mammographic density. In the first study, the Study of Osteoporotic Fractures (SOF), complete NSAID medication and breast cancer risk factor information was available for 6695 women, mean (SD) age 73 (5) years. During a mean (SD) of 13.2 (3.8) years of follow-up, 372 women were diagnosed with primary breast cancer. There were no differences in incident breast cancer by NSAID use, either before or after adjusting for covariates. In the second study, Mammograms and Masses (MAMS), mean mammographic density was lower among women in the highest quartiles of circulating soluble TNF receptor levels. After adjustment for body mass index, the inverse association disappeared. In evaluating the TNFR2 -196 M/R polymorphism (T>G), the unadjusted mean (SD) mammographic density was higher in women with the TT genotype (32.3% (21.0)) as compared to women with the TG/GG genotypes (26.6% (17.2)), p=0.003. The association remained statistically significant after adjustment for age and BMI (p=0.03); however, inclusion of additional covariates reduced the level of statistical significance (p=0.08). There was no observable difference in circulating sTNFR2 levels between the TNFR2 genotypes. An increased understanding of factors that affect mammographic density and their underlying mechanisms is needed, and inflammation may be involved. An association between breast cancer risk and inflammation would have important pubic health implications for screening and primary prevention of breast cancer

The Effects of Anthropometry and Angiogenesis on Breast Cancer Etiology

Factors such as mammographic breast density and angiogenesis may be related to breast cancer development, though numerous questions about the etiologic mechanisms remain. Percent density is positively associated with breast cancer risk, yet is negatively associated with another breast cancer risk factor, body mass index (BMI). Vascular endothelial growth factor (VEGF) is a primary regulator of angiogenesis, yet its relationship to breast cancer risk is unclear. We evaluated the longitudinal association between BMI and breast density in the Study of Women's Health Across the Nation (SWAN) Mammographic Density Substudy (N=834). Using adjusted random intercept models, changes in BMI were not associated with changes in dense breast area (Beta=-0.0105, p=0.34), but were strongly negatively associated with changes in percent density (Beta=-1.18, p<0.001). Thus, effects of changes in anthropometry on percent breast density may reflect effects on non-dense tissue, rather than on the dense tissue where cancers arise. Breast density was measured from routine screening mammograms which were not timed with SWAN visits. We developed a method to align the off-schedule mammogram data to the study visit times using linear interpolation with multiple imputation. Our method was shown to be valid, with an average bias for dense breast area of 0.11 cm2. In the random intercept models, use of a simple matching algorithm to estimate breast density produced different (Beta=-0.0155, p=0.04), and likely incorrect, results. Our linear interpolation with multiple imputations method may be applicable to other longitudinal datasets with important data collected off-schedule. In a separate case-control study, the Mammograms and Masses Study (MAMS), we evaluated the association between serum VEGF levels and breast cancer (N=407). Geometric mean VEGF levels were higher among cases (331.4 pg/mL) than controls (291.4 pg/mL; p=0.21). In a multivariable logistic regression model, VEGF greater than or equal to 314.2 pg/mL was positively associated with breast cancer (odds ratio 1.37, 95% confidence interval 0.88-2.12), albeit non-significantly. Higher levels of VEGF may increase breast cancer risk. We have identified roles for anthropometry and angiogenesis in breast carcinogenesis. Enhancing knowledge of breast cancer etiology is a significant contribution to public health and may lead to improved opportunities for prevention or early detection

Breast cancer natural history models and risk prediction in mammography screening cohorts

In this thesis, the foundations are laid for a new natural history model for breast cancer—specifically designed to take advantage of detailed screening cohorts. Three diverse applications of this model are then presented. Study I develops the statistical framework for the natural history model, and shows with simulations that the model parameters can be estimated based on only the information available at diagnosis. It also describes how to adjust for random left truncation—an important aspect to consider when studying prospective cohorts. In Study II, the newly developed natural history model is applied to a Swedish mammography screening cohort. It estimates the population-level distributions of age at onset and tumor volume doubling time. As an extension, the tumor volume doubling time is allowed to depend on the age at onset. The study also estimates the rate of symptomatic detection and screening sensitivity as functions of tumor size. Simulations are used to validate the estimates. Study III shifts the focus from inference to risk prediction. The natural history model is modified to incorporate risk factors separately in each of the four components of the model. Short-term risk prediction is then performed on the screening cohort and the results are compared to a conventional approach to breast cancer risk prediction. The study also develops novel predictions based on, for example, having experienced tumor onset, having a tumor detected at the next screening, and having a tumor detected before it reaches a certain size if attending the next screening. In Study IV, the model is used to study the effect that certain acquisition parameters used in mammography have on the detectability of the breast cancer tumor. With the model, it is possible to more directly study the mammography screening sensitivity, compared to the ad hoc definition of sensitivity commonly seen in the screening literature. It was identified that the compressed breast thickness—in addition to the percent mammographic density and latent tumor size—was inversely associated with the screening sensitivity