Anthropometric factors, adult weight gain, and mammographic features

The association between mammographic density and breast cancer risk in Chinese women: a systematic review and meta-analysis

PURPOSE

Breast density has consistently been shown to be an independent risk factor for breast cancer in Western populations; however, few studies have evaluated this topic in Chinese women and there is not yet a unified view. This study investigated the association between mammographic density (MD) and breast cancer risk in Chinese women.

METHODS

The PubMed, Cochrane Library, Embase, and Wanfang databases were systematically searched in June 2023 to include all studies on the association between MD and breast cancer risk in Chinese women. A total of 13,977 breast cancer cases from 14 studies were chosen, including 10 case-control/cross-sectional studies, and 4 case-only studies. For case-control/cross-sectional studies, the odds ratios (ORs) of MD were combined using random effects models, and for case-only studies, relative odds ratios (RORs) were combinations of premenopausal versus postmenopausal breast cancer cases.

RESULTS

Women with BI-RADS density category II-IV in case-control/cross-sectional studies had a 0.93-fold (95% confidence interval [CI] 0.55, 1.57), 1.08-fold (95% CI 0.40, 2.94), and 1.24-fold (95% CI 0.42, 3.69) higher risk compared to women with the lowest density category. Combined RORs for premenopausal versus postmenopausal women in case-only studies were 3.84 (95% CI 2.92, 5.05), 22.65 (95% CI 7.21, 71.13), and 42.06 (95% CI 4.22, 419.52), respectively, for BI-RADS density category II-IV versus I.

CONCLUSIONS

For Chinese women, breast cancer risk is weakly associated with MD; however, breast cancer risk is more strongly correlated with mammographic density in premenopausal women than postmenopausal women. Further research on the factors influencing MD in premenopausal women may provide meaningful insights into breast cancer prevention in China.

Lipidome of mammographic breast density in premenopausal women

BACKGROUND

High mammographic breast density (MBD) is a strong risk factor for breast cancer development, but the biological mechanisms underlying MBD are unclear. Lipids play important roles in cell differentiation, and perturbations in lipid metabolism are implicated in cancer development. Nevertheless, no study has applied untargeted lipidomics to profile the lipidome of MBD. Through this study, our goal is to characterize the lipidome of MBD in premenopausal women.

METHODS

Premenopausal women were recruited during their annual screening mammogram at the Washington University School of Medicine in St. Louis, MO. Untargeted lipidomic profiling for 982 lipid species was performed at Metabolon (Durham, NC®), and volumetric measures of MBD (volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV)) was assessed using Volpara 1.5 (Volpara Health®). We performed multivariable linear regression models to investigate the associations of lipid species with MBD and calculated the covariate-adjusted least square mean of MBD by quartiles of lipid species. MBD measures were log10 transformed, and lipid species were standardized. Linear coefficients of MBD were back-transformed and considered significant if the Bonferroni corrected p-value was < 0.05.

RESULTS

Of the 705 premenopausal women, 72% were non-Hispanic white, and 23% were non-Hispanic black. Mean age, and BMI were 46 years and 30 kg/m2, respectively. Fifty-six lipid species were significantly associated with VPD (52 inversely and 4 positively). The lipid species with positive associations were phosphatidylcholine (PC)(18:1/18:1), lysophosphatidylcholine (LPC)(18:1), lactosylceramide (LCER)(14:0), and phosphatidylinositol (PI)(18:1/18:1). VPD increased across quartiles of PI(18:1/18:1): (Q1 = 7.5%, Q2 = 7.7%, Q3 = 8.4%, Q4 = 9.4%, Bonferroni p-trend = 0.02). The lipid species that were inversely associated with VPD were mostly from the triacylglycerol (N = 43) and diacylglycerol (N = 7) sub-pathways. Lipid species explained some of the variation in VPD. The inclusion of lipid species increased the adjusted R2 from 0.45, for a model that includes known determinants of VPD, to 0.59.

CONCLUSIONS

We report novel lipid species that are associated with MBD in premenopausal women. Studies are needed to validate our results and the translational potential.

Studies of parenchymal texture added to mammographic breast density and risk of breast cancer: a systematic review of the methods used in the literature

This systematic review aimed to assess the methods used to classify mammographic breast parenchymal features in relation to the prediction of future breast cancer. The databases including Medline (Ovid) 1946-, Embase.com 1947-, CINAHL Plus 1937-, Scopus 1823-, Cochrane Library (including CENTRAL), and Clinicaltrials.gov were searched through October 2021 to extract published articles in English describing the relationship of parenchymal texture features with the risk of breast cancer. Twenty-eight articles published since 2016 were included in the final review. The identification of parenchymal texture features varied from using a predefined list to machine-driven identification. A reduction in the number of features chosen for subsequent analysis in relation to cancer incidence then varied across statistical approaches and machine learning methods. The variation in approach and number of features identified for inclusion in analysis precluded generating a quantitative summary or meta-analysis of the value of these features to improve predicting risk of future breast cancers. This updated overview of the state of the art revealed research gaps; based on these, we provide recommendations for future studies using parenchymal features for mammogram images to make use of accumulating image data, and external validation of prediction models that extend to 5 and 10 years to guide clinical risk management. Following these recommendations could enhance the applicability of models, helping improve risk classification and risk prediction for women to tailor screening and prevention strategies to the level of risk.

Association between skeletal muscle mass and mammographic breast density

Mammographic density (MD) of the breast and body mass index (BMI) are inversely associated with each other, but have inconsistent associations with respect to the risk of breast cancer. Skeletal muscle mass index (SMI) has been considered to reflect a relatively accurate fat and muscle percentage in the body. So, we evaluated the relation between SMI and MD. A cross-sectional study was performed in 143,456 women who underwent comprehensive examinations from 2012 to 2016. BMI was adjusted to analyze whether SMI is an independent factor predicting dense breast. After adjustment for confounding factors including BMI, the odds ratios for MD for the dense breasts was between the highest and lowest quartiles of SMI at 2.65 for premenopausal women and at 2.39 for postmenopausal women. SMI was a significant predictor for MD, which could be due to the similar growth mechanism of the skeletal muscle and breast parenchymal tissue. Further studies are needed to understand the causal link between muscularity, MD and breast cancer risk.

The Importance of Breast Adipose Tissue in Breast Cancer

Adipose tissue is a complex endocrine organ, with a role in obesity and cancer. Adipose tissue is generally linked to excessive body fat, and it is well known that the female breast is rich in adipose tissue. Hence, one can wonder: what is the role of adipose tissue in the breast and why is it required? Adipose tissue as an organ consists of adipocytes, an extracellular matrix (ECM) and immune cells, with a significant role in the dynamics of breast changes throughout the life span of a female breast from puberty, pregnancy, lactation and involution. In this review, we will discuss the importance of breast adipose tissue in breast development and its involvement in breast changes happening during pregnancy, lactation and involution. We will focus on understanding the biology of breast adipose tissue, with an overview on its involvement in the various steps of breast cancer development and progression. The interaction between the breast adipose tissue surrounding cancer cells and vice-versa modifies the tumor microenvironment in favor of cancer. Understanding this mutual interaction and the role of breast adipose tissue in the tumor microenvironment could potentially raise the possibility of overcoming breast adipose tissue mediated resistance to therapies and finding novel candidates to target breast cancer.

Adiposity Change Over the Life Course and Mammographic Breast Density in Postmenopausal Women

Mammographic breast density is a strong risk factor for breast cancer. We comprehensively investigated the associations of body mass index (BMI) change from ages 10, 18, and 30 to age at mammogram with mammographic breast density in postmenopausal women. We used multivariable linear regression models, adjusted for confounders, to investigate the associations of BMI change with volumetric percent density, dense volume, and nondense volume, assessed using Volpara in 367 women. At the time of mammogram, the mean age was 57.9 years. Compared with women who had a BMI gain of 0.1-5 kg/m2 from age 10, women who had a BMI gain of 5.1-10 kg/m2 had a 24.4% decrease [95% confidence interval (CI), 6.0%-39.2%] in volumetric percent density; women who had a BMI gain of 10.1-15 kg/m2 had a 46.1% decrease (95% CI, 33.0%-56.7%) in volumetric percent density; and women who had a BMI gain of >15 kg/m2 had a 56.5% decrease (95% CI, 46.0%-65.0%) in volumetric percent density. Similar, but slightly attenuated associations were observed for BMI gain from ages 18 and 30 to age at mammogram and volumetric percent density. BMI gain over the life course was positively associated with nondense volume, but not dense volume. We observed strong associations between BMI change over the life course and mammographic breast density. The inverse associations between early-life adiposity change and volumetric percent density suggest that childhood adiposity may confer long-term protection against postmenopausal breast cancer via its effect of mammographic breast density.

Inflammation and breast density among female Chinese immigrants: exploring variations across neighborhoods

PURPOSE

We examined associations of inflammation with breast density, a marker of breast cancer risk, among female Chinese immigrants and explored whether associations varied by neighborhood environment.

METHODS

Assessments of serum C-reactive protein (CRP), soluble tumor necrosis factor receptor 2 (sTNFR2), and breast density were performed among 401 Chinese immigrants across the Philadelphia region. Participant addresses were geocoded, with the majority residing in areas representing traditional urban enclaves (i.e., Chinatown and South Philadelphia) or an emerging enclave with a smaller, but rapidly growing Chinese immigrant population (i.e., the Near Northeast). The remainder was classified as residing in non-enclaves.

RESULTS

In multivariable adjusted regression models, CRP was inversely associated with dense breast area (p = 0.01). Levels of sTNFR2 were also inversely associated with dense breast area, but these associations varied by neighborhood (interaction p = 0.01); specifically, inverse associations were observed among women residing in the emerging enclave (p = 0.03), but not other neighborhoods.

CONCLUSIONS

Among Chinese immigrant women, aggregate analyses that do not take neighborhood context into consideration can mask potential variations in association of inflammatory markers with breast density. Future studies should consider how neighborhood contextual factors may contribute to differential risk pathways.

An isoform of AIF1 involved in breast cancer

Background

Inflammation is a major player in breast cancer (BC) progression. Allograft-inflammatory factor-1 (AIF1) is a crucial mediator in the inflammatory response. AIF1 reportedly plays a role in BC, but the mechanism remains to be elucidated. We identified two AIF1 isoforms, AIF1v1 and AIF1v3, which were differentially expressed between affected and unaffected sisters from families with high risk of BC with no deleterious BRCA1/BRCA2 mutations (BRCAX). We investigated potential functions of AIFv1/v3 in BC of varying severity and breast adipose tissue by evaluating their expression, and association with metabolic and clinical parameters of BC patients.

Methods

AIF1v1/v3 expression was determined in BC tissues and cell lines using quantitative real-time PCR. Potential roles and mechanisms were examined in the microenvironment (fibroblasts, adipose tissue, monocytes and macrophages), inflammatory response (cell reaction in BC subgroups), and metabolism [treatment with docosahexaenoic acid (DHA)]. Association of AIF1 transcript expression with clinical factors was determined by Spearman’s rank correlation. Bioinformatics analyses were performed to characterize transcripts.

Results

AIF1v1/v3 were mostly expressed in the less severe BC samples, and their expression appeared to originate from the tumor microenvironment. AIF1 isoforms had different expression rates and sources in breast adipose tissue; lymphocytes mostly expressed AIF1v1 while activated macrophages mainly expressed AIF1v3. Bioinformatics analysis revealed major structural differences suggesting distinct functions in BC progression. Lymphocytes were the most infiltrating cells in breast tumors and their number correlated with AIF1v1 adipose expression. Furthermore, DHA supplementation significantly lowered the expression of AIF1 isoforms in BRCAX cell lines. Finally, the expression of AIF1 isoforms in BC and breast adipose tissue correlated with clinical parameters of BC patients.

Conclusions

Results strongly suggest that AIF1v1 as much as AIF1v3 play a major role in the crosstalk between BC and infiltrating immune cells mediating tumor progression, implying their high potential as target molecules for BC diagnostic, prognostication and treatment.

Electronic supplementary material

The online version of this article (10.1186/s12935-018-0663-3) contains supplementary material, which is available to authorized users.

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.

Age at Menarche and Late Adolescent Adiposity Associated with Mammographic Density on Processed Digital Mammograms in 24,840 Women

Background: High mammographic density is strongly associated with increased breast cancer risk. Some, but not all, risk factors for breast cancer are also associated with higher mammographic density.Methods: The study cohort (N = 24,840) was drawn from the Research Program in Genes, Environment and Health of Kaiser Permanente Northern California and included non-Hispanic white females ages 40 to 74 years with a full-field digital mammogram (FFDM). Percent density (PD) and dense area (DA) were measured by a radiological technologist using Cumulus. The association of age at menarche and late adolescent body mass index (BMI) with PD and DA were modeled using linear regression adjusted for confounders.Results: Age at menarche and late adolescent BMI were negatively correlated. Age at menarche was positively associated with PD (P value for trend <0.0001) and DA (P value for trend <0.0001) in fully adjusted models. Compared with the reference category of ages 12 to 13 years at menarche, menarche at age >16 years was associated with an increase in PD of 1.47% (95% CI, 0.69-2.25) and an increase in DA of 1.59 cm² (95% CI, 0.48-2.70). Late adolescent BMI was inversely associated with PD (P < 0.0001) and DA (P < 0.0001) in fully adjusted models.Conclusions: Age at menarche and late adolescent BMI are both associated with Cumulus measures of mammographic density on processed FFDM images.Impact: Age at menarche and late adolescent BMI may act through different pathways. The long-term effects of age at menarche on cancer risk may be mediated through factors besides mammographic density. Cancer Epidemiol Biomarkers Prev; 26(9); 1450-8. ©2017 AACR.