The relative importance of genetics and environment on mammographic density

Mammographic density and breast cancer risk: current understanding and future prospects

Variations in percent mammographic density (PMD) reflect variations in the amounts of collagen and number of epithelial and non-epithelial cells in the breast. Extensive PMD is associated with a markedly increased risk of invasive breast cancer. The PMD phenotype is important in the context of breast cancer prevention because extensive PMD is common in the population, is strongly associated with risk of the disease, and, unlike most breast cancer risk factors, can be changed. Work now in progress makes it likely that measurement of PMD will be improved in the near future and that understanding of the genetics and biological basis of the association of PMD with breast cancer risk will also improve. Future prospects for the application of PMD include mammographic screening, risk prediction in individuals, breast cancer prevention research, and clinical decision making.

Expression levels of uridine 5'-diphospho-glucuronosyltransferase genes in breast tissue from healthy women are associated with mammographic density

INTRODUCTION

Mammographic density (MD), as assessed from film screen mammograms, is determined by the relative content of adipose, connective and epithelial tissue in the female breast. In epidemiological studies, a high percentage of MD confers a four to six fold risk elevation of developing breast cancer, even after adjustment for other known breast cancer risk factors. However, the biologic correlates of density are little known.

METHODS

Gene expression analysis using whole genome arrays was performed on breast biopsies from 143 women; 79 women with no malignancy (healthy women) and 64 newly diagnosed breast cancer patients, both included from mammographic centres. Percent MD was determined using a previously validated, computerized method on scanned mammograms. Significance analysis of microarrays (SAM) was performed to identify genes influencing MD and a linear regression model was used to assess the independent contribution from different variables to MD.

RESULTS

SAM-analysis identified 24 genes differentially expressed between samples from breasts with high and low MD. These genes included three uridine 5'-diphospho-glucuronosyltransferase (UGT) genes and the oestrogen receptor gene (ESR1). These genes were down-regulated in samples with high MD compared to those with low MD. The UGT gene products, which are known to inactivate oestrogen metabolites, were also down-regulated in tumour samples compared to samples from healthy individuals. Several single nucleotide polymorphisms (SNPs) in the UGT genes associated with the expression of UGT and other genes in their vicinity were identified.

CONCLUSIONS

Three UGT enzymes were lower expressed both in breast tissue biopsies from healthy women with high MD and in biopsies from newly diagnosed breast cancers. The association was strongest amongst young women and women using hormonal therapy. UGT2B10 predicts MD independently of age, hormone therapy and parity. Our results indicate that down-regulation of UGT genes in women exposed to female sex hormones is associated with high MD and might increase the risk of breast cancer.

Breast tissue composition and susceptibility to breast cancer

Breast density, as assessed by mammography, reflects breast tissue composition. Breast epithelium and stroma attenuate x-rays more than fat and thus appear light on mammograms while fat appears dark. In this review, we provide an overview of selected areas of current knowledge about the relationship between breast density and susceptibility to breast cancer. We review the evidence that breast density is a risk factor for breast cancer, the histological and other risk factors that are associated with variations in breast density, and the biological plausibility of the associations with risk of breast cancer. We also discuss the potential for improved risk prediction that might be achieved by using alternative breast imaging methods, such as magnetic resonance or ultrasound. After adjustment for other risk factors, breast density is consistently associated with breast cancer risk, more strongly than most other risk factors for this disease, and extensive breast density may account for a substantial fraction of breast cancer. Breast density is associated with risk of all of the proliferative lesions that are thought to be precursors of breast cancer. Studies of twins have shown that breast density is a highly heritable quantitative trait. Associations between breast density and variations in breast histology, risk of proliferative breast lesions, and risk of breast cancer may be the result of exposures of breast tissue to both mitogens and mutagens. Characterization of breast density by mammography has several limitations, and the uses of breast density in risk prediction and breast cancer prevention may be improved by other methods of imaging, such as magnetic resonance or ultrasound tomography.

Determinants of percentage and area measures of mammographic density

Mammographic density is one of the strongest predictors of breast cancer risk. Typically expressed as a percentage of the breast area occupied by radiologically dense tissue on a mammogram, its full value may not be realized because of its negative association with body mass index. A simpler measure of mammographic density, independent of other breast cancer risk factors and equally predictive of risk, would be preferable for risk prediction models. Percentage and area measures of mammographic density were determined for 815 women at high risk for breast cancer from the baseline assessments in the International Breast Cancer Intervention Study I, a trial of tamoxifen for breast cancer prevention conducted between 1992 and 2001. Multivariate linear regression was used to assess associations between risk factors and the mammographic measures. Percent dense area was negatively associated with age, body mass index, menopausal status, predicted risk, and smoking status (R(2) = 24%). Dense area was negatively associated with only age and body mass index (R(2) = 7%), and the latter association was much weaker than for percent dense area. Nondense area was positively associated with age, body mass index, and predicted risk (R(2) = 36%). Dense area was not associated with the multitude of risk factors that percent dense area was, making it a simpler biomarker for risk prediction modeling. Both dense area and percent dense area should be presented whenever possible for comparisons in research.

The effect of transdermal testosterone on mammographic density in postmenopausal women not receiving systemic estrogen therapy

CONTEXT

Greater mammographic density is associated with increased breast cancer risk and reduced diagnostic mammographic sensitivity and may be seen with estrogen/progestin therapy (EPT). The effects of testosterone therapy on mammographic density in postmenopausal women not on EPT are not known.

OBJECTIVE

Our objective was to compare effects of two doses of the testosterone transdermal patch (TTP) with placebo in postmenopausal women without concomitant EPT on mammographic density over 52 wk.

DESIGN

We conducted a randomized, double-blind, placebo-controlled, parallel-group, multinational trial.

PATIENTS

Patients included 279 postmenopausal women participating in a testosterone and sexual function study with paired mammograms for baseline and 52 wk/exit.

INTERVENTIONS

Patients were randomized to placebo, TTP 150 microg/d, or TTP 300 microg/d, stratified by menopause type (natural or surgical).

MAIN OUTCOME MEASURES

Change from baseline to wk 52 in the percentage of dense tissue (PD) on digital mammograms.

RESULTS

A total of 250 women with paired mammograms for study baseline and wk 52 were included in the primary analysis. Mean age was 54.6 yr, baseline body mass index was 27.5 kg/m(2), and 78% were naturally menopausal. There were no baseline differences between groups. Mean changes from baseline (+/-SEM) in PD for placebo, TTP 150 microg/d and TTP 300 microg/d were small (0.05 +/- 0.16, 0.06 +/- 0.19, and 0.21 +/- 0.17%) and not significantly different. There were no statistically significant differences from placebo for total dense or nondense area and no significant relationships between hormone levels and PD after adjustment for body mass index.

CONCLUSION

TTP therapy over 52 wk appears to have no significant effect on digitally quantified absolute or percent dense mammographic area in postmenopausal women not using EPT.

Sex steroid metabolism polymorphisms and mammographic density in pre- and early perimenopausal women

Introduction

We examined the association between mammographic density and single-nucleotide polymorphisms (SNPs) in genes encoding CYP1A1, CYP1B1, aromatase, 17β-HSD, ESR1, and ESR2 in pre- and early perimenopausal white, African-American, Chinese, and Japanese women.

Methods

The Study of Women's Health Across the Nation is a longitudinal community-based cohort study. We analyzed data from 451 pre- and early perimenopausal participants of the ancillary SWAN Mammographic Density study for whom we had complete information regarding mammographic density, genotypes, and covariates. With multivariate linear regression, we examined the relation between percentage mammographic breast density (outcome) and each SNP (primary predictor), adjusting for age, race/ethnicity, parity, cigarette smoking, and body mass index (BMI).

Results

After multivariate adjustment, the CYP1B1 rs162555 CC genotype was associated with a 9.4% higher mammographic density than the TC/TT genotype (P = 0.04). The CYP19A1 rs936306 TT genotype was associated with 6.2% lower mammographic density than the TC/CC genotype (P = 0.02). The positive association between CYP1A1 rs2606345 and mammographic density was significantly stronger among participants with BMI greater than 30 kg/m² than among those with BMI less than 25 kg/m² (P_interaction = 0.05). Among white participants, the ESR1 rs2234693 CC genotype was associated with a 7.0% higher mammographic density than the CT/TT genotype (P = 0.01).

Conclusions

SNPs in certain genes encoding sex steroid metabolism enzymes and ESRs were associated with mammographic density. Because the encoded enzymes and ESR1 are expressed in breast tissue, these SNPs may influence breast cancer risk by altering mammographic density.