Can the stroma provide the clue to the cellular basis for mammographic density?

Associations of reproductive breast cancer risk factors with breast tissue composition

BACKGROUND

We investigated the associations of reproductive factors with the percentage of epithelium, stroma, and fat tissue in benign breast biopsy samples.

METHODS

This study included 983 cancer-free women with biopsy-confirmed benign breast disease (BBD) within the Nurses' Health Study and Nurses' Health Study II cohorts. The percentage of each tissue type (epithelium, stroma, and fat) was measured on whole-section images with a deep-learning technique. All tissue measures were log-transformed in all the analyses to improve normality. The data on reproductive variables and other breast cancer risk factors were obtained from biennial questionnaires. Generalized linear regression was used to examine the associations of reproductive factors with the percentage of tissue types, while adjusting for known breast cancer risk factors.

RESULTS

As compared to parous women, nulliparous women had a smaller percentage of epithelium (β = - 0.26, 95% confidence interval [CI] - 0.41, - 0.11) and fat (β = - 0.34, 95% CI - 0.54, - 0.13) and a greater percentage of stroma (β = 0.04, 95% CI 0.01, 0.08). Among parous women, the number of children was inversely associated with the percentage of stroma (β per child = - 0.01, 95% CI - 0.02, - 0.00). The duration of breastfeeding of ≥ 24 months was associated with a reduced proportion of fat (β = - 0.30, 95% CI - 0.54, - 0.06; p-trend = 0.04). In a separate analysis restricted to premenopausal women, older age at first birth was associated with a greater proportion of epithelium and a smaller proportion of stroma.

CONCLUSIONS

Our findings suggest that being nulliparous as well as having a fewer number of children (both positively associated with breast cancer risk) is associated with a smaller proportion of epithelium and a greater proportion of stroma, potentially suggesting the importance of epithelial-stromal interactions. Future studies are warranted to confirm our findings and to elucidate the underlying biological mechanisms.

Stromal characteristics may hold the key to mammographic density: the evidence to date

There is strong epidemiological data indicating a role for increased mammographic density (MD) in predisposing to breast cancer, however, the biological mechanisms underlying this phenomenon are less well understood. Recently, studies of human breast tissues have started to characterise the features of mammographically dense breasts, and a number of in-vitro and in-vivo studies have explored the potential mechanisms through which dense breast tissue may exert this tumourigenic risk. This article aims to review both the pathological and biological evidence implicating a key role for the breast stromal compartment in MD, how this may be modified and the clinical significance of these findings. The epidemiological context will be briefly discussed but will not be covered in detail.

Possible influence of mammographic density on local and locoregional recurrence of breast cancer

Introduction

It is debated whether mammographic density gives rise to more aggressive cancers. We therefore aimed to study the influence of mammographic density on prognosis.

Methods

This is a case-only study within a population-based case-control study. Cases were all postmenopausal women in Sweden with incident breast cancer, diagnosed 1993-1995, and aged 50-74 years. Women with pre-diagnostic/diagnostic mammograms were included (n = 1774). Mammographic density of the unaffected breast was assessed using a computer-assisted thresholding technique. The Cox proportional hazards model was used to study recurrence and survival with and without stratification on surgical procedure (breast-conserving surgery vs. mastectomy).

Results

Percentage density (PD) was associated with both local and locoregional recurrence even after adjustment for established prognosticators; hazards ratio (HR) 1.92, p = 0.039, for local recurrence and HR 1.67, p = 0.033, for locoregional recurrence for women with PD≥25% compared to PD<25%. Stratification on surgical procedure showed that the associations were also present in mastectomized women. PD was neither associated with distant recurrence nor survival.

Conclusions

High mammographic density is an independent risk factor of local and locoregional recurrence but is neither associated with distant metastasis nor survival. The relationships with local and locoregional recurrences were also present in women treated with mastectomy, indicating that they are not merely explained by density masking residual disease in women treated with breast-conserving surgery. Rather there appears to be a true association. Thus, mammographic density should possibly influence adjuvant therapy decisions in the future.

Relationship of mammographic density and gene expression: analysis of normal breast tissue surrounding breast cancer

PURPOSE

Previous studies of breast tissue gene expression have shown that the extratumoral microenvironment has substantial variability across individuals, some of which can be attributed to epidemiologic factors. To evaluate how mammographic density and breast tissue composition relate to extratumoral microenvironment gene expression, we used data on 121 patients with breast cancer from the population-based Polish Women's Breast Cancer Study.

EXPERIMENTAL DESIGN

Breast cancer cases were classified on the basis of a previously reported, biologically defined extratumoral gene expression signature with two subtypes: an Active subtype, which is associated with high expression of genes related to fibrosis and wound response, and an Inactive subtype, which has high expression of cellular adhesion genes. Mammographic density of the contralateral breast was assessed using pretreatment mammograms and a quantitative, reliable computer-assisted thresholding method. Breast tissue composition was evaluated on the basis of digital image analysis of tissue sections.

RESULTS

The Inactive extratumoral subtype was associated with significantly higher percentage mammographic density (PD) and dense area (DA) in univariate analysis (PD: P = 0.001; DA: P = 0.049) and in multivariable analyses adjusted for age and body mass index (PD: P = 0.004; DA: P = 0.049). Inactive/higher mammographic density tissue was characterized by a significantly higher percentage of stroma and a significantly lower percentage of adipose tissue, with no significant change in epithelial content. Analysis of published gene expression signatures suggested that Inactive/higher mammographic density tissue expressed increased estrogen response and decreased TGF-β signaling.

CONCLUSIONS

By linking novel molecular phenotypes with mammographic density, our results indicate that mammographic density reflects broad transcriptional changes, including changes in both epithelia- and stroma-derived signaling.

Progesterone--promoter or inhibitor of breast cancer

Based on the results of a French cohort of postmenopausal women, it has been claimed that micronized progesterone does not enhance breast cancer risk. The impact of reproductive factors on breast cancer risk and a high prevalence of occult breast carcinomas at the time of menopause suggest an involvement of endogenous progesterone in the development of breast cancer. High mammographic density in the luteal phase and during treatment with estrogen/progestogen combinations reflect a change in the composition of mammary stroma and an increased water accumulation in the extracellular matrix which is caused by hygroscopic hyaluronan-proteoglycan aggregates. Proteoglycans are also involved in the regulation of proliferation, migration, and differentiation of epithelial cells and angiogenesis, and may influence malignant transformation of breast cells and progression of tumors. Reports on a lack of effect of estrogen/progesterone therapy on breast cancer risk may be rooted in a selective prescription to overweight women and/or to the very low progesterone serum levels after oral administration owing to a strong inactivation rate. The contradictory results concerning the proliferative effect of progesterone may be associated with a different local metabolism in normal compared to malignant breast tissue. Similar to other progestogens, hormone replacement therapy with progesterone seems to promote the development of breast cancer, provided that the progesterone serum levels have reached the threshold for endometrial protection.

Can mammographic assessments lead to consider density as a risk factor for breast cancer?

Admitting that mammographic breast density is an important independent risk factor for breast cancer in the general population, has a crucial economical health care impact, since it might lead to increasing screening frequency or reinforcing additional modalities. Thus, the impact of density as a risk factor has to be carefully investigated and might be debated. Some authors suggested that high density would be either a weak factor or confused with a masking effect. Others concluded that most of the studies have methodological biases in basic physics to quantify percentage of breast density, as well as in mammographic acquisition parameters. The purpose of this review is to evaluate mammographic procedures and density assessments in published studies regarding density as a breast cancer risk. No standardization was found in breast density assessments and compared density categories. High density definitions varied widely from 25 to 75% of dense tissues on mammograms. Some studies showed an insufficient follow-up to reveal masking effect related to mammographic false negatives. Evaluating breast density impact needs thorough studies with consensual mammographic procedures, methods of density measurement, breast density classification as well as a standardized definition of high breast density. Digital mammography, more effective in dense breasts, should help to re-evaluate the issue of density as a risk factor for breast cancer.

Mammographic density and matrix metalloproteinases in breast tissue

Mammographic density is a strong risk factor for breast cancer, yet the underlying histopathologic correlates are not clear. Matrix metalloproteinases (MMPs) and their inhibitors (TIMPs) play important roles in multiple stages of tumorigenesis. This study examined the association between mammographic density and expression of MMPs 1, 3, 9, and 12 and TIMP3 in benign and malignant breast tissue of 277 women with mainly Caucasian and Japanese ancestry. Tissue microarrays with up to 4 benign and 4 malignant cores per woman were stained immunohistochemically and evaluated. Digitized prediagnostic mammograms were assessed for densities using a computer-assisted method. General linear models adjusted for known confounders were applied to estimate mean densities by staining category. Strong expression of all MMPs was about twice as frequent in malignant as in benign tissue, while TIMP3 expression in stromal tissue was higher in benign than malignant cores. For MMP3 and 9, less than 10% of cores stained positive; thus, they were not further analyzed. None of the markers showed a statistically significant association with breast density in the entire study population and ethnic-specific results were conflicting and difficult to explain. Although not statistically significant, mean density was consistently lower with more extensive TIMP3 expression in stromal and epithelial tissue. These findings indicate that the higher breast cancer risk in women with dense breasts may be influenced by lower TIMP3 expression. However, future investigations into activities and ratios of additional proteases and their inhibitors as well as other pathways, such as inflammation, are needed.

Mammographic density and epithelial histopathologic markers

BACKGROUND

We explored the association of mammographic density, a breast cancer risk factor, with hormonal and proliferation markers in benign tissue from tumor blocks of pre-and postmenopausal breast cancer cases.

METHODS

Breast cancer cases were recruited from a case-control study on breast density. Mammographic density was assessed on digitized prediagnostic mammograms using a computer-assisted method. For 279 participants of the original study, we obtained tumor blocks and prepared tissue microarrays (TMA), but benign tissue cores were only available for 159 women. The TMAs were immunostained for estrogen receptor alpha (ERalpha) and beta (ERbeta), progesterone receptor (PR), HER2/neu, Ki-67, and Proliferating Cell Nuclear Antigen (PCNA). We applied general linear models to compute breast density according to marker expression.

RESULTS

A substantial proportion of the samples were in the low or no staining categories. None of the results was statistically significant, but women with PR and ERbeta staining had 3.4% and 2.4% higher percent density. The respective values for Caucasians were 5.7% and 11.6% but less in Japanese women (3.5% and -1.1%). Percent density was 3.4% higher in women with any Ki-67 staining and 2.2% in those with positive PCNA staining.

CONCLUSION

This study detected little evidence for an association between mammographic density and expression of steroid receptors and proliferation markers in breast tissue, but it illustrated the problems of locating tumor blocks and benign breast tissue samples for epidemiologic research. Given the suggestive findings, future studies examining estrogen effects in tissue, cell proliferation, and density in the breast may be informative.

[Mammographic density: a valid risk factor for breast cancer?]

Whether estimated or measured, mammographic or breast density, which may be subject to physiological and therapeutic variations, is widely viewed in the literature as an important factor of increased risk for breast cancer. A high breast density, the causes of which are being refined, would increase the relative risk of breast cancer four to six fold, even though some authors direct critics at methodological flaws supporting these results. Three-dimensional imaging will confirm or refute the available results. Meanwhile, radiologists and clinicians must remain vigilant in patients with high breast density.

Mammographic density does not correlate with Ki-67 expression or cytomorphology in benign breast cells obtained by random periareolar fine needle aspiration from women at high risk for breast cancer

Background

Ki-67 expression is a possible risk biomarker and is currently being used as a response biomarker in chemoprevention trials. Mammographic breast density is a risk biomarker and is also being used as a response biomarker. We previously showed that Ki-67 expression is higher in specimens of benign breast cells exhibiting cytologic atypia that are obtained by random periareolar fine needle aspiration (RPFNA). It is not known whether there is a correlation between mammographic density and Ki-67 expression in benign breast ductal cells obtained by RPFNA.

Methods

Included in the study were 344 women at high risk for developing breast cancer (based on personal or family history), seen at The University of Kansas Medical Center high-risk breast clinic, who underwent RPFNA with cytomorphology and Ki-67 assessment plus a mammogram. Mammographic breast density was assessed using the Cumulus program. Categorical variables were analyzed by χ² test, and continuous variables were analyzed by nonparametric test and linear regression.

Results

Forty-seven per cent of women were premenopausal and 53% were postmenopausal. The median age was 48 years, median 5-year Gail Risk was 2.2%, and median Ki-67 was 1.9%. The median mammographic breast density was 37%. Ki-67 expression increased with cytologic abnormality (atypia versus no atypia; P ≤ 0.001) and younger age (≤50 years versus >50 years; P ≤ 0.001). Mammographic density was higher in premenopausal women (P ≤ 0.001), those with lower body mass index (P < 0.001), and those with lower 5-year Gail risk (P = 0.001). Mammographic density exhibited no correlation with Ki-67 expression or cytomorphology.

Conclusion

Given the lack of correlation of mammographic breast density with either cytomorphology or Ki-67 expression in RPFNA specimens, mammographic density and Ki-67 expression should be considered as potentially complementary response biomarkers in breast cancer chemoprevention trials.

Breast response to menopausal hormone therapy--aspects on proliferation, apoptosis and mammographic density

Breast cancer is the major malignancy among women in the Western world. The breast is clearly a target organ for sex steroid hormones and hormonal treatments have been associated with an increased risk of breast cancer. The balance between proliferation and apoptosis is important for breast cell homeostasis. Mammographic breast density has been identified as a strong and independent risk factor for breast cancer. It seems clear that there is a difference between various hormonal treatments with regard to their effects on breast density and cell proliferation. Also, not all women respond similarly to the same treatment. Combined estrogen and progestogen therapy generally will enhance density and proliferation more than treatment with estrogen alone. Certain constitutional and hormonal factors appear to be predictive of breast reactivity. Older women with a low body mass index respond more strongly to treatment. Estrogen levels have a positive and androgens a negative association to increase in density and proliferation. A combination of increased proliferation and decreased apoptosis could be one mechanism to explain the excess risk of breast cancer during combined estrogen/progestogen treatment. Tibolone seems to have less impact on breast response than conventional hormone therapy. Efforts should be made to identify those women with an adverse response to treatment as well as therapeutic principles with the least possible influence on the breast.

Hormones and mammographic breast density

Mammographic density reveals information about the hormonal environment along with the heritability in which breast cancer develops. This is made possible by the widespread use of population screening by mammography. Increasingly this is an important observation not just for population studies, which reveal disease determinants, but also for the individual. Density reveals the effect of the intrinsic hormonal environment and its background genetics, and also the effect of pharmaceuticals--agents used for disease control and prevention and hormone replacement therapy (HRT) used for well-being around the menopause. Increasingly this focus on the individual will need methods of measurement of density that can be monitored with greater accuracy than the widely used BI-RADS 4 categories. For this purpose studies are under way to measure volume of dense tissue as a continuous variable. In due course, measurement of density will be used as a biomarker of risk, employed in risk models and to monitor interventions. Before this can happen more knowledge will be needed of the change occurring naturally through the menopause and the differences between individuals. This will need specific study backed up with detailed information about the patient on large numbers of women and their mammograms. Currently the widespread use of HRT has increased the prevalence of the dense patterns and potentially may adversely affect the effectiveness of mammographic screening programmes. There is a large literature recording this from which we see that combined continuous preparations of oestrogen progestin are more likely to cause increased density than oestrogen alone or tibolone. Breast density, measured more accurately, has the potential to be an important adjunct to risk estimation and to monitor interventions for breast cancer prevention with pharmaceuticals (such as SERMS) and by change in lifestyle behaviours.

Experimental manipulation of radiographic density in mouse mammary gland

INTRODUCTION

Extensive mammographic density in women is associated with increased risk for breast cancer. Mouse models provide a powerful approach to the study of human diseases, but there is currently no model that is suited to the study of mammographic density.

METHODS

We performed individual manipulations of the stromal, epithelial and matrix components of the mouse mammary gland and examined the alterations using in vivo and ex vivo radiology, whole mount staining and histology.

RESULTS

Areas of density were generated that resembled densities in mammographic images of the human breast, and the nature of the imposed changes was confirmed at the cellular level. Furthermore, two genetic models, one deficient in epithelial structure (Pten conditional tissue specific knockout) and one with hyperplastic epithelium and mammary tumors (MMTV-PyMT), were used to examine radiographic density.

CONCLUSION

Our data show the feasibility of altering and imaging mouse mammary gland radiographic density by experimental and genetic means, providing the first step toward modelling the biological processes that are responsible for mammographic density in the mouse.