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

Abstract

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.

Figure 1. Breast tissue composition distribution by the Active/Inactive subtype and mammographic density

Using quantitative analysis of digital histology images, each sample from the PWBCS for which gene expression was measured also was assessed for composition. Non-fatty stromal percentage was higher in Inactive subtype samples (A) and women with higher mammographic density (percentage, B; dense area, C). In contrast, adipose concentration was lower in the Inactive/higher density patients. Epithelial content did not vary significantly by any of these variables.

Figure 2. Conceptual model for potential mechanisms of the association between mammographic density and breast cancer risk with a focus on the role of stroma

This figure is adapted from the biological model proposed by Martin et al. (24), showing the underlying biological processes linking risk factors to breast cancer and suggesting the surrogate role of mammographic density in these settings. The genetic and environmental factors not only influence epithelial cell proliferation and induce genetic damage, but also regulate the surrounding microenvironment and stromal composition. The abnormalities in mitogenesis, mutagenesis, and morphogenesis result in breast cancer development. By comprehensively summarizing the variation in these three aspects, mammographic density works as an intermediate phenotype strongly indicating breast cancer risk.