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

Xuezheng Sun, Gretchen L. Gierach, Rupninder Sandhu, Tyisha Williams, Bentley R. Midkiff, Jolanta Lissowska, Ewa Wesolowska, Norman F. Boyd, Nicole B. Johnson, Jonine D. Figueroa, Mark E. Sherman, Melissa A. Troester

Research output: Contribution to journalArticlepeer-review

43 Scopus citations

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 populationbased 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 computerassisted 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.

Original languageEnglish (US)
Pages (from-to)4972-4982
Number of pages11
JournalClinical Cancer Research
Volume19
Issue number18
DOIs
StatePublished - Sep 15 2013

ASJC Scopus subject areas

  • General Medicine

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