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Impact of Estrogen Deprivation on Gene Expression Profiles of Normal Postmenopausal Breast Tissue In vivo

¹ Department of Medical Oncology, Guys and St. Thomas' NHS Foundation Trust; ² Academic Department of Biochemistry, Royal Marsden Hospital; ³ The Breakthrough Breast Cancer Research Centre, The Institute of Cancer Research, London, United Kingdom; ⁴ Department of Medical Oncology, Institut Català d'Oncologia, Barcelona, Spain; and ⁵ Department of Medical Oncology, Kent Oncology Centre, Maidstone Hospital, Maidstone, United Kingdom

Requests for reprints: Mitch Dowsett, Academic Department of Biochemistry, Royal Marsden Hospital, London SW3 6JJ, United Kingdom. Phone: 44-207-808-2885; Fax: 44-207-376-3918. E-mail: mitch.dowsett{at}icr.ac.uk

Aromatase inhibitors play a key role in the clinical management of hormone receptor–positive breast cancer and have potential utility as chemopreventive agents. Further understanding of the molecular effects of estrogen and its deprivation in normal breast tissue may allow the development of biomarkers of risk of breast cancer and help to predict the value of chemoprevention with aromatase inhibitors. Core biopsies of normal breast tissue were taken before and after letrozole treatment from postmenopausal women in the LITMaS pilot prevention study. RNA was extracted from these samples and used for cDNA microarray analysis. Gene expression changes induced by letrozole treatment were much less extensive than observed in estrogen receptor–positive malignant tissue; however, overall, they correlated to a highly significant degree ( = 0.511; P < 10^–20). As well as some classically estrogen-associated genes, many genes associated with extracellular matrix remodeling were affected by estrogen deprivation in the normal breast in vivo. These data indicate for the first time that gene expression of normal breast tissue remains dependent on endogenous estrogens after the menopause. The modest degree of gene change suggests that intermediate markers of chemoprevention may be difficult to identify. (Cancer Epidemiol Biomarkers Prev 2008;17(4):855–63)