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Cancer Res. 2007 Nov 1;67(21):10608-17. Epub 2007 Oct 29.

Hormonal markers in breast cancer: coexpression, relationship with pathologic characteristics, and risk factor associations in a population-based study.

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Genetic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, NIH, Bethesda, MD 20892-7236, USA.


The objective of this study was to evaluate the coexpression patterns of hormonal markers in breast cancer tissue and their relationship with pathologic characteristics and epidemiologic risk factors. We evaluated the expression of 17 markers by immunohistochemistry in 842 invasive breast carcinomas collected in a population-based case-control study conducted in Poland. Based on marker correlations, factor analysis identified four major coexpression patterns (factors): "nuclear receptor factor" [estrogen receptor (ER)-alpha, progesterone receptor, androgen receptor, cyclin D1, and aromatase], "estrogen metabolism/ER-beta factor" (ER-beta, peroxisome proliferator-activated receptor-gamma, steroid sulfatase, estrogen sulfonotransferase, and cytochrome P450 1B1), "HER2 factor" (human epidermal growth factor receptor 2, E-cadherin, cyclooxygenase-2, aromatase, steroid sulfatase), and "proliferation factor" (cytokeratin 5, cytokeratin 5/6, epidermal growth factor receptor, P53). Three of these factors corresponded to molecular subtypes previously defined by expression profiling; however, the estrogen metabolism/ER-beta factor seemed to be distinctive. High scores for this factor were associated with high tumor grade (P heterogeneity = 0.02), younger age at menarche (P heterogeneity = 0.04), lower current body mass index among premenopausal women (P heterogeneity = 0.01), and older age at menopause (P heterogeneity = 0.04). High scores for the proliferation factor were also associated with early menarche (P heterogeneity < 0.0001), and in contrast to the estrogen metabolism/ER-beta factor, higher current body mass index among premenopausal women (P heterogeneity = 0.03). Our analysis of hormonal pathway markers independently confirmed several previously defined molecular subtypes identified by gene expression profiling and augmented these findings by suggesting the existence of additional relationships related to ER-beta and enzymes involved in hormone metabolism.

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