Gene expression preferentially regulated by tamoxifen in breast cancer cells and correlations with clinical outcome.
The beneficial effect of the selective estrogen receptor (ER) modulator tamoxifen in the treatment and prevention of breast cancer is assumed to be through its ability to antagonize the stimulatory actions of estrogen, although tamoxifen can also have some estrogen-like agonist effects. Here, we report that, in addition to these mixed agonist/antagonist actions, tamoxifen can also selectively regulate a unique set of >60 genes, which are minimally regulated by estradiol (E2) or raloxifene in ERalpha-positive MCF-7 human breast cancer cells. This gene regulation by tamoxifen is mediated by ERalpha and reversed by E2 or ICI 182,780. Introduction of ERbeta into MCF-7 cells reverses tamoxifen action on approximately 75% of these genes. To examine whether these genes might serve as markers of tamoxifen sensitivity and/or the development of resistance, their expression level was examined in breast cancers of women who had received adjuvant therapy with tamoxifen. High expression of two of the tamoxifen-stimulated genes, YWHAZ/14-3-3z and LOC441453, was found to correlate significantly with disease recurrence following tamoxifen treatment in women with ER-positive cancers and hence seem to be markers of a poor prognosis. Our data indicate a new dimension in tamoxifen action, involving gene expression regulation that is tamoxifen preferential, and identify genes that might serve as markers of tumor responsiveness or resistance to tamoxifen therapy. This may have a potential effect on the choice of tamoxifen versus aromatase inhibitors as adjuvant endocrine therapy.[1]References
- Gene expression preferentially regulated by tamoxifen in breast cancer cells and correlations with clinical outcome. Frasor, J., Chang, E.C., Komm, B., Lin, C.Y., Vega, V.B., Liu, E.T., Miller, L.D., Smeds, J., Bergh, J., Katzenellenbogen, B.S. Cancer Res. (2006) [Pubmed]
Annotations and hyperlinks in this abstract are from individual authors of WikiGenes or automatically generated by the WikiGenes Data Mining Engine. The abstract is from MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine.About WikiGenesOpen Access LicencePrivacy PolicyTerms of Useapsburg
