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Papers In Press, published online ahead of print March 15, 2000
Department of Cancer Research, Berlex Biosciences, Richmond, CA 94804-0099
Corresponding Author: deb_zajchowski{at}berlex.com
Clinical studies have shown that estrogen replacement therapy (ERT) reduces the incidence and severity of osteoporosis and cardiovascular disease in post-menopausal women. However, long term estrogen treatment also increases the risk of endometrial and breast cancer. The selective estrogen receptor (ER) modulators (SERMs) tamoxifen and raloxifene, cause both antagonistic and agonistic responses when bound to the ER. Their predominantly antagonistic actions in the mammary gland form the rationale for their therapeutic utility in estrogen-responsive breast cancer, while their agonistic estrogen-like effects in bone and the cardiovascular system make them candidates for HRT regimens. Of these two SERMs, raloxifene is preferred because it has markedly less uterine-stimulatory activity. In order to identify additional SERMs, a method to classify compounds based upon differential gene expression modulation was developed. By analysis of 24 different combinations of genes and cells, a selected set of assays that permitted discrimination between estrogen, tamoxifen, raloxifene, and the pure ER antagonist, ICI164384 was generated. This assay panel was employed to measure the activity of 38 compounds and the gene expression fingerprints (GEFs) obtained for each compound were used to classify all compounds into eight groups. The compound?s GEF predicted it?s uterine-stimulatory activity. One group of compounds was evaluated for activity in attenuating bone loss in ovariectomized rats. Most compounds with similar GEFs had similar in vivo activities, thereby suggesting that GEF-based screens might be useful in predicting a compound?s in vivo pharmacological profile.
J. Biol. Chem, 10.1074/jbc.M909865199
Submitted on December 8, 1999
Revised on March 2, 2000
Accepted on March 13, 2000
Identification of selective estrogen receptor modulators by their gene expression fingerprints
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