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Transforming growth factors-β are not good biomarkers of chemopreventive efficacy in a preclinical breast cancer model system

Overview of attention for article published in Breast Cancer Research, December 2000
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Title
Transforming growth factors-β are not good biomarkers of chemopreventive efficacy in a preclinical breast cancer model system
Published in
Breast Cancer Research, December 2000
DOI 10.1186/bcr273
Pubmed ID
Authors

JoAnne Zujewski, Anika Vaughn-Cooke, Kathleen C Flanders, Michael A Eckhaus, Ronald A Lubet, Lalage M Wakefield

Abstract

Using a carcinogen-initiated rat model of mammary tumorigenesis, we tested the hypothesis that transforming growth factor (TGF)-betas are useful biomarkers of chemopreventive efficacy in the breast. The chemopreventive agents tested were tamoxifen and the retinoids 9-cis-retinoic acid (9cRA) and N-(4-hydroxyphenyl)retinamide (4-HPR), because both antiestrogens and retinoids have previously been shown to upregulate TGF-betas in vitro. Despite demonstrable chemopreventive efficacy in this model, none of these agents, alone or in combination, had any significant impact on the expression of TGF-betas in the mammary ductal epithelium or periductal stroma as determined by immunohistochemistry. These data suggest that TGF-betas are not likely to be useful biomarkers of chemopreventive efficacy in a clinical setting.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 4 25%
Other 3 19%
Professor > Associate Professor 2 13%
Student > Ph. D. Student 1 6%
Student > Bachelor 1 6%
Other 2 13%
Unknown 3 19%
Readers by discipline Count As %
Agricultural and Biological Sciences 4 25%
Biochemistry, Genetics and Molecular Biology 2 13%
Computer Science 2 13%
Psychology 2 13%
Business, Management and Accounting 1 6%
Other 2 13%
Unknown 3 19%