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A New Mouse Model for the Study of Human Breast Cancer Metastasis

Overview of attention for article published in PLOS ONE, October 2012
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Title
A New Mouse Model for the Study of Human Breast Cancer Metastasis
Published in
PLOS ONE, October 2012
DOI 10.1371/journal.pone.0047995
Pubmed ID
Authors

Elizabeth Iorns, Katherine Drews-Elger, Toby M. Ward, Sonja Dean, Jennifer Clarke, Deborah Berry, Dorraya El Ashry, Marc Lippman

Abstract

Breast cancer is the most common cancer in women, and this prevalence has a major impact on health worldwide. Localized breast cancer has an excellent prognosis, with a 5-year relative survival rate of 85%. However, the survival rate drops to only 23% for women with distant metastases. To date, the study of breast cancer metastasis has been hampered by a lack of reliable metastatic models. Here we describe a novel in vivo model using human breast cancer xenografts in NOD scid gamma (NSG) mice; in this model human breast cancer cells reliably metastasize to distant organs from primary tumors grown within the mammary fat pad. This model enables the study of the entire metastatic process from the proper anatomical site, providing an important new approach to examine the mechanisms underlying breast cancer metastasis. We used this model to identify gene expression changes that occur at metastatic sites relative to the primary mammary fat pad tumor. By comparing multiple metastatic sites and independent cell lines, we have identified several gene expression changes that may be important for tumor growth at distant sites.

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Mendeley readers

The data shown below were compiled from readership statistics for 408 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 8 2%
Germany 2 <1%
Netherlands 2 <1%
United Kingdom 2 <1%
Spain 1 <1%
Kenya 1 <1%
Unknown 392 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 94 23%
Researcher 79 19%
Student > Master 52 13%
Student > Doctoral Student 32 8%
Student > Bachelor 29 7%
Other 58 14%
Unknown 64 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 116 28%
Biochemistry, Genetics and Molecular Biology 100 25%
Medicine and Dentistry 35 9%
Engineering 23 6%
Pharmacology, Toxicology and Pharmaceutical Science 20 5%
Other 42 10%
Unknown 72 18%