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MMTV-PyMT and Derived Met-1 Mouse Mammary Tumor Cells as Models for Studying the Role of the Androgen Receptor in Triple-Negative Breast Cancer Progression

Overview of attention for article published in Hormones and Cancer, February 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)

Mentioned by

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1 X user
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2 patents

Citations

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49 Dimensions

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89 Mendeley
Title
MMTV-PyMT and Derived Met-1 Mouse Mammary Tumor Cells as Models for Studying the Role of the Androgen Receptor in Triple-Negative Breast Cancer Progression
Published in
Hormones and Cancer, February 2017
DOI 10.1007/s12672-017-0285-6
Pubmed ID
Authors

Jessica L. Christenson, Kiel T. Butterfield, Nicole S. Spoelstra, John D. Norris, Jatinder S. Josan, Julie A. Pollock, Donald P. McDonnell, Benita S. Katzenellenbogen, John A. Katzenellenbogen, Jennifer K. Richer

Abstract

Triple-negative breast cancer (TNBC) has a faster rate of metastasis compared to other breast cancer subtypes, and no effective targeted therapies are currently FDA-approved. Recent data indicate that the androgen receptor (AR) promotes tumor survival and may serve as a potential therapeutic target in TNBC. Studies of AR in disease progression and the systemic effects of anti-androgens have been hindered by the lack of an AR-positive (AR+) immunocompetent preclinical model. In this study, we identified the transgenic MMTV-PyMT (mouse mammary tumor virus-polyoma middle tumor-antigen) mouse mammary gland carcinoma model of breast cancer and Met-1 cells derived from this model as tools to study the role of AR in breast cancer progression. AR protein expression was examined in late-stage primary tumors and lung metastases from MMTV-PyMT mice as well as in Met-1 cells by immunohistochemistry (IHC). Sensitivity of Met-1 cells to the AR agonist dihydrotestosterone (DHT) and anti-androgen therapy was examined using cell viability, migration/invasion, and anchorage-independent growth assays. Late-stage primary tumors and lung metastases from MMTV-PyMT mice and Met-1 cells expressed abundant nuclear AR protein, while negative for estrogen and progesterone receptors. Met-1 sensitivity to DHT and AR antagonists demonstrated a reliance on AR for survival, and AR antagonists inhibited invasion and anchorage-independent growth. These data suggest that the MMTV-PyMT model and Met-1 cells may serve as valuable tools for mechanistic studies of the role of AR in disease progression and how anti-androgens affect the tumor microenvironment.

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 89 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 89 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 22 25%
Student > Bachelor 11 12%
Researcher 8 9%
Student > Doctoral Student 5 6%
Student > Master 5 6%
Other 9 10%
Unknown 29 33%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 15 17%
Medicine and Dentistry 12 13%
Agricultural and Biological Sciences 7 8%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Immunology and Microbiology 3 3%
Other 11 12%
Unknown 37 42%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 09 April 2024.
All research outputs
#8,194,369
of 25,988,468 outputs
Outputs from Hormones and Cancer
#25
of 86 outputs
Outputs of similar age
#143,337
of 436,361 outputs
Outputs of similar age from Hormones and Cancer
#1
of 3 outputs
Altmetric has tracked 25,988,468 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 86 research outputs from this source. They receive a mean Attention Score of 3.9. This one has gotten more attention than average, scoring higher than 67% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 436,361 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them