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Hormonal Modulation of Breast Cancer Gene Expression: Implications for Intrinsic Subtyping in Premenopausal Women

Overview of attention for article published in Frontiers in oncology, November 2016
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Title
Hormonal Modulation of Breast Cancer Gene Expression: Implications for Intrinsic Subtyping in Premenopausal Women
Published in
Frontiers in oncology, November 2016
DOI 10.3389/fonc.2016.00241
Pubmed ID
Authors

Sarah M. Bernhardt, Pallave Dasari, David Walsh, Amanda R. Townsend, Timothy J. Price, Wendy V. Ingman

Abstract

Clinics are increasingly adopting gene-expression profiling to diagnose breast cancer subtype, providing an intrinsic, molecular portrait of the tumor. For example, the PAM50-based Prosigna test quantifies expression of 50 key genes to classify breast cancer subtype, and this method of classification has been demonstrated to be superior over traditional immunohistochemical methods that detect proteins, to predict risk of disease recurrence. However, these tests were largely developed and validated using breast cancer samples from postmenopausal women. Thus, the accuracy of such tests has not been explored in the context of the hormonal fluctuations in estrogen and progesterone that occur during the menstrual cycle in premenopausal women. Concordance between traditional methods of subtyping and the new tests in premenopausal women is likely to depend on the stage of the menstrual cycle at which the tissue sample is taken and the relative effect of hormones on expression of genes versus proteins. The lack of knowledge around the effect of fluctuating estrogen and progesterone on gene expression in breast cancer patients raises serious concerns for intrinsic subtyping in premenopausal women, which comprise about 25% of breast cancer diagnoses. Further research on the impact of the menstrual cycle on intrinsic breast cancer profiling is required if premenopausal women are to benefit from the new technology of intrinsic subtyping.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 62 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 62 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 18%
Researcher 8 13%
Student > Ph. D. Student 7 11%
Other 4 6%
Student > Bachelor 4 6%
Other 14 23%
Unknown 14 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 23%
Agricultural and Biological Sciences 11 18%
Medicine and Dentistry 11 18%
Pharmacology, Toxicology and Pharmaceutical Science 3 5%
Nursing and Health Professions 2 3%
Other 6 10%
Unknown 15 24%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 19 November 2016.
All research outputs
#20,656,820
of 25,374,917 outputs
Outputs from Frontiers in oncology
#11,313
of 22,416 outputs
Outputs of similar age
#241,528
of 313,258 outputs
Outputs of similar age from Frontiers in oncology
#33
of 62 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 22,416 research outputs from this source. They receive a mean Attention Score of 3.0. This one is in the 28th percentile – i.e., 28% of its peers scored the same or lower than it.
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We're also able to compare this research output to 62 others from the same source and published within six weeks on either side of this one. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.