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Decoding the usefulness of non-coding RNAs as breast cancer markers

Overview of attention for article published in Journal of Translational Medicine, September 2016
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  • Above-average Attention Score compared to outputs of the same age and source (55th percentile)

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Title
Decoding the usefulness of non-coding RNAs as breast cancer markers
Published in
Journal of Translational Medicine, September 2016
DOI 10.1186/s12967-016-1025-3
Pubmed ID
Authors

Maria Amorim, Sofia Salta, Rui Henrique, Carmen Jerónimo

Abstract

Although important advances in the management of breast cancer (BC) have been recently accomplished, it still constitutes the leading cause of cancer death in women worldwide. BC is a heterogeneous and complex disease, making clinical prediction of outcome a very challenging task. In recent years, gene expression profiling emerged as a tool to assist in clinical decision, enabling the identification of genetic signatures that better predict prognosis and response to therapy. Nevertheless, translation to routine practice has been limited by economical and technical reasons and, thus, novel biomarkers, especially those requiring non-invasive or minimally invasive collection procedures, while retaining high sensitivity and specificity might represent a significant development in this field. An increasing amount of evidence demonstrates that non-coding RNAs (ncRNAs), particularly microRNAs (miRNAs) and long noncoding RNAs (lncRNAs), are aberrantly expressed in several cancers, including BC. miRNAs are of particular interest as new, easily accessible, cost-effective and non-invasive tools for precise management of BC patients because they circulate in bodily fluids (e.g., serum and plasma) in a very stable manner, enabling BC assessment and monitoring through liquid biopsies. This review focus on how ncRNAs have the potential to answer present clinical needs in the personalized management of patients with BC and comprehensively describes the state of the art on the role of ncRNAs in the diagnosis, prognosis and prediction of response to therapy in BC.

X Demographics

X Demographics

The data shown below were collected from the profiles of 5 X users 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 92 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 1%
Pakistan 1 1%
Belgium 1 1%
Unknown 89 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 21%
Student > Ph. D. Student 15 16%
Student > Bachelor 14 15%
Researcher 13 14%
Student > Doctoral Student 5 5%
Other 17 18%
Unknown 9 10%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 28 30%
Medicine and Dentistry 16 17%
Agricultural and Biological Sciences 14 15%
Psychology 4 4%
Nursing and Health Professions 4 4%
Other 12 13%
Unknown 14 15%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 22 September 2016.
All research outputs
#13,989,437
of 22,888,307 outputs
Outputs from Journal of Translational Medicine
#1,697
of 4,004 outputs
Outputs of similar age
#177,219
of 321,166 outputs
Outputs of similar age from Journal of Translational Medicine
#31
of 74 outputs
Altmetric has tracked 22,888,307 research outputs across all sources so far. This one is in the 37th percentile – i.e., 37% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,004 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.5. This one has gotten more attention than average, scoring higher than 55% 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 321,166 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 43rd percentile – i.e., 43% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 74 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 55% of its contemporaries.