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Identification of non-invasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes

Overview of attention for article published in Molecular Cancer, October 2017
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

blogs
1 blog

Citations

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132 Dimensions

Readers on

mendeley
105 Mendeley
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Title
Identification of non-invasive miRNAs biomarkers for prostate cancer by deep sequencing analysis of urinary exosomes
Published in
Molecular Cancer, October 2017
DOI 10.1186/s12943-017-0726-4
Pubmed ID
Authors

Marta Rodríguez, Cristina Bajo-Santos, Nina P. Hessvik, Susanne Lorenz, Bastian Fromm, Viktor Berge, Kirsten Sandvig, Aija Linē, Alicia Llorente

Abstract

The aim of this study was to identify microRNAs in urinary exosomes that are differently expressed in prostate cancer patients and healthy donors. For this purpose, RNA was extracted from urinary exosomes from 20 prostate cancer patients and 9 healthy males and the microRNAs were analyzed by next generation sequencing. Interestingly, 5 microRNAs - miR-196a-5p, miR-34a-5p, miR-143-3p, miR-501-3p and miR-92a-1-5p - were significantly downregulated in exosomes from prostate cancer patients. Furthermore, RT-qPCR analysis of an independent cohort of 28 prostate cancer patients and 19 healthy males confirmed that miR-196a-5p and miR-501-3p were downregulated in prostate cancer samples. These results suggest that specific microRNAs in urinary exosomes might serve as non-invasive biomarkers for prostate cancer. In particular, miR-196a-5p and miR-501-3p are promising biomarkers that need to be further studied in large patient cohorts.

Mendeley readers

The data shown below were compiled from readership statistics for 105 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 105 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 14%
Student > Bachelor 14 13%
Researcher 12 11%
Student > Master 12 11%
Student > Doctoral Student 10 10%
Other 14 13%
Unknown 28 27%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 32 30%
Medicine and Dentistry 12 11%
Agricultural and Biological Sciences 9 9%
Pharmacology, Toxicology and Pharmaceutical Science 4 4%
Computer Science 3 3%
Other 8 8%
Unknown 37 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 26 June 2020.
All research outputs
#4,572,030
of 18,038,980 outputs
Outputs from Molecular Cancer
#242
of 1,412 outputs
Outputs of similar age
#94,286
of 330,800 outputs
Outputs of similar age from Molecular Cancer
#13
of 129 outputs
Altmetric has tracked 18,038,980 research outputs across all sources so far. This one has received more attention than most of these and is in the 74th percentile.
So far Altmetric has tracked 1,412 research outputs from this source. They receive a mean Attention Score of 4.0. This one has done well, scoring higher than 82% 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 330,800 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 70% of its contemporaries.
We're also able to compare this research output to 129 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.