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Novel diagnostic and prognostic classifiers for prostate cancer identified by genome-wide microRNA profiling

Overview of attention for article published in Oncotarget, April 2016
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Title
Novel diagnostic and prognostic classifiers for prostate cancer identified by genome-wide microRNA profiling
Published in
Oncotarget, April 2016
DOI 10.18632/oncotarget.8953
Pubmed ID
Authors

Helle Kristensen, Anni R. Thomsen, Christa Haldrup, Lars Dyrskjøt, Søren Høyer, Michael Borre, Peter Mouritzen, Torben F. Ørntoft, Karina Dalsgaard Sørensen

Abstract

This study investigates the diagnostic and prognostic biomarker potential of miRNAs in prostate cancer (PC). We identified several new deregulated miRNAs between non-malignant (NM) and PC tissue samples and between more/less aggressive PC subgroups. We also developed and validated a novel 13-miRNA diagnostic classifier with high sensitivity and specificity for PC. Finally, we trained a new 3-miRNA prognostic classifier (miR-185-5p+miR-221-3p+miR-326) that predicted time to biochemical recurrence (BCR) independently of routine clinicopathological variables in a training radical prostatectomy (RP) cohort (n = 126) as well as in two independent validation cohorts (n = 110 and n = 99). After RT-qPCR-based profiling of 752 miRNAs in 13 NM and 134 PC tissue samples (cohort 1), we selected 93 top candidate diagnostic/prognostic miRNAs for validation in two independent patient sets (cohort 2: 19 NM and 138 PC; cohort 3: 28 NM and 113 PC samples). Diagnostic potential was assessed by ROC curve analysis and prognostic potential by Kaplan-Meier, uni- and multivariate Cox regression analyses. BCR after RP was used as endpoint. This is the first report of a miRNA signature with significant independent prognostic value demonstrated in three PC patient cohorts.

Twitter Demographics

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

Mendeley readers

The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Denmark 1 2%
Unknown 46 98%

Demographic breakdown

Readers by professional status Count As %
Researcher 13 28%
Student > Bachelor 8 17%
Student > Ph. D. Student 6 13%
Student > Master 4 9%
Other 2 4%
Other 4 9%
Unknown 10 21%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 12 26%
Medicine and Dentistry 10 21%
Agricultural and Biological Sciences 8 17%
Neuroscience 2 4%
Computer Science 2 4%
Other 2 4%
Unknown 11 23%

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 28 April 2016.
All research outputs
#6,597,485
of 7,621,460 outputs
Outputs from Oncotarget
#5,331
of 7,459 outputs
Outputs of similar age
#223,535
of 266,739 outputs
Outputs of similar age from Oncotarget
#72
of 96 outputs
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