| 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. |
X Demographics
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Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Denmark | 1 | 2% |
| Unknown | 54 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 13 | 24% |
| Student > Bachelor | 10 | 18% |
| Student > Ph. D. Student | 6 | 11% |
| Student > Master | 4 | 7% |
| Other | 3 | 5% |
| Other | 7 | 13% |
| Unknown | 12 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 16 | 29% |
| Medicine and Dentistry | 10 | 18% |
| Agricultural and Biological Sciences | 7 | 13% |
| Computer Science | 2 | 4% |
| Chemistry | 2 | 4% |
| Other | 3 | 5% |
| Unknown | 15 | 27% |
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.
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#20,322,106
of 22,865,319 outputs
Outputs from Oncotarget
#10,574
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#253,439
of 299,158 outputs
Outputs of similar age from Oncotarget
#932
of 1,310 outputs
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