Evidence map›Paper›PMID 32612164›Full record

ArticleScientific reports2020

Validation of the four-miRNA biomarker panel MiCaP for prediction of long-term prostate cancer outcome.

Siri H Strand, Linnéa Schmidt, Simone Weiss, Michael Borre, Helle Kristensen, Anne Karin Ildor Rasmussen, Tina Fuglsang Daugaard, Gitte Kristensen, Hein Vincent Stroomberg, Martin Andreas Røder and 3 more

Abstract read
In one paragraph

Article in Scientific reports, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

13 authors.

Siri H StrandDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.
Linnéa SchmidtDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.
Simone WeissDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark.
Michael BorreDepartment of Clinical Medicine, Aarhus University, Aarhus, Denmark.
Helle KristensenExiqon - a Qiagen Company, Vedbæk, Denmark.
Anne Karin Ildor RasmussenExiqon - a Qiagen Company, Vedbæk, Denmark.
Tina Fuglsang DaugaardDepartment of Biomedicine, Aarhus University Hospital, Aarhus, Denmark.
Gitte KristensenDepartment of Urology, Rigshospitalet, Faculty of Health and Medical Sciences, Copenhagen Prostate Cancer Center (CPC), University of Copenhagen, Copenhagen, Denmark.
Hein Vincent StroombergDepartment of Urology, Rigshospitalet, Faculty of Health and Medical Sciences, Copenhagen Prostate Cancer Center (CPC), University of Copenhagen, Copenhagen, Denmark.
Martin Andreas RøderDepartment of Urology, Rigshospitalet, Faculty of Health and Medical Sciences, Copenhagen Prostate Cancer Center (CPC), University of Copenhagen, Copenhagen, Denmark.
Klaus BrassoDepartment of Urology, Rigshospitalet, Faculty of Health and Medical Sciences, Copenhagen Prostate Cancer Center (CPC), University of Copenhagen, Copenhagen, Denmark.
Peter MouritzenExiqon - a Qiagen Company, Vedbæk, Denmark.
Karina Dalsgaard SørensenDepartment of Molecular Medicine (MOMA), Aarhus University Hospital, Aarhus, Denmark. kdso@clin.au.dk.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Improved prostate cancer prognostic biomarkers are urgently needed. We previously identified the four-miRNA prognostic biomarker panel MiCaP ((miR-23a-3p × miR-10b-5p)/(miR-133a-3p × miR-374b-5p)) for prediction of biochemical recurrence (BCR) after radical prostatectomy (RP). Here, we identified an optimal numerical cut-off for MiCaP dichotomisation using a training cohort of 475 RP patients and tested this in an independent cohort of 281 RP patients (PCA281). Kaplan-Meier, uni- and multivariate Cox regression analyses were conducted for multiple endpoints: BCR, metastatic-(mPC) and castration-resistant prostate cancer (CRPC), prostate cancer-specific (PCSS) and overall survival (OS). Functional effects of the four MiCaP miRNAs were assessed by overexpression and inhibition experiments in prostate cancer cell lines. We found the numerical value 5.709 optimal for MiCaP dichotomisation. This was independently validated in PCA281, where a high MiCaP score significantly [and independent of the Cancer of the Prostate Risk Assessment Postsurgical (CAPRA-S) score] predicted BCR, progression to mPC and CRPC, and PCSS, but not OS. Harrell's C-index increased upon addition of MiCaP to CAPRA-S for all endpoints. Inhibition of miR-23a-3p and miR-10b-5p, and overexpression of miR-133a-3p and miR-374b-5p significantly reduced cell survival. Our results may promote future implementation of a MiCaP-based test for improved prostate cancer risk stratification.

Indexed as

Biomarkers, TumorCell Line, TumorCell SurvivalGene Expression ProfilingHumansMaleMicroRNAsPrognosisProstateProstatectomyProstatic Neoplasms, Castration-ResistantBiomarkers, TumorMicroRNAsMIRN10 microRNA, humanMIRN133 microRNA, humanMIRN23a microRNA, humanMIRN374 microRNA 374, human

Identifiers

PMID32612164
PMCPMC7329825

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.