Evidence map›Paper›PMID 26203762›Full record

ArticleBritish journal of cancer2015

Construction of therapeutically relevant human prostate epithelial fate map by utilising miRNA and mRNA microarray expression data.

Jayant K Rane, Antti Ylipää, Rachel Adamson, Vincent M Mann, Matthew S Simms, Anne T Collins, Tapio Visakorpi, Matti Nykter, Norman J Maitland

Abstract read
In one paragraph

Article in British journal of cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 pooled it
–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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. MicroRNA Dysregulation in Prostate Cancer.Pharmacogenomics and personalized medicine · 2022
    Article
  3. Review
  4. Article
  5. Article
  6. 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

9 authors.

Jayant K RaneDepartment of Biology, YCR Cancer Research Unit, University of York, York YO10 5DD, North Yorkshire, UK.
Antti Ylipää1] Prostate Cancer Research Center, Institute of Biosciences and Medical Technology (BioMediTech), University of Tampere and Tampere University Hospital, Biokatu 8, Tampere 33520, Finland [2] Department of Signal Processing, Tampere University of Technology, Korkeakoulunkatu 10, Tampere 33720, Finland.
Rachel AdamsonDepartment of Biology, YCR Cancer Research Unit, University of York, York YO10 5DD, North Yorkshire, UK.
Vincent M Mann1] Hull York Medical School, University of Hull, Hull HU6 7RX, East Yorkshire, UK [2] Department of Urology, Castle Hill Hospital, Cottingham HU16 5JQ, East Yorkshire, UK.
Matthew S Simms1] Hull York Medical School, University of Hull, Hull HU6 7RX, East Yorkshire, UK [2] Department of Urology, Castle Hill Hospital, Cottingham HU16 5JQ, East Yorkshire, UK.
Anne T CollinsDepartment of Biology, YCR Cancer Research Unit, University of York, York YO10 5DD, North Yorkshire, UK.
Tapio VisakorpiMolecular Biology of Prostate Cancer Group, Institute of Biosciences and Medical Technology (BioMediTech), University of Tampere and Tampere University Hospital, BioMediTech, Biokatu 8, Tampere 33520, Finland.
Matti Nykter1] Prostate Cancer Research Center, Institute of Biosciences and Medical Technology (BioMediTech), University of Tampere and Tampere University Hospital, Biokatu 8, Tampere 33520, Finland [2] Department of Signal Processing, Tampere University of Technology, Korkeakoulunkatu 10, Tampere 33720, Finland.
Norman J Maitland1] Department of Biology, YCR Cancer Research Unit, University of York, York YO10 5DD, North Yorkshire, UK [2] Department of Urology, Castle Hill Hospital, Cottingham HU16 5JQ, East Yorkshire, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundObjective identification of key miRNAs from transcriptomic data is difficult owing to the inherent inconsistencies within miRNA target-prediction algorithms and the promiscuous nature of miRNA-mRNA target relationship.

methodsAn integrated database of miRNAs and their 'relevant' mRNA targets was generated from validated miRNA and mRNA microarray data sets generated from patient-derived prostate epithelial normal and cancer stem-like cells (SCs) and committed basal (CB) cells. The effect of miR-542-5p inhibition was studied to provide proof-of-principle for database utility.

resultsIntegration of miRNA-mRNA databases showed that signalling pathways and processes can be regulated by a single or relatively few miRNAs, for example, DNA repair/Notch pathway by miR-542-5p, P=0.008. Inhibition of miR-542-5p in CB cells (thereby achieving miR-542-5p expression levels similar to SCs) promoted efficient DNA repair and activated expression of Notch reporters, HES1 and Survivin, without inducing dedifferentiation into SCs.

conclusionsOur novel framework impartially identifies therapeutically relevant miRNA candidates from transcriptomic data sets.

Indexed as

DNA RepairEpithelial CellsGene Expression Regulation, NeoplasticHumansMaleMicroRNAsNeoplastic Stem CellsProstateReceptors, NotchRNA, MessengerSignal TransductionMicroRNAsReceptors, NotchRNA, Messenger

Identifiers

PMID26203762
PMCPMC4647689

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-SA
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Registered trials

None linked

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.