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

Background: Objective 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. Methods: An integrated database of miRNAs and their ‘relevant’ mRNA t...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:British journal of cancer 2015-08, Vol.113 (4), p.611-615
Hauptverfasser: Rane, Jayant K, Ylipää, Antti, Adamson, Rachel, Mann, Vincent M, Simms, Matthew S, Collins, Anne T, Visakorpi, Tapio, Nykter, Matti, Maitland, Norman J
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Background: Objective 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. Methods: An 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. Results: Integration 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. Conclusions: Our novel framework impartially identifies therapeutically relevant miRNA candidates from transcriptomic data sets.
ISSN:0007-0920
1532-1827
DOI:10.1038/bjc.2015.262