MicroRNA profiles of prostate carcinoma detected by multiplatform microRNA screening

Sven Wach(Friedrich-Alexander-Universität Erlangen-Nürnberg), Elke Nolte(Friedrich-Alexander-Universität Erlangen-Nürnberg), Jaroslaw Szczyrba(Saarland University), Robert Stöhr(Friedrich-Alexander-Universität Erlangen-Nürnberg), Arndt Hartmann(Friedrich-Alexander-Universität Erlangen-Nürnberg), Torben Ørntoft(Aarhus University Hospital), Lars Dyrskjøt(Aarhus University Hospital), Elke Eltze(University Hospital Münster), Wolf F. Wieland(University Hospital Regensburg), Bastian Keck(Friedrich-Alexander-Universität Erlangen-Nürnberg), Arif B. Ekici(Friedrich-Alexander-Universität Erlangen-Nürnberg), Friedrich A. Grässer(Saarland University), Bernd Wullich(Friedrich-Alexander-Universität Erlangen-Nürnberg)
International Journal of Cancer
March 11, 2011
Cited by 164

Abstract

MicroRNAs (miRNAs) are small RNA molecules that regulate gene expression via posttranscriptional inhibition of protein synthesis. They play a vital role in tumorigenesis. To characterize the diagnostic potential of miRNAs in prostate cancer, a leading cause of cancer mortality, we performed screening of miRNA expression profiles. We used commercially available microarrays to establish miRNA expression profiles from a cohort of 20 cancer samples. The expression of selected miRNAs was analyzed by quantitative real-time PCR and the identity of miRNA expressing cells was determined by miRNA in situ hybridization. We identified 25 miRNAs that showed a significant differential expression in cancer samples. The comparison with previously published data generated by deep sequencing of cDNA libraries of small RNA molecules revealed a concordance rate of 47% among miRNAs identified with both techniques. The differential expression of miRNAs miR-375, miR-143 and miR-145 was validated by quantitative PCR. MiRNA in situ hybridization revealed that the differential expression is cancer-cell associated. A combination of three miRNAs correctly classified tissue samples with an accuracy of 77.6% with an area under the receiver-operator characteristic curve of 0.810. Our data extend the knowledge about the deregulation of miRNAs in prostate cancer. The differential expression of several miRNAs is highly consistent using independent cohorts of tumor samples, different tissue preservation methods and different experimental methods. Our results indicate that combinations of miRNAs are promising biomarkers for the diagnosis of prostate cancer.


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