Investigative UrologyIdentification of miR-187 and miR-182 as Biomarkers of Early Diagnosis and Prognosis in Patients with Prostate Cancer Treated with Radical Prostatectomy
Review articleOpen access
2014/07/01 Full-length article DOI: 10.1016/j.juro.2014.01.107
Journal: The Journal of Urology
PurposemiRNAs are noncoding RNAs that negatively regulate target mRNA gene expression. Aberrant miRNA expression is associated with prostate cancer pathogenesis. We identified miRNAs as potential biomarkers for prostate cancer diagnosis and prognosis.Materials and MethodsTotal RNA was obtained from 10 normal prostate and 50 prostate cancer samples, and analyzed using the GeneChip® miRNA 2.0 Array. At a median followup of 92 months (range 2 to 189) an independent cohort of 273 paraffin embedded prostate cancer samples was used for validation by quantitative reverse transcriptase-polymerase chain reaction. Another 92 urine samples from patients undergoing prostate biopsy were evaluated for these miRNAs.ResultsmiR-182 and 187, the miRNAs most differentially expressed between normal and tumor tissue, were selected for further validation. miR-187 inversely correlated with cT (p = 0.125) and pT (p = 0.0002) stages, Gleason score (p = 0.003) and TMPRSS2-ERG status (p = 0.003). The log rank test showed associations of miR-182 with biochemical (p = 0.026) and clinical (p = 0.043) progression-free survival, as also noted on multivariate analysis. A significant independent improvement in the definition of risk of progression was achieved by combining miR-182 expression with Gleason score (p <0.0001). miR-187 detection in urine provided an independent predictive value for positive biopsy. A prediction model including serum prostate specific antigen, urine PCA3 and miR-187 provided 88.6% sensitivity and 50% specificity (AUC 0.711, p = 0.001).ConclusionsResults show that miR-182 and 187 are promising biomarkers for prostate cancer prognosis to identify patients at risk for progression and for diagnosis to improve the predictive capability of existing biomarkers.
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