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Abstract
ObjectiveTo validate previously discovered miRNAs (miR-31-5p and miR-149-5p) as prognostic factors for UTUC in an independent cohort of UTUC patients.Patients and MethodsMulticenter, international and retrospective study of formalin-fixed paraffin-embedded tissue samples from 103 UTUC patients (45 progressing and 58 non-progressing) who underwent radical nephroureterectomy. Total RNA was isolated and reverse transcribed. The expression of target miRNAs (miR-31-5p and miR-149-5p) and the endogenous control miR-218-5p was evaluated in all samples by reverse transcription quantitative PCR. Normalized miRNA expression values were evaluated by multivariate forward stepwise Cox regression analysis. Kaplan Meier curves were used to discriminate between two groups of patients with a different probability of tumour progression.ResultsThe mean age (range) of the series was 67 (33-94) years. Overall, 45 patients (43.7%) developed tumour progression and 32 patients (31.2%) died, 20 of these (62.5%) due to their UTUC, after a median follow-up of 36 months. The mean time for tumour progression and cancer-specific survival were 15 and 20 months, respectively. Five year tumour progression free survival and cancer-specific survival were 58% for ≤ pT2, 36% for pT3 and 0% for pT4 and 67.8% for ≤ pT2, 50.6% for pT3 and 0% for pT4, respectively. In the multivariate analysis, expression of miR-31-5p was found to be an independent prognostic factor of tumour progression (HR 1.1; 95% CI 1.039-1.273; p=0.02). Kaplan Meier curve shows that miR-31-5p expression values are able to discriminate between two groups of UTUC patients with a different probability of tumour progression (p=0.007).ConclusionsWe have been able to validate our previous results in an independent multicentre international cohort of UTUC patients, suggesting that miRNA-31-5p could be a useful prognostic marker of UTUC progression. The application of miRNA expression values to clinical practice could refine the currently used clinicopathological-based approach for predicting UTUC patients’ outcome.
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