Oncotarget

Research Papers:

Urinary cell microRNA-based prognostic classifier for non-muscle invasive bladder cancer

Mercedes Ingelmo-Torres, Juan Jose Lozano, Laura Izquierdo, Albert Carrion, Meritxell Costa, Lidia Gomez, María José Ribal, Antonio Alcaraz and Lourdes Mengual _

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Oncotarget. 2017; 8:18238-18247. https://doi.org/10.18632/oncotarget.15315

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Abstract

Mercedes Ingelmo-Torres1, Juan José Lozano2, Laura Izquierdo1, Albert Carrion1, Meritxell Costa1, Lidia Gómez1, María José Ribal1, Antonio Alcaraz1, Lourdes Mengual1

1Laboratory and Department of Urology, Hospital Clínic de Barcelona, Centre de Recerca Biomèdica CELLEX, Institut d’Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Universitat de Barcelona, Barcelona, Spain

2CIBERehd, Plataforma de Bioinformática, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas, Hospital Clínic de Barcelona, Barcelona, Spain

Correspondence to:

Lourdes Mengual, email: lmengual@clinic.ub.es

Keywords: biomarkers, bladder cancer, microRNA, tumour progression, urine

Received: October 11, 2016    Accepted: November 30, 2016    Published: February 14, 2017

ABSTRACT

Current prognostic tools for non-muscle invasive bladder cancer (NMIBC) do not have enough discriminative capacity to predict the risk of tumour progression. This study aimed to identify urinary cell microRNAs that may be useful as non-invasive predictive biomarkers of tumour progression in NMIBC patients. To this end, 210 urine samples from NMIBC patients were included in the study. RNA was extracted from urinary cells and expression of 8 microRNAs, previously described by our group, was analysed by quantitative PCR. A tumour progression predicting model was developed by Cox regression analysis and validated by bootstrapping. Regression analysis identified miR-140-5p and miR-92a-3p as independent predictors of tumour progression. The risk score derived from the model containing these two microRNAs was able to discriminate between two groups with a highly significant different probability of tumour progression (HR, 5.204; p<0.001) which was maintained when patients were stratified according to tumour risk. The algorithm was also able to identify two groups with different cancer-specific survival (HR, 3.879; p=0.021). Although the data needs to be externally validated, miRNA analysis in urine appears to be a valuable prognostic tool in NMIBC patients.


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