microRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes

// Barbara Pardini 1, 2, * , Francesca Cordero 3, * , Alessio Naccarati 1, * , Clara Viberti 1, 2 , Giovanni Birolo 1, 2 , Marco Oderda 4 , Cornelia Di Gaetano 1, 2 , Maddalena Arigoni 5 , Federica Martina 3 , Raffaele A. Calogero 5 , Carlotta Sacerdote 6 , Paolo Gontero 4 , Paolo Vineis 1, 7 and Giuseppe Matullo 1, 2 1 Italian Institute for Genomic Medicine, Turin, Italy 2 Department of Medical Sciences, University of Turin, Turin, Italy 3 Department of Computer Science, University of Turin, Turin, Italy 4 Department of Surgical Sciences, University of Turin and Citta della Salute e della Scienza, Turin, Italy 5 Molecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Turin, Turin, Italy 6 Center for Cancer Prevention, CPO-Piemonte, Turin, Italy 7 MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom * These authors contributed equally to this work Correspondence to: Barbara Pardini, email: barbara.pardini@hugef.org Keywords: bladder cancer; microRNA profiling; urine biomarkers; next-generation sequencing; liquid biopsy Received: September 06, 2017      Accepted: March 18, 2018      Published: April 17, 2018 ABSTRACT Bladder cancer (BC) is the most frequent malignancy of the urinary tract with a high incidence in men and smokers. Currently, there are no non-invasive markers useful for BC diagnosis and subtypes classification that could overcome invasive procedures such as cystoscopy. Dysregulated miRNA profiles have been associated with numerous cancers, including BC. Cell-free miRNAs are abundantly present in a variety of biofluids including urine and make them promising candidates in cancer biomarker discovery. In the present study, the identification of miRNA fingerprints associated with different BC status was performed by next-generation sequencing on urine samples from 66 BC and 48 controls. Three signatures based on dysregulated miRNAs have been identified by regression models, assessing the power to discriminate different BC subtypes. Altered miRNAs according to invasiveness and grade were validated by qPCR on 112 cases and 65 controls (among which 46 cases and 16 controls were an independent group of subjects while the rest were replica samples). The area under the curve (AUC) computed including three miRNAs (miR-30a-5p, let-7c-5p and miR-486-5p) altered in all BC subtypes showed a significantly increased accuracy in the discrimination of cases and controls (AUC model = 0.70; p -value = 0.01). In conclusions, the non-invasive detection in urine of a selected number of miRNAs altered in different BC subtypes could lead to an accurate early diagnosis of cancer and stratification of patients.