microRNA profiles in urine by next-generation sequencing can stratify bladder cancer subtypes
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Barbara Pardini1,2,*, Francesca Cordero3,*, Alessio Naccarati1,*, Clara Viberti1,2, Giovanni Birolo1,2, Marco Oderda4, Cornelia Di Gaetano1,2, Maddalena Arigoni5, Federica Martina3, Raffaele A. Calogero5, Carlotta Sacerdote6, Paolo Gontero4, Paolo Vineis1,7 and Giuseppe Matullo1,2
1Italian Institute for Genomic Medicine, Turin, Italy
2Department of Medical Sciences, University of Turin, Turin, Italy
3Department of Computer Science, University of Turin, Turin, Italy
4Department of Surgical Sciences, University of Turin and Città della Salute e della Scienza, Turin, Italy
5Molecular Biotechnology Center, Department of Biotechnology and Health Sciences, University of Turin, Turin, Italy
6Center for Cancer Prevention, CPO-Piemonte, Turin, Italy
7MRC-HPA Centre for Environment and Health, School of Public Health, Imperial College London, London, United Kingdom
*These authors contributed equally to this work
Barbara Pardini, email: [email protected]
Keywords: bladder cancer; microRNA profiling; urine biomarkers; next-generation sequencing; liquid biopsy
Received: September 06, 2017 Accepted: March 18, 2018 Published: April 17, 2018
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.
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