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© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Abstract

Bladder cancer is the 10th most common cancer type worldwide. Cystoscopy represents the gold standard for bladder cancer diagnosis, but this procedure is invasive and painful, hence the need to identify new biomarkers through noninvasive procedures. microRNAs (miRNAs) are considered to be promising diagnostic molecules, because they are very stable in biological fluids (including urine) and easily detectable. This systematic review analyses the power of urine miRNAs as bladder cancer diagnostic markers. We conducted this systematic review according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. A total of 293 records related to miRNAs and their diagnostic significance in BC were retrieved from the PubMed and Embase databases. A systematic search of the literature was performed, and a total of 25 articles (N = 4054 participants) were identified and reviewed. Although many of the selected studies were of high scientific quality, the results proved to be quite heterogeneous, because we did not identify a univocal consensus for a specific miRNA signature but only isolated the signatures. We did not identify a univocal consensus for a specific diagnostic miRNA signature but only isolated the signatures, some of them with better diagnostic power compared to the others.

Details

Title
Urinary miRNAs as a Diagnostic Tool for Bladder Cancer: A Systematic Review
Author
Grimaldi, Anna Maria 1   VIAFID ORCID Logo  ; Lapucci, Cristina 2 ; Salvatore, Marco 1   VIAFID ORCID Logo  ; Incoronato, Mariarosaria 1   VIAFID ORCID Logo  ; Ferrari, Maurizio 1 

 IRCCS SYNLAB SDN, Via Gianturco 113, 80143 Naples, Italy 
 Genetic Unit, Synlab Italia, 25014 Castenedolo, Italy 
First page
2766
Publication year
2022
Publication date
2022
Publisher
MDPI AG
e-ISSN
22279059
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2748270118
Copyright
© 2022 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.