The role of microRNAs in non-invasive diagnosis of bladder cancer: a systematic review.

IF 1.1 Q2 MEDICINE, GENERAL & INTERNAL

Einstein-Sao Paulo Pub Date : 2024-11-29 eCollection Date: 2024-01-01 DOI:10.31744/einstein_journal/2024RW0611

Pedro Ivo de Sousa Neto, Vicktor Bruno Pereira Pinto, Elaine Dos Santos Piancó, Malene Lima Gomes, Sally Cristina Moutinho Monteiro, Flávia Castello Branco Vidal, Maria do Desterro Soares Brandão Nascimento, Jaqueline Diniz Pinho, José de Ribamar Rodrigues Calixto, Marcelo Souza de Andrade

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Abstract

Objective: MicroRNAs are small non-coding RNAs that are abundantly expressed in various biofluids, making them promising candidates for cancer biomarkers. This review aims to present current evidence on the use of miRNA as biomarkers for the non-invasive diagnosis of bladder cancer.

Methods: A systematic literature review, using the Medline database, was performed in July 2022 according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. All articles were required to satisfy the risk-of-bias assessment using the Joanna Briggs Institute Critical Assessment Tools. Data were collected based on miRNA expression, sample type, expression profiles, and accuracy.

Results: The initial search retrieved 437 studies, 21 of which were included in the final analysis. Most studies on miRNA expression in human fluids used urine samples for analysis.

Conclusion: There is a trend to cluster the expressed miRNAs to build diagnostic panels or use them in association with other diagnostic methods to achieve reasonable accuracy.Prospero database registration: (https://www.crd.york.ac.uk/prospero/) under ID CRD42022351686.

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microrna在膀胱癌非侵袭性诊断中的作用：系统综述。

目的：microrna是一种小的非编码rna，在各种生物体液中大量表达，使其成为癌症生物标志物的有希望的候选者。本综述旨在介绍miRNA作为膀胱癌非侵入性诊断的生物标志物的最新证据。方法：根据系统评价和荟萃分析指南的首选报告项目，于2022年7月使用Medline数据库进行系统文献综述。所有的文章都需要满足使用乔安娜布里格斯研究所关键评估工具的偏倚风险评估。根据miRNA表达、样本类型、表达谱和准确性收集数据。结果：初始检索检索到437项研究，其中21项纳入最终分析。大多数关于人体体液中miRNA表达的研究使用尿液样本进行分析。结论：将表达的mirna聚集在一起构建诊断面板或与其他诊断方法联合使用以达到合理的准确性是一种趋势。普洛斯彼罗数据库注册：（https://www.crd.york.ac.uk/prospero/） ID CRD42022351686。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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