Li Rongkang, Chen Xuan, Li Xinji, Huang Guocheng, Lu Chong, Wen Zhenyu, Chen Zebo, Lai Yongqing
Department of Urology, Guangdong and Shenzhen Key Laboratory of Male Reproductive Medicine and Genetics, Peking University Shenzhen Hospital, Clinical College of Anhui Medical University Shenzhen 518036, Guangdong, China.
The Fifth Clinical Medical College of Anhui Medical University Hefei 230032, Anhui, China.
Am J Transl Res. 2022 Jul 15;14(7):4606-4616. eCollection 2022.
Urinary bladder cancer (BCa) is globally the 10th most frequent cancer. As a novel diagnostic tool, miRNA in serum screening is non-invasive. This project aimed to determine particular serum miRNAs as novel biomarkers for diagnosing urinary BCa.
We designed a three-phase study with 122 healthy controls (HCs) and 132 BCa patients. The 30 miRNAs' expressions in serum from HCs and BCa patients were detected during the screening phase. The miRNAs with the most dysregulation were tested in the training (HCs vs. BCa, 30 each) and validation (80 HCs vs. 82 BCa) phase further. The diagnostic ability of these candidate miRNAs was estimated by the receiver operating characteristic (ROC) curves as well as the area under the ROC curve (AUC). The miRNAs' target genes and their annotations to functions were predicted utilizing bioinformatic assays.
Six serum miRNAs (miR-124-3p, miR-182-5p, miR-1-3p, miR-196a-5p, miR-23b-3p and miR-34a-5p) had significantly different expression between BCa patients and HCs in the training and validation phase. The four-microRNA panel improved the diagnostic value, with AUC =0.985. The result of bioinformatic analysis showed that these miRNAs' target genes in the panel may be related to the MAPK signaling pathway in bladder cancer.
Our study identified a four-miRNA panel that is a non-invasive new biomarker for diagnosing BCa.
膀胱癌（BCa）是全球第10大常见癌症。作为一种新型诊断工具，血清筛查中的miRNA具有非侵入性。本项目旨在确定特定的血清miRNA作为诊断膀胱癌的新型生物标志物。
我们设计了一项三相研究，纳入122名健康对照者（HCs）和132名膀胱癌患者。在筛查阶段检测HCs和膀胱癌患者血清中30种miRNA的表达。对失调最明显的miRNA在训练阶段（HCs与膀胱癌患者各30例）和验证阶段（80名HCs与82名膀胱癌患者）进一步进行检测。通过受试者工作特征（ROC）曲线以及ROC曲线下面积（AUC）评估这些候选miRNA的诊断能力。利用生物信息学分析预测miRNA的靶基因及其功能注释。
在训练和验证阶段，6种血清miRNA（miR-124-3p、miR-182-5p、miR-1-3p、miR-196a-5p、miR-23b-3p和miR-34a-5p）在膀胱癌患者和HCs之间表达存在显著差异。四miRNA组合提高了诊断价值，AUC = 0.985。生物信息学分析结果表明，该组合中这些miRNA的靶基因可能与膀胱癌中的MAPK信号通路有关。
我们的研究确定了一种四miRNA组合，它是诊断膀胱癌的非侵入性新型生物标志物。
