Lin Shengjie, Li Xutai, Ge Zhenjian, Chen Wenkang, Li Yingqi, Zhang Pengwu, Wu Yutong, Wang Wuping, Chen Siwei, Zhou Huimei, Tao Lingzhi, Lai Yongqing
Department of Urology, Peking University Shenzhen Hospital, The fifth Clinical Medical College of Anhui Medical University, 1120 Lianhua Road, Shenzhen, 518036, China.
Institute of Urology, Shenzhen Peking University-The Hong Kong University of Science and Technology Medical Center, Shenzhen, 518036, China.
Sci Rep. 2025 May 25;15(1):18135. doi: 10.1038/s41598-025-01225-6.
Hitherto there is no praiseworthy noninvasive methods in the early diagnosis of renal cell carcinoma (RCC). MicroRNAs (miRNAs) could be utilized as molecular markers for diverse malignancies. In this study, we aim to discern potential miRNAs as markers for screening RCC. We employed quantitative reverse transcription-polymerase chain reaction (RT-qPCR) to detect expression levels of candidate miRNAs in serum specimens of 108 RCC patients and 112 health volunteers. Diagnostic values of miRNAs were appraised, and panel was constructed by dint of receiver operating characteristic curves, the area under the ROC curve and backward stepwise logistic regression analysis. Moreover, we capitalized on bioinformatics analysis for exploration of miRNAs biological functions. The expression of five miRNAs (miR-30c-5p, miR-142-3p, miR-206, miR-223-3p, miR-200c-5p) were markedly alteration in serum specimens of RCC patients and health subjects. A three-miRNA panel combining miR-30c-5p, miR-142-3p and miR-206 was constructed and could discriminate RCC patients and healthy subjects satisfactorily with 0.872 (0.811-0.919, P < 0.001) AUC, 81.25% sensitivity and 86.90% specificity. ATF3 and MYC seem to be potential targets of the three-miRNA panel. The novel miRNA-based panel may perform as potential noninvasive markers to discriminate RCC patients and healthy subjects in advance.
迄今为止,在肾细胞癌(RCC)的早期诊断中尚无值得称赞的非侵入性方法。微小RNA(miRNA)可作为多种恶性肿瘤的分子标志物。在本研究中,我们旨在识别潜在的miRNA作为筛查RCC的标志物。我们采用定量逆转录-聚合酶链反应(RT-qPCR)检测108例RCC患者和112名健康志愿者血清标本中候选miRNA的表达水平。评估了miRNA的诊断价值,并通过绘制受试者工作特征曲线、计算ROC曲线下面积和向后逐步逻辑回归分析构建了诊断模型。此外,我们利用生物信息学分析来探索miRNA的生物学功能。5种miRNA(miR-30c-5p、miR-142-3p、miR-206、miR-223-3p、miR-200c-5p)在RCC患者和健康受试者的血清标本中的表达有明显改变。构建了一个包含miR-30c-5p、miR-142-3p和miR-206的三miRNA诊断模型,其AUC为0.872(0.811-0.919,P < 0.001),灵敏度为81.25%,特异性为86.90%,能够较好地区分RCC患者和健康受试者。ATF3和MYC似乎是该三miRNA诊断模型的潜在靶点。基于miRNA的新型诊断模型可能作为潜在的非侵入性标志物,提前区分RCC患者和健康受试者。