Urinary MicroRNA-21 for Prostate Cancer Detection Using a Silver Nanoparticle Sensor: A Promising Diagnostic Tool

In this study, we detected the expression levels of miR-21 in 38 clinical urine samples, obtained from 10 patients with PCa (with each sample obtained at three time points: before surgery, 1 month after surgery, and 3 months after surgery), 3 patients with benign prostatic hypertrophy (BPH), and 5 h...

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Bibliographic Details
Main Authors: See-Tong Pang, Yueh-Er Chiou, Jasmine Lim, Yi-Chun Zhang, Wen-Zhen Zeng, Teng Aik Ong, Wen-Hui Weng
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Biosensors
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Online Access:https://www.mdpi.com/2079-6374/14/12/599
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Summary:In this study, we detected the expression levels of miR-21 in 38 clinical urine samples, obtained from 10 patients with PCa (with each sample obtained at three time points: before surgery, 1 month after surgery, and 3 months after surgery), 3 patients with benign prostatic hypertrophy (BPH), and 5 healthy subjects (as a control group). All of the samples were examined using a silver nanoparticle-based biosensor, and the sensitivity of the biosensor was simultaneously confirmed via qRT-PCR. The results were further analyzed together with clinical data such as PSA values and cancer stages. The sensitivity of the biosensor ranged up to 100 fM, and it presented a rather high selectivity rate. Our results indicated a significantly decreased expression level of miR-21 in the patient cases at 3 months post-surgery when compared with pre-surgery levels (<i>p</i>-value < 0.001). In addition, when distinguishing the differences in the expression level of miR-21 between healthy subjects and patients with PCa or BPH, both groups showed highly significant differences (<i>p</i> = 0.008 and <i>p</i> < 0.001, respectively). The results strongly suggest that the proposed miR-21 biosensor can be used as an auxiliary screening tool for the early detection of PCa and may effectively facilitate tracking of the progression of PCa, thus enabling more accurate healthcare decision making.
ISSN:2079-6374