Translational oncology · 2026
Integrative analysis of urinary microRNAs for prostate cancer detection: A proof-of-concept study.
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Samani Leila Asadi, Rahmani Saeid, Kashi Amir Hossein, Ziaee Seyed Amir Mohsen, Mowla Seyed Javad
Аннотация
BACKGROUND: Liquid biopsies analyzing circulating nucleic acids offer a non‑invasive strategy for early detection, disease monitoring, and precision medicine. Among these, urinary microRNAs (miRNAs) have emerged as robust biomarkers owing to their stability and regulatory effects on gene expression and tumor progression.
METHODS: A multi‑omics integrative analysis combining public microarray, bulk RNA‑seq, and single‑cell RNA‑seq datasets was performed to identify miRNAs differentially expressed between prostate cancer (PCa) patients and healthy controls. The diagnostic potential of these candidates was assessed using receiver operating characteristic (ROC) analysis and support vector machine (SVM) modeling. Validation was conducted through quantitative polymerase chain reaction (qPCR) on urine samples from 19 PCa and 7 benign prostatic hyperplasia (BPH) subjects.
RESULTS: miR-23b-3p demonstrated consistent downregulation across transcriptomic datasets derived from urine, serum, and tissue. ROC and SVM analyses indicated strong diagnostic performance. Urinary qPCR validation yielded an area under the curve (AUC) of 0.79 (95% CI: 0.51-1.00), sensitivity of 0.73 (95% CI: 0.39-0.94), and specificity of 0.86 (95% CI: 0.42-1.00).
CONCLUSIONS: The findings suggest that miR-23b-3p represents a promising complementary biomarker for non‑invasive PCa diagnosis. Further large‑scale validation integrating transcriptomic and clinical data is warranted to confirm its clinical applicability.
METHODS: A multi‑omics integrative analysis combining public microarray, bulk RNA‑seq, and single‑cell RNA‑seq datasets was performed to identify miRNAs differentially expressed between prostate cancer (PCa) patients and healthy controls. The diagnostic potential of these candidates was assessed using receiver operating characteristic (ROC) analysis and support vector machine (SVM) modeling. Validation was conducted through quantitative polymerase chain reaction (qPCR) on urine samples from 19 PCa and 7 benign prostatic hyperplasia (BPH) subjects.
RESULTS: miR-23b-3p demonstrated consistent downregulation across transcriptomic datasets derived from urine, serum, and tissue. ROC and SVM analyses indicated strong diagnostic performance. Urinary qPCR validation yielded an area under the curve (AUC) of 0.79 (95% CI: 0.51-1.00), sensitivity of 0.73 (95% CI: 0.39-0.94), and specificity of 0.86 (95% CI: 0.42-1.00).
CONCLUSIONS: The findings suggest that miR-23b-3p represents a promising complementary biomarker for non‑invasive PCa diagnosis. Further large‑scale validation integrating transcriptomic and clinical data is warranted to confirm its clinical applicability.