Introduction: Urinary microRNAs (miRNAs) may serve as promising biomarkers for non-invasive early detection of prostate cancer (PCa). We aimed to identify multi-miRNA urinary biomarker panel for early detection of PCa.
Methods: Urine samples from 83 PCa patients and 88 healthy control subjects in a Chinese population were collected for miRNA profiling. The absolute expression of 360 unique miRNAs were measured in each sample using a highly sensitive and robust RT-qPCR workflow. Candidate urinary miRNA biomarkers were identified based on differential expression between PCa patients and healthy controls. Multi-miRNA biomarker panels were optimised for detection of PCa using three regression algorithms (Lasso, Stepwise, Exhaustive) to identify an optimal biomarker panel with best detection performance and least number of miRNAs.
Results: A total of 312 miRNAs were detected in urine samples, 10 candidate urinary miRNA biomarkers differentially expressed between PCa and healthy samples were identified. A panel comprising these 10 miRNAs detected PCa with an area under the curve (AUC) of 0.738. Optimization of multi-miRNA panels resulted in a 6-miRNA biomarker panel (hsa-miR-375, hsa-miR-520d-5p, hsa-miR-199b-5p, hsa-miR-518e-5p, hsa-miR-31-3p and hsa-miR-4306) that had an AUC of 0.750.
Conclusion: We identified a urinary miRNA biomarker panel for early detection of PCa in a Chinese population.
Keywords: biomarker; detection; microRNAs; prostate cancer; urinary.