Identification of cell-free microRNAs in the urine of patients with prostate cancer

Objectives: Current methods for the early detection of prostate cancer (PCa), in particular prostate-specific antigen screening, are likely to benefit from complementary molecular analyses to enhance specificity. MicroRNAs (miRNA) are small endogenously expressed noncoding RNAs that negatively regulate the expression of protein-coding genes at the transcriptional or translational level. Accumulating evidence suggests that miRNAs play an important role in tumorigenesis, are differentially expressed in different cancer types, and can be found in all bodily fluids so-far tested, including urine.

Methods and materials: This study was undertaken to determine if miRNA could be isolated from the cell-free fraction of freely voided urine of PCa patients and if a miRNA signature could be found that would identify patients with cancer.

Results: In a first set of proof-of-concept experiments, we isolated RNA from the supernatant of cultured PCa cells, as well as cellular RNA, and compared the expression of cell-free miRNAs vs. cellular miRNAs. We identified miRNA-483-5p, miRNA-1275, and miRNA-1290 among the most abundant cell-free miRNAs. We then tested the expression of these miRNAs in patient urine samples. A total of 18 patients without detectable PCa by transperineal template-saturation biopsy and 71 patients with diagnosed biopsy-proven PCa were retrospectively analyzed. We could confirm that cell-free miRNAs found in cultures of PCa cells can in fact be isolated from freely voided patients' urine. Furthermore, we found that patients with PCa express miR-483-5p in the cell-free urine fraction at a higher level than control patients do.

Conclusions: The present study is among the first to show that miRNAs can be detected in the cell-free, non-exosome-enriched fraction of urine collected from patients with PCa. As the method used here does not require isolation of exosomes, it could potentially simplify the future use of miRNAs as urine-based biomarkers.