Abstract
Objectives: MicroRNAs have been shown to be related to specific types of malignant cell growth. In case of urothelial bladder cancer (BCa), novel noninvasive diagnosis is particularly required and it is attractive to consider, as urine is an easily available source for molecular markers including RNA. In this context, we aimed to develop a clinically applicable and sensitive protocol for the preparation and molecular analysis of low molecular weight RNA from urine samples obtained from bladder cancer patients or healthy volunteers. Materials and methods: First, a method was developed for the preparation of low molecular weight RNA from a set of urine samples from different donor groups: (1) patients with low-grade BCa, (2) patients with high-grade BCa, (3) patients with urinary tract infections, (4) healthy donors; each n = 9. The RNA extracts were then used to monitor a number of 157 microRNA species by quantitative reverse transcriptase-polymerase chain reaction. Subsequently, those microRNAs that showed a higher abundance in urine samples from BCa patients were detected in an independent set of urine samples (n = 47). Results: The significance and diagnostic usefulness of this methodology is reflected by the finding that the RNA ratio of microRNA-126:microRNA-152 enabled the detection of BCa from urine at a specificity of 82% and a sensitivity of 72%, with an area under the curve of 0.768 (95% confidence interval, 0.605-0.931). Conclusions: This study describes a novel, robust, and useful technology platform that is suitable to analyze small RNAs, including novel RNA-based tumor markers, in urine samples. A detailed technical analysis of this methodology provides new insights into the characteristics of urine microRNA such as composition and the donor-dependent variability.
| Original language | English |
|---|---|
| Journal | Urologic Oncology: Seminars and Original Investigations |
| Volume | 28 |
| Issue number | 6 |
| Pages (from-to) | 655-661 |
| Number of pages | 7 |
| ISSN | 1078-1439 |
| DOIs | |
| Publication status | Published - 01.11.2010 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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