Quantification of microRNA editing using two-tailed RT-qPCR for improved biomarker discovery

Abstract

Even though microRNAs have been viewed as promising biomarkers for years, their clinical implementation is still lagging far behind. This is in part due to the lack of RT-qPCR technologies that can differentiate between microRNA isoforms. For example, A-to-I editing of microRNAs through adenosine deaminase acting on RNA (ADAR) enzymes can affect their expression levels and functional roles, but editing isoform-specific assays are not commercially available. Here, we describe RT-qPCR assays that are specific for editing isoforms, using microRNA-379 (miR-379) as a model. The assays are based on two-tailed RT-qPCR, and we show them to be compatible both with SYBR Green and hydrolysis-based chemistries, as well as with both qPCR and digital PCR. The assays could readily detect different miR-379 editing isoforms in various human tissues as well as changes of editing levels in ADAR-overexpressing cell lines. We found that the miR-379 editing frequency was higher in prostate cancer samples compared to benign prostatic hyperplasia samples. Furthermore, decreased expression of unedited miR-379, but not edited miR-379, was associated with treatment resistance, metastasis, and shorter overall survival. Taken together, this study presents the first RT-qPCR assays that were demonstrated to distinguish A-to-I-edited microRNAs, and shows that they can be useful in the identification of biomarkers that previously have been masked by other isoforms.