Recent discoveries highlight the importance of cell-free miRNAs (cf-miRNAs) as promising diagnostic and prognostic biomarkers for cancer and many other diseases. Biofluids such as plasma can be accessed with minimal invasiveness, unlike tissue biopsies. This, together with the high stability of cf-miRNAs in biofluids, makes them attractive for use in molecular diagnostics compared to other, more labile biomolecules. However, current techniques are inadequate for sensitive, specific and reliable quantification of miRNAs in biofluids. Microarrays and RT-qPCR are currently the preferred tools for expression profiling of cf-miRNAs, although each has major drawbacks. Microarrays suffer from low sensitivity, low dynamic range, and the inability to distinguish closely related miRNA sequences, while RT-qPCR has limited multiplexing capability and amplification biases. While next-generation sequencing (NGS) is superior in many of these respects, its reliability for cf-miRNA profiling in biofluids is limited due to bias (under- and over-detection) towards particular miRNA sequences, overwhelming amounts of unrelated sequencing data, the need for gel-purification of amplicons, and its high cost. Here we propose a new approach for constructing cf-miRNA sequencing libraries that addresses these problems. Called miR-SEQ, it incorporates a new combination of hybridization and enzymatic steps to simplify the preparation of miRNA sequencing libraries while significantly decreasing the sequencing bias. It involves a targeted sequencing approach allowing the quantification of all miRNAs of interest including rare tissue- (e.g., cancer-) derived miRNA species and their isomiRs representing the highest interest as biomarkers that would otherwise be represented by none or low numbers of sequencing reads, making their quantification problematic and expensive. In Phase I we demonstrated the feasibility of our approach by accurately detecting more than 100 cf-miRNAs with a targeted sequencing approach. In Phase II we will thoroughly optimize miR-SEQ to maximize its sensitivity and to allow sequencing of a larger variety of cf-miRNAs for commercial viability. In addition, we will streamline the protocol to facilitate its adoption by end users including academic labs, contract research facilities, corporate R&D and molecular diagnostic labs.
Health relatedness narrative The goal of this grant application is to solve a detection problem in quantification of microRNAs (miRNAs) from biofluids using next-generation sequencing (NGS). Current methods of preparation of miRNA sequencing libraries are not accurate and detect many other non-target molecules, confounding the identification of biomarkers. An accurate and targeted method will help to fully realize the potential of miRNAs as biomarkers of cancer and other diseases. In addition, this method may help reduce the cost of sequencing clinical samples, making this powerful diagnostic tool more accessible to patients.