Recent discoveries highlight the importance of extracellular miRNAs (ex-miRNAs) as promising noninvasive biomarkers for many diseases. It has also been reported that several ex-miRNAs species might be important for cell-cell signaling. While there is still controversy about their biological importance, it is clear that ex-miRNAs hold promise as biomarkers for different pathologies. It has been reported that distinct expression patterns of miRNAs are associated with cancer and other diseases, and ex-miRNAs may reflect these signatures. Biofluids such as plasma can be accessed with minimal invasiveness, unlike tissue biopsies. This, together with the high stability of ex-miRNAs in biofluids, makes them attractive for use in molecular diagnostics compared to other, more labile biomolecules. Despite these advantages, current techniques are inadequate for specific and reliable quantification of miRNAs in biofluids. Microarrays and RT-qPCR are currently the preferred tools for expression profiling of ex-miRNAs, although each has major drawbacks. Microarrays suffer from low sensitivity, low dynamic range, and the inability to distinguish closel 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 ex-miRNA profiling in biofluids is limited due to bias (underdetection) towards particular miRNAs, 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 ex-miRNA sequencing libraries that addresses these problems. Called miR-SEQ, it incorporates new enzymatic steps to simplify and increase the sensitivity of ligation reactions, and it involves a targeted sequencing approach that allows for the quantification of rare ex-miRNAs that would otherwise be represented by low numbers of reads, making their quantification problematic and/or expensive. Although our method is applicable to any miRNA, to establish proof-of-concept this Phase I proposal focuses on the 119 ex- miRNAs reported to be most abundant in plasma. Once we achieve reliable quantification for known plasma miRNAs, we expect to use the method to discover and validate ex-miRNAs biomarkers in human plasma for Parkinson's Disease and develop miR-SEQ diagnostic assays using those validated biomarkers.
The goal of this grant application is to solve a detection problem in profiling microRNAs (miRNAs) from biofluids using next-generation sequencing (NGS) methods. Current methods lead to serious undercounting of many miRNAs due to bias in the enzymatic reactions used to prepare the samples for NGS, and because of their intrinsically low concentrations in biofluids. Eliminating this bias 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.
