The ultimate vision of this proposal is to develop a technology platform for the rapid, robust single molecule analysis of microRNA (miRNA) biomarkers in cancer research that quantifies a panel of up to two hundred cancer-associated miRNAs in a patient sample in under 30 minutes. miRNAs are non-coding RNAs with pervasive gene regulatory function in higher eukaryotes. Over 1,000 miRNA genes compose ~2% of the human genome, more than all protein-coding genes combined. Although typically only 22 nucleotides (nt) in length, miRNAs regulate essentially all cellular pathways relevant to human health and disease, including cancer. Once released from cells through apoptosis or possibly as external signaling molecules, circulating, cell-free miRNAs are more stable in blood than most other nucleic acids, rendering them of high interest as clinical cancer biomarkers. The validation of blood-borne cell-free miRNA biomarkers as clinically useful has been hindered, however, by difficulties due to inherent, both pre-analytic and analytic, day-to-day and lab-to-lab variations associated with PCR assays as the state-of-the-art for miRNA biomarker detection. The resulting both false- positive and false-negative miRNA associations present a major barrier to developing miRNAs as validated clinical biomarkers. We recently invented a novel, innovative technology paradigm for the direct single-molecule identification and counting of miRNAs in crude biofluids that overcomes any need for either miRNA amplification or labeling, promising to overcome many of the current challenges. Our approach, termed Single-Molecule Recognition through Equilibrium Poisson Sampling (SiMREPS), exploits the binding of a short (9- to 10-nt), fluorescently labeled DNA reader probe to an unlabeled miRNA immobilized on a glass surface through a specific, short LNA capture probe. Using total internal reflection fluorescence (TIRF) microscopy, both specific binding to the immobilized target and non-specific surface binding are detected. However, the equilibrium binding of the reader probe to the target is distinctive in its kinetic signature, or fingerprint, a feature we have used to achieve ultrahigh-confidence discrimination against false positives. Through varying the probe length we have fine-tuned specificity, including the >500-fold discrimination between single nucleotide polymorphisms. As initial proof-of-principle, we have demonstrated the direct in situ quantification of spiked-in prostate cancer biomarker hsa-miR-141 in blood serum, after only minimal pre-treatment of a sample. We now propose to further develop SiMREPS as a platform technology, by pursuing the following two Specific Aims: (i) We will develop an optimized pre-analytic sample prep that efficiently liberates endogenous miRNAs from their serum matrix for direct SiMREPS detection, and benchmark the results against current PCR assays requiring miRNA extraction. (ii) We will develop SiMREPS toward miniaturization and multiplexing on a lens-free microscope. This project will lay the foundation for SiMREPS to have a transformative impact by breaking down the technology barriers currently limiting the successful development and validation of blood-based miRNA biomarkers for the clinic.
microRNAs (miRNAs) are promising biomarkers found ubiquitously in blood samples of cancer patients, yet their clinical applications have been hampered by inconsistencies among studies and detection methodologies. We will optimize our newly developed Single-Molecule Recognition through Equilibrium Poisson Sampling (SiMREPS) technology platform for endogenous miRNA detection in human blood serum and develop a microfluidic chip with associated lens-free readout device that eventually can quantify a panel of cancer- associated miRNAs in a patient sample in under 30 minutes, benchmarking the results against current state-of- the-art technologies. This project will lay the foundation for SiMREPS to become the rapid, robust, quantitative technology platform of choice that transforms blood-based miRNA research and helps bring miRNA biomarkers to the clinic.
|Johnson-Buck, Alexander; Li, Jieming; Tewari, Muneesh et al. (2018) A guide to nucleic acid detection by single-molecule kinetic fingerprinting. Methods :|
|Hayward, Stephen L; Lund, Paul E; Kang, Qing et al. (2018) Ultraspecific and Amplification-Free Quantification of Mutant DNA by Single-Molecule Kinetic Fingerprinting. J Am Chem Soc 140:11755-11762|