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Exonuclease III-Proofread high-fidelity primer exchange reaction enables ultrasensitive analysis of prostate cancer MicroRNA.

Oct 2026 · Biosensors & bioelectronics · Vol 315, pp. 119288 · 0 citations · 30 references
Medicine

Abstract

The primer exchange reaction (PER) has emerged as a versatile isothermal amplification technique for biosensing, yet its practical application is severely hampered by non-specific hybridization-induced background signals. Here, we report a high-fidelity PER (Hf-PER) strategy that overcomes this limitation through a rationally designed template architecture integrating exonuclease III (Exo III)-mediated target recycling, blocked primer binding, and self-priming amplification. In this design, Exo III strictly discriminates perfectly matched targets from mismatched sequences, while the absence of free primers and magnetic bead separation effectively suppress spurious amplification. Using miR-21, a prostate cancer-associated biomarker, as a model, the Hf-PER assay achieves a remarkable limit of detection of 0.15 fM with a wide dynamic range spanning five orders of magnitude and single-base discrimination capability. The method demonstrates excellent recovery (95.6%-101.2%) in spiked serum samples, high repeatability (CV < 4.5%), and strong concordance with qPCR (R2 > 0.99). Moreover, it successfully distinguishes prostate cancer cells from normal cells and accurately identifies miR-21 elevation in clinical serum samples from prostate cancer patients. By simply reprogramming the recognition domain, this platform can be readily adapted for other nucleic acid biomarkers; as a proof of concept, we further applied the Hf-PER strategy to detect miR-155, achieving a limit of detection of 0.21 fM and comparable specificity, demonstrating excellent versatility. The Hf-PER strategy offers a robust, sensitive, specific, and programmable tool for early cancer diagnosis, liquid biopsy, and point-of-care testing, addressing a critical need for reliable isothermal amplification in complex biological matrices.

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