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Accurate detection of tumor-associated biomarkers from different molecular classes is important for early diagnosis and disease monitoring. However, the development of a single sensing strategy that can be adapted to nucleic acids, proteins, and small molecules remains challenging because of their distinct recognition mechanisms and physicochemical properties. In this work, we developed a modular biosensing strategy based on a hairpin adapter-initiated dual catalytic hairpin assembly (dCHA), for the sensitive and separate detection of representative biomarkers from three molecular classes using a unified signal transduction framework. In this design, target-specific recognition events were converted into a unified intermediate DNA trigger, thereby coupling different recognition modules with a common nucleic acid amplification module. As proof-of-concept targets, miRNA-183 (miR-183), prostate-specific antigen (PSA), and sarcosine were selected to represent nucleic acid, protein, and small-molecule biomarkers, respectively. The proposed system showed sensitive analytical performance, with limits of detection of 0.070 nM for miR-183, 0.48 ng/mL for PSA, and 0.26 nM for sarcosine, which are comparable to or within the range of gold-standard methods. In addition, recovery experiments in spiked human urine samples demonstrated the preliminary applicability of the assay in a complex biological matrix. This study provides a modular signal transduction strategy for detecting representative biomarkers of different molecular types and may offer a useful basis for further development of multiplexed and clinically validated biosensing systems.
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Min et al. (2026) studied this question.
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