Related Experiment Video
Updated: Apr 29, 2026

Author Spotlight: Engineering Molecular Tools for Disease Detection and Imaging
Published on: December 8, 2023
Self-Assembled DNA Nanoladder-Based Electrochemical Biosensor for Rapid and Sensitive Detection of Bladder
Jiaoli Wang1, Jingping Liu1, Yajun Wang1
1School of Electrical Engineering, University of South China, Hengyang 421001, P. R. China.
Abstract:
Early diagnosis is critical for improving the survival rate of patients with bladder cancer (BCa), and urinary biomarker detection offers a promising noninvasive approach for early BCa screening. However, the typically low abundance of these biomarkers in urine samples remains a major challenge for conventional detection methods. To address this, we developed a self-assembled DNA nanoladder-based electrochemical biosensor for the rapid and sensitive detection of miR-126 in urine. Upon introduction of target miR-126, it hybridizes with the C/W duplex, leading to the production of single C strands on the electrode surface. This single-stranded C strand then triggers the hybridization chain reaction (HCR) of the DNA nanoladder (DNL), resulting in the formation of elongated ladder-like nicked double-stranded DNA polymers on the electrode surface. These dsDNA structures subsequently capture a large number of RuHex molecules through electrostatic interactions, generating a significantly enhanced differential pulse voltammetry (DPV) signal. Benefiting from the high signal amplification efficiency and fast kinetics of the DNA nanoladder (DNL), the developed electrochemical biosensor enables the sensitive detection of miR-126 with a detection limit of 59.0 aM, a linear detection range of 5 fM to 1 nM, and a total detection time of less than 30 min. In a cohort of 15 cancer patients and 10 negative control samples, the constructed DNL-based biosensors could detect bladder cancer with 93.3% sensitivity, 100% specificity, and an accuracy of 96.0%. The designed DNA nanoladder electrochemical biosensor provides a new strategy to realize accurate detection of complex clinical samples to achieve early cancer diagnostics.

