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Highly Sensitive Hybridization Chain Reaction-Based miRNA Detection Technology Using Diffusivity Analysis of

Momoka Nakai1, Yui Watanabe1, Maho Koda1

  • 1Department of Frontier Fiber and Technology and Science, Graduate School of Engineering, University of Fukui, Fukui 910-8507, Fukui, Japan.

Sensors (Basel, Switzerland)
|January 28, 2026
PubMed
Summary
This summary is machine-generated.

This study introduces a novel method for detecting microRNAs (miRNAs) by analyzing particle movement, enabling highly sensitive cancer biomarker detection in serum. This technique offers potential for earlier cancer diagnosis.

Keywords:
MicroRNAhybridization chain reactionimage analysisphoto-crosslinkable artificial nucleic acidprobe-modified particle

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Area of Science:

  • Biomarker Discovery
  • Molecular Diagnostics
  • Nanotechnology

Background:

  • MicroRNAs (miRNAs) are crucial biomarkers for early disease detection, especially in oncology.
  • Existing miRNA detection technologies require further advancements in sensitivity and selectivity.
  • Developing novel diagnostic tools is essential for timely disease intervention.

Purpose of the Study:

  • To establish a new miRNA detection technique using image analysis of Brownian motion.
  • To leverage changes in particle size upon target hybridization for miRNA identification and quantification.
  • To enhance detection sensitivity and specificity for cancer biomarkers in biological samples.

Main Methods:

  • Utilizing image analysis to track the Brownian motion (diffusivity) of fluorescent probe-modified miRNA particles.
  • Employing a photo-crosslinkable artificial nucleic acid (CNV-D) probe for covalent capture of target miRNAs.
  • Integrating Hybridization Chain Reaction (HCR) to amplify complex size and improve detection sensitivity.

Main Results:

  • Demonstrated highly sensitive and specific detection of the cancer biomarker miR-21 in serum.
  • Achieved an exceptionally low limit of detection (LOD) of 1 femtomolar (fM).
  • Confirmed the method's effectiveness in biological samples under stringent washing conditions.

Conclusions:

  • The developed miRNA detection technique shows significant potential for early cancer diagnosis.
  • Image analysis of Brownian motion offers a novel approach for sensitive and selective biomarker detection.
  • This technology could advance the field of liquid biopsy and personalized medicine.