Simultaneous Recognition of Over- and Under-Expressed MicroRNAs Using Nanopore Decoding.

Area of Science:

• Biotechnology
• Molecular Diagnostics
• Nanotechnology

Background:

• MicroRNAs (miRNAs) are vital biomarkers for cancer diagnosis due to their cancer-type-specific expression.
• Nanopore technology offers a label-free approach for miRNA detection, but recognizing simultaneous expression changes remains challenging.
• Current methods struggle with complex miRNA expression patterns essential for accurate cancer subtyping.

Purpose of the Study:

• To develop a strategy for simultaneous recognition of over- and under-expressed miRNAs using nanopore decoding.
• To design specific DNA probes for detecting multiple miRNAs indicative of oral squamous cell carcinoma.
• To establish a robust method for miRNA pattern recognition in clinical samples for diagnostic purposes.

Main Methods:

• Signal classification-based nanopore decoding was employed.
• Diagnostic DNA probes were designed for simultaneous detection of two specific miRNAs.
• Nanopore measurements analyzed current signals based on hybridized miRNA species (duration vs. current blocking ratio).

Main Results:

• Designed probes generated characteristic nanopore signals correlating with hybridized miRNA abundance.
• Signal classification successfully identified patterns of over- and under-expressed miRNAs.
• The method demonstrated effectiveness in recognizing miRNA expression patterns in clinical samples of oral squamous cell carcinoma.

Conclusions:

• The developed nanopore decoding strategy enables simultaneous recognition of over/under-expressed miRNAs.
• This approach facilitates simple, label-free miRNA detection for liquid biopsy applications.
• The method holds promise for advancing early cancer diagnosis and personalized medicine.