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DNA Self-Assembly Generated by Aptamer-Triggered Rolling Circle Amplification Cascades for Profiling Colorectal
Yawei Feng1,2, Yunshan Yang1, Pei Guo1
1Zhejiang Cancer Hospital, Key Laboratory of Zhejiang Province for Aptamers and Theranostics, Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, Zhejiang 310022, P. R. China.
ACS Nano
|January 8, 2025
Summary
This study introduces a new method for detecting colorectal cancer (CRC) using small extracellular vesicles (sEVs) and multiaptamer-triggered rolling circle amplification (RCA). This approach offers high accuracy for early cancer diagnosis and monitoring.
Area of Science:
- Biochemistry
- Molecular Biology
- Nanotechnology
Background:
- Small extracellular vesicles (sEVs) are crucial biomarkers for cancer diagnostics, prognostics, and monitoring.
- Current limitations in profiling multiple sEV protein parameters hinder clinical applications.
- Blood-derived sEVs show promise, but advanced profiling techniques are needed.
Purpose of the Study:
- To develop a novel method for profiling colorectal cancer (CRC)-derived sEVs.
- To enable specific multi-parameter analysis of sEVs for improved clinical diagnostics.
- To validate a new diagnostic approach for early CRC detection.
Main Methods:
- Utilized multiaptamer-triggered rolling circle amplification (RCA) cascades for sEV profiling.
- Employed structure-switching aptamers to release complementary strands upon target sEV detection.
- Generated micrometer-sized DNA assemblies for analysis via conventional flow cytometry.
Main Results:
- Successfully verified the diagnostic method on cell-derived sEVs.
- Achieved promising diagnostic efficacy on a clinical cohort of CRC-derived sEVs.
- Demonstrated high diagnostic performance: 92% sensitivity, 86.7% specificity, and 90% overall accuracy.
Conclusions:
- The developed multiaptamer-RCA method facilitates facile clinical diagnostics of CRC.
- sEVs show substantial potential as reliable biomarkers for CRC diagnosis.
- This advancement significantly contributes to developing clinical tools for early cancer detection.
