Modular RCA-CRISPR/Cas12a Amplification on a Multi-Volume SlipChip for Ultrafast, Single-Copy Quantification of circRNA and miRNA in Ovarian Cancer

Abstract

The aberrant expression of RNAs in ovarian cancer (OC) progression highlights their potential as clinical biomarkers. However, rapid and accurate quantification of these RNAs in biosamples remains a significant challenging. In this study, we develop a Modular Isothermal Rolling circle amplification (RCA)-Activated Cas12a Loop-Enhanced amplification (MIRACLE) method for circRNA and miRNA quantification without the need of reverse transcription. In this design, isothermal amplification of modular DNA can be initiated by target-specific RCA primers or miRNAs, with the amplification products subsequently recognized by the Cas12a system to generate measurable signals. When integrated with a multi-volume sliding chip (SlipChip) platform, this MIRACLE method enables portable, rapid and ultra-sensitive quantification of these two types of RNA. Under optimized conditions, this platform exhibits detection limits of 0.125 copies/μL for circRNA and 0.326 copies/μL for miRNA, covering a 5-log dynamic range from 10-1 to 103 copies/μL within 35 min. The platform was validated using OC cell lines and clinical blood samples. It successfully profiled OC RNA biomarkers (hsa_circ_0049101 and hsa-miR-338-3p), and effectively distinguishing between early and advanced stages of OC. These results show a strong correlation with RT-qPCR (R²=0.953 for circRNA and R²=0.947 for miRNA). This work establishes a versatile CRISPR-microfluidic platform for cancer diagnosis. Its modular design allows for adaptation to detect other cancer-related RNA biomarkers, thereby addressing critical needs in precision oncology.

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Article information

Article type
Paper
Submitted
13 Jun 2025
Accepted
13 Aug 2025
First published
20 Aug 2025

Lab Chip, 2025, Accepted Manuscript

Modular RCA-CRISPR/Cas12a Amplification on a Multi-Volume SlipChip for Ultrafast, Single-Copy Quantification of circRNA and miRNA in Ovarian Cancer

L. Tian, Y. Gao, Y. Lu, F. Xu, Z. Feng, L. Zi, Z. Deng and J. Yang, Lab Chip, 2025, Accepted Manuscript , DOI: 10.1039/D5LC00585J

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