Abstract
<jats:p>Extracellular vesicle (EV)-derived microRNAs serve as important biomarkers for cancer diagnosis, yet their accurate detection remains limited by insufficient control of nucleic acid recognition and signal activation. Here, we identified a previously unrecognized feature of CRISPR/Cas12a, in which incorporation of ribonucleotides into single stranded DNA targets modulates Cas12a activation efficiency, revealing a hybrid DNA/RNA-dependent regulation of Cas12a activity. Leveraging this mechanism, we established a programmable detection strategy that enables sequence dependent tuning of Cas12a activation without the need for target amplification. By coupling DNAzyme mediated cleavage with Cas12a trans-cleavage, a cascade signal amplification system was established, enabling highly sensitive and selective detection of miRNAs. To facilitate clinical applications, an EV-based sample processing strategy was integrated to simplify isolation of EV associated miRNAs and allow direct miRNA detection without conventional RNA extraction. The resulting platform demonstrated robust discrimination of multiple miRNA targets in clinical cohorts and supported accurate classification of cancer subtypes according to expression signatures. By integrating machine learning analysis, the system accurate distinguished breast cancer (BC) patients from healthy donors (HD), as well as triple-negative breast cancer (TNBC) from BC. This study provides a mechanism-guided strategy for programmable CRISPR-based nucleic acid detection in complex biological samples.</jats:p>