A Minimalist Cascade Logic Amplifier Engineered on a Multilayered Metal–Organic Framework for Intracellular miRNAs Profiling and Breast Cancer Staging

Current strategies for microRNAs (miRNAs) detection in live-cell imaging are hindered by several methodological limitations, including poor delivery efficiency, inadequate signal amplification, insufficient target specificity, and overly complex reaction architectures. To address these issues, we present a streamlined cascade logic system mediated by multilayered metal-organic framework nanomaterials (PCZF-8), which integrates catalytic hairpin assembly (CHA) and DNAzyme sequences for the fluorescent detection of endogenous intracellular miRNAs (miR-21 and miR-155) and enables precise cancer cell identification. Central to this approach is a bifunctional double-loop hairpin probe (H1) that incorporates both miRNA recognition sequences and a DNAzyme motif, endowing it with dual capabilities for target binding and catalytic signal generation. Upon recognition of miR-21 and miR-155, the CHA-DNAzyme cascade amplification reaction is effectively triggered, enabling rapid cleavage of a fluorogenic substrate probe (H3) and a robust fluorescent output. Remarkably, the entire dual miRNAs recognition, CHA-DNAzyme cascade amplification, and logic-gated response are achieved with only three hairpin components (H1, H2, and H3), underscoring the system's molecular economy and design elegance. The assay achieves femtomolar (fM) detection limits for both miR-21 and miR-155 and operates as an AND-gated logic circuit, selectively identifying breast cancer cells based on their characteristic coexpression profile of these miRNAs. Furthermore, the intrinsic pH-responsive fluorescence property of PCZF-8 enhances cellular discrimination by distinguishing the acidic tumor microenvironment of cancer cells from that of normal cells. By synergistically combining nanomaterial engineering with molecular logic and cascade amplification, this platform establishes a novel paradigm for intelligent, highly specific cancer diagnostics in live-cell settings.