Matrix-Boosted Electrochemiluminescence Biosensor for Ultrasensitive Exosome Detection and Automated Phenotype Discrimination.

Accurate quantification and phenotypic discrimination of exosomes in complex biological fluids remain technically challenging sensing issues, yet they are essential for early cancer diagnosis. To address this challenge, an ultrasensitive electrochemiluminescence (ECL) biosensor is engineered by integrating a "matrix-boosted" Cp-Pt-Ti3-xC2Ty MXene emitter with a proximity-dependent "signal-off-on" aptamer strategy. Upon target recognition, the thermodynamically favored desorption of methylene blue-labeled aptamers triggers a dramatic ECL signal recovery, while the resulting multifeatured sensing data are processed using a support vector machine (SVM) algorithm. The sensing platform achieves a high quenching efficiency of 99.8% and a low limit of detection of 35 particles/μL for MCF-7 exosomes without requiring enzymatic amplification. Furthermore, integrating the SVM model with 3D principal component analysis enables the highly accurate and automated discrimination of varying exosome phenotypes derived from distinct cell lines in clinical serum samples, establishing a smart, AI-empowered paradigm for liquid biopsy.