Lung cancer is a leading cause of cancer mortality, yet early diagnosis remains difficult, highlighting the need for sensitive, noninvasive methods. Extracellular vesicles (EVs) and their surface proteins (e.g., PD-L1) are promising biomarkers; nevertheless, current EV detection requires time-consuming purification, sophisticated instrumentation, and long measurement protocols, resulting in high expenses and operational difficulties. This study developed an integrated colorimetric sensor, IMAN, based on a strategy of "Immunomagnetic Microbeads (IM) capture + Aptamer(Apt) recognition + Nanozyme (N) catalysis". IMAN employs magnetic beads modified with antibodies against CD9 and CD81 to directly capture EVs from serum, eliminating the need for time-consuming prior isolation; combined with a one-step colorimetric readout, the entire workflow can be completed with only ∼40 min of hands-on time, requiring no complex instrumentation. The PD-L1 protein on the EV surface is specifically recognized by a nanoparticle-bound nucleic acid aptamer. Signal generation is achieved through the catalytic oxidation of 3,3',5,5'-tetramethylbenzidine (TMB) by a platinum-gold bimetallic nanozyme (Pt@Au). The facile IMAN colorimetric method demonstrated a relatively broad dynamic range (107-1010 particles/mL), high specificity (unaffected by 100 pg/mL soluble PD-L1 in serum), and reproducibility (relative standard deviation, RSD = 9.1%). Analysis of clinical serum samples revealed significantly elevated EV-PD-L1 levels in patients with lung cancer compared with healthy donors and patients with benign nodule (p < 0.01). Receiver operating characteristic (ROC) analysis yielded areas under the curve (AUC) of 0.849 for distinguishing patients with lung cancer from healthy donors and 0.860 for distinguishing patients with lung cancer from patients with benign nodules, which are superior to those of the conventional serum biomarkers CEA and Cyfra21-1. By addressing the cost, complexity, and slow response of current methods, IMAN offers a simple, cost-effective platform for direct EV surface protein detection without complex instrumentation, providing a novel tool for the noninvasive lung cancer diagnosis.
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Han et al. (2026) studied this question.
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