Multiplexed Profiling of Individual Extracellular Vesicles Reveals Lung Cancer‐Associated Protein Signatures
Year: 2026
Type: article
Abstract: Lung cancer is frequently diagnosed after curative treatment windows have narrowed, creating a need for minimally invasive biomarkers that report tumor development at earlier stages. Extracellular vesicles (EVs) are promising analytical targets because they carry molecular cargo from their originating cells, but tumor-associated EV signals can be rare in blood and obscured in bulk measurements. Here, we present Cygnus (Cyclic-imaging gateway to nanovesicles underlying signature), an end-to-end workflow that integrates cyclic immunofluorescence imaging with multiscale analysis of individual EVs. Cygnus preserves vesicle-level measurements, quantifies marker co-expression, resolves EV subpopulations, and summarizes single-vesicle phenotypes into sample-level profiles. In a genetically engineered mouse model of lung adenocarcinoma, Cygnus revealed dynamic changes in EV protein composition and identified an EpCAM- and/or CTSH-positive EV subpopulation before tumors were detectable by radiography. In a pilot clinical cohort (n = 35), plasma EV profiling showed lung cancer-associated marker patterns compared with non-cancer controls and nominated a CTSH/PDL1/MET marker combination for future validation. These findings support multiplexed individual-EV profiling as a strategy for defining candidate lung cancer-associated EV signatures and position Cygnus as an integrated workflow for translating vesicle-level heterogeneity into sample-level EV profiles.
Source: Advanced Science
DOI: 10.1002/advs.77301
Language: English
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $6,730
Funders: U.S. Department of Defense, Massachusetts General Hospital, National Research Foundation, Chonnam National University, Korea Basic Science Institute, National Research Foundation of Korea, Chonnam National University Hwasun Hospital, National Institutes of Health, National Heart, Lung, and Blood Institute, National Cancer Institute, National Institute of General Medical Sciences
Awards: G1644562230, Dissection of in situ myeloid signaling using image-guided synthetic control, EARLY DETECTION OF LUNG CANCER THROUGH MOLECULAR ANALYSES OF SINGLE EXTRACELLULAR VESICLES, G3177873128, G321704082, G4241453214, Imaging and Liquid Biopsy for Glioma Diagnosis and Treatment Monitoring, G500901450, G7258413213, G8896277309, G9000029313, G9000046953, G9000100727, G9000130347, Molecular profiling of global tissue dynamics at sub cellular resolution, Imaging radiation-enhanced drug delivery for safer and more effective chemoradiotherapy, Empowering cancer detection and monitoring with CampEx - CRISPR-accelerated molecular profiling of Extracellular vesicles, High-throughput Phenotyping of iPSC-derived Airway Epithelium by Multiscale Machine Learning Microscopy, Streamlining sample preparation with high throughput SpinEx (Separation processing integration for Extracellular vesicles), Expanding the therapeutic window of chemoradiation through radiation-responsive nanoparticle drug depots, Expanding early cancer detection with high throughput OCEANA - Ovarian Cancer Exosome Analysis with Nanoplasmonic Array, Composing CODAs to cervical cancer screening through an integrated CRISPR and fluorescent nucleic acid approach
OpenAlex ID: W7204167050