ArticleJournal of extracellular vesicles2025
Identification of a Biomarker Panel in Extracellular Vesicles Derived From Non-Small Cell Lung Cancer (NSCLC) Through Proteomic Analysis and Machine Learning.
Article in Journal of extracellular vesicles, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
10 citing papers in PubMed.
- Role and clinical significance of VISTA (PD-1H) and PVR (CD155) expression in non-small cell lung carcinoma: a systematic review.Translational lung cancer research · 2026Review
- Rab27: Molecular switch of tumor exosome secretion (Review).International journal of molecular medicine · 2026Review
- SERPINA3 as a Secreted-Protein Biomarker Associated with Poor Prognosis and T-Cell Dysfunction in Non-small Cell Lung Cancer.Tuberculosis and respiratory diseases · 2026Article
- Clinical significance of serum levels of 14-3-3β protein in patients with non-small cell lung cancer.Scientific reports · 2026Article
- Deep learning predicts stent implantation in borderline coronary lesions from angiography.NPJ digital medicine · 2026Article
- Glycosylation of Extracellular Vesicles: Analytical and Translational Insights into Biomarker Discovery and Regenerative Medicine.International journal of molecular sciences · 2026Review
- A new era of precision diagnosis and treatment for lung cancer: artificial intelligence-driven multimodal data integration and clinical applications.Cell death & disease · 2026Review
- Recent advances in machine learning-enhanced extracellular vesicle omics for oncology.Journal of nanobiotechnology · 2026Review
- Artificial Intelligence and the Expanding Universe of Cardio-Oncology: Beyond Detection Toward Prediction and Prevention of Therapy-Related Cardiotoxicity-A Comprehensive Review.Diagnostics (Basel, Switzerland) · 2026Review
- Computational frameworks for enhanced extracellular vesicle biomarker discovery.Experimental & molecular medicine · 2026Review
Corrections and comments
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Authors and funding
13 authors.
Funding
Abstract
Antigen fingerprint profiling of tumour-derived extracellular vesicles (TDEVs) in the body fluids is a promising strategy for identifying tumour biomarkers. In this study, proteomic and immunological assays reveal significantly higher CD155 levels in plasma extracellular vesicles (EVs) from patients with non-small cell lung cancer (NSCLC) than from healthy individuals. Utilizing CD155 as a bait protein on the EV membrane, CD155+ TDEVs are enriched from NSCLC patient plasma EVs. In the discovery cohort, 281 differentially expressed proteins are identified in TDEVs of the NSCLC group compared with the healthy control group. In the verification cohort, 49 candidate biomarkers are detected using targeted proteomic analysis. Of these, a biomarker panel of seven frequently and stably detected proteins-MVP, GYS1, SERPINA3, HECTD3, SERPING1, TPM4, and APOD-demonstrates good diagnostic performance, achieving an area under the curve (AUC) of 1.0 with 100% sensitivity and specificity in receiver operating characteristic (ROC) curve analysis, and 92.3% sensitivity and 88.9% specificity in confusion matrix analysis. Western blotting results confirm upregulation trends for MVP, GYS1, SERPINA3, HECTD3, SERPING1 and APOD, and TPM4 is downregulated in EVs of NSCLC patients compared with healthy individuals. These findings highlight the potential of this biomarker panel for the clinical diagnosis of NSCLC.
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