ArticleJournal of experimental & clinical cancer research : CR2025
Extracellular vesicle digital scoring assay for assessment of treatment responses in hepatocellular carcinoma patients.
Article in Journal of experimental & clinical cancer research : CR, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Bioorthogonal Click Chemistry-Enabled Enrichment of Extracellular Vesicles for Integrated Molecular and Functional Liquid Biopsy§.Accounts of chemical research · 2026Article
- Developing blood extracellular vesicle protein biomarkers for hepatocellular carcinoma: mechanisms, methods, and translation.Journal of nanobiotechnology · 2026Review
- Clinically interpretable extracellular vesicle gene model for Non-Invasive liver cancer diagnosis.Scientific reports · 2026Article
- Computational frameworks for enhanced extracellular vesicle biomarker discovery.Experimental & molecular medicine · 2026Review
- Large extracellular vesicles and blebbisomes in cancer: emerging and translational opportunities highlights.Cell communication and signaling : CCS · 2026Review
- Lipid nanoparticles and extracellular vesicles: emerging cell free therapeutic platforms for hepatobiliary cancers.Frontiers in cell and developmental biology · 2026Review
- Tumor Extracellular Vesicle Digital Scoring Assays for Cancer Detection and Monitoring.Precision chemistry · 2025Review
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Authors and funding
44 authors.
Funding
Abstract
backgroundThere are no validated biomarkers for assessing hepatocellular carcinoma (HCC) treatment response (TR). Extracellular vesicles (EVs) are promising circulating biomarkers that may detect minimal residual disease in patients with treated HCC.
methodsWe developed the HCC EV TR Score using HCC EV Digital Scoring Assay involving click chemistry-mediated enrichment of HCC EVs, followed by absolute quantification of HCC EV-specific genes by RT-digital PCR. Six HCC EV-specific genes were selected and validated through i) a comprehensive data analysis pipeline with an unprecedentedly large collection of liver transcriptome datasets (n = 9,160), ii) RNAscope validation on HCC tissues (n = 6), and iii) a pilot study on early- or intermediate-stage HCC and liver cirrhosis patients (n = 70). The performance of HCC EV TR Score was assessed in a phase-2 retrospective case-control study (n = 100).
resultsHCC EV TR Scores, calculated from pre- and post-treatment plasma samples in the phase-2 case-control study, accurately differentiated post-treatment viable from nonviable HCC in the training (area under the ROC curve [AUROC] of 0.90, n = 49) and validation set (AUROC of 0.88, n = 51). At an optimal cutoff of 0.76 identified in the training set, HCC EV TR Score had high accuracy in detecting viable tumors (sensitivity: 76.5%, specificity: 88.2%) and found residual disease not initially observed on MRI in six patients with a median lead time of 63 days.
conclusionsThis EV-based digital scoring approach shows great promise to augment cross-sectional imaging for the assessment of HCC treatment response.
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