Unlocking the future of hepatocellular carcinoma early diagnosis: The promise of extracellular vesicle biomarkers
image: EVs have evolved from experimental biomarkers into a clinically actionable platform for HCC early detection, risk stratification, and targeted therapy. With the adoption of standardized isolation and characterization protocols—as defined by MISEV2023—and rigorous large-scale multicenter validation, EV-based liquid biopsy is poised to become an integral component of clinical guidelines for HCC management, transforming how this disease is detected and treated.
Credit: Yongcan Guo
Hepatocellular carcinoma (HCC) has a low five‑year survival rate, largely due to difficult early detection. Extracellular vesicles (EVs) carry proteins, nucleic acids, and lipids, playing key roles in tumour progression and emerging as promising liquid biopsy biomarkers. This review summarises EV‑derived biomarkers (miRNAs, lncRNAs, circRNAs, mRNAs, proteins, and lipids) for HCC diagnosis, discusses multi‑omics integration, and addresses technical challenges in EV isolation, characterisation, and the need for standardisation.
Introduction
HCC accounts for 75–85% of liver cancers; major risks include HBV/HCV, NAFLD, and alcohol. Early‑stage HCC is often asymptomatic, and current surveillance (ultrasound + AFP) has low sensitivity (<50% for early tumours). CT/MRI are less accurate for small lesions, and biopsy is invasive. EVs, stable in circulation and carrying tumour‑specific cargoes, offer a promising minimally invasive alternative.
Role of EVs in HCC
EVs mediate intercellular communication: they can promote or suppress HCC via immune modulation (e.g., miR‑3129 promotes; Vps4A suppresses). They facilitate angiogenesis, metastasis, and immune evasion (e.g., LOXL4 induces PD‑L1). EVs also serve as drug delivery vehicles, and their tumour‑specific cargoes make them valuable for diagnosis.
EV‑Derived miRNAs
EV‑miRNAs are more stable than free serum miRNAs. Key candidates: miR‑21 (AUC 0.912), miR‑10b‑5p (AUC 0.968), miR‑122 (AUC 0.9), and miR‑148a (AUC 0.891) outperformed AFP. Panels like miR‑21+miR‑96+miR‑122 reached AUC 0.996. Performance varies by aetiology and population; most studies are Asian HBV‑related, requiring diverse validation.
EV‑Derived lncRNAs
EV‑lncRNAs are stable and dysregulated in HCC. LINC00853 shows the best performance (AUC 0.934, 93.75% sensitivity, 89.77% specificity for stage I HCC), even in AFP‑negative cases. Other candidates include Inc85 (AUC 0.873), CRNDE (AUC 0.839), and RP11‑513115.6 (AUC 0.964). Panels like THEMIS2‑211+PRKACA‑202+AFP achieved AUC 0.947.
EV‑Derived circRNAs
circRNAs are exonuclease‑resistant and act as miRNA sponges. Promising candidates: circ‑0072088 (AUC 0.899), circ‑0006602 (AUC 0.907; 0.956 for early HCC), and circ‑0070396 (AUC 0.857; combined with AFP, AUC 0.938). Multi‑circRNA signatures also improve accuracy.
EV‑Derived mRNAs
EV‑mRNAs can be translated in recipient cells. LDHC mRNA in EVs achieved AUC 0.945; hnRNPH1 mRNA (AUC 0.865) combined with AFP gave AUC 0.891. A MYL6B+THOC2 model reached AUC 0.907, and a 10‑mRNA signature achieved AUC 0.93.
EV‑Derived Proteins and Lipids
EV proteins like CCT8 (AUC 0.698) and CFL1 (AUC 0.677) combined with AFP raised AUC to 0.838. Lipidomics is emerging; over 2,800 lipids were differentially expressed in HCC EVs, but clinical data remain limited.
Critical Analysis of Clinical Trials
Strengths: well‑defined case‑control designs, inclusion of high‑risk controls, multi‑marker panels improving specificity, and confirmed pre‑analytical stability.
Weaknesses: mostly single‑centre, retrospective, small samples; almost all Asian HBV‑related; lack of standardised isolation protocols and externally validated cut‑offs; few follow‑up studies.
EV Isolation and Clinical Translation
Methods include ultracentrifugation (gold standard but time‑consuming), size‑based methods (preserve function but co‑isolate impurities), polymer precipitation (convenient but low purity), and advanced microfluidics/immunoaffinity (specific but costly). Major hurdles: high cost, methodological heterogeneity (sample source, isolation, detection), and no universally accepted diagnostic thresholds. Adherence to MISEV2023 and multicenter validation are essential.
Endogenous Controls for EV Data
Common U6 and miR‑16 are often unstable. Recommended alternatives include miR‑106a, miR‑1280, miR‑4644 (for HBV/LC‑HCC), miR‑24‑3p, and miR‑151a‑3p. GAPDH is frequently used for lncRNAs/mRNAs but should be validated per experiment. Traditional genes like ACTB may be nearly absent in liver cancer EVs.
Future Perspectives
EV‑based liquid biopsy should first target high‑risk populations (HBV/HCV, cirrhosis, NAFLD fibrosis, AFP‑negative cases). Most promising candidates—EV‑miRNA panels, LINC00853, and combined protein signatures—need large‑scale prospective validation. Standardisation per MISEV2023 is critical. Engineered EVs as drug carriers also show preclinical promise. Integration with imaging and clinical scores will enable precision management.
Conclusions
EVs have evolved into a clinically actionable platform for HCC early detection and risk stratification. With standardised protocols and rigorous validation, EV‑based liquid biopsy is poised to become integral to HCC guidelines, transforming disease detection and management.
Full text
https://www.xiahepublishing.com/2310-8819/JCTH-2025-00589
The study was recently published in the Journal of Clinical and Translational Hepatology.
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