Engineering Extracellular Vesicle Isolation and Sensing Technologies for Hepatocellular Carcinoma Diagnostics

Extracellular vesicles (EVs) are promising liquid-biopsy analytes for hepatocellular carcinoma (HCC) because they carry complementary biomarker information in both surface and luminal compartments and are accessible from multiple clinically relevant biofluids. In HCC, however, the diagnostic performance of EV assays is constrained by low tumor-derived EV fraction, chronic liver disease confounding, matrix-dependent background, enrichment bias, and limited cross-platform comparability. In this Review, we examine EV-based HCC diagnostics through the lens of sensing technology and analytical workflow design. We organize the field around biofluid-specific design constraints, isolation strategies, recognition interfaces, transduction architectures, and benchmarking metrics that determine assay performance in complex liver-disease matrices. We compare established and emerging enrichment methods together with major sensing modalities for EV protein and nucleic-acid analysis, including fluorescence, electrochemical, electrochemiluminescent, field-effect transistor, plasmonic, mass spectrometric, and single-EV platforms. We further discuss how enrichment modules reshape the biological EV fraction being measured and why assay claims should be judged using matrix-aware limits of detection, recovery, throughput, and cost per test. By linking HCC-relevant EV biology to platform selection and validation strategy, this review summarizes design considerations for HCC-EV sensing workflows across early screening, differential diagnosis from benign liver disease, prognosis assessment, recurrence surveillance, and treatment monitoring.