# Extracellular Vesicle-Based Digital Scoring Assay for Detecting Early-stage Hepatocellular Carcinoma

> **NIH NIH R01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2022 · $645,686

## Abstract

PROJECT SUMMARY
Extracellular vesicles (EVs) are a heterogeneous group of phospholipid bilayer-enclosed particles that are
released by all types of cells, and even more so by tumor cells. Since the biomolecular cargoes of tumor-
derived EVs mirror those of the parental tumor cells, characterizing tumor-derived EVs and profiling their cargo
are expected to be of substantial diagnostic value. Hepatocellular carcinoma (HCC), the fourth most common
cause of cancer-related deaths worldwide, most often develops in patients with underlying liver cirrhosis
secondary to alcoholic liver disease (ALD), nonalcoholic fatty liver disease (NAFLD), or hepatitis B/C
infections. Cirrhosis from any cause is a well-established risk factor for HCC; however, current surveillance
regimens with abdominal imaging and serum biomarkers (e.g., AFP) have poor sensitivity for diagnosing HCC
at an early stage, when it is potentially curable. Therefore, biomarkers that sensitively distinguish early-stage
HCC from at-risk liver cirrhosis are desperately needed. Exploring the diagnostic potential of HCC EVs and EV
cargo profiling for detecting early-stage HCC holds great promise to significantly augment the ability of current
diagnostic modalities.
We propose an HCC EV digital scoring assay for detecting early-stage HCC, which couples two very powerful
technologies: EV Click Chip for purification of HCC EVs and reverse-transcription droplet digital PCR (RT-
ddPCR) for EV cargo profiling. One of the major challenges emerging in the field of EV utilization for clinical
use is the lack of robust and reproducible methods for the isolation of a pure tumor-derived EV population.
Conventional methods for isolating EVs, such as ultracentrifugation, filtration, and precipitation, are incapable
of discriminating tumor-derived EVs from non-tumor-derived EVs. New research efforts have been devoted to
exploring immunoaffinity-based capture techniques for enriching tumor-derived EVs in different solid tumors.
However, there are challenges identified for the single antibody-mediated tumor-derived EV enriching
approaches, such as limited sensitivity/specificity and a need for multiple capture antibodies to overcome the
tumor heterogeneity. The EV Click Chips can address these concerns with a 2-step covalent chemistry-based
tumor-derived EV purification (click chemistry-mediated EV capture/disulfide cleavage-driven EV release)
instead of antibody-mediated EV capture. The purified HCC EVs can then be characterized by quantifying a
panel of 20 HCC-specific mRNA markers by incorporating RT-ddPCR technology. The proposed research will
conduct: i) an exploratory development and optimization of the two functional components (i.e., EV Click Chip
and RT-ddPCR) and analytically validate the proposed HCC EV digital scoring assay, and ii) an evaluation of
the diagnostic performance of the proposed HCC EV digital scoring assay for detecting early-stage HCC using
training and validation cohorts. The long-term...

## Key facts

- **NIH application ID:** 10330444
- **Project number:** 5R01CA255727-02
- **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES
- **Principal Investigator:** Yazhen Zhu
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $645,686
- **Award type:** 5
- **Project period:** 2021-01-18 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10330444

## Citation

> US National Institutes of Health, RePORTER application 10330444, Extracellular Vesicle-Based Digital Scoring Assay for Detecting Early-stage Hepatocellular Carcinoma (5R01CA255727-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10330444. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*