# Peptide multimer for early detection of hepatocellular carcinoma

> **NIH NIH R01** · UNIVERSITY OF MICHIGAN AT ANN ARBOR · 2024 · $421,744

## Abstract

The incidence of hepatocellular carcinoma (HCC) is rising rapidly worldwide. In the U.S., this cancer is
growing at a rate faster than that of any other cancer. New biomarkers specific for HCC tissue targets are
critically needed to develop improved diagnostic and therapeutic strategies and better manage the increasing
tumor burden. While alpha fetoprotein (AFP) is a common serological marker for HCC, no tissue targets are
currently being used as imaging biomarkers to detect this tumor, which is growing rapidly in incidence.
Individual HCC cells will be evaluated using scRNA-seq with trajectory analysis to identify promising early-
stage targets that are highly specific for this tumor. This methodology will examine the molecular pathogenesis
that drives hepatocyte transformation to identify promising imaging biomarkers that can accurately distinguish
malignant from benign lesions in the context of the tumor microenvironment. Antibodies are large in
dimensions, and have reduced ability to extravasate from vasculature, diffuse and penetrate into tumor, and
clear from interstitial space, resulting in higher background. Peptides are much smaller in size and lower in
molecular weight. The diminutive dimensions can overcome irregular microvasculature, heterogeneous uptake,
and transport barriers found in HCC tumors. These protein fragments can extravasate through leaky tumor
microvasculature for deeper penetration and better access to tumor targets. Peptides have less potential for
immunogenicity, allowing for repeat use. Conventional ligands are being developed for specific binding to single
targets only. This strategy is limited in effectiveness for heterogeneous tumor cell populations, such as HCC.
Monomer peptides will be arranged in a multimer configuration to produce multivalent ligand-target
interactions. Increased sensitivity occurs from simultaneous detection of multiple targets. Greater specificity
arises from the multimer binding to a larger combined target epitope. Cancer targets may be detected at lower
levels of expression, and at an earlier time point. Peptides specific for GPC3, CD44, and EpCAM will be used
as an initial demonstration. Peptides specific for new early-stage HCC targets identified from scRNAseq will
be identified and inserted. The multimer will be labeled with Gd-Dota for in vivo use to detect HCC tumors
using MR imaging, and will be labeled with IRDye800 for optical imaging with laparoscopy. Cell-derived and
subcutaneous tumor models do not accurately reflect the molecular and genetic profile and vascular delivery of
human disease. A pre-clinical model of HCC using patient-derived tumor specimens will be implanted in an
orthotopic location to validate specific multimer uptake. These tumors provide clinically relevant molecular and
genetic profiles. Tumor implantation in the orthotopic location provides vascular delivery with intact stroma and
vasculature that is representative of the clinical scenario. Success completion...

## Key facts

- **NIH application ID:** 10979395
- **Project number:** 1R01CA285303-01A1
- **Recipient organization:** UNIVERSITY OF MICHIGAN AT ANN ARBOR
- **Principal Investigator:** Thomas D Wang
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $421,744
- **Award type:** 1
- **Project period:** 2024-07-03 → 2029-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10979395

## Citation

> US National Institutes of Health, RePORTER application 10979395, Peptide multimer for early detection of hepatocellular carcinoma (1R01CA285303-01A1). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10979395. Licensed CC0.

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