Evidence map›Paper›PMID 42708014›Full record

ArticleTheranostics2026

A multimodal pipeline for the identification and diagnostic immunoPET validation of hepatocellular carcinoma targets for radiotheranostic development.

Philip Homan, Joon-Yong Chung, Woonghee Lee, Divya Nambiar, Julia Sheehan-Klenk, Hima Makala, Stanley Fayn, Orit Jacobson, Arthur Paden King, Kyungeun Kim and 7 more

Abstract read
In one paragraph

Article in Theranostics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

17 authors.

Philip HomanAdvanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
Joon-Yong ChungMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Woonghee LeeMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Divya NambiarMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Julia Sheehan-KlenkMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Hima MakalaMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Stanley FaynMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Orit JacobsonMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Arthur Paden KingMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Kyungeun KimDepartment of Pathology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Republic of Korea.
Jeong Won KimDepartment of Pathology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, 07441, Republic of Korea.
Sung Ryol LeeDepartment of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Republic of Korea.
Maggie CamCenter for Collaborative Bioinformatics, National Institutes of Health, Bethesda, MD 20892, USA.
Stephen M HewittLaboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Xin Wei WangLaboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Mitchell HoLaboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
Freddy E EscorciaMolecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.

Funding

WORK ORDER 126643 B539 EXPAND IC SUITE75N91019D00024 · NIAID · LEIDOS BIOMEDICAL RESEARCH, INC. · 2019 to 2025
$3932.6M
Engineering HCC-selective PET agentZIABC011800 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI ESCORCIA, FREDDY · 2018 to 2025
$10.6M
Antibody Engineering ProgramZICBC011891 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI HO, MITCHELL · 2019 to 2025
$4.5M
Intramural NIH HHS ZIA BC011800Intramural NIH HHS ZIC BC011891NIH HHS 75N91019D00024
6 · The paper itself

Abstract

Background: Identifying tumor selective targets is critical for the development of precision diagnostic and therapeutic agents in oncology. Despite advances in precision oncology elsewhere, there are no FDA-approved hepatocellular carcinoma (HCC) antigen-selective antibody-drug conjugates or radiopharmaceuticals. This study establishes an integrated workflow to identify HCC-enriched plasma membrane targets and assess their suitability for targeted molecular imaging as foundational candidates for future radiopharmaceutical therapy. Methods: Bulk RNA sequencing (371 tumors), single cell RNA sequencing (34 HCC cases), and a normal liver dataset were analyzed to identify HCC-enriched plasma membrane targets. Candidate molecules were examined on HCC and normal tissue microarrays (TMAs) and further evaluated in liver cancer cell lines by quantitative PCR, Western blot, and flow cytometry. Selected targets were then tested in mouse models of liver cancer using antibody-based positron emission tomography (immunoPET) to assess Results: Integrated transcriptomic analysis identified several tumor plasma membrane molecules with strong tumor enrichment, including GPC3, MUC13, TSPAN8, MET, and EGFR. TMAs confirmed prominent membrane expression in HCC with little signal in normal organs. Combinations of four prioritized markers captured up to 88.5% of patient tumors. Antibody-based immunoPET agents directed against prioritized targets demonstrated specific tumor accumulation Conclusions: This study establishes a multimodal framework integrating transcriptomic predictions and experimental protein validation to identify HCC targets for molecular imaging and radiopharmaceutical development. This translational blueprint successfully advances precision diagnostic and theranostic-ready agents for this disease for HCC, and a similar approach may be useful for identifying and validating targets in other malignancies.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsPositron-Emission TomographyAnimalsBiomarkers, TumorCell Line, TumorFemaleGlypicansHumansMiceRadiopharmaceuticalsTetraspaninsBiomarkers, TumorGlypicansRadiopharmaceuticalsTetraspaninsdrug developmenthepatocellular carcinomaprecision oncologyradiopharmaceuticalsradiotheranostics

Identifiers

PMID42708014
PMCPMC13549132

What Socratic holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.