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Theranostics, Published 2026-7-29; 16(15):8501-8520. | doi:10.7150/thno.136906 A multimodal pipeline for the identification and diagnostic immunoPET validation of hepatocellular carcinoma targets for radiotheranostic development

Philip Homan^1,†,*, Joon-Yong Chung^2,†,*, Woonghee Lee², Divya Nambiar², Julia Sheehan-Klenk², Hima Makala², Stanley Fayn^2,3, Orit Jacobson², Arthur Paden King², Kyungeun Kim⁴, Jeong Won Kim⁵, Sung Ryol Lee⁶, Maggie Cam⁷, Stephen M. Hewitt⁸, Xin Wei Wang⁹, Mitchell Ho¹⁰, Freddy E. Escorcia^2,11,*

¹Advanced Biomedical Computational Science, Frederick National Laboratory for Cancer Research, Frederick, MD, 21702, USA.
²Molecular Imaging Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
³Oxford Institute for Radiation Oncology, Department of Oncology, University of Oxford, Oxford Ox3 7DQ, UK.
⁴Department of Pathology, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Republic of Korea.
⁵Department of Pathology, Kangnam Sacred Heart Hospital, Hallym University College of Medicine, Seoul, 07441, Republic of Korea.
⁶Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, 03181, Republic of Korea.
⁷Center for Collaborative Bioinformatics, National Institutes of Health, Bethesda, MD 20892, USA.
⁸Laboratory of Pathology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
⁹Laboratory of Human Carcinogenesis, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
¹⁰Laboratory of Molecular Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.
¹¹Radiation Oncology Branch, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Bethesda, MD 20892, USA.

^†These authors contributed equally to this work.
^*Corresponding authors: Philip Homan, Ph.D., Joon-Yong Chung, Ph.D., Freddy E. Escorcia MD, Ph.D.

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 in vivo target engagement and distribution.

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 in vivo, and signal intensity correlated with membrane staining by immunohistochemistry. These results highlight the potential of these markers to serve as diagnostic tools and promising candidate platforms for therapeutic development, demonstrating the utility of this approach to identify novel oncology targets.

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.

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본 연구는 간세포암의 정밀 진단 및 방사선테라노스틱스 (Radiotheranostics) 치료제 개발을 목적으로, 대규모 데이터 기반 In silico 스크리닝 - 조직/세포 단백질 검증 - 생체 내 ImmunoPET 영상화로 이어지는 다중모드 분석 파이프라인을 구축하고 실증한 성과입니다.  TCGA Bulk RNA-seq 및 단일세포 RNA-seq (scRNA-seq, 10만여 개 세포) 데이터를 통합 분석하여 암세포 집단에 선택적으로 과발현된 세포막 표적을 선별하였습니다. 이어 165쌍의 간암 조직마이크로어레이(TMA) 면역조직화학 (IHC) 검증을 통해 GPC3, MUC13, TSPAN8, MET, EGFR, CD24, CD147이 정상 간 대비 암 조직 세포막에 유의미하게 과발현됨을 입증했습니다. 반면, 전사체 분석에서 도출되었으나 정상 간세포에서도 발현이 확인된 ROBO1을 오탐 표적으로 제외함으로써 mRNA-단백질 발현 간 불일치를 필터링하는 파이프라인의 유용성을 증명했습니다. 또한, 종양 이질성 극복을 위한 Co-expression Score 기반 조합 분석을 시행하여 GPC3+MUC13 조합 시 78.8%, GPC3+MUC13+TSPAN8+CD24 4종 조합 시 환자 조직의 최대 88.5%를 커버할 수 있음을 확인하여 다중표적 치료제 개발의 근거를 마련했습니다. 선별된 표적에 동위원소를 표지한 항체 및 나노바디를 간암 마우스 모델에 투여해 ImmunoPET 영상화를 진행한 결과, 우수한 종양 특이적 집적을 확인하였으며 영상 신호 강도가 실제 조직의 IHC 표적 발현량과 강한 양의 상관관계를 나타냄을 증명했습니다.  본 연구는 간암 방사선테라노스틱스 및 항체-약물 접합체 (ADC) 개발을 위한 신규 표적 자원을 제공하며, 타 난치성 악성 종양의 표적 발굴 연구에도 확장 적용 가능한 표준화된 분석 플랫폼을 제시합니다.

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