Multimodal Approach for Identification and Validation of Hepatocellular Carcinoma Targets for Radiotheranostics

Abstract

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)-selective treatments. HCC is the most common type of liver cancer and accounts for significant morbidity and mortality worldwide. Here, we sought to integrate bulk (371 cases) and single cell RNA sequencing (scRNAseq, n=2 datasets, 34 cases, 102,956 cells) of patient samples to enrich for molecules that are overexpressed in HCC, which could serve as HCC-selective targets. To guide definitions of tumor and normal cell clusters with higher fidelity, we also imported a normal liver scRNAseq dataset. Using this integrated approach, we identified several HCC-selective plasma membrane molecules. To validate these targets, we performed immunohistochemical staining of HCC and normal tissue microarrays and confirmed HCC-selective staining of identified targets. Next, we verified the presence of these targets in several commercially available HCC cell lines by flow cytometry and western blot. Finally, we designed, engineered, and tested novel antibody-based positron emission tomography (immunoPET) agents to these targets in various murine models of liver cancer. Our findings confirm that we can leverage this multimodal approach to identify and validate of HCC-selective targets, which can be used to develop tumor-selective diagnostic and therapeutic radiopharmaceuticals, or radiotheranostics, and other precision oncology agents. One Sentence SummaryA multimodal pipeline defines and validates tumor-selective surface targets for radiotheranostic use in hepatocellular carcinoma.