Abstract 7457: Personalized treatment for hepatocellular carcinoma (HCC) patients

Abstract Predicting drug response is crucial for personalized medicine, especially in cancer research and drug resistance studies. Accurate prediction of drug response, such as the half-maximal inhibitory concentration (IC50) in cell culture models, is vital for establishing personalized treatment models. In particular, patient-derived cell culture models have garnered increasing attention due to their precise prediction of therapeutic responses in targeted drug therapies. However, the prediction of drug response in hepatocellular carcinoma (HCC) patient-derived cells (PDCs) has not been fully explored. In this study, we aimed to predict personalized drug responses to anticancer drugs in HCC. We characterized hepatic stem-like cancer cells using various human HCC cell lines (Hep3B, SkHep1, PLCPRF5, MHCC-LM3, HepG2, Huh-7). Different types of cell culture media were tested to identify HCC-specific conditions. Anticancer agents such as sorafenib and regorafenib were found to increase drug resistance in 3D cell culture models of HCC. A high-throughput screening of 300 media conditions, each with varying growth factor compositions, was conducted, and cell viability was assessed in 17 HCC patient-derived PDC models. Drug resistance profiles varied among HCC patients, with some demonstrating sensitivity to sorafenib and lapatinib, while others showed resistance to tivantinib. Next-generation sequencing (NGS) revealed unique mutations across different HCC patients. In particular, one individualized HCC patient showed the best drug response to lenvatinib and sunitinib. Furthermore, our prediction model revealed that lapatinib exhibited higher drug resistance, mirroring patterns observed in tumor cells associated with regulatory T cells, tissue-resident memory T cells (TRM), and tumor-associated macrophages (TAMs). These findings suggest that our approach offers a promising framework for predicting drug responses in HCC, supporting its application in personalized medicine. Citation Format: Jinhee Kim, Miseol Son, Da Som Kim, Yunjeong Oh, Naeun Jeon, Inhee Roh, Jayeon Kim, Vinay Tergaonkar, Do-Hyun Nam, Pierce Kah-Hoes Chow, Yong Jae Shin. Personalized treatment for hepatocellular carcinoma (HCC) patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2025; Part 1 (Regular Abstracts); 2025 Apr 25-30; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2025;85(8_Suppl_1):Abstract nr 7457.