Analysis of Liver Cancer Cell Lines Identifies Agents With Likely Efficacy Against Hepatocellular Carcinoma and Markers of Response

Abstract

Background and aims: Hepatocellular carcinomas (HCCs) are heterogeneous aggressive tumors with low rates of response to treatment at advanced stages. We screened a large panel of liver cancer cell lines (LCCLs) to identify agents that might be effective against HCC and markers of therapeutic response.

Methods: We performed whole-exome RNA and microRNA sequencing and quantification of 126 proteins in 34 LCCLs. We screened 31 anticancer agents for their ability to decrease cell viability. We compared genetic, RNA, and protein profiles of LCCLs with those of primary HCC samples and searched for markers of response.

Results: The protein, RNA and mutational signatures of the LCCLs were similar to those of the proliferation class of HCC, which is the most aggressive tumor type. Cell lines with alterations in genes encoding members of the Ras-MAPK signaling pathway and that required fibroblast growth factor (FGF)19 signaling via FGF receptor 4 for survival were more sensitive to trametinib than to FGF receptor 4 inhibitors. Amplification of FGF19 resulted in increased activity of FGF19 only in tumor cells that kept a gene expression pattern of hepatocyte differentiation. We identified single agents and combinations of agents that reduced viability of cells with features of the progenitor subclass of HCC. LCCLs with inactivating mutations in TSC1 and TSC2 were sensitive to the mammalian target of rapamycin inhibitor rapamycin, and cells with inactivating mutations in TP53 were sensitive to the Aurora kinase A inhibitor alisertib. Amplification of MET was associated with hypersensitivity to cabozantinib and the combination of sorafenib and inhibitors of MAP kinase 1 and MAP kinase2 had a synergistic antiproliferative effect.

Conclusion: LCCLs can be screened for drugs and agents that might be effective for treatment of HCC. We identified genetic alterations and gene expression patterns associated with response to these agents. This information might be used to select patients for clinical trials.

Keywords: Biomarker; Liver Tumor; MEK Inhibitor; Response to Therapy.