A human liver cell-based system modeling a clinical prognostic liver signature combined with single-cell RNA-Seq for discovery of liver disease therapeutics

Abstract: Chronic liver disease and hepatocellular carcinoma (HCC) are life-threatening with limited treatment options. The lack of clinically relevant/tractable experimental models hampers therapeutic discovery. We developed a simple and robust human liver cell-based system modeling a clinical prognostic liver signature (PLS) predicting long-term liver disease progression toward HCC. Using the PLS as a readout, followed by validation in NASH-HCC animal models and patient-derived tumorspheroids, we identified nizatidine, a histamine receptor H2 (HRH2) blocker, for treatment of advanced liver disease and HCC chemoprevention. Perturbation studies combined with scRNA-Seq analyses of patient liver tissues uncovered HRH2+, CLEC5Ahigh, MARCOlow liver macrophages and hepatocytes as nizatidine targets. The PLS model combined with scRNA-Seq of patient tissues enables discovery of urgently needed targets and therapeutics for treatment of advanced liver disease and cancer prevention. Overall design: We performed bulk RNA sequencing of DMSO differentiated Huh751 at different time points