High-throughput single-cell RNA-Seq profiling of DMSO-differentiated Huh7.5.1 undergoing or not long-term HCV infection

Hepatocellular carcinoma (HCC) is the second leading cause of cancer death worldwide, indicating urgent need for novel preventive strategies. Cancer chemoprevention discovery has been challenging due to the absence of tractable and clinically relevant model systems. Here, we developed a simple and robust human liver cell-based system, in which persistent hepatitis C virus (HCV) infection induces a HCC risk signature robustly predicting long-term HCC risk in cirrhotic patients. Using single-cell RNA-Seq analysis we observed a virus-dependent induction of the HCC high-risk gene signature and EGFR/MAPK signaling in HCV-infected liver cells. Our system, modeling the cell circuits encoded in the clinical HCC risk signature, enables investigation of the mechanisms of hepatocarcinogenesis and the discovery of cancer preventive strategies for HCC. Overall design: DMSO-differentiated Huh7.5.1 cells were infected or not using HCV cell-culture derived (HCVcc) Jc1E2FLAG. On day 7 post-infection, single-cells were isolated, total cellular RNA was purified, and subjected to RNA-Seq. The modulation of specific gene signatures in association with the normalized HCV copy number in single cell RNA-Seq data was determined using the pre-ranked GSEA module implemented in GenePattern with Pearson correlation as the rank metric.