A human liver cell-based system modeling a clinical prognostic liver signature for therapeutic discovery
A lack of suitable experimental models hampers drug discovery for chronic liver disease and hepatocellular carcinoma. So Crouchet et al. developed a human liver cell–based model predicting long-term liver disease progression toward hepatocellular carcinoma. They identified nizatidine as a potential therapeutic and, with single-cell RNA sequencing, could identify hepatocytes and certain liver macrophage subtypes as a potential therapeutical targets.
Segeren et al. describe a workflow to capture, image, and collect fluorescent human retina pigment epithelium cells for SORT-seq using the VYCAP puncher system. This protocol is relevant for cells that cannot be FACS-sorted.
The authors applied SORT-seq and Smart-seq2 to study the interactions between hepatitis B virus and patient-derived hepatocellular carcinoma host cells. They detected active virus replication correlated with host factor expression at the single-cell level.