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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: 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.

ORGANISM(S): Homo sapiens

PROVIDER: GSE173671 | GEO | 2021/07/01

REPOSITORIES: GEO

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Project description:Background & Aims: Cirrhosis and liver cancer are potential outcomes of advanced nonalcoholic fatty liver disease (NAFLD). It is not clear what factors determine whether patients will develop advanced or mild NAFLD, limiting non-invasive diagnosis and treatment before clinical sequelae emerge. We investigated whether DNA methylation profiles can distinguish patients with mild disease from those with advanced NAFLD, and how these patterns are functionally related to hepatic gene expression. Methods: We collected frozen liver biopsies and clinical data from patients with biopsy-proven NAFLD (56 in the discovery cohort and 34 in the replication cohort). Samples were divided into groups based on histologic severity of fibrosis: F0?1 (mild) and F3?4 (advanced). DNA methylation profiles were determined and coupled with gene expression data from the same biopsies; differential methylation was validated in subsets of the discovery and replication cohorts. We then analyzed interactions between the methylome and transcriptome. Results: Clinical features did not differ between patients known to have mild or advanced fibrosis based on biopsy analysis. There were 69,247 differentially methylated CpG sites (76% hypomethylated, 24% hypermethylated) in patients with advanced vs mild NAFLD (P<.05). Methylation at FGFR2, MAT1A, and CASP1 was validated by bisulfite pyrosequencing and the findings were reproduced in the replication cohort. Methylation correlated with gene transcript levels for 7% of differentially methylated CpG sites, indicating that differential methylation contributes to differences in expression. In samples with advanced NAFLD, many tissue repair genes were hypomethylated and overexpressed, whereas genes in certain metabolic pathways, including 1-carbon metabolism, were hypermethylated and under-expressed. Conclusions: Functionally relevant differences in methylation can distinguish patients with advanced vs mild NAFLD. Altered methylation of genes that regulate processes such as steatohepatitis, fibrosis, and carcinogenesis indicate the role of DNA methylation in progression of NAFLD. Three technical replicates were included for quality control along with 35 mild NAFLD (33 unique samples) and 24 advanced NAFLD (23 unique sample). One sample per technical duplication was randomly included for a total of 56 NAFLD samples used for study.

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

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