Transcriptomic Analysis of Cholestatic Compounds In Vitro

Methods Mol Biol. 2019;1981:175-186. doi: 10.1007/978-1-4939-9420-5_12.

Abstract

Drug-induced cholestasis is one of the most severe manifestations of drug-induced liver injury. Drug-induced cholestasis is characterized by an accumulation of endogenous metabolites normally excreted in the bile such as bile salts, cholesterol, bilirubin, or drug metabolites. The possibility to determine early in the drug development process whether a compound presents a risk of inducing drug-induced cholestasis is key information. Since preclinical repeated dose toxicity studies have limited predictive value, large efforts in identifying alternative in vitro models with improved prediction are being made. One of the best current models for in vitro human liver is primary human hepatocytes, and we recently reported that primary human hepatocytes can be kept as long-term cultures in 2D-sandwich configuration when regularly renewing the Matrigel overlay, thereby making the model useful for repeat exposure-related toxicities, as well as for the study of adaptive responses. This primary human hepatocyte culture system combined with transcriptomics carries the future promise to identify individual gene expression profiles predictive of increased drug-induced cholestasis risk.This chapter describes the various steps for culturing and exposing primary human hepatocytes to drugs during long-term 2D-sandwich culture, performing RNA extraction, gene chip assay and selecting hepatotoxic signature using the IPA software and highlighting genes involved in bile acid homeostasis.

Keywords: Acute and repeat exposure-related toxicities; Adaptive response; Bile acid disposition; Conjugation and secretion of bile salts; Genes involved in the uptake; Long-term 2D-sandwich culture; Matrigel re-overlay; Primary human hepatocytes; Synthesis; Transcriptomic signature of cholestasis.

MeSH terms

  • Cells, Cultured
  • Chemical and Drug Induced Liver Injury / genetics
  • Cholestasis / genetics*
  • Gene Expression Profiling / methods*
  • Hepatocytes / metabolism
  • Humans
  • Software