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. 2013 Oct 10:6:39.
doi: 10.1186/1755-8794-6-39.

Treatment of mouse liver slices with cholestatic hepatotoxicants results in down-regulation of Fxr and its target genes

Affiliations

Treatment of mouse liver slices with cholestatic hepatotoxicants results in down-regulation of Fxr and its target genes

Ewa Szalowska et al. BMC Med Genomics. .

Abstract

Background: Unexpected cholestasis substantially contributes to drug failure in clinical trials. Current models used for safety assessment in drug development do not accurately predict cholestasis in humans. Therefore, it is of relevance to develop new screening models that allow identifying drugs with cholestatic properties.

Methods: We employed mouse precision cut liver slices (PCLS), which were incubated 24 h with two model cholestatic compounds: cyclosporin A (CsA) and chlorpromazine (CPZ). Subsequently, transcriptome analysis using DNA microarrays and q-PCR were performed to identify relevant biological processes and biomarkers. Additionally, histology was carried out and levels of triglycerides (TG) and bile acids (BA) were measured. To verify the ex vivo mouse data, these were compared with publically available human data relevant for cholestasis.

Results: Whole genome gene expression analysis showed that CsA up-regulated pathways related to NF-κB, ER stress and inflammation. Both CsA and CPZ down-regulated processes related to extracellular matrix (ECM) remodelling, BA homeostasis, Fxr signalling, and energy metabolism. The differential expression of a number of characteristic genes (e.g. Abcg5, Abcg8, Klf15, and Baat) could be confirmed by q-PCR. Histology revealed that CsA but not CPZ induced "ballooning" of hepatocytes. No effects on TG and BA levels were observed after incubation of PCLS with CsA and CPZ. A substantial number of processes altered in CsA- and CPZ-treated mouse PCLS ex vivo was also found to be affected in liver biopsies of cholestatic patients.

Conclusion: The present study demonstrated that mouse PCLS can be used as a tool to identify mechanisms of action of cholestatic model compounds. The induction of general stress responses and down-regulated Fxr signalling could play a role in the development of drug induced cholestasis. Importantly, comparative data analysis showed that the ex vivo mouse findings are also relevant for human pathology. Moreover, this work provides a set of genes that are potentially useful to assess drugs for cholestatic properties.

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Figures

Figure 1
Figure 1
Biochemical characterization of mouse liver slices in exposure experiments. Liver slices were incubated for 24 hours with pre-selected concentrations of cyclosporin A (CsA) 40 μM and chlorpromazine (CPZ) 20 μM. Protein content (A), ATP content (B) and LDH leakage into medium compared to total LDH content in slices (C) were measured to assess liver slices viability. Ctr stands for control. Each point is the mean ± SD of five independent experiments (liver slices were isolated from livers of five mice) and each measurement was performed in technical duplicates. None of the measured parameters were significantly affected.
Figure 2
Figure 2
Effects of cholestatic drugs on gene expression in mouse PCLS. PCLS obtained from 5 mice were treated with 40 μM cyclosporin A (CsA), 20 μM chlorpromazine (CPZ) or vehicle (DMSO) for 24 hours and subjected to Affymetrix microarray analysis. The biological processes in the heat map correspond to gene sets significantly affected according to GSEA analysis (p < 0.05, FDR < 0.25). Gene sets were obtained using the ANNI text mining tool. Processes that were up-regulated are represented by red color, the down-regulated processes are depicted in green, processes that were unchanged are depicted in black.
Figure 3
Figure 3
Effects of cyclosporin A and chlorpromazine on the expression of genes involved in Fxr and Rxr-regulated pathways related to metabolism and/or transport of bile acids and lipids. Cyclosporin A (CsA) and chlorpromazine (CPZ) significantly affected Fxr-regulated cholesterol and bile acids cellular transport pathway (A), Bile acids regulation of glucose and lipid metabolism via Fxr(B), and Rxr-dependent regulation of lipid metabolism via Ppar, Rar and Vdr pathway (C). Blue and red bars indicate down-and up-regulation respectively of significantly affected genes. 1 and 2 indicate liver slices treated with CsA and CPZ respectively. Each bar represents average fold change of gene expression (treatment vs. control) in liver slices from five mice. ECM: extracellular matrix. For an explanation of the MetaCore symbols is referred to http://pathwaymaps.com/pdf/MC_legend.pdf.
Figure 4
Figure 4
Effects of cholestasis on the expression of genes involved in the Cell adhesion_ECM remodelling pathway and in mouse PCLS. Both cyclosporin A (CsA) and chlorpromazine (CPZ) significantly affected the Cell adhesion_ECM remodelling pathway (p < 0.005). Explanation of the bars is given in the legend of Figure 3.
Figure 5
Figure 5
Functional clustering of biomarkers. In total 73 genes were identified as candidate biomarkers for drug-induced cholestasis. Clustering of biomarkers was performed in STRING using the functional clustering option. The analysis identified 5 functional clusters; yellow represents β-oxidation, blue represents biotransformation, brown represents bile acids and drugs conjugation, green represents lipid metabolism, and red regulation of bile acids metabolism via Fxr (Nr1h4). A total of 46 out of 73 genes formed connected nodes. Disconnected genes (27genes) were removed from the figure.
Figure 6
Figure 6
Identification of potential biomarkers for cholestasis in PCLS. PCLS were exposed for 24 hours to model toxicants for cholestasis (cyclosporin A (CsA)-A, chlorpromazine (CPZ)-B), steatosis (amiodarone (A)-C, valproic acid (VA)-D, necrosis, isoniazid (ISND-E), paraquat (PQ)-F, and controls (ctr)). GSEA led to the identification of 73 genes for which the mRNA expression was down-regulated by both CsA and CPZ. mRNA expression values for the selected biomarkers are derived from DNA-microarrays and results are presented as heat maps of log2, median centered gene expression values. Red and green indicate expression higher or lower respectively than the average expression of all samples within the same heat map. Please note Fxr is also depicted as Nr1h4.
Figure 7
Figure 7
Histological analysis of liver slices treated with CsA and CPZ. PCLS were cultured for 24 and 48 hours in the presence of DMSO (control) (A and B), 40 μM CsA (C and D) or 20 μM CPZ (E and F). Histology of PCLS treated with CsA revealed ballooning of hepatocytes at the outer parts of slices after 24 and 48 hours (C and D respectively). Histology of CPZ treated slices cultured for 24 and 48 hours (E and F respectively) revealed a slight increase in number of cells containing pycnotic nuclei compared to control slices cultured equally long (A and B).
Figure 8
Figure 8
Biochemical analysis and specific histological staining of liver slices treated with CsA. Bile acid (BA) (A) and triglyceride (TG) (B) levels in PCLS cultured for 24 or 48 hours in the presence of either DMSO or 40 μM cyclosporin A (CsA) were not affected by any of the conditions, X- axis represents the tested conditions and Y-axis represents content of BA (A) or TG (B) in nmol per slice. Glycogen was assessed by PAS staining in PCLS cultured for 24 h in the presence of DMSO (C) or 40 μM CsA (D) demonstrating the absence of glycogen in ballooning hepatocytes. Arrows in (C) indicate the presence of glycogen in controls. Fouchet staining in PCLS cultured for 24 h in the presence of DMSO (E) or 40 μM CsA (F) demonstrating accumulation of several vacuoles in CsA treated slices (see arrows in F). All pictures were taken using 100-fold magnification.
Figure 9
Figure 9
Effects of cholestasis on gene expression in human liver biopsies. A publically available transcriptomics data set (GSE46960) of liver biopsies obtained from 64 infants with biliary atresia, 14 infants with intrahepatic cholestasis of other origin than biliary atresia, and 7 age-matched controls were subjected to GSEA. The biological processes in the heat map correspond to gene sets significantly affected according to GSEA analysis (p < 0.05, FDR < 0.25). Gene sets were obtained using the ANNI text mining tool. Processes that were up-regulated are represented by red color, the down-regulated processes are depicted in green, and processes that were unchanged are depicted in black.

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