Gene expression profiles of murine fatty liver induced by the administration of methotrexate

Toxicology 249 (2008) 75–84

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Gene expression profiles of murine fatty liver induced by the administration of methotrexate Min-Ho Lee a,b , Il Hong a,b , Mingoo Kim c,h , Byung-Hoon Lee a,h , Ju-Han Kim c,h , Kyung-Sun Kang d,h , Hyung-Lae Kim e,h , Byung-Il Yoon f,h , Heekyoung Chung g,h , Gu Kong g,h , Mi-Ock Lee a,b,h,∗ a

College of Pharmacy, Seoul National University, Seoul 151-742, Republic of Korea Bio-MAX Institute, Seoul National University, Seoul 151-742, Republic of Korea c Seoul National University Biomedical Informatics College of Medicine, Seoul National University, Seoul 151-742, Republic of Korea d Department of Veterinary Public Health College of Veterinary Medicine, Seoul National University, Seoul 151-742, Republic of Korea e Department of Biochemistry College of Medicine, Ewha Womans University, Seoul 158-710, Republic of Korea f School of Veterinary Medicine, Kangwon National University, Kangwon 200-701, Republic of Korea g Department of Pathology College of Medicine, Hanyang University, Seoul 133-791, Republic of Korea h Toxicogenomics Research Consortium, Hanyang University, Seoul 133-791, Republic of Korea b

a r t i c l e

i n f o

Article history: Received 22 February 2008 Received in revised form 14 April 2008 Accepted 14 April 2008 Available online 22 April 2008 Keywords: Methotrexate Toxicogenomics Microarray analysis Fatty liver

a b s t r a c t Methotrexate (MTX) is used to treat a variety of chronic inflammatory and neoplastic diseases. However, it can induce hepatotoxicity such as microvesicular steatosis and necrosis. To explore the mechanisms of MTX-induced hepatic steatosis, we used microarray analysis to profile the gene expression patterns of mouse liver after MTX treatment. MTX was administered orally as a single dose of 10 mg/kg (low dose) or 100 mg/kg (high dose) to ICR mice, and the livers were obtained 6 h, 24 h, and 72 h after treatment. Serum alanine aminotransferase, aspartate aminotransferase and triacylglycerol levels were not significantly altered in the experimental animals. Signs of steatosis were observed at 24 h after administration of high dose of MTX. From microarray data analysis, 908 genes were selected as MTX-responsive genes (P < 0.05, two-way ANOVA; cutoff ≥1.5-fold). Database for Annotation, Visualization and Integrated Discovery (DAVID) analysis revealed that the predominant biological processes associated with these genes are response to unfolded proteins, phosphate metabolism, and cellular lipid metabolism. Functional categorization of these genes identified 28 genes involved in lipid metabolism that was interconnected with the biological pathways of biosynthesis, catabolism, and transport of lipids and fatty acids. Taken together, these data provide a better understanding of the molecular mechanisms of MTX-induced steatogenic hepatotoxicity, and useful information for predicting hepatotoxicity through pattern recognition. © 2008 Elsevier Ireland Ltd. All rights reserved.

1. Introduction Methotrexate (MTX) is a synthetic analogue of dihydrofolate which is a potent inhibitor of dihydrofolate reductase catalyzing a key step in the production of tetrahydrofolate. Because tetrahydrofolate is required for the biosynthesis of purine nucleotides, MTX inhibits DNA synthesis and thereby blocks growth of rapidly dividing cells. Thus, MTX is used as a chemotherapeutic agent for a variety of human malignancies (Huennekens, 1994). MTX is the most frequently used anti-inflammatory drug for the treatment of

∗ Corresponding author at: College of Pharmacy, Seoul National University, Seoul 151-742, Republic of Korea. Fax: +82 2 872 1795. E-mail address: [email protected] (M.-O. Lee). 0300-483X/$ – see front matter © 2008 Elsevier Ireland Ltd. All rights reserved. doi:10.1016/j.tox.2008.04.011

chronic inflammatory diseases such as rheumatoid arthritis and psoriasis (Genestier et al., 2000). However, long-term therapy or a high cumulative dose of MTX is associated with an increased risk of liver injury (Richard et al., 2000). The histological features of MTX-induced hepatotoxicity include microvesicular steatosis, portal tract inflammation, focal liver cell necrosis, and fibrosis in the pericellular and portal tract regions (Kevat et al., 1988; Ahern et al., 1998; Richard et al., 2000), that resembles non-alcoholic steatohepatitis (NASH) (Langman et al., 2001). Therefore, the American Academy of Dermatology recommends monitoring hepatic safety with regular liver biopsies after an initial cumulative dose of 1500 mg of MTX, in patients with psoriasis (Roenigk et al., 1988). Although a clear relationship between hepatic injury and cumulative dose of MTX in patients, the underlying mechanisms that contribute to MTX-induced hepatic steatosis have not been studied

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Fig. 1. (A) Serum ALT, AST and TG levels after exposure to MTX. Shade area indicates the normal reference value (ALT 21–48 U/l, AST 40–71 U/l, and TG 60–143 mg/dl) (Song et al., 1989). () Vehicle, ( ) low dose, and () high dose. Result are mean ± S.D. (n = 3). (B) Histological assessment of hepatic steatosis after 24 h exposure to high dose MTX. Photomicrographs of Oil red O stained liver sections form a vehicle and high-dose MTX-treated mouse (400× magnification).

thoroughly. Variable dosage regimens and pre-existing liver conditions such as alcohol abuse, diabetes mellitus, and obesity make it difficult or impossible to ascribe the hepatotoxicity to MTX alone. Drug-induced hepatotoxicity is an important healthcare issue because of the associated mortality and morbidity, which are difficult to predict (Kaplowitz, 2001). Evaluating the mechanism responsible for drug-induced hepatotoxicity is important and necessary for identifying risk factors and developing appropriate treatment regimens. Recently developed microarray assays provide highly sensitive and informative markers of toxicity and new information about the mechanism of action by analysing gene expression patterns provoked by toxicants (Nuwaysir et al., 1999). A large-scale analysis of gene expression profiling of hepatotoxicants using rat hepatocytes showed a correlation between the gene expression pattern and mechanism of toxicity (Waring et al., 2001a). Further hepatotoxicants could be clustered based on their mechanisms of toxicity using gene expression profiles in animal model (Waring et al., 2001b). Here, we profiled the gene expression patterns of MTX-induced hepatic steatosis that is accompanied by clear histopathology of hepatic steatosis in a mouse model. Our gene expression profiling data show significant changes in the expression of genes important in the biosynthesis and catabolism of lipids and fatty acids. We compared our data with the gene expression profiles associated with other fatty liver-inducing drugs such as valproic acid and tetracycline. This information will be useful for developing tools to predict toxicity of unknown chemicals or new drug candidates, which will eventually contribute to improved processes for risk assessment and safety evaluation.

mouse chow (Certified Rodent Diet 5002; Purina Mills Inc., St. Louis, MO) and water were supplied ad libitum. The animal laboratory was located at the Animal Center for Pharmaceutical Research, College of Pharmacy, Seoul National University (Seoul, Korea). It was maintained at a temperature of 20–23 ◦ C, and humidity of 30–48%, with 12 h light and dark cycles. Upon arrival at the animal laboratory, the mice were allowed at least 4 days to acclimatize. Food was withdrawn for 4 h before and was resupplied 2 h after MTX administration. MTX was obtained from Sigma Chemical Co. (St. Louis, MO) and suspended in 0.1% carboxymethyl cellulose. Mice (n = 3) were dosed by oral gavage with 10 mg/kg and 100 mg/kg in 400 ␮l, and the livers were obtained at 6 h, 24 h, or 72 h after drug treatment. The doses of 10 mg/kg and 100 mg/kg were selected as low dose and high dose, respectively, by range-finding studies. High dose was determined as a minimal dose that induced microvesicular

2. Materials and methods 2.1. Animals and study design Male ICR mice, 6 weeks of age, were obtained from Japan SLC Inc. (Hamamatsu, Japan). The mice were housed three per cage in polycarbonate cages, and commercial

Fig. 2. Schematic representation of the experimental design and flow chart for this microarray data analysis.

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Fig. 3. Validation of gene expression changes by quantitative real-time PCR. The y-axis represents the fold change in expression (MTX-treated vs. vehicle-treated control) on a log 2 scale. Results are mean ± S.D. (n = 3) obtained by qRT-PCR () and microarray analysis (). Low, low dose MTX; high, high dose MTX.

steatosis at 24 h of treatment. 0.1% carboxymethyl cellulose was administered to the vehicle-treated control groups. 2.2. Clinical chemistry and histopathology For the analysis of serum liver enzymes, animals were euthanized with diethyl ether and blood was drawn from the inferior vena cava. Serum alanine aminotransferase (ALT), aspartate aminotransferase (AST) activities and triacylglycerol (TG) levels were measured with the Prestige 24i fully automated biochemical analyzer (Tokyo Boeki Pty Ltd., Tokyo, Japan). For histopathological assessment, livers were removed, and embedded in Polyfreeze tissue freezing medium (Polyscience Inc., Warrinton, PA) and slowly frozen at –80 ◦ C. The frozen liver tissues were sectioned to 5 ␮m thickness. Sections were stained with Oil Red O and counterstained with hematoxylin. Histopathological examination of the liver sections was conducted by a pathologist and peer-reviewed. 2.3. Microarray analysis Total RNA was isolated from the RNAlater-permeated liver sections using easyBLUE (iNtRON Biotechnology Inc., Sungnam, Korea), and was purified using an RNeasy® Mini Kit (Qiagen, Valencia, CA). The quality of the total RNA was determined using RNA Nano LabChip® (Agilent Technologies, Palo Alto, CA). Applied Biosystems Mouse Genome Survey Arrays (Applied Biosystems, Foster City, CA), which contain 60-mer oligonucleotide probes representing a set of 32,996 individual mouse genes and more than 1000 control probes, were used for this investigation. Total RNA isolation, generation and labeling of cRNA, and hybridization of microarray were performed as previously described (Lee et al., 2007a,b). Microarray images were collected and the chemiluminescent signals were quantified, corrected for background, spatially normalized, and exported for a quality report. Data with quality reports above the manufacturer’s threshold were used for further analysis. 2.4. Data analysis The assay signal and the assay signal-to-noise ratio values for the microarray images were extracted using Applied Biosystems Expression System software. Bad spots flagged by the software (flag < 100) were removed from the analysis. The assay signals of the probe sets were imputed by a KNN imputation algorithm (Troyanskaya et al., 2001), variance stabilization transformed (Huber et al., 2002) and quantile normalized (Bolstad et al., 2003). Differentially expressed probe sets were selected by two-way ANOVA (P < 0.05). Gene sets with different dose and time effects according to two-way ANOVA were classified into time-dependent (MTx), dose-dependent (MxD), and combined effect (MTD) groups. The three groups were then classified into with- and without-interaction groups according to the significance of the interaction terms under saturated linear models. K-means clustering

and hierarchical clustering were applied to the differentially expressed genes using the Multiexperiment Viewer software (Saeed et al., 2003; http://www.tm4.org). Genes were annotated and biological processes were analyzed by the Database for Annotation, Visualization and Integrated Discovery (DAVID) (Dennis et al., 2003; http://david.abcc.ncifcrf.gov), Protein ANalysis THrough Evolutionary Relationships (PANTHER) (Mi et al., 2005; http://www.pantherdb.org), and Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis (Ogata et al., 1999; http://www.genome.ad.jp/kegg/genes.html). 2.5. Quantitative real-time polymerase chain reaction (qRT-PCR) To confirm the changes in gene expression identified using the oligonucleotide microarray, qRT-PCR was performed as previously described (Lee et al., 2007b). Primer sequences used for real-time PCR were: Elovl3 (forward, 5 -GCCTCTCATCCTCTGGTCCT-3 , reverse, 5 -TGCCATAAACTTCCACATCCT-3 ), Cpt1b (forward, 5 -CATCCCAGGCAAAGAGACA-3 , reverse, 5 -AAGCGACCTTTGTGGTAGACA3 ), Pltp (forward, 5 -GTCTAAAATGAATATGGCCTTCG-3 , reverse, 5 -CCAGAAGTGATGAA CGTGGA-3 ) and Cyp17a1 (forward, 5 -CATCCC ACACAAGGCTAACA-3 , reverse, 5 -CCCATTCATTTTTATCGTGATG-3 ).

3. Results 3.1. Hepatotoxicity of MTX: clinical chemistry and histopathology MTX was administered orally to male ICR mice as single dose of 10 mg/kg (low dose) or 100 mg/kg (high dose), and the livers were obtained 6 h, 24 h, or 72 h after treatment. The experimental doses are comparable to human therapeutic doses: the conventional dose in humans is about 0.2–10 mg/kg, and high dose in humans is approximately between 90 mg/kg and 350 mg/kg (Chan ¨ et al., 1980; Breithaupt and Kuenzlen, 1983; Aquerreta et al., 2004). Hepatotoxicity was evaluated from serum ALT and AST levels (Fig. 1A). No significant changes were observed between MTX-treated groups and vehicle-treated control groups. Serum TG concentration increased above the reference range after MTX treatment, however, it was not statistically significant (Fig. 1A). Signs of steatosis were observed only at 24 h after administration of high dose of MTX. Oil red O staining of liver sections obtained from the MTX-treated groups showed microvesicular lipid droplets around

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the central vein 24 h after the high dose treatment, but these disappeared 72 h after treatment. Representative stained liver sections are shown in Fig. 1B. Together, these data indicate that MTX induces microvesicular steatosis at an early stage of administration without marked elevation of serum liver enzyme levels under our experimental conditions. 3.2. Gene expression analysis To identify changes in global gene expression associated with MTX treatment, we performed a multi-step analysis of the microarray gene expression data (Fig. 2). The transformed and normalized data were subjected to two-way ANOVA, and 2070 probe sets were identified with significantly altered expression levels (P < 0.05). After removing unannotated probe sets, 1218 probe sets were considered to represent MTX-responsive genes. The genes were classified into four groups under the terms of a saturated linear model: 522 of 1218 differentially expressed genes showed a timedependent response, 367 genes were dose-dependent, and 120 genes were both time- and dose-dependent. To verify the gene expression level in the oligonucleotide microarray analysis, quantitative real-time polymerase chain reaction analysis was performed using individual liver samples from vehicle and MTX-treated mice. The results of qRT-PCR and microarray analysis of four genes associated with lipid metabolism were highly compatible, as shown in Fig. 3. To profile the expression of genes that are associated with steatogenic hepatotoxicity as well as other biological and pharmacological functions of MTX, we first extracted 908 characteristically upregulated or downregulated genes, of which expression changes greater than 1.5-fold with respect to the mean intensity of the time-matched control groups (Supplementary Table 1). The cutoff of 1.5-fold corresponded to about upper 33% of the genes with changes. With these MTX-responsive genes, we first performed hierarchical clustering analysis (Fig. 4). At each time point, low and high dose-treated groups were in the same node, and the distance between nodes 24 h and 72 h after treatment was closer than those 6 h after treatment. This profile indicates that there are two distinct phases of gene expression changes, i.e., an early phase at 6 h and a late phase at 24 h and 72 h after treatment, suggesting that a dynamic and complex program of gene regulatory events accompanies the MTX-induced hepatic steatogenesis. Second, the 908 differentially expressed genes were submitted to DAVID (Dennis et al., 2003), to determine the most significantly overrepresented biological process annotation. The significantly overrepresented biological process terms identified included “cellular lipid metabolism” (Table 1). Third, to gain more insight into the biological functions of these gene products relative to the

Table 1 Statistically significantly altered gene ontology biological process terms in MTXaltered genesa GO biological process term

P-value

Response to unfolded protein Phosphate metabolism Cellular lipid metabolism Cellular protein metabolism Transcription Regulation of nucleobase, nucleoside, nucleotide and nucleic acid metabolism Ossification Osteoblast differentiation

9.40E−06 1.23E−02 2.27E−02 2.38E−02 2.40E−02 4.19E−02 4.64E−02 4.85E−02

a GO analysis was performed using DAVID Bioinformatics Resources. Shown are GO biological process terms that significantly overrepresented (a modified Fisher Exact P-value <0.05) for the MTX-responsive genes.

Fig. 4. Hierachical clustering of 908 genes that gave differential expression during at least one time point. The y-axis of the dendrogram represents the genes and the corresponding expression level displayed in green for down-regulation, red for up-regulation, and black for insignificant change in gene expression.

time and dose of MTX treatment, the 908 MTX-responsive genes were divided into four clusters using K-means clustering algorithm (Steinley, 2006) (Fig. 5). The biological processes related to lipid metabolism such as “cellular lipid metabolism” and “sterol metabolism” were significantly overrepresented in Cluster 3, which included genes downregulated at the early phase that recovered to normal at the late phase (Fig. 5).

3.3. Expression of genes associated with lipid, fatty acid, and steroid metabolism Functional categorization of 908 genes using the DAVID revealed that 28 genes are associated with lipid metabolism such as lipid biosynthesis, lipid and fatty acid metabolism and lipid transport (Table 2). The fold-change in expression of some of these genes with respect to the mean intensity of the time-matched control groups are shown in Fig. 6A. Further submission of these genes to the KEGG pathway database revealed that six genes are closely associated with two major lipid metabolic pathways, e.g., fatty acid elongation in mitochondria and fatty acid ␤-oxidation (Fig. 6B).

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Fig. 5. K-means clustering analysis of the genes differentially expressed after MTX treatment. K-means clustering analysis of 908 differentially expressed genes produced four clusters (䊉, low dose, and , high dose). The number of genes belonged to each cluster is given in parentheses. The bar graph indicates the numbers of genes belonged to the significantly overrepresented biological process terms that are identified by DAVID Bioinformatics Resources. The P-value for each biological process term is indicated in parenthesis.

4. Discussion 4.1. Gene expression patterns associated with lipid, fatty acid, and steroid metabolism We noted fatty changes in the mouse liver 24 h after MTX treatment, which recovered to normal by 72 h. These results are consistent with previous observations that MTX-induced hepatic steatosis which was associated with inhibition of fatty acid ␤oxidation and triglyceride secretion from the liver (Deboyser et al., 1992; Huang et al., 2004). Using this mouse model, we identified the mechanism responsible for the MTX-induced steatogenic hepatotoxicity, and our data link the gene expression pattern to the histopathology. Our microarray study identified 908 MTXresponsive genes that were significantly associated with the biological process terms of “cellular lipid metabolism” (Table 1).

In the K-means clusters, lipid metabolism-associated genes were significantly overrepresented in cluster 3, whose genes were downregulated at 6 h, and recovered to the control level thereafter (Fig. 5). These results correlate well with the histological changes of hepatic steatosis in the early phase of MTX treatment. To understand the molecular basis of MTX-induced steatosis, we employed DAVID and KEGG pathway database, and we identified 28 lipid metabolism-associated genes that are involved in lipid biosynthesis, lipid and fatty acid metabolism, and lipid transport (Table 2 and Fig. 6). Notably, MTX treatment altered gene whose products are involved in fatty acid and cholesterol biosynthesis. Expression of Agt, whose product is the precursor of angiotensin I, increased in the early phase of MTX treatment and returned to normal thereafter. This result may be relevant to a recent observation that Agt−/− mice gain less weight than wild-type mice in response to chow or a high-fat diet (Massiera et al., 2001). The

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Fig. 6. Expression pattern of MTX-responsive genes associated with lipid metabolism. (A) Characteristically upregulated or downregulated genes, whose expression changes greater than 1.5-fold with respect to the mean intensity of the time-matched control groups. The y-axis represents the fold change in expression (MTX-treated vs. vehicletreated control) on a log 2 scale. (B) KEGG pathways of fatty acid elongation in mitochondria and fatty acid ␤-oxidation. Six MTX-responsive genes were shown.

function of Elovl3 gene product is associated with very long chain fatty acid elongation (Tvrdik et al., 2000) and is critical for lipid accumulation and metabolism in brown adipocytes (Westerberg et al., 2006). In this study, expression of Elovl3 increased in the early phase but decrease in the late phase, suggesting that this gene contributes to the transient appearance of hepatic steatosis in the early phase of MTX treatment. In contrast, Sc4mol, whose product catalyzes a step of cholesterol biosynthesis (Risley, 2002), decreased in the early phase and increased in the late phase, indicating that synthesis of fatty acid and cholesterol may be regulated differentially by MTX (Fig. 6A). MTX also induced expression of genes that are associated with fatty acid catabolism. Fatty acid oxidation occurs mainly in mitochondria and peroxisomes (␤-oxidation) and microsomes (␻oxidation). A series of genes catalyzing peroxisomal fatty acid ␤-oxidation, Slc27a2 and acyl-CoA thioesterases subunits, Pte2a, Pte2b, and Cte1, were downregulated at 6 h and returned to normal or remained low at 72 h (Fig. 6A). The mitochondrial ␤oxidation gene Cpt1b, whose product transports fatty acids across

the inner mitochondrial membrane, the rate-limiting step in fatty acid ␤-oxidation (Jogl et al., 2004), was downregulated at all experimental times. Together, these results indicate that MTX treatment decreases both peroxisomal and mitochondrial ␤-oxidation. In contrast, expression of a lipid catabolic gene Pnliprp2, whose product transforms triacylglycerol to fatty acids, was upregulated through the entire experiment. Induction of this gene may increase the production of hepatic fatty acids, which may counteract the accumulation of hepatic TG. Finally, MTX administration altered the expression of genes associated with lipid transport (Fig. 6). Expression of the adipose differentiation-related protein gene, Adfp, which is strongly induced in cells with increased lipid load (Chang et al., 2006), increased in the early stage of MTX treatment. The phospholipid transfer protein gene, Pltp, which enhances hepatic uptake of phospholipids and cholesteryl ester from high-density lipoprotein (Foger et al., 1997), was downregulated at all experimental times. Alteration in the expression of these genes may have affected the hepatic TG concentrations and may

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Table 2 Lipid metabolism related genes that were altered by MTX treatmenta GripQuery

GeneSymbol

NM 023858

NM 015828 Lipid catabolism NM 026925 NM 011128 NM 008868

72 h

6h

24 h

72 h

Sphingomyelin phosphodiesterase 3, neutral Longevity assurance homolog 5 (S. cerevisiae) Phosphatidylinositol glycan, class B Sialyltransferase 9 (CMP-NeuAc:lactosylceramide alpha-2,3-sialyltransferase) Myotubularin related protein 2

1.22 −0.51 0.54 0.14

0.21 −0.79 −0.06 1.32

1.27 −0.51 0.05 0.19

0.07 −1.52 −0.07 0.70

0.55 −0.68 0.70 0.93

0.37 −0.44 0.32 0.26

−0.61

−0.50

0.25

−0.75

−0.23

−0.30

−0.17 0.36

0.66 −0.73

−1.03 0.44

−1.16 0.17

0.56 −0.21

0.31 −0.22

Gne

Sterol-C4-methyl oxidase-like Sialyltransferase 7 ((alpha-N-acetylneuraminyl 2,3-betagalactosyl-1,3)-N-acetyl galactosaminide alpha-2,6-sialyltransferase) F Glucosamine

−0.08

−0.04

−0.87

0.22

−0.07

−0.27

Pnlip Pnliprp2 Pla2g2c

Pancreatic lipase Pancreatic lipase-related protein 2 Phospholipase A2, group IIC

0.46 1.36 0.29

−0.01 0.60 −0.51

0.07 −0.03 0.18

0.60 1.22 0.77

1.46 0.91 0.04

0.28 0.63 0.26

Elongation of very long chain fatty acids (FEN1/Elo2, SUR4/Elo3, yeast)-like 3 Angiotensinogen

−0.64

−3.23

−4.70

0.35

−1.13

−0.95

0.03

−0.28

0.49

0.63

−0.20

−0.14

−0.27 −0.55

−2.16 −1.01

−0.86 0.24

−0.32 −0.76

−0.59 −0.12

−0.72 0.09

−0.59 −0.69 0.04

0.14 0.50 −0.95

2.36 0.83 −0.05

−0.56 −1.20 −0.04

0.94 0.74 0.04

−0.24 −0.02 0.17

−0.90

−1.05

−0.57

−0.97

−0.43

−0.72

−0.36 0.13 0.18 −0.34 −0.37

−0.86 −0.17 −0.51 0.13 0.02

−1.26 −0.52 0.43 −0.79 −0.66

−0.27 0.65 −1.63 −0.93 −0.19

−0.63 −0.13 −0.21 −0.15 0.03

−0.39 −0.35 −0.53 0.28 0.04

1.10 0.79

0.55 0.95

0.52 1.71

0.16 0.08

0.47 −0.02

0.03 −0.01

−0.67 0.34

−0.28 1.53

−0.56 2.36

−0.17 0.30

−0.57 1.08

−0.78 −0.07

Mtmr2 Sc4mol Siat7f

Agt

Fatty acid metabolism Cte1 NM 012006 Slc27a2 NM 011978 NM 134246 AK050420 NM 177470

Pte2a Pte2b Acaa2

NM 009948

Cpt1b

Cytosolic acyl-CoA thioesterase 1 Solute carrier family 27 (fatty acid transporter), member 2 Peroxisomal acyl-CoA thioesterase 2A Peroxisomal acyl-CoA thioesterase 2B Acetyl-Coenzyme A acyltransferase 2 (mitochondrial 3-oxoacyl-Coenzyme A thiolase) Carnitine palmitoyltransferase 1b, muscle

Lipid transport NM 011125 NM 007408 NM 175489 NM 013703 NM 133997

Pltp Adfp Osbpl8 Vldlr Apof

Phospholipid transfer protein Adipose differentiation-related protein Oxysterol binding protein-like 8 Very low density lipoprotein receptor Apolipoprotein F

Steroid metabolism NM 013873 NM 008293

Sult4a1 Hsd3b1

Sulfotransferase family 4A, member 1 Hydroxysteroid dehydrogenase-1, delta<5>-3-beta Leptin Cytochrome P450, family 17, subfamily a, polypeptide 1

NM 008493 NM 007809

High dose 24 h

Fatty acid biosynthesis Elovl3 NM 007703 NM 007428

Low dose 6h

Cellular lipid metabolism Smpd3 NM 021491 Lass5 NM 028015 Pigb NM 018889 Siat9 NM 011375

Lipid biosynthesis NM 025436 NM 016973

Description

Lep Cyp17a1

a Characteristically upregulated or downregulated genes, of which expression changes greater than 1.5-fold with respect to the mean intensity of the time-matched control groups. Data represent fold-changes on log 2 scale compared to corresponding vehicle control.

have induced the steatogenic histopathology of the MTX-treated mice. 4.2. Comparisons of gene expression profiles for fatty liver-inducing drugs Several recent studies have profiled gene expression changes caused by fatty liver-inducing drugs, as a part of project of the Korean Toxicogenomic Research Consortium (Yin et al., 2006, 2007; Lee et al., 2007a,b). Three steatogenic hepatotoxicants examined (valproic acid, tetracycline, and ethanol) alter mouse hepatic genes involved in the biosynthesis of TG and cholesterol, and fatty acid ␤-oxidation. To compare the gene expression profiles of these hepatotoxicants, we analyzed gene expression patterns in the fatty-liver stage, i.e., 24 h after the high dose treatment. We found 69 lipid metabolism-associated genes whose expression changed twofold

or more for at least one compound and subjected these genes to HA clustering analysis (Supplementary Fig. 1). We found a close association between MTX and ethanol, which agreed well with the observation that MTX-induced hepatotoxicity resembles NASH (Langman et al., 2001). Among the genes involved, the fatty acid elongation-associated gene, Elovl3, was significantly upregulated by all of these hepatotoxicants. Several genes involved in fatty acid ␤-oxidation were also altered in common. Valproic acid and tetracycline modulated the expression of genes such as Ehhadh, Crat, Decr1 and Dci, whereas ethanol and MTX regulated genes such as Slc27a2, Pte2a, Pte2b and Cte1. Thus, fatty acid elongation and fatty acid ␤-oxidation may be important targets for these steatogenic hepatotoxicants. The integration of these gene expression profiles showing responses to diverse fatty liver-inducing chemicals should facilitate the design of novel strategies for predicting hepatotoxicity through pattern recognition.

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Table 3 Genes associated with known biological and pharmacological function of MTXa GripQuery

GeneSymbol

Description

Low dose 6h

Immunity and defense Cytokine/chemokine-mediated immunity Ccrl2 Chemokine (C–C motif) receptor-like 2 NM 017466 Cxcr6 Chemokine (C–X–C motif) receptor 6 NM 030712 NM 009139 Ccl6 Chemokine (C–C motif) ligand 6 Cxcl10 Chemokine (C–X–C motif) ligand 10 NM 021274

High dose 24 h

72 h

6h

24 h

72 h

1.00 0.59 1.03 0.41

1.00 0.59 1.03 0.41

1.38 -0.13 0.42 1.03

0.41 −0.63 1.78 −1.01

0.35 0.23 0.25 0.69

0.27 0.98 0.46 −1.12

0.03 0.04 0.73 0.64

0.03 0.04 0.73 0.64

−0.49 −0.53 −0.21 0.75

1.33 1.18 1.14 0.21

−0.75 −0.19 0.18 0.79

0.39 −0.44 0.12 0.75

−1.93 0.43 −0.67 1.04

−1.93 0.43 −0.67 1.04

0.61 −0.43 −0.56 0.67

−1.45 0.37 −0.17 0.34

0.54 −1.26 −0.57 0.11

0.16 −0.40 −0.78 0.05

B-cell- and antibody-mediated immunity Vav3 vav 3 oncogene NM 146139 Relb Avian reticuloendotheliosis viral (v-rel) oncogene related B NM 009046

0.63 0.44

0.63 0.44

1.02 0.38

−0.08 −0.71

0.09 −0.72

0.46 0.01

Macrophage-mediated immunity NM 011925 Cd97 CD97 antigen Fcgr3 Fc receptor, IgG, low affinity III NM 010188

0.51 0.63

0.51 0.63

0.61 −0.23

0.40 1.17

0.01 −0.19

−0.13 0.06

Kinesin family member 9 Cyclin E1 Budding uninhibited by benzimidazoles 3 homolog (S. cerevisiae) Serine/threonine kinase 38 Ribosomal protein S6 kinase polypeptide 3 Sloan-Kettering viral oncogene homolog Cytoplasmic linker 2 RNA binding motif, single stranded interacting protein 2 Polo-like kinase 4 (Drosophila) Cyclin G1 Indian hedgehog TYRO3 protein tyrosine kinase 3 Tubulin, alpha 1 Rous sarcoma oncogene Macrophage stimulating 1 receptor (c-met-related tyrosine kinase) Anaphase promoting complex subunit 1 Cyclin-dependent kinase-like 2 (CDC2-related kinase) Schlafen 10 v-maf musculoaponeurotic fibrosarcoma oncogene family, protein B (avian) Hemopoietic cell kinase Kinesin-associated protein 3 MYB binding protein (P160) 1a Fibroblast growth factor 3 Fibroblast growth factor 1 Origin recognition complex, subunit 4-like (S. cerevisiae) Neuroepithelial cell transforming gene 1 Forkhead box O1 Malignant T cell amplified sequence 1 RAN, member RAS oncogene family Forkhead box E3 Calneuron 1

0.16 −0.21 0.26 −0.55 −0.55 0.10 0.05 −0.13 −1.38 −0.11 −0.40 −0.19 0.22 −0.51 0.19 −0.36 −0.15 −0.92 1.21

0.16 −0.21 0.26 −0.55 −0.55 0.10 0.05 −0.13 −1.38 −0.11 −0.40 −0.19 0.22 −0.51 0.19 −0.36 −0.15 −0.92 1.21

−0.31 −0.63 0.74 −0.08 0.59 −0.08 0.42 −0.18 −0.77 0.68 −0.73 0.15 −0.19 0.15 0.16 −0.97 0.57 −0.39 −0.08

0.38 0.08 0.26 −0.89 0.02 −0.76 0.36 −2.16 −1.03 −0.23 −0.51 0.36 0.42 0.16 0.09 −0.81 −1.31 −0.16 −0.21

0.43 1.26 0.50 −0.34 0.17 0.06 −1.04 −0.01 −0.44 −0.16 −0.14 0.78 0.29 0.61 0.99 −0.58 0.81 −0.94 0.31

−0.74 0.13 0.07 −0.08 0.27 −0.32 0.52 −0.11 −0.90 0.06 −0.63 −0.42 −0.60 0.30 0.34 −1.43 0.78 −0.55 −0.47

−0.30 −0.38 −0.20 0.03 −0.10 0.07 −0.59 0.59 −0.47 −0.32 −0.94 −0.49

−0.30 0.27 −0.20 0.03 0.37 0.07 −0.59 0.59 −0.47 −0.32 −0.94 −0.49

−0.29 0.06 1.70 0.26 0.52 0.76 0.02 0.26 −0.88 1.07 −0.16 −0.64

0.77 −1.89 0.41 0.15 0.46 −0.29 −0.43 0.79 −0.18 0.20 −0.57 −0.81

0.29 −0.49 0.21 0.77 0.58 0.30 −0.87 0.08 −0.81 0.63 0.12 −0.25

0.55 0.38 0.12 0.04 0.51 −0.12 0.04 0.07 −0.91 0.29 0.60 −0.95

Heat shock protein 1 (chaperonin) Endoplasmic reticulum (ER) to nucleus signalling 1 Heat shock protein 4 Homocysteine-inducible, endoplasmic reticulum stress-inducible, ubiquitin-like domain member 1 DNA-damage inducible transcript 3 Tumor rejection antigen gp96 Serine (or cysteine) proteinase inhibitor, clade H, member 1 Heat shock factor 2 Heat shock protein 8 DnaJ (Hsp40) homolog, subfamily B, member 1 Heat shock protein 1

−0.07 −0.13 −0.19 0.90

−0.07 −0.13 −0.19 0.90

0.82 1.73 0.80 1.60

0.01 −1.14 −0.11 0.95

0.12 −0.77 −0.04 0.35

0.02 1.13 −0.38 −0.09

0.06 −0.05 0.12 0.47 0.19 −0.10 −0.55

0.06 −0.05 0.12 0.47 0.19 −0.10 −0.55

2.52 1.09 0.22 −0.15 1.54 1.43 1.00

0.31 0.18 −0.59 −1.31 −0.80 −0.55 0.68

−0.03 0.29 0.75 −1.46 −0.57 0.38 −0.15

0.16 0.05 0.32 0.72 −1.31 −0.26 0.44

Cytokine and chemokine-mediated signaling pathway Il1r2 Interleukin 1 receptor, type II NM 010555 Il23a Interleukin 23, alpha subunit p19 NM 031252 Il6ra Interleukin 6 receptor, alpha NM 010559 NM 007780 Csf2rb1 Colony stimulating factor 2 receptor, beta 1, low-affinity (granulocyte-macrophage) Traip TRAF-interacting protein NM 011634 NM 007395 Acvr1b Activin A receptor, type 1B NM 008493 Lep Leptin NM 008355 Il13 Interleukin 13

Cell cycle NM 010628 NM 007633 NM 009774 NM 134115 NM 148945 NM 011385 NM 009990 AK054482 NM 173169 BC005534 NM 010544 NM 019392 NM 011653 BC039953 NM 009074 NM 008569 NM 177270 NM 181542 NM 010658 NM 010407 NM 010629 NM 016776 AK021062 NM 010197 NM 011958 NM 019671 NM 019739 NM 026902 NM 009391 NM 015758 NM 021371

Kif9 Ccne1 Bub3 Stk38 Rps6ka3 Ski Cyln2 Rbms2 Plk4 Ccng1 Ihh Tyro3 Tuba1 Src Mst1r Anapc1 Cdkl2 Slfn10 Mafb Hck Kifap3 Mybbp1a Fgf3 Fgf1 Orc4l Net1 Foxo1 Mcts1 Ran Foxe3 Caln1

Response to unfolded protein HSPD1 NM 010477 ERN1 NM 023913 HSPA4 NM 008300 HERPUD1 NM 022331 NM 007837 NM 011631 NM 009825 NM 008297 AK004608 NM 018808 BC018257

DDIT3 TRA1 SERPINH1 HSF2 HSPA8 DNAJB1 HSPB1

a Characteristically upregulated or downregulated genes, of which expression changes greater than 1.5-fold with respect to the mean intensity of the time-matched control groups. Data represent fold-changes on log 2 scale compared to corresponding vehicle control.

M.-H. Lee et al. / Toxicology 249 (2008) 75–84

4.3. Gene expression changes associated with biological and pharmacological function of MTX MTX treatment altered the expression of genes involved in diverse biological processes, which may be related to the known pharmacological effects of MTX such as its anti-inflammatory, immunosuppressive and anti-proliferative effects (Table 3 and Supplementary Table 2). First, “immunity and defense” and related terms such as “cytokine/chemokine-mediated immunity”, and “cytokine and chemokine-mediated signaling pathway” may be related to the potent immunosuppressive properties of MTX (Swierkot and Szechinski, 2006). In particular, expression of genes for cytokine receptors such as Ccrl2, Cxcr6, Il1r2, and Il6ra, were altered significantly, suggesting a potential effect of the specific cytokine pathways in the liver during MTX treatment (Table 3). This result may be relevant with a recent microarray study showing that an activation of inflammatory pathways is present at a very early stage of human liver steatosis, even if no morphological sign of inflammation was observed (Chiappini et al., 2006). MTX also affected the expression of genes associated with “cell cycle” and “cellular proliferation”. MTX treatment significantly altered the expression of Ccne1 and Ccng1, whose products play a role in cell cycle progression and tumor proliferation (Jensen et al., 2003; Geng et al., 2007). This result agrees with the observation that MTX-induced cell cycle arrest occurs at S or G2 phase (Gorczyca et al., 1992). In addition, expression of Stk38, Cdkl2 and Plk4, whose products are protein kinases that regulated a wide range of cellular processes involved in cell proliferation and differentiation (Ko et al., 2005), was downregulated in the early phase. Together, these gene expression pattern changes may induce the known anti-proliferative effects of MTX. Interestingly, the terms “response to unfolded protein” were significantly overrepresented in the MTX-responsive genes. One of the most representative factors for this biological process could be heat shock proteins (HSPs), which are generated after exposure to biological stress such as heat (Lindquist and Craig, 1988). We found that MTX treatment significantly altered the expression of the genes Hspb1, Hspd1, Hsf2, Hspa4 and Hspa8. These alterations may be related to the antiproliferative properties of MTX because a transient increase in the expression of Hspb1 mRNA is associated with inhibition of cellular proliferation (Shakoori et al., 1992). Our results are consistent with a recent finding that MTX increases prostaglandin D2 -stimulated Hspb1 induction (Yoshida et al., 2004). In summary, we used oligonucleotide microarrays to identify and profile the expression of genes in mouse liver after MTX treatment. We found that MTX regulated genes are important in the biosynthesis of fatty acid, fatty acid ␤-oxidation and lipid transport. Although the contributions of individual genes to the MTX-induced fatty liver require further investigation, this study provides a significant understanding into the mechanisms underlying MTX-mediated hepatotoxicity. Further comprehensive analysis of the gene expression profiles associated with hepatic steatosis may be a useful tool for identifying potential hepatotoxicants. Acknowledgments This work was supported by Korea Food and Drug Administration grant (KFDA-05122-TGP-584), the SRC/ERC program of MOST/KOSEF (R11-2007-107-01001-0) and the Ministry of Education as The Brain Korea 21 Project. Appendix A. Supplementary data Supplementary data associated with this article can be found, in the online version, at doi:10.1016/j.tox.2008.04.011.

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