DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 DMD FastThis Forward.article has not Published been copyedited on and October formatted. 12, The 2011final version as doi:10.1124/dmd.111.042028 may differ from this version. DMD #42028

TITLE PAGE

Inter-individual variability in gene expression profiles in human hepatocytes and comparison with HepaRG cells

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Alexandra ROGUE, Carine LAMBERT, Catherine SPIRE, Nancy CLAUDE and André GUILLOUZO

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UMR INSERM U991, Faculté des Sciences Pharmaceutiques et Biologiques, Rennes, France (AR, CL, AG) ; Université de Rennes 1, Rennes, France (AR, CL, AG) ; Biologie Servier, Gidy, France (AR, CS) and Institut de Recherches Servier, Courbevoie, France (NC)

at ASPET Journals on October 4, 2021

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Copyright 2011 by the American Society for Pharmacology and Experimental Therapeutics. DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028

Running title page

Running title: Inter-donor gene expression in human hepatocytes

Corresponding authors :Prof. Andre Guillouzo, INSERM U991, Faculté de Pharmacie, 2 avenue L. Bernard, 35043 Rennes Cedex, France ; Phone: +33 2 23234391 ; Fax: +33 2 23 53 86 ; Email address : [email protected] or Dr. Catherine Spire, Drug Safety Assessment, Biologie Servier, 905 route de Saran, 45520 Gidy, France ; Phone: +33 2 38238613; Email :address:[email protected] Downloaded from

Number of text pages: 23 dmd.aspetjournals.org

Number of tables: 2

Number of figures: 2

Number of references: 28 at ASPET Journals on October 4, 2021

Number of words in the:

− Abstract: 235

− Introduction: 405

− Discussion: 1337

Supplemental data: Tables: 5

Figures: 3

The abbreviations used are: CAR, constitutive androstane receptor; CYP, cytochrome P450; DMSO, dimethylsulfoxide; FCS, fetal calf serum; FXR, farnesoid X receptor, GST, glutathione transferase; PPAR, peroxisome proliferator-activated receptor, RT-qPCR, reverse transcriptase-quantitative polymerase chain reaction; UGT, UDP-glucuronosyl transferase.

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Abstract

Inter-individual variations in functions, other than drug metabolism activity, remain poorly elucidated in human liver. In the present study, the whole transcriptome of several human hepatocyte populations and the differentiated human HepaRG cell line have been analyzed and compared, using oligonucleotide pangenomic microarrays. We show that, while the variation in the percentages of expressed genes did not exceed 14% between the primary human hepatocyte populations, huge inter-individual differences in the transcript levels of many genes were observed. Variable genes were related to various functions; in addition to drug metabolism, they mainly concerned carbohydrate, amino acid and lipid metabolisms. Downloaded from HepaRG cells expressed from 81 to 92% of the genes active in human hepatocytes and in addition, a specific gene subset mainly related to their transformed status, some chromosomal abnormalities and the presence of primitive biliary epithelial cells. Interestingly, a relationship dmd.aspetjournals.org was evidenced between abnormal basal expression levels of some target genes and their corresponding previously reported fold changes in one out of four human hepatocyte populations treated with the hepatotoxic drug troglitazone and not with other non-hepatotoxic peroxisome proliferator-activated receptor agonists (Rogue et al., 2011). Taken altogether, our at ASPET Journals on October 4, 2021 results support the view that HepaRG cells express most of the genes active in primary human hepatocytes and show that expression of most human hepatic genes can quantitatively greatly vary between individuals, thereby contributing to explain the huge inter-individual variability in susceptibility to drugs and other environmental factors.

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Introduction

The liver performs major functions of the organism, which include uptake of amino acid, lipids, carbohydrate and vitamins, and their subsequent storage, conversion and release into the blood and bile. This organ is also the principal target involved in the biotransformation of chemicals with its capacity to convert hydrophobic compounds into water-soluble products that can be secreted readily from the body. A number of drugs and other xenobiotics are potentially hepatotoxic either directly or more frequently after biological activation leading to the formation of chemically reactive metabolites or generation of reactive oxygen species. Drug-induced liver injury is broadly classified into intrinsic and idiosyncratic types. While the Downloaded from former is dose-dependent and predictable the latter is not directly dose-dependent, unpredictable and occurs in rare patients only. Various genetic and non-genetic factors are thought to cause predisposition to idiosyncratic drug-induced liver injury that accounts for the majority of hepatotoxicity associated with medication use, probably by altering the expression dmd.aspetjournals.org level of target genes. Over 1000 drugs and herbal products have been reported to cause this type of liver injury (Biour et al., 2004; Stickel et al., 2005). There are presently no suitable preclinical models to study idiosyncratic drug-induced liver injury. at ASPET Journals on October 4, 2021 A large inter-individual variability has long been observed in the expression and corresponding activities of many genes related to drug metabolism and drug induction in either human liver or primary human hepatocytes (Morel et al., 1990; LeCluyse et al., 2000; Madan et al., 2003). These results have been confirmed and extended by analysing responses to chemicals across the entire transcriptome in primary human hepatocytes (Liguori et al., 2005; Goyak et al., 2008; Lambert et al., 2009; Rogue et al., 2011). By contrast, although a variety of genes related to other hepatic functions can be the target of hepatotoxic drugs, much less information exists about inter-individual variability in their basal expression.

In the present study we compared the whole transcriptome of six human hepatocyte populations in primary culture and human differentiated HepaRG cells. Recent studies using whole genome microarrays have indeed confirmed the great similarity between primary human hepatocytes and HepaRG cells in the responsiveness of genes related to chemical metabolism (Jennen et al., 2010; Lambert et al., 2009). We show that, whereas variations in the percentages of expressed genes were low, huge inter-individual differences in the transcripts levels were observed between the primary human hepatocyte populations and that HepaRG cells expressed most of the genes active in human hepatocytes.

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Material and methods

Chemicals. Williams' E medium was supplied by Eurobio (Les Ulis, France) and fetal calf serum (FCS) by Perbio (Brebieres, France). All other chemicals were of the highest quality available.

Primary human hepatocytes. Human hepatocytes from 6 adult donors undergoing resection for primary and secondary tumors, were provided by Biopredic International (Rennes, France) (Supplemental Table 1). They were obtained by collagenase perfusion of histologically normal liver fragments and freshly seeded at a density of 17×104 cells/cm2 in 6-well dishes in a Williams' E medium supplemented with 10% FCS, 100 units/μl penicillin, 100 μg/ml Downloaded from streptomycin, 1 μg/ml insulin, 2 mM glutamine and 1 μg/ml bovine serum albumin. The medium was discarded 12h after seeding and cells were thereafter maintained in serum-free medium supplemented with 10–7 M hydrocortisone hemisuccinate. dmd.aspetjournals.org

HepaRG cells. The cells were obtained from Biopredic International at passages 14 and 16. For the present studies, they were first seeded at a density of 2.6×104 cells/cm2 in 6-well dishes in a Williams' E medium supplemented with 10% FCS, 100 units/µl penicillin, 100 −5 μg/ml streptomycin, 5 μg/ml insulin, 2 mM glutamine and 5×10 M hydrocortisone at ASPET Journals on October 4, 2021 hemisuccinate. After two weeks of culture, they were shifted to the same culture medium supplemented with 2% dimethylsulfoxide (DMSO) for two further weeks in order to reach maximum functional activities. Media were renewed every 2–3 days. Differentiated HepaRG cell cultures were composed of both hepatocyte-like and biliary epithelial-like cells (about 50% of each type) (Cerec et al., 2007).

RNA isolation. Primary human hepatocytes (after 48 h of culture) and differentiated HepaRG cells (after 20 h of incubation in a medium deprived of DMSO) were harvested in lysis buffer (RLT buffer and β-mercaptoethanol). Total RNA was isolated using the RNeasy mini Kit (Qiagen, Venlo, Netherlands). RNA quantity and purity were assessed with a Nanodrop ND- 1000 spectrophotometer (Nyxor Biotech, Paris, France) and RNA integrity was checked on a Bioanalyzer 2100 (Agilent Technologies, Massy, France).

Microarray hybridizations. Five hundred ng of total RNA from each cell culture sample were separately reverse-transcribed into double-strand cDNAs by the Moloney murine leukaemia virus reverse transcriptase and amplified for 2h at 40 °C using the Quick Amplification Labeling Kit (Agilent). The cDNAs were then transcribed into antisense cRNA

5 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028 and labelled with either CTP-Cy3 fluorescent dye for 2h at 40°C following the manufacturer's protocol. Cyanine-labeled cRNAs were purified using RNeasy minikit (Qiagen). cRNAs were hybridized onto 4×44K Agilent Gene chip human genome Microarrays (G4112F) according to standard Agilent protocols. Human hepatocyte and HepaRG cell samples were hybridized separately but all samples of each model were hybridized simultaneously. Data analyses were performed using Rosetta Resolver v.7.0 software (Rosetta Biosoftware, Seattle, WA) for database management, quality control and analysis. All microarray data reported in this study complied with MIAME guidelines (Brazma et al., 2001). Data storage and analyses were performed using the Rosetta Resolver v.6.0 software (Rosetta Biosoftware, Seattle, WA) for

database management, quality control and analysis. Ingenuity Pathways Analysis (IPA) and Downloaded from David analysis were used to identify relevant relationships, interactions, and pathways from normalized data or selected profiles from exploratory or statistical methods. Microarray data have been deposited in GEO (http://www.ncbi.nlm.nih.gov/geo/). dmd.aspetjournals.org

RT-qPCR analysis. Transcripts of some genes were also estimated by quantitative PCR in order to confirm microarrays results. Briefly, 500 ng of total RNA was reverse-transcribed into cDNA using the High-Capacity cDNA Archive kit (Applied Biosystems, Foster City,

CA). RT-qPCR was performed by the fluorescent dye SYBR Green methodology using the at ASPET Journals on October 4, 2021 SYBR Green PCR Master Mix (Applied Biosystems) and the STEP one Plus (Applied Biosystems). Primer pairs for each transcript were chosen with qPrimer depot software (http://primerdepot.nci.nih.gov/). Amplification curves were read with the StepOne software V2.1 (Applied Biosystems) using the comparative cycle threshold method. The relative quantification of the steady-state mRNA levels was normalized against 18S mRNA.

Statistical analysis and filtering Normalization algorithms and background subtractions were automatically applied to each array to reduce systematic errors and to adjust effects due to technical rather than biological variations using Feature Extraction® and Resolver® softwares. Expressed genes (at the Entrez Gene level) were extracted from the normalized data (intensity>200 and pv<0.01). All gene sets on the arrays were included for correlation analysis. A Pearson correlation coefficient, noted r, was calculated for each hepatocyte donor versus the five other donors and for each donor versus HepaRG cells. Principal component analysis (PCA) and hierarchical clustering using the Euclidian distance associated to the ward’s min variance link heuristic criteria were performed to visualize behavior of data through the different human hepatocyte populations and HepaRG cells. One-way ANOVA (with the Benjamini & Hochberg correction, FDR=1 %, p<0.01) following by a Tukey

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Kramer test (p<0.01) were performed to evidence significant differences between human hepatocytes from all the donors as well as between hepatocyte populations and HepaRG cells.

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Results

Correlation coefficients between primary human hepatocytes and HepaRG cells A total of 45520 probe sets corresponding to 20235 genes were present on each array. The presence of control probes and several probes which matched with only one gene explained these differences. The 20235 gene set was used for all transcriptomic analyses. To assess the magnitude of variation between hepatocyte cultures from the six donors across the entire transcriptome, correlation coefficients were compared and used as a global measure of similarity between donors as well as between donors and HepaRG cells. A similarity matrix was constructed for each pairwise of any two sets of the data and the Pearson correlation Downloaded from coefficient (r) was used to represent the strength of the linear relationship between any two sets of variable (Table 1A). The correlation coefficients were relatively high and ranged from

0.88 to 0.95. The highest r value of 0.95 was observed between donors #1 and #3 and the dmd.aspetjournals.org lowest of 0.88 between donors #4 and #5 or #6. The biological replicates of HepaRG cells, corresponding to 2 different passages, which were combined together, showed close and high correlation coefficients between 0.86 and 0.88 with the 6 human hepatocyte populations. The highest r value was obtained with donors #2, #3 and #6 and the lowest with donor #1. at ASPET Journals on October 4, 2021

Hierarchical clustering and principal component analysis All gene sets from the six human hepatocyte populations and HepaRG cells were subjected to hierarchical clustering and PCA (Figure 1). Both clustering and PCA representations showed that donors #5 and #6 were separated from the four other donors according to the principal component one on the PCA and with a distance of 0.65 on the cluster. Moreover, with a distance of 0.94, donors #3 and #4 grouped closer than with the others (Figure 1A). Both representations showed that gene expression profiles of HepaRG cells grouped separately from all human hepatocyte populations. As shown by PCA, HepaRG cells and human hepatocyte populations separated according to the principal component one whereas each human hepatocyte population separated from others according to the principal component two (Figure 1B). On the dendrogram, the distance between HepaRG cells and primary human hepatocyte populations was equal to 0.5. Noticeably, HepaRG cells clustered more closely with donors #5 and #6 than with the other donors.

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Numbers of expressed genes Only genes exhibiting an intensity signal superior to 200 associated with a p-value <0.01 were considered to be expressed in primary human hepatocytes and HepaRG cells (Table 1B). Indeed, this cut-off removed most of the non-hepatic genes. Moreover, since HepaRG cells are derived from a liver tumor of a female patient, we looked for expression of genes known to be located on chromosome Y. However, numerous genes located on this chromosome are also found on other chromosomes, e.g. Interleukin 9 Receptor (IL9R) and CD99, and were, as expected, also expressed in HepaRG cells. Nevertheless, few genes were not expressed in HepaRG cells or in hepatocytes from the unique female patient (donor #6). One example was

the Dead box protein 3, Y linked (DDX3Y) gene whose intensity signal was much lower than Downloaded from the background signal (Figure 2A).

The total number of genes expressed in human hepatocytes varied from 8335 to 9501 genes

depending on the donor (Table 1B). A maximum variation of 14% was observed between dmd.aspetjournals.org donors #1 and #2. The number of genes commonly expressed between donors for pairwise comparison of any two sets of the data varied from 7842 and 9030 genes (Table 2C). Noticeably, 7780 genes were common to the 6 donors, whereas 10095 genes were expressed

in at least one donor. at ASPET Journals on October 4, 2021

The number of genes expressed in HepaRG cells was analyzed at two different passages; it reached 11888 and 12036 genes at passages 14 and 16, respectively. Among them, 11691 were common (Table 1B). Comparison of the numbers of genes expressed in human hepatocytes revealed that 8168 to 9262 genes were expressed in common in at least one human hepatocyte donor and HepaRG cells, representing 81 to 92 % of the total genes expressed in at least one human hepatocyte donor (Table 1C).

Gene expression analysis across human hepatocyte donors An ANOVA statistical analysis followed by a PostHoc Tuckey Kramer test was performed in order to identify the genes statistically differentially expressed between hepatocytes from the 6 donors (Table 1D). Their number varied between 298 and 2099. The lowest and the highest variations were observed between donors #1 and #3 and donors #1 and #6 respectively. The statistically differentially expressed genes included genes expressed at different levels between donors as well as genes expressed only in some donors. Most of them were involved in drug, carbohydrate, amino acid and lipid metabolisms; those related to metabolism of drugs and/or endogenous and other exogenous substances exhibiting the largest inter-individual

9 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028 variability. Thus, genes involved in phase I drug biotransformation such as CYP2A6, CYP3A4 and CYP2E1, were markedly differentially expressed between all donors. The lowest expression values of these genes were usually found in donors #5 and #6. As an example, CYP3A4 was 31-fold less expressed in donor #6 than in donor #1. Other CYPs, such as CYP2D6, CYP1A2 and CYP2C19, were also expressed in all six donors with expression levels similarly lower in donors #5 and #6 than in others (Supplemental Table 2). Noteworthy, the prototypical nuclear receptor, the constitutive androstane receptor gene (CAR also known as NR1I3), was more expressed in donors #1, #2, #3 and #4 (Supplemental Table 2). Likewise, the CAR-dependent responsive gene, CYP2C9, was much more expressed in

donors #1 to #4 than in donors #5 and #6 (Supplemental Figure 1). Downloaded from Expression of many genes encoding various phase II conjugating enzymes, including several UDP-glucuronosyltransferases (UGT), such as UGT2A3 and UGT2B10, and glutathione S- transferases (GST), such as GSTA1 and GSTA2, also markedly varied from one donor to dmd.aspetjournals.org another. Moreover, GSTM1, which is known to be expressed in only 50% of the individuals, was not detected in 2 out of the 6 donors (i.e. donors #1 and #3). Various transporters were also differentially expressed across the donors; they included multidrug resistance protein (MDR) 1, multi-drug resistance associated protein (MRP) 3 and 4, and ATP binding cassette at ASPET Journals on October 4, 2021 subfamily G member 5 (ABCG5). The bile salt efflux pump (BSEP also known as ABCB11) was detected in donor #1 only. Interestingly, CYP7A1 as well as ABCG5, both involved in cholesterol metabolism, were dramatically expressed in donor #1. By contrast, CYP8B1 was expressed at similar levels in all hepatocyte populations (Supplemental Table 2). Most genes involved in other hepatic functions, such as carbohydrate and lipid metabolisms, and the urea cycle, were less differentially expressed between primary human hepatocyte populations than those related to xenobiotic metabolism. Nevertheless, few genes involved in carbohydrate [glucose-6-phosphatase (G6Pc), glycogen synthase 2 (GYS-2), hexokinase 1 (HK-1), phosphoenolpyruvate carboxykinase 2 (PCK2)], lipid [(stearoyl-CoA desaturase (SCD), CYP4A11, lipoprotein lipase (LPL), acyl-CoA dehydrogenase (ACADS)] and amino acid [4-aminobutyrate aminotransferase (ABAT), glutaminase 2 (GLS2)] metabolisms were expressed at quite variable levels across the donors (Figure 2 and Supplemental Table 2). Noticeably, most genes related to peroxisome proliferator-activated receptors (PPARs) or the farnesoid X receptor (FXR), which are nuclear receptors involved in some major hepatic functions, also showed large inter-individual variability in their expression levels, as for example apolipoprotein C3 (APOC3) which was less expressed in donors #5 and #6 (Supplemental Figure 1).

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Gene expression analysis between hepatocyte donors and HepaRG cells Venn diagrams showed that 9754 genes were expressed in at least one hepatocyte donor while 2887 genes were expressed in HepaRG cells only and 341genes in HepaRG cells and at least one human hepatocyte population (Supplemental Figure 2). This indicates that 96% and 78% of the genes expressed in at least one human hepatocyte population and HepaRG cells respectively, were in common. These values corresponded to 7618 genes expressed in all hepatocyte populations and HepaRG cells, 162 in hepatocyte populations only and 4587 in HepaRG cells only. Many genes involved in phase I drug metabolism, such as CYP2C9, were

expressed at comparable levels in both HepaRG cells and the majority of hepatocyte donors. Downloaded from However, a number of genes exhibited large quantitative variations in their expression levels between the two cell models. Thus, 3356 and 1532 genes were respectively at least 2-fold more or less expressed in HepaRG cells compared to all primary human hepatocyte dmd.aspetjournals.org populations. These genes usually corresponded with those extracted from the loading plot (Supplemental Figure 3 and supplemental Table 4) and responsible for the discrimination between the two cell models. A great number of genes involved in DNA repair and the cell cycle were always more expressed in HepaRG cells while genes involved in xenobiotic at ASPET Journals on October 4, 2021 metabolism, complement and coagulation cascade and inflammatory processes, were frequently expressed at higher levels in primary hepatocytes. The less expressed xenobiotic- related genes in HepaRG cells included genes encoding some CYPs (e.g. CYP2D6, CYP2E1), conjugating enzymes (e.g. GSTP1, UGT1A6) and membrane transporters involved in excretion of endogenous and/or exogenous compounds (e.g. ABCG5). However, ABCB11 (BSEP) and ABCB4 (MDR3), two genes encoding bile acid transporters, were at least 1.5- and 3-fold more expressed in HepaRG cells than in human and 341 hepatocytes, with the exception of donor #1. The basolateral transporter ABCC3 (MRP3) was also much more expressed in HepaRG cells than in human hepatocytes. Less than 350 genes expressed in at least one human hepatocyte population were not detected in HepaRG cells; they included some phases I and II genes, such as CYP2C18, GSTP1 and GSTM3 (Supplemental Tables 2 and 3). Importantly, HepaRG cells expressed 29% more genes than the human hepatocyte populations, in particular genes involved in the cell cycle, such as cyclin B1 (CCNB1), cyclin D1 (CCND1), cell division cycle (CDC) 2 and 6, as well as genes involved in focal adhesion and transcriptional activity, such as signal transducer and activator of transcription 3

(STAT3), deleted in polyposis 1 (DP1) and inhibitor of DNA binding 1 (ID1) (Figure 2).

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Since these transformed cells exhibit a trisomic chromosome 7 (Gripon et al., 2002) we examined whether some of the genes located on chromosome 7 were selectively expressed. Among the 1500 genes located on this chromosome approximately 110 genes, including IL6, carnitine O-octanoyltransferase (CROT) and SLC25A40, were found to be expressed in HepaRG cells only (Table S3). Interestingly, the cytokeratin 19 (KRT19), known as a stemness and biliary cell marker, was dramatically more expressed in HepaRG cells than in human hepatocytes (Figure 2). Another biliary cell marker, the α6-integrin (Couvelard et al., 1998), was expressed in both HepaRG cells and human hepatocytes but was 2-fold higher in the former. Downloaded from Is a basal gene expression level predictable of an unusual response to a hepatotoxic drug? To date, gene expression changes induced by chemicals have been mostly focused on genes

related to xenobiotic metabolism and inter-individual responses were found to be more dmd.aspetjournals.org variable than were the corresponding global basal gene expression profiles (Goyak et al., 2008; Rakhshandehroo et al., 2009; Rogue et al., 2011). Moreover, a higher induction level was frequently observed for CYPs with a low basal expression or activity (Guillouzo and

Guguen-Guillouzo, 2008). We postulated that an abnormal basal expression of some target at ASPET Journals on October 4, 2021 genes could lead to an abnormal response to a hepatotoxic drug in some patients and could help to explain an idiosyncratic toxicity. Four out of the six human hepatocyte populations analysed in the present study have been previously used to investigate changes in the transcriptome profiles induced by four PPAR agonists, e.g. two glitazones (troglitazone and rosiglitazone) and two glitazars (muraglitazar and tesaglitazar) (Rogue et al., 2011). Comparison of basal expression levels of target and non target genes (this study) and their PPAR-induced fold changes in the same culture conditions, showed that basal gene expression levels could greatly influence the level of response to the treatment, particularly with the hepatotoxic drug troglitazone (Table 2). For instance, pyruvate dehydrogenase kinase isozyme 4 (PDK4), an enzyme involved in fatty acid and glucose oxidation, was up- and down-regulated with 20 µM troglitazone in the two hepatocyte populations which had the lowest and the highest basal expression levels respectively. Similarly, CYP7A1, implicated in bile synthesis, as well as BSEP and ABCG5, both involved in bile acid secretion, showed 8.6- , 2.5- and 1.5-fold decrease respectively, with troglitazone, that has been reported to cause cholestasis, in donor #4 hepatocytes which had the highest gene expression levels. In addition, the heme oxygenase 1 gene (HMOX1) involved in oxidative stress and inflammation,

12 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028 frequently associated with cholestasis, was also highly induced by troglitazone treatment (9.7- fold) in the same donor #4, which had the lowest basal gene expression. No such strong relationships between basal transcript levels of target genes and their drug-induced fold changes were evidenced with the three other hepatocyte populations treated with troglitazone or with the four hepatocyte populations treated either with rosiglitazone which has caused only very rare cases of hepatotoxicity or with the two glitazars which have induced only non- hepatic toxicities. No obvious relationship between basal transcript levels of target genes and their drug-induced fold changes was also observed in HepaRG cells treated with either troglitazone or the three other PPAR agonists (Table 2).

Downloaded from Comparative microarray and qPCR data Microarray and qPCR results were compared for several genes in each hepatocyte population (Supplemental Table 5). The direction of change obtained by q-PCR was similar to that dmd.aspetjournals.org observed with microarrays for each analysis. Thus, donors #5 and #6 generally exhibited the lowest basal gene expression levels, as illustrated for CYP3A4, CYP2B6 and CAR.

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Discussion

In the present study, we report the first analysis of the genome-wide expression profiles of human hepatocytes from several donors and the differentiated human HepaRG cell line. Based on a cut-off intensity signal of 200 and a technical p-value < 0.01, 7780 out of 20232 genes present on the microarrays were found to be expressed in the 6 human hepatocyte populations analysed. These genes included both annotated and non annotated genes. If most human genes were represented on the microarrays, few important ones were however lacking, Downloaded from e.g. UGT1A1 (Lambert et al., 2009). Over the 7780 expressed genes, 86% were found in all donors. Accordingly, in agreement with previous observations (Goyak et al., 2008), relatively high correlation coefficient values (0.88 to 0.95) were found across primary human

hepatocytes from the six donors, especially between donors #1 and #3. Genes expressed in dmd.aspetjournals.org only some hepatocyte populations included the well-known polymorphic gene GSTM1 and the plasma membrane transporter BSEP. Similar observations have already been reported by measuring mRNA levels of various transporters by PCR (Jigorel et al., 2006). The choice to

use human liver samples or freshly isolated human hepatocytes would probably allow to at ASPET Journals on October 4, 2021 detect a few more active genes. Indeed, it is well established that when placed in culture, isolated hepatocytes exhibit early decrease in both transcriptional and translational activity of many genes, especially those encoding mature functions (Guillouzo and Guguen-Guillouzo, 2008). However, 2-day hepatocyte cultures, as used in the present study, are more representative of the conditions in which these cells are normally used in vitro.

In contrast with the low inter-individual qualitative differences not exceeding 14% in the 6 tested human hepatocyte populations, huge variations were observed in the transcript levels of a number of genes, especially among those related to drug, carbohydrate, amino-acid and lipid metabolisms. Indeed, many genes involved in xenobiotic metabolism, such as CYP1A2, CYP2C9, CYP2C19, CYP2D6, CYP2E1, CYP3A4, GSTT1 and UGT2B7, were highly differentially expressed across individuals particularly between donors #5 and #6. It is well established that both donor characteristics (genetic polymorphism, disease, drug treatments) and culture conditions can greatly influence in vitro gene expression (Guguen-Guillouzo and Guillouzo, 2010 ; Russmann et al., 2010; Zhou et al., 2009). For instance, alterations of various human P450s have been reported in hepatocytes isolated from steatotic livers (Fisher et al., 2004; Gomez-Lechon et al., 2004). Noticeably, in the present study, high CAR

14 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028 expression levels were found in hepatocytes from 4 out of 6 donors, perhaps because of their isolation from a drug-treated and/or a diseased liver, which could explain high expression levels of CAR-responsive genes such as CYP3A4 in these cells.

HepaRG cells expressed from 81 to 92 % of the genes active in at least one human hepatocyte population with, in addition, a subset of 2887 genes. As previously reported from transcriptomic analysis of untreated and drug-treated HepaRG cells (Lambert et al., 2009; Hart et al., 2010), these cells exhibited a gene expression profile close to that of human hepatocytes, as demonstrated by hierarchical clustering, PCA and the global gene expression profile. Moreover, our data show that limited variations were evidenced when comparing Downloaded from different passages (number of deregulated genes, coefficient correlations, whole genome profiles) and that HepaRG cells appeared closer to certain human hepatocyte populations, especially donors #5 and #6 who exhibited low expression of several genes involved in

xenobiotic (CYP3A4, CYP2C9), lipid (ACADS) and carbohydrate (PCK2) metabolisms dmd.aspetjournals.org (Figure 2 and supplemental Table 2). These data, together with the responses to treatment with several tested drugs (Lambert et al., 2009; Rogue et al., 2011), suggest that HepaRG cells behave as a primary human hepatocyte population, and could be classified as an

“average human hepatocyte population” and used as such, to identify the major changes at ASPET Journals on October 4, 2021 induced by a given drug at the entire transcriptome level. Accordingly, after treatment with the PPAR agonists, HepaRG cells behave as the majority of human hepatocyte donors (Rogue et al., 2011). However, it must be borne in mind that genes encoding some phase I and phase II enzymes and membrane transporters were expressed at lower levels than in primary human hepatocytes from most donors and consequently, it cannot be excluded that metabolic pathways and toxic responses obtained with some drugs could not completely reflect data obtained with primary human hepatocytes. Moreover, the levels of expression and activity of various genes related to drug metabolism are dependent upon addition of DMSO to the culture medium; they can be greatly lower in the absence of DMSO as for example shown for CYP3A4 (Aninat et al., 2006; Kanebratt and Andersson, 2008). However, whether in the presence or absence of DMSO, drug-metabolizing enzyme activities and their responsiveness to prototypical inducers remained relatively stable in differentiated HepaRG cells for a prolonged period (Antherieu et al., 2010; Josse et al., 2008; Kanebratt and Andersson, 2008).

Nearly 2900 genes were expressed solely in HepaRG cells. Many of these genes were likely related to the transformed state of these cells and included genes usually expressed in cancerous and/or stem cells, as well as genes related to the cell cycle. Indeed, at any culture

15 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028 time a fraction of HepaRG cells was probably engaged in the cell cycle. In addition, HepaRG cell cultures were composed of both hepatocyte-like and bile epithelial-like cells (around 50% each), thereby explaining expression of some specific biliary cell markers such as cytokeratin 19 (Cerec et al., 2007). Moreover, HepaRG cells exhibit some karyotypic alterations consisting in a surnumerary and remodelled chromosome 7 and a translocation t(12;22) with a loss of the 12p fragment leading to a monosomy 12p (Gripon et al., 2002), which likely resulted in altered expression of a gene subset. The transformed phenotype of HepaRG cells could also lead to overexpression or repression of certain genes. Thus, as in HepG2 cells (Harris et al., 2004), STAT3, DP1 and ID1 were significantly overexpressed in HepaRG cells

compared to primary human hepatocytes. Interestingly, the absence of DDX3Y, selectively Downloaded from located on chromosome Y, indicated the female origin of the HepaRG cell line.

Noteworthy, a number of genes not related to drug metabolism also exhibited a marked inter-

individual variability. Since these are putative drug-target genes we compared basal dmd.aspetjournals.org expression levels of putative target and non target genes (this study) and corresponding fold changes induced by several PPAR agonists (Rogue et al., 2011) in the same four human hepatocyte populations and HepaRG cells. Basal expression levels of few target genes were

found to greatly influence their level of response to the treatment, particularly with at ASPET Journals on October 4, 2021 troglitazone, in one human hepatocyte population, as shown for PDK4, an enzyme involved in fatty acid and glucose oxidation, and CYP7A1, BSEP and ABCG5, implicated in bile acid synthesis and secretion (Table 2). Troglitazone was developed for the treatment of hyperglycemia and was withdrawn from the market for major liver damage, including cholestasis in few patients. Noteworthy, such a strong relationship between basal transcript levels and the extent of drug-induced deregulation of target genes was limited to one hepatocyte donor treated with troglitazone and not observed with the other PPAR agonists which have induced only rare non hepatic toxicities if any. These data support the view that comparative analysis of the magnitude of variation of basal and drug-induced expression of target genes in primary hepatocytes from several donors could help predicting drug-induced liver injury and that similar investigations deserve exploration with various hepatotoxic drugs.

In conclusion, the present transcriptomic study highlights the qualitative and especially quantitative inter-individual variability in gene expression profiles of human hepatocytes and the close resemblance in gene expression profiles between primary human hepatocytes and HepaRG cells. In addition, the relationship between abnormal basal expression and response of some target genes to treatment with the hepatotoxic troglitazone could reflect the variable

16 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028 susceptibility of humans to DILI and suggest that comparison of basal and drug-deregulated expression levels of target genes in primary hepatocytes from several donors deserves exploration with other idiosyncratic hepatotoxic drugs. Moreover, one may expected that the use of the new RNA and ChIP sequencing techniques will allow the elucidation of more precise information on basal and drug-induced gene expression profiles.

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Aknowledgements:

We thank Dr. Wynne Ellis for careful reading of the manuscript.

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dmd.aspetjournals.org

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Authorship Contributions.

Participated in research design: Rogue, Claude, Spire, Guillouzo Conducted experiments: Rogue Contributed new reagents or analytic tools: Rogue, Lambert, Spire. Performed data analysis: Rogue, Lambert, Spire Wrote or contributed to the writing of the manuscript: Rogue, Claude, Spire, Guillouzo.

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References

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hepatoma HepaRG cell line through bipotent progenitor. Hepatology 45:957-967. dmd.aspetjournals.org Couvelard A, Bringuier AF, Dauge MC, Nejjari M, Darai E, Benifla JL, Feldmann G, Henin D and Scoazec JY (1998) Expression of integrins during liver organogenesis in humans. Hepatology 27:839- 847. Fisher RA, Bu D, Thompson M, Wolfe L and Ritter JK (2004) Optimization of conditions for clinical human hepatocyte infusion. Cell Transplant 13:677-689. Gomez-Lechon MJ, Donato MT, Castell JV and Jover R (2004) Human hepatocytes in primary culture: at ASPET Journals on October 4, 2021 the choice to investigate drug metabolism in man. Curr Drug Metab 5:443-462. Goyak KM, Johnson MC, Strom SC and Omiecinski CJ (2008) Expression profiling of interindividual variability following xenobiotic exposures in primary human hepatocyte cultures. Toxicol Appl Pharmacol 231:216-224. Gripon P, Rumin S, Urban S, Le Seyec J, Glaise D, Cannie I, Guyomard C, Lucas J, Trepo C and Guguen- Guillouzo C (2002) Infection of a human hepatoma cell line by hepatitis B virus. Proc Natl Acad Sci U S A 99:15655-15660. Guguen-Guillouzo C and Guillouzo (2010) A General review on in vitro hepatocyte models and their applications. Methods Mol Biol 640:1-40. Guillouzo A and Guguen-Guillouzo C (2008) Evolving concepts in liver tissue modeling and implications for in vitro toxicology. Expert Opin Drug Metab Toxicol 4:1279-1294. Harris AJ, Dial SL and Casciano DA (2004) Comparison of basal gene expression profiles and effects of hepatocarcinogens on gene expression in cultured primary human hepatocytes and HepG2 cells. Mutat Res 549:79-99. Hart SN, Li Y, Nakamoto K, Subileau EA, Steen D and Zhong XB (2010) A comparison of whole genome gene expression profiles of HepaRG cells and HepG2 cells to primary human hepatocytes and human liver tissues. Drug Metab Dispos 38:988-994. Jennen DG, Magkoufopoulou C, Ketelslegers HB, van Herwijnen MH, Kleinjans JC and van Delft JH (2010) Comparison of HepG2 and HepaRG by whole-genome gene expression analysis for the purpose of chemical hazard identification. Toxicol Sci 115:66-79. Jigorel E, Le Vee M, Boursier-Neyret C, Parmentier Y and Fardel O (2006) Differential regulation of sinusoidal and canalicular hepatic drug transporter expression by xenobiotics activating drug- sensing receptors in primary human hepatocytes. Drug Metab Dispos 34:1756-1763.

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Josse R, Aninat C, Glaise D, Dumont J, Fessard V, Morel F, Poul JM, Guguen-Guillouzo C and Guillouzo A (2008) Long-term functional stability of human HepaRG hepatocytes and use for chronic toxicity and genotoxicity studies. Drug Metab Dispos 36:1111-1118. Kanebratt KP and Andersson TB (2008) HepaRG cells as an in vitro model for evaluation of cytochrome P450 induction in humans. Drug Metab Dispos 36:137-145. Lambert CB, Spire C, Claude N and Guillouzo A (2009) Dose- and time-dependent effects of phenobarbital on gene expression profiling in human hepatoma HepaRG cells. Toxicol Appl Pharmacol 234:345-360. LeCluyse E, Madan A, Hamilton G, Carroll K, DeHaan R and Parkinson A (2000) Expression and regulation of cytochrome P450 enzymes in primary cultures of human hepatocytes. J Biochem Mol Toxicol 14:177-188. Liguori MJ, Anderson MG, Bukofzer S, McKim J, Pregenzer JF, Retief J, Spear BB and Waring JF (2005) Microarray analysis in human hepatocytes suggests a mechanism for hepatotoxicity induced by trovafloxacin. Hepatology 41:177-186.

Madan A, Graham RA, Carroll KM, Mudra DR, Burton LA, Krueger LA, Downey AD, Czerwinski M, Downloaded from Forster J, Ribadeneira MD, Gan LS, LeCluyse EL, Zech K, Robertson P, Jr., Koch P, Antonian L, Wagner G, Yu L and Parkinson A (2003) Effects of prototypical microsomal enzyme inducers on cytochrome P450 expression in cultured human hepatocytes. Drug Metab Dispos 31:421- 431. Morel F, Beaune PH, Ratanasavanh D, Flinois JP, Yang CS, Guengerich FP and Guillouzo A (1990) dmd.aspetjournals.org Expression of cytochrome P-450 enzymes in cultured human hepatocytes. Eur J Biochem 191:437-444. Rakhshandehroo M, Hooiveld G, Muller M and Kersten S (2009) Comparative analysis of gene regulation by the transcription factor PPARalpha between mouse and human. PLoS One 4:e6796. Rogue A, Lambert CB, Josse R, Antherieu S, Spire C, Claude N and Guillouzo A (2011) Comparative gene expression profiles induced by PPARγ and PPARα/γ agonists in human hepatocytes. at ASPET Journals on October 4, 2021 PLoS One 6:e18816 Russmann S, Jetter A and Kullak-Ublick GA (2010) Pharmacogenetics of drug-induced liver injury. Hepatology 52:748-761. Stickel F, Patsenker E and Schuppan D (2005) Herbal hepatotoxicity. J Hepatol 43:901-910. Zhou SF, Liu JP and Chowbay B (2009) Polymorphism of human cytochrome P450 enzymes and its clinical impact. Drug Metab Rev 41:89-295.

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Footnote

Alexandra Rogue was a recipient of a CIFRE contract. This work was supported by the Servier Group and the EEC contract Predict-IV, number 20222. We thank the Biological Resources Centre of Rennes and Biopredic International for the supply of isolated human hepatocytes.

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Legends for figures

Figure 1: Two-dimensional hierarchical clustering and principal component analysis of gene expression profiles of primary human hepatocyte populations and HepaRG cells A: Two-dimensional hierarchical clustering of gene expression profiles of primary human hepatocyte populations and HepaRG cells.

The clustering was generated by using Resolver system software with an agglomerative algorithm Ward’s min variance link heuristic criteria and Euclidean distance metric (Intensity≥200 and p≤0.01). Two-dimensional clustering was performed on gene expression profiles obtained with the 6 primary human hepatocyte donors and HepaRG cells.

B: Principal component analysis of gene expression profiles in primary human hepatocyte Downloaded from populations and HepaRG cells.

Figure 2. Expression levels of few genes in the 6 primary human hepatocyte populations and the two HepaRG cell passages. dmd.aspetjournals.org Intensity values of various genes involved in xenobiotic, lipid and carbohydrate metabolisms, hepatic functions and miscellaneous in primary human hepatocytes (PHH) from the 6 donors and the two passages of HepaRG cells.

at ASPET Journals on October 4, 2021

23 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. DMD #42028

Tables Table 1: A similarity matrix of gene expression profiles of each pairwise comparison of primary human hepatocytes from 6 donors and HepaRG cells (A) and comparison of total (B), common (C) and differentially (D) expressed genes between primary human hepatocytes from 6 donors and HepaRG cells

A: Similarity matrix of gene expression profiles of each pairwise comparison of primary human hepatocytes from 6 donors and HepaRG cells

Donor #2 Donor #3 Donor #4 Donor #5 Donor #6 HepaRG Donor #1 0.94 0.95 0.89 0.93 0.91 0.86 Donor #2 0.93 0.89 0.93 0.93 0.88 Donor #3 0.89 0.92 0.92 0.88 Donor #4 0.88 0.88 0.87 Donor #5 0.93 0.87

Donor #6 0.88 Downloaded from The numbers in each column represent Pearson’s coefficient correlation r value.

B: Total numbers of genes expressed in the 6 human hepatocyte populations and HepaRG cell passages Donor or Passage number Expressed genes number Donor #1 8335 dmd.aspetjournals.org Donor #2 9501 Donor #3 9041 Donor #4 8918 Donor #5 9032 Donor #6 9396 HepaRG Passage 14 11888

HepaRG Passage 16 12036 at ASPET Journals on October 4, 2021 The values in each column represent the numbers of expressed genes (intensity≥200 with pv≤0.01).

C: Numbers of genes expressed in common between the 6 human hepatocyte populations and HepaRG cells Donor #2 Donor #3 Donor #4 Donor #5 Donor #6 HepaRG Donor #1 8238 8239 8101 7874 8098 8168 Donor #2 8880 8796 8733 9030 9262 Donor #3 8670 8462 8723 8860 Donor #4 8494 8698 8721 Donor #5 7842 8856 Donor #6 9197 The values in each column represent the numbers of genes expressed in common between each pairwise comparison.

D: Numbers of genes differentially expressed between the 6 human hepatocyte donors and HepaRG cells Donor #2 Donor #3 Donor #4 Donor #5 Donor #6 HepaRG Donor #1 933 298 541 1893 2099 3841 Donor #2 861 690 1312 1019 6376 Donor #3 468 1914 1716 6060 Donor #4 1435 1322 6517 Donor #5 761 6515 Donor #6 6699 The values in each column represent the number of differently expressed genes according to an ANOVA analysis following by a Tuckey Kramer postHoc test.

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Table 2 : Comparison of basal expression and fold modulation levels of target and non target genes in 4 human hepatocyte populations and in HepaRG cells treated or not with PPAR agonists This articlehasnotbeencopyeditedandformatted.Thefinalversionmaydifferfromthisversion. Basal gene expression Fold modulation with TRO Fold modulation with ROSI Fold modulation with MURA Fold modulation with TESA Donor Donor # Donor # Donor # HepaR Donor Donor Donor Donor HepaR Donor Donor Donor Donor HepaR Donor Donor Donor Donor HepaR Donor Donor Donor Dono HepaR

# 2 4 5 6 G cells # 2 # 4 # 5 # 6 G cells # 2 # 4 # 5 # 6 G cells # 2 # 4 # 5 # 6 G cells # 2 # 4 # 5 r # 6 G cells DMD FastForward.PublishedonOctober12,2011asDOI:10.1124/dmd.111.042028 ACADL 609 602 342 386 33 1.0 -1.7 1.0 -1.2 -1.2 -1.3 -1.1 -1.2 -1.3 -1.6 1.0 -1.2 1.0 1.1 -1.3 -1.1 -1.2 -1.1 1.1 -1.3 ACADS 499 564 241 428 35 2.7 2.9 1.1 1.2 1.3 1.0 1.1 -1.2 1.1 1.3 1.2 1.3 -1.1 -1.2 1.6 1.1 -1.2 -1.4 -1.6 1.7 ACOT12 3935 3086 1146 1538 134526 1.2 -1.6 1.1 1.2 -1.1 -1.1 -1.0 1.1 1.0 1.2 1.1 1.3 1.1 -1.2 -1.0 1.2 1.2 -1.1 1.0 1.8 ACOT2 13294 18468 13025 11174 10965 1.2 1.1 1.1 1.1 1.0 -1.3 1.1 -1.1 1.2 -1.0 1.4 1.7 -1.0 -1.1 1.2 1.6 1.5 -1.0 1.2 1.5 ACSL1 11507 18436 8491 8619 2180 -1.1 -1.9 1.3 1.7 1.5 1.4 2.7 1.8 2.3 1.8 2.2 4.3 2.9 2.3 1.8 2.2 3.6 2.2 2.8 2.5 ADH4 1880 3113 559 812 127 -4.2 -4.8 -1.0 -2.0 -1.8 -3.6 -3.3 -1.3 -2.5 -3.2 -3.6 -3.6 1.1 -1.7 -2.0 -4.2 -4.1 1.1 -1.7 -3.0 ADFP 3110 3474 2350 1281 19191 1.6 1.0 2.6 2.0 2.9 3.8 6.6 4.8 3.6 4.9 4.3 6.8 5.0 8.3 7.7 5.9 7.1 6.7 7.0 7.4 ANGPTL4 4734 3225 13651 8977 51129 1.3 2.0 1.6 2.7 1.9 12.7 3.6 2.0 4.0 3.9 6.8 6.1 4.1 2.7 6.9 9.6 9.8 3.6 4.2 7.0 APOA4 552 536 47 196 456 -1.3 -2.6 2.2 1.3 1.1 1.2 8.6 1.7 1.4 1.3 -1.6 -1.1 1.4 2.0 1.2 -1.1 -1.1 1.4 1.0 1.7 APOC3 92071 101537 31961 47656 345 -1.4 -1.1 -1.0 1.0 -1.2 1.3 -1.0 1.0 -1.1 -1.3 1.2 1.1 1.0 -1.0 -1.2 1.0 -1.0 1.2 -1.1 -1.1 AQP3 1902 2013 1993 2981 360 2.4 2.3 -1.1 -1.2 1.2 -1.4 -1.5 -1.8 1.1 -1.4 -1.2 1.6 -1.2 -1.6 -1.1 1.3 1.0 -1.9 -1.5 1.0 AQP7 2802 2582 1227 1720 364 -1.1 1.2 1.1 1.5 1.2 1.3 1.2 1.4 1.7 1.2 2.3 1.3 1.4 1.6 1.3 2.3 1.8 1.3 1.3 1.7 CPT1A 123 76 114 128 1374 1.5 1.7 1.7 2.6 1.2 4.6 2.8 1.7 3.0 1.7 4.8 5.9 3.5 3.7 2.2 3.6 4.0 2.8 2.5 2.3 CPT1B 150 116 172 163 1375 1.7 2.4 -1.1 -1.0 -1.1 1.5 -1.1 -1.0 -1.1 -1.3 1.2 1.2 -1.1 -1.5 -1.1 1.3 1.4 -1.6 -1.1 -1.2 CPT2 2544 2443 1328 1882 1376 2.3 1.8 1.6 2.6 1.3 2.2 1.6 1.4 2.7 1.4 2.3 2.6 1.9 2.8 1.6 1.5 2.4 1.7 2.5 1.9 CROT 159 118 88 56 54677 -2.4 -2.2 -1.7 -1.9 1.0 -1.4 1.0 -1.6 -1.6 1.1 -1.2 -1.2 -1.3 -2.0 -1.1 1.1 -1.2 -1.6 -1.6 -1.0 CRP 185 54 677 765 1401 1.1 -1.8 -1.0 1.2 1.6 1.5 1.4 -1.0 1.1 2.4 2.6 -1.5 -1.1 -1.0 2.2 1.6 1.5 -1.8 1.0 1.9 CYP2B6 15866 13449 15098 8823 1555 4.2 1.4 1.7 1.5 1.1 4.1 2.4 2.3 1.8 2.1 -1.0 -1.2 -1.3 -1.3 1.1 1.4 1.5 1.2 1.2 1.1 CYP3A4 65886 64170 3872 7344 1576 2.5 -1.2 2.6 5.5 3.3 2.6 1.1 3.1 4.7 14.9 -1.5 -1.3 -1.1 1.1 2.3 -1.4 -1.1 1.4 1.6 3.0 PPAR CYP4A11 329 299 68 82 1799 1.3 1.4 1.3 2.0 -1.4 2.0 2.8 1.9 2.3 -1.5 6.4 5.1 2.6 2.4 1.2 5.4 6.9 2.6 4.3 1.7 target CYP4B1 2 2 2 2 30666 1.1 1.1 3.1 -1.1 -1.2 1.1 -1.0 -1.0 -1.0 -2.5 1.1 1.1 1.0 1.1 -1.6 1.2 1.1 1.2 1.0 -1.7 genes CYP4F3 2491 2126 560 866 2313 -1.0 -1.3 1.4 1.1 -1.2 -1.3 -1.6 1.2 -1.6 -1.4 1.2 -2.9 1.2 -3.5 -1.1 1.1 1.4 -1.8 -1.6 -1.5 CYP4F22 25 13 9 13 2028 -2.4 -1.7 -1.1 1.1 -1.1 1.0 1.7 1.5 -1.1 1.3 -1.5 -1.5 -1.1 -1.2 -1.3 -1.5 -1.6 1.3 1.3 -1.2 CYP7A1 649 1472 85 10 3389 -3.5 -8.6 -1.5 -1.0 -4.2 -3.2 1.4 -4.1 1.3 -7.5 -3.0 -2.7 -2.9 1.2 -1.9 -3.3 -2.6 -2.4 -1.6 -5.5 ELOVL6 388 720 542 586 79071 1.8 1.8 1.3 1.6 -1.0 1.4 1.5 1.4 1.6 -1.0 1.2 1.1 1.9 1.8 -1.1 1.8 1.2 1.4 1.4 1.1 FABP1 33861 38334 17575 16961 2168 3.6 5.3 1.9 3.4 1.4 1.7 4.0 1.8 3.3 1.5 5.2 2.7 3.4 4.4 2.6 4.6 2.5 3.0 4.2 2.7 FGF21 239 99 59 141 26291 3.5 1.7 1.5 2.3 -1.1 2.1 1.8 1.6 1.5 1.6 2.6 3.9 3.2 3.2 3.1 3.4 5.7 1.8 1.8 2.3 GK 448 325 461 361 2710 -1.0 -1.2 1.3 1.2 1.5 1.2 1.4 1.3 1.4 1.4 1.8 2.0 1.9 2.2 1.6 1.7 1.7 2.0 2.0 2.0 HADHA 2238 2530 1891 1845 8900 1.7 1.7 2.1 1.3 1.2 1.6 2.2 2.4 1.3 1.6 2.6 2.8 1.9 3.2 2.0 2.4 1.9 1.5 2.9 2.2 HMGCR 4409 4550 2692 3599 3156 -1.3 -1.5 -1.1 -1.1 -1.3 -1.2 -1.2 -1.1 -1.2 -1.5 -1.1 -1.2 1.1 1.2 -1.4 -1.1 -1.1 1.0 1.3 -1.1 HMGCS1 10529 11863 6948 10066 3157 -1.4 -1.9 -1.2 -1.3 -1.5 -1.4 -1.0 -1.6 -1.7 -1.6 -1.1 -1.4 1.3 -1.0 -1.5 -1.2 -1.5 -1.3 -1.1 -1.1 IRF7 1440 1059 1108 1807 3665 2.3 2.4 1.1 2.0 2.3 2.6 2.1 -1.1 1.7 2.5 3.5 2.5 1.2 1.2 3.5 3.6 3.4 -1.1 1.2 3.0 LIPC 13012 6183 3955 3474 3990 -1.5 -1.5 1.3 -1.2 -1.2 1.4 1.1 1.3 -1.0 1.1 -1.3 1.2 1.8 1.4 1.2 -1.2 -1.3 2.1 1.3 1.3 MBL2 1461 1157 164 681 4153 3.1 1.6 1.9 2.5 2.5 6.9 3.8 3.6 3.4 2.7 3.9 3.7 2.9 3.0 2.9 3.9 4.0 2.7 4.4 2.9 PDK4 779 626 215 136 1987 -1.9 -2.3 3.2 1.8 1.7 2.7 3.9 4.3 3.1 7.2 5.8 11.8 10.0 10.9 11.6 5.5 9.7 10.0 11.1 20.4 PEX11A 338 274 154 278 8800 1.3 1.2 1.4 1.8 1.8 3.2 2.5 1.8 2.4 2.5 5.3 3.9 2.9 2.7 3.1 4.1 4.0 2.5 2.4 3.7 PLIN4 448 344 986 552 114782 4.2 4.2 1.2 1.6 3.3 1.8 2.5 -1.0 1.8 2.9 4.7 4.4 1.1 1.1 4.5 4.7 5.6 -1.0 1.4 4.1 PPARA 472 626 540 444 1847 -1.1 -1.2 -1.0 -1.1 1.0 -1.1 -1.2 -1.0 -1.1 -1.1 -1.0 1.1 -1.1 1.1 -1.1 -1.4 -1.4 -1.2 1.1 -1.2 PPARG 197 297 205 119 3640 -1.3 1.1 -1.0 1.1 -1.1 -1.3 -1.3 1.1 1.0 -1.3 1.0 1.1 1.1 1.0 -1.1 1.3 1.2 1.1 1.0 -1.1 SGK2 431 405 140 289 10110 3.2 2.1 1.8 2.9 2.3 4.1 2.7 2.4 3.6 2.3 2.9 2.6 2.1 2.4 2.3 2.5 3.2 1.5 2.3 2.2

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Downloaded from from Downloaded dmd.aspetjournals.org at ASPET Journals on October 4, 2021 4, October on Journals ASPET at DMD #42028

SLC2A2 3427 3496 1510 2724 6514 -1.8 -1.8 -1.4 -1.4 -1.3 -3.2 -1.7 -1.8 -1.8 -2.1 -1.9 -1.3 -1.5 -1.3 -1.3 -2.0 -1.7 -1.3 -1.1 -1.6 TXNIP 637 846 456 1812 14907 1.4 -1.0 1.2 1.1 1.6 2.2 2.3 -1.3 1.1 2.5 4.5 8.2 4.6 1.8 4.1 4.7 8.4 2.9 1.9 4.8 VLDLR 339 205 244 539 7436 1.5 1.2 1.6 1.5 1.6 2.5 1.9 2.0 1.8 1.7 1.5 1.2 1.8 1.1 -1.2 2.3 1.8 1.7 1.3 1.8

ABAT 11603 15998 4899 5254 18 -1.5 -1.4 -1.3 -1.2 -1.3 -2.7 -1.7 -1.5 -1.7 -2.1 -2.0 -1.8 -1.9 -2.1 -2.1 -2.5 -1.9 -1.8 -1.9 -1.7 This articlehasnotbeencopyeditedandformatted.Thefinalversionmaydifferfromthisversion. ABCB11 136 143 31 71 8647 -1.3 -2.5 -1.3 1.1 -1.6 1.1 -1.6 1.1 1.3 1.1 -2.0 -1.9 -1.1 -1.0 -1.4 -3.3 -3.3 -1.7 -1.4 -1.3 ABCG5 7295 4665 2156 2672 387 -1.5 -1.5 -1.0 1.0 -1.3 -1.1 -1.1 1.0 1.0 -1.5 1.0 1.2 -1.2 -1.2 -1.1 1.1 1.0 -1.3 -1.0 -1.1 DMD FastForward.PublishedonOctober12,2011asDOI:10.1124/dmd.111.042028 BRCA1 698 371 105 92 662 -2.4 -2.3 1.1 -1.1 1.4 -1.6 -6.0 1.0 1.0 2.0 -3.2 -1.7 1.0 1.1 1.3 -3.8 -1.9 -1.1 1.1 1.2 CYP2E1 12166 14594 4600 1779 1571 -2.2 -2.9 1.0 1.2 -1.0 -2.7 -2.2 -1.0 -1.4 -1.9 -1.2 -1.7 -1.0 -1.2 -1.1 -2.3 -1.9 -1.2 -1.1 -1.1 CYP8B1 41844 40094 13969 22570 1582 -1.0 -1.3 -1.1 1.0 -1.5 1.0 1.0 1.3 1.1 -1.4 -1.0 -1.0 -1.1 1.0 -1.0 1.2 -1.1 1.2 1.6 1.1 DEFB1 72067 28637 36921 5918 1672 -1.3 -1.1 -1.1 -1.2 -1.6 -2.5 -1.1 -1.2 -1.6 -1.2 -1.6 -1.2 1.2 1.1 1.2 -1.5 -2.3 -1.0 -1.4 -1.1 EGR1 1296 1299 1691 2666 1958 -1.3 -1.5 -1.2 -1.3 -1.0 -2.5 -1.3 -1.4 -1.4 -1.3 -1.4 -1.3 -1.0 -1.1 -1.2 1.2 -1.2 1.2 1.3 -1.4 GGT1 2014 1023 1672 584 2678 1.4 1.8 -1.1 -1.1 -1.1 1.2 -1.2 -1.4 -1.3 -1.2 -1.2 -1.1 -1.9 -2.1 1.0 -1.2 -1.1 -2.2 -1.4 1.1 HAL 116 348 363 425 3034 -1.5 -1.3 -1.4 -1.3 -1.3 -2.4 1.0 -1.2 -1.2 -2.0 1.0 -1.2 -1.0 1.1 -1.8 1.3 -1.4 -1.2 1.4 -1.3 HHEX 2090 1973 815 1224 3087 -1.3 -1.9 1.1 1.1 1.1 -1.1 -1.0 1.2 1.1 1.0 -1.3 -1.0 1.0 1.2 -1.2 -1.4 -1.3 -1.1 1.3 -1.3 HIBCH 7322 6926 5351 5998 26275 -1.3 -1.3 -1.1 -1.2 1.0 -1.4 -1.1 1.0 -1.1 -1.1 1.1 -1.0 1.1 -1.0 -1.1 1.1 -1.1 -1.1 -1.0 1.0 HIF1A 1119 845 3789 2599 3091 -1.3 -1.3 1.1 -1.4 -1.1 -1.8 1.1 1.4 -1.1 -1.2 -1.8 -1.2 1.3 1.2 -1.4 -1.2 -1.4 1.9 1.5 -1.2 HMOX1 706 582 828 1860 17090 6.4 9.7 1.5 1.3 1.6 1.1 1.3 3.1 2.0 2.2 2.6 1.2 3.3 2.5 3.9 -1.2 1.3 5.3 2.4 2.5 miscell HPX 46736 44689 33659 38779 3263 1.1 1.2 -1.2 1.2 -1.4 -1.3 -1.3 -1.1 1.1 -1.5 1.1 -1.2 -1.5 -1.2 -1.4 -1.2 -1.2 -1.7 -1.1 -1.2 anous ICAM1 972 787 3180 2782 3383 1.0 -1.0 -1.0 -1.0 1.0 -1.9 -1.5 -1.1 -1.1 1.0 -1.5 -1.3 -1.4 -1.3 -1.2 -1.6 -1.2 -1.6 -1.4 -1.0 genes IGF1 993 1508 542 1120 858 -3.3 -1.9 -1.6 -1.3 -1.1 -2.4 -3.9 -1.5 -1.2 -1.1 -1.4 -2.6 -1.0 -1.1 -1.1 -2.1 -3.0 1.1 -1.5 1.1 IL1B 32 12 59 51 3553 -1.0 -1.5 1.1 1.2 3.6 -1.4 1.1 1.9 1.5 8.6 -1.1 1.2 1.7 1.5 8.0 -1.1 1.2 2.0 -1.2 7.7 INSIG1 9795 15138 3770 7152 3638 -1.1 -1.1 1.2 1.7 -1.2 -1.6 -1.0 1.0 1.3 1.1 1.3 -1.1 1.3 1.6 -1.0 -1.2 -1.3 -1.2 1.2 -1.1 JUN 6574 5213 4942 4495 3725 -1.3 -1.6 -1.0 1.0 1.0 -1.2 -1.2 -2.0 -1.0 1.0 -1.5 -1.2 -1.4 -1.1 1.4 -1.6 -1.6 -1.7 -2.1 1.1 LBP 10370 3743 20630 17853 3929 1.4 1.4 -1.0 1.2 1.1 1.2 -1.4 -1.2 -1.1 1.0 1.2 -1.1 -1.4 -1.1 1.0 -1.3 1.4 -1.7 -1.2 1.2 LCAT 556 511 199 238 3931 -1.2 -1.1 -1.1 -1.3 -1.1 -1.3 -1.6 -1.3 -1.4 -1.3 -1.1 -1.2 -1.4 -1.8 -1.1 -1.4 -1.1 -1.6 -1.4 -1.1 LDLR 2452 2786 3724 3159 3949 1.2 1.1 1.2 1.0 -1.1 -1.2 -1.2 -1.1 -1.1 -1.1 -1.1 -1.2 -1.1 -1.1 -1.2 -1.3 -1.0 -1.3 -1.2 -1.0 LECT2 1262 1135 2796 1175 3950 -1.7 -1.2 -1.3 -1.7 -4.1 -1.2 -1.3 -1.3 -1.6 -5.5 -1.0 1.0 -1.5 -1.6 -7.3 1.3 1.4 -1.2 1.2 -2.6 MT1A 99558 68833 109515 59968 4489 1.0 1.0 -1.1 1.1 -1.1 1.0 -1.0 1.1 1.1 -1.0 -1.1 -1.1 1.0 1.2 -1.1 -1.2 -1.5 -1.0 -1.5 -1.2 MYC 750 655 1700 1712 4609 1.3 -1.2 -1.0 1.2 -1.0 -1.0 1.0 1.2 1.3 1.1 -1.8 1.0 1.1 1.5 -1.0 -1.0 1.4 1.2 1.3 -1.1 NR1I3 3594 4935 751 1014 9970 -1.4 -1.6 -1.2 1.1 -1.2 -1.6 -1.3 1.0 -1.0 -1.6 -1.1 -1.3 -1.6 -1.7 -1.4 -1.3 -1.3 -1.8 -1.5 -1.2 PECI 26767 30088 14949 22812 10455 -1.2 -1.3 1.1 1.0 -1.0 -1.1 -1.1 1.1 1.1 -1.1 -1.2 -1.1 1.1 1.0 -1.1 -1.3 -1.2 1.1 -1.1 -1.0 PECR 1631 1656 710 1446 55825 -1.1 -2.0 -1.3 -1.4 -1.3 -1.3 -1.4 -1.6 -1.4 -1.5 -1.1 -1.1 -1.1 -1.2 -1.4 -1.3 -1.1 -1.4 -1.1 -1.1 SAA1 147553 140546 207482 221246 6288 1.6 1.5 -1.1 -1.2 1.0 -3.4 1.2 -1.2 -1.3 -1.2 1.1 -1.1 -1.2 -1.4 -1.0 -1.0 -1.1 -1.5 -1.3 1.2

2-day human hepatocyte cultures from 4 donors (#2, #4, #5 and #6) and HepaRG cells were previously treated for 24h with 20 µM of troglitazone (TRO), 50 µM of rosiglitazone (ROSI), 50 µM of muraglitazar or 300 µM of tesaglitazar (TESA) (Rogue et al., 2011) and the fold changes obtained for various genes are displayed in this table. The four compounds were synthesized by the Servier Chemical Department and the two color –microarray technology was used to obtain these fold changes (Rogue et al., 2011). The same RNA samples were used in the present study for obtaining basal gene expression values (hybridizations were performed as described in the material and methods section). In bold abnormal basal expression levels and corresponding fold changes after troglitazone treatment of some genes in the human hepatocytes from donor # 4.

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Downloaded from from Downloaded dmd.aspetjournals.org at ASPET Journals on October 4, 2021 4, October on Journals ASPET at DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. Downloaded from dmd.aspetjournals.org at ASPET Journals on October 4, 2021 DMD Fast Forward. Published on October 12, 2011 as DOI: 10.1124/dmd.111.042028 This article has not been copyedited and formatted. The final version may differ from this version. Downloaded from dmd.aspetjournals.org at ASPET Journals on October 4, 2021

DMD #42028

Supplemental data

Inter-individual variability in gene expression profiles in human hepatocytes and comparison with HepaRG cells

Alexandra ROGUE, Carine LAMBERT, Catherine SPIRE, Nancy CLAUDE and André GUILLOUZO

Drug and metabolism disposition

Supplemental Table 1: Characteristics of the human liver donors

Donor Sex Age (years) Pathology Ethnicity Alcoholism Diabetes Smoker 1 Male 63 Metastasis caucasian No No No 2 Male 48 Metastasis NA NA NA NA 3 Male 61 Metastasis NA NA NA NA 4 Male 75 Metastasis caucasian No No Yes 5 Male 75 Metastasis NA NA No Yes 6 Female 81 Metastasis NA No No No NA: not available

DMD #42028

Supplemental data

Inter-individual variability in gene expression profiles in human hepatocytes and comparison with HepaRG cells

Alexandra ROGUE, Carine LAMBERT, Catherine SPIRE, Nancy CLAUDE and André GUILLOUZO

Drug and metabolism disposition

Supplemental Table 2 : Intensity values of some major genes in the 6 human hepatocyte populations and HepaRG cells.

Gene symbol Gene description Donor # 1 Donor # 2 Donor # 3 Donor # 4 Donor # 5 Donor # 6 HepaRG ABAT 4-aminobutyrate aminotransferase 14539.39 11602.69 14616.05 17618.16 4899.27 5254.34 11928.62 ABCB1 ATP-binding cassette, sub-family B (MDR/TAP), member 1 863.91 1677.95 1158.19 1235.74 2589.67 2299.44 5336.81 ABCB10 ATP-binding cassette, sub-family B (MDR/TAP), member 10 138.92 186.97 172.54 132.16 90.82 140.79 465.96 ABCB11 ATP-binding cassette, sub-family B (MDR/TAP), member 11 535.99 135.67 195.99 120.14 30.70 70.87 255.17 ABCB4 ATP-binding cassette, sub-family B (MDR/TAP), member 4 803.95 384.93 372.87 235.11 151.23 279.58 989.41 ABCB6 ATP-binding cassette, sub-family B (MDR/TAP), member 6 3833.11 4199.17 6405.20 4370.31 3918.44 4726.12 19119.33 ABCB7 ATP-binding cassette, sub-family B (MDR/TAP), member 7 1345.07 1420.86 1365.57 1268.81 1108.82 1149.20 4052.01 ABCB8 ATP-binding cassette, sub-family B (MDR/TAP), member 8 68.98 80.78 90.46 99.22 107.97 90.55 411.33 ABCC1 ATP-binding cassette, sub-family C (CFTR/MRP), member 1 1.69 23.33 2.19 3.43 9.52 9.88 735.97 ABCC2 ATP-binding cassette, sub-family C (CFTR/MRP), member 2 10233.04 8525.98 9247.76 8572.62 7020.57 7817.22 13791.13 ABCC3 ATP-binding cassette, sub-family C (CFTR/MRP), member 3 7518.63 10873.24 16616.45 12706.13 12103.09 20762.36 75939.51 ABCD1 ATP-binding cassette, sub-family D (ALD), member 1 159.49 201.47 202.15 244.30 236.99 220.86 350.43 ABCD3 ATP-binding cassette, sub-family D (ALD), member 3 736.43 612.80 586.77 627.10 391.93 477.00 1981.45 ABCD4 ATP-binding cassette, sub-family D (ALD), member 4 880.67 1110.88 1183.04 1055.09 661.97 663.88 3532.72 ABCG2 ATP-binding cassette, sub-family G (WHITE), member 2 2811.16 1994.83 2338.23 2336.77 2075.70 3022.38 1766.28 ABCG4 ATP-binding cassette, sub-family G (WHITE), member 4 2.39 3.89 7.90 2.74 2.48 2.20 74.11 ABCG5 ATP-binding cassette, sub-family G (WHITE), member 5 10030.65 4664.54 7619.57 7295.02 2156.45 2672.19 1995.26 ABCG8 ATP-binding cassette, sub-family G (WHITE), member 8 87.66 109.84 143.80 164.23 60.94 86.69 387.32 ADH1B alcohol dehydrogenase 1B (class I), beta polypeptide 3355.50 1052.20 1596.78 704.33 16.35 81.43 3375.10 AK3L2 adenylate kinase 3-like 2 1541.47 1650.12 1617.27 1344.14 888.75 780.19 2055.84 ANKRD18A ankyrin repeat domain 18A 20.85 101.05 42.10 41.12 12.30 55.17 336.15 ATP11C ATPase, class VI, type 11C 600.45 709.66 712.26 697.11 472.92 487.14 688.69 CCL2 chemokine (C-C motif) ligand 2 100.86 4692.64 212.61 883.38 43349.70 21663.60 3567.26 CCNB1 cyclin B1 60.14 113.21 76.92 124.58 174.63 154.57 1034.00 CCND1 cyclin D1 61.20 191.13 168.76 172.89 481.02 268.47 1938.49 CDC2 cell division cycle 2, G1 to S and G2 to M 2.97 10.91 3.50 21.29 12.39 12.32 2909.83 CDC2L2 Cell division cycle 2-like 2 (PITSLRE proteins) 73.78 109.55 96.77 74.09 67.49 82.76 729.20 CDC6 cell division cycle 6 homolog (S. cerevisiae) 40.09 49.42 59.96 52.26 73.03 109.25 1596.11 CROT carnitine O-octanoyltransferase 128.30 158.79 110.35 121.16 87.59 56.26 921.79 CRP C-reactive protein, pentraxin-related 11.13 185.06 57.94 51.08 676.93 765.18 701.77 CYP1A1 cytochrome P450, family 1, subfamily A, polypeptide 1 27.51 63.26 73.67 112.57 32.52 76.42 225.79 CYP1A2 cytochrome P450, family 1, subfamily A, polypeptide 2 805.83 856.33 1121.52 1577.54 250.18 366.28 811.23 CYP1B1 cytochrome P450, family 1, subfamily B, polypeptide 1 366.86 351.27 341.74 281.16 191.42 195.96 2624.95 CYP2A6 cytochrome P450, family 2, subfamily A, polypeptide 6 21852.20 9811.85 12044.00 1676.03 1041.71 385.29 4730.14 CYP2B6 cytochrome P450, family 2, subfamily B, polypeptide 6 32752.94 15866.03 15330.56 13332.79 15097.85 8823.01 9838.97 CYP2C18 cytochrome P450, family 2, subfamily C, polypeptide 18 19045.02 24596.46 22426.98 25409.16 19967.10 20887.69 3498.10 CYP2C19 cytochrome P450, family 2, subfamily C, polypeptide 19 21225.20 12942.72 17534.55 15723.74 2323.39 2676.69 19148.31 CYP2C8 cytochrome P450, family 2, subfamily C, polypeptide 8 13556.76 7043.40 10360.58 7287.89 451.97 918.45 8240.05 CYP2C9 cytochrome P450, family 2, subfamily C, polypeptide 9 66006.50 58821.84 68860.59 46485.20 11595.16 15408.15 58214.34 CYP2D6 cytochrome P450, family 2, subfamily D, polypeptide 6 3095.31 1481.71 2640.80 2335.44 342.73 680.93 102.76 CYP2E1 cytochrome P450, family 2, subfamily E, polypeptide 1 10847.38 12166.37 14574.39 15078.34 4599.93 1778.54 2859.10 CYP3A4 cytochrome P450, family 3, subfamily A, polypeptide 4 122248.70 65885.79 107782.20 46811.34 3872.06 7344.10 17894.76 DMD #42028

CYP3A5 cytochrome P450, family 3, subfamily A, polypeptide 5 15590.35 13206.06 15546.33 11660.02 6711.16 7565.16 10747.37 CYP3A7 cytochrome P450, family 3, subfamily A, polypeptide 7 86760.32 60642.05 72828.29 39119.79 17833.63 18903.58 18593.44 CYP4A11 cytochrome P450, family 4, subfamily A, polypeptide 11 599.94 328.82 541.92 299.23 68.33 81.92 1798.92 CYP4B1 cytochrome P450, family 4, subfamily B, polypeptide 1 2.02 2.30 2.42 2.36 1.83 2.14 30665.77 CYP7A1 cytochrome P450, family 7, subfamily A, polypeptide 1 7137.73 1472.14 1597.33 238.16 10.08 85.01 3389.15 CYP8B1 cytochrome P450, family 8, subfamily B, polypeptide 1 53472.84 41843.94 50875.07 38874.58 13968.59 22569.78 13697.15 G6PC glucose-6-phosphatase, catalytic subunit 792.81 129.31 321.05 117.36 20.79 103.23 2645.17 GLS2 glutaminase 2 (liver, mitochondrial) 1870.92 1059.78 1744.78 3338.50 507.93 567.53 1553.38 GSTA1 glutathione S-transferase A1 12835.29 7313.03 7046.94 4006.48 3043.50 4436.92 132174.14 GSTA2 glutathione S-transferase A2 19079.46 12146.50 14000.58 7885.15 7835.02 8940.39 156444.44 GSTA3 glutathione S-transferase A3 7428.07 4870.79 4125.35 3064.37 2025.36 2909.73 104941.18 GSTA4 glutathione S-transferase A4 742.57 1088.28 897.66 713.56 366.23 583.59 1271.29 GSTA5 glutathione S-transferase A5 20730.74 12869.37 16552.82 7323.20 7943.03 9544.20 172713.91 GSTK1 glutathione S-transferase kappa 1 2660.97 3421.33 3231.59 2477.01 1686.68 2225.51 7974.88 GSTM1 glutathione S-transferase M1 134.42 296.98 148.01 544.44 549.83 215.24 696.45 GSTM2 glutathione S-transferase M2 (muscle) 19.64 51.73 26.18 28.90 34.51 27.33 332.09 GSTM3 glutathione S-transferase M3 (brain) 1408.34 917.53 1757.79 4501.24 7147.25 2238.52 382.00 GSTM4 glutathione S-transferase M4 102.76 544.58 126.87 534.79 331.51 151.27 1702.87 GSTM5 glutathione S-transferase M5 40.82 162.16 35.05 134.76 51.85 40.45 115.70 GSTO1 glutathione S-transferase omega 1 32595.79 28088.99 32277.48 31921.33 20177.97 23478.58 84031.16 GSTP1 glutathione S-transferase pi 381.33 18694.40 1268.11 2464.42 9057.18 1835.39 32.07 GSTT1 glutathione S-transferase theta 1 1673.58 1902.74 2197.52 4247.26 1365.08 1548.33 4327.36 GSTT2 glutathione S-transferase theta 2 771.36 674.54 3624.29 138.64 450.74 357.17 3292.19 GYS1 glycogen synthase 1 (muscle) 59.09 116.51 112.39 132.10 122.98 152.38 3653.22 GYS2 glycogen synthase 2 (liver) 212.02 154.06 162.86 175.57 34.13 86.58 235.92 HK2 hexokinase 2 40.24 30.77 4.29 35.79 26.28 50.43 348.17 ID1 inhibitor of DNA binding 1 87.35 1865.83 352.13 1141.34 8233.91 3291.92 13947.58 IL6 interleukin 6 (interferon, beta 2) 7.65 20.05 8.67 8.13 29.70 18.02 634.69 IL8 interleukin 8 11.01 535.67 68.73 122.48 1904.09 1931.49 1172.45 IQSEC3 IQ motif and Sec7 domain 3 69.52 141.05 108.93 91.08 104.49 157.49 959.00 ITGA6 integrin, alpha 6 940.73 2242.44 1225.20 1363.68 1173.62 1243.42 2779.24 KRT19 keratin 19 212.46 1284.85 1524.38 2784.58 18759.64 1248.98 438659.56 LPL lipoprotein lipase 5.03 109.48 4.09 48.62 63.89 107.24 17122.36 MAG myelin associated glycoprotein 30.22 46.48 28.90 25.49 22.62 38.11 53.48 MAST4 microtubule associated serine/threonine kinase family member 4 111.86 347.79 214.37 104.23 214.01 180.21 160.88 MUC5B mucin 5B, oligomeric mucus/gel-forming 98.23 67.94 61.18 43.72 47.99 50.81 79.14 NR1I2 nuclear receptor subfamily 1, group I, member 2 1280.11 1583.55 1743.94 2123.87 756.28 1226.49 2849.87 NR1I3 nuclear receptor subfamily 1, group I, member 3 4372.04 3593.94 4396.47 5326.02 751.10 1014.35 1578.57 PANK2 pantothenate kinase 2 (Hallervorden-Spatz syndrome) 346.20 388.95 480.03 511.51 519.12 470.66 2081.87 PCDH15 protocadherin 15 1.81 2.20 2.38 51.50 1.75 2.04 6.72 PRG2 plasticity-related gene 2 5.04 8.33 7.42 15.02 7.59 15.87 32.90 SCD stearoyl-CoA desaturase (delta-9-desaturase) 6387.03 4304.54 3490.19 4979.74 1641.27 2086.32 12601.06 SLC10A1 solute carrier family 10, member 1 6349.59 6439.49 8601.18 9517.40 2333.55 4296.67 2388.22 STAT3 signal transducer and activator of transcription 3 125.26 445.58 282.65 438.76 586.12 511.64 1707.19 UGT1A6 UDP glucuronosyltransferase 1 family, polypeptide A6 26742.89 22432.98 25888.48 23396.19 14742.54 14773.91 76495.72 UGT1A8 UDP glucuronosyltransferase 1 family, polypeptide A8 1311.95 1085.12 1173.22 660.03 99.06 128.84 8923.29 UGT2B10 UDP glucuronosyltransferase 2 family, polypeptide B10 97307.70 51140.00 79815.04 38157.33 18158.80 33385.90 62976.09 UGT2B11 UDP glucuronosyltransferase 2 family, polypeptide B11 61511.58 32917.77 48652.55 25133.39 11650.58 24340.17 57241.30 UGT2B15 UDP glucuronosyltransferase 2 family, polypeptide B15 17895.15 15153.98 17903.04 12655.68 1401.86 2020.51 57875.84 UGT2B17 UDP glucuronosyltransferase 2 family, polypeptide B17 18873.20 12439.82 17572.27 10116.09 2370.88 5495.25 30706.93 UGT2B28 UDP glucuronosyltransferase 2 family, polypeptide B28 12175.01 6517.27 8902.42 2182.55 993.89 2563.55 4898.08 UGT2B4 UDP glucuronosyltransferase 2 family, polypeptide B4 48908.05 27819.35 49736.63 22529.01 8320.08 20269.05 40771.50 UGT2B7 UDP glucuronosyltransferase 2 family, polypeptide B7 97110.26 52618.81 74590.88 25838.88 12841.03 24127.98 23621.23

DMD #42028

Supplemental data

Inter-individual variability in gene expression profiles in human hepatocytes and comparison with HepaRG cells

Alexandra ROGUE, Carine LAMBERT, Catherine SPIRE, Nancy CLAUDE and André GUILLOUZO

Drug and metabolism disposition Supplemental Table 3: Genes expressed only in HepaRG cells located on the chromosome 7

Gene symbol Gene description SEPT13 septin 13 SEPT14 hCG_18833 ACHE acetylcholinesterase (Yt blood group) AMPH amphiphysin ANKIB1 ankyrin repeat and IBR domain containing 1 ANKMY2 ankyrin repeat and MYND domain containing 2 ANLN anillin, actin binding protein AP1S1 adaptor-related protein complex 1, sigma 1 subunit ATXN7L1 ataxin 7-like 1 C1GALT1 core 1 synthase, glycoprotein-N-acetylgalactosamine 3-beta-galactosyltransferase, 1 C7orf31 hCG_39028 C7orf38 chromosome 7 open reading frame 38 C7orf41 chromosome 7 open reading frame 41 C7orf53 chromosome 7 open reading frame 53 CADPS2 Ca++-dependent secretion activator 2 CALCR calcitonin receptor CALN1 calneuron 1 CASD1 CAS1 domain containing 1 CBLL1 Cas-Br-M (murine) ecotropic retroviral transforming sequence-like 1 CCDC132 coiled-coil domain containing 132 CD36 CD36 molecule (thrombospondin receptor) CDC14C CDC14 cell division cycle 14 homolog C (S. cerevisiae) CHN2 chimerin (chimaerin) 2 CHRM2 cholinergic receptor, muscarinic 2 CLDN15 claudin 15 CLIP2 CAP-GLY domain containing linker protein 2 CNPY4 canopy 4 homolog (zebrafish) COX19 COX19 cytochrome c oxidase assembly homolog (S. cerevisiae) CROT carnitine O-octanoyltransferase DBF4 DBF4 homolog (S. cerevisiae) DKFZp434F142 hypothetical DKFZp434F142 DNAH11 dynein, axonemal, heavy chain 11 DUS4L dihydrouridine synthase 4-like (S. cerevisiae) DYNC1I1 dynein, cytoplasmic 1, intermediate chain 1 ELMO1 engulfment and cell motility 1 DMD #42028

EPHB4 EPH receptor B4 ETV1 ets variant 1 FAM126A family with sequence similarity 126, member A FBXL18 F-box and leucine-rich repeat protein 18 FBXO24 F-box protein 24 FDPSL2A farnesyl diphosphate synthase pseudogene 2 FIGNL1 hCG_1645062 FKBP9L FK506 binding protein 9-like FZD1 frizzled homolog 1 (Drosophila) GATS GATS, stromal antigen 3 opposite strand GBAS glioblastoma amplified sequence GCK glucokinase (hexokinase 4) GHRHR growth hormone releasing hormone receptor GIGYF1 GRB10 interacting GYF protein 1 GLI3 GLI family zinc finger 3 GPC2 glypican 2 GRM3 glutamate receptor, metabotropic 3 HGF hCG_19052 IGF2BP3 hCG_2010038 IKZF1 IKAROS family zinc finger 1 (Ikaros) IL6 hCG_38231 KBTBD2 hCG_37345 KCND2 hCG_2039708 KIAA1324L KIAA1324-like KRIT1 KRIT1, ankyrin repeat containing LIMK1 LIM domain kinase 1 LOC441238 NMD3 homolog (S. cerevisiae) pseudogene 1 LOC442292 coiled-coil domain containing 86 pseudogene LOC442517 ATP-binding cassette, sub-family E (OABP), member 1 pseudogene LOC642006 glucuronidase, beta pseudogene LOC728376 zinc finger protein pseudogene MAGI2 hCG_40263 MGC27345 hypothetical protein MGC27345 MOGAT3 hCG_17352 MOSPD3 hCG_20462 NFE2L3 hCG_2009876 NOD1 hCG_39138 NRCAM hCG_17111 OSBPL3 oxysterol binding protein-like 3 PCLO piccolo (presynaptic cytomatrix protein) PDE1C hCG_2010079 PEG10 paternally expressed 10 PHTF2 hCG_40629 PILRA hCG_2039461 PLEKHA8 hCG_37326 PMS2 PMS2 postmeiotic segregation increased 2 (S. cerevisiae) PMS2CL PMS2 C-terminal like pseudogene DMD #42028

PRKAR1B hCG_1993358 PRKAR2B hCG_17936 PTN hCG_18946 PVRIG hCG_1735849 RNF148 hCG_2013925 RP9P retinitis pigmentosa 9 pseudogene SAMD9L hCG_1815681 SCIN hCG_18526 SEMA3A hCG_17200 SEMA3C hCG_17980 SEMA3D hCG_18258 SEMA3E hCG_19251 SLC25A40 hCG_20823 SLC29A4 hCG_2036981 SMURF1 SMAD specific E3 ubiquitin protein ligase 1 STAG3 stromalin-3 STAG3L1 stromal antigen 3-like 1 STX1A hCG_96107 TFPI2 hCG_19196 THSD7A thrombospondin, type I, domain containing 7A TRA2A hCG_37979 TSC22D4 TSC22 domain family, member 4 TSGA14 hCG_18971 TWIST1 hCG_37310 VPS37D vacuolar protein sorting 37 homolog D (S. cerevisiae) WBSCR27 Williams Beuren syndrome chromosome region 27 ZKSCAN5 hCG_1788530 ZNF107 hCG_41164 ZNF273 hCG_1773147 ZNF498 hCG_1742894 ZNF800 hCG_2014287

The list of genes located on chromosome 7 was extracted from www.ncbi.nlm.nih.gov

DMD #42028

Supplemental data

Inter-individual variability in gene expression profiles in human hepatocytes and comparison with HepaRG cells

Alexandra ROGUE, Carine LAMBERT, Catherine SPIRE, Nancy CLAUDE and André GUILLOUZO

Drug and metabolism disposition

Supplemental Table 4: Genes more expressed in primary human hepatocyte populations or in HepaRG cells according to the loading plot representation

Genes more expressed in primary human hepatocytes (x <-0.03)

ANKRD35 ankyrin repeat domain 35 APOC2 apolipoprotein C-II BHMT betaine-homocysteine methyltransferase CBLC Cas-Br-M (murine) ecotropic retroviral transforming sequence c CGREF1 cell growth regulator with EF-hand domain 1 CNDP1 carnosine dipeptidase 1 (metallopeptidase M20 family) CXCL6 chemokine (C-X-C motif) ligand 6 (granulocyte chemotactic protein 2) EFHD1 EF-hand domain family, member D1 FBP1 fructose-1,6-bisphosphatase 1 FTCD formiminotransferase cyclodeaminase GSTP1 glutathione S-transferase pi HGFAC HGF activator IGFALS insulin-like growth factor binding protein, acid labile subunit LDOC1L leucine zipper, down-regulated in cancer 1-like MAGEH1 melanoma antigen family H, 1 ME1 malic enzyme 1, NADP(+)-dependent, cytosolic MTB metallothionein B MUPCDH mucin-like protocadherin OAT ornithine aminotransferase (gyrate atrophy) PIGR polymeric immunoglobulin receptor PRAP1 proline-rich acidic protein 1 PYCARD PYD and CARD domain containing RPS4Y1 ribosomal protein S4, Y-linked 1 RPS4Y2 ribosomal protein S4, Y-linked 2 SERP2 stress-associated endoplasmic reticulum protein family member 2 SLC13A5 solute carrier family 13 (sodium-dependent citrate transporter), member 5 TMEM45B transmembrane protein 45B UCHL1 ubiquitin carboxyl-terminal esterase L1 (ubiquitin thiolesterase) VSIG4 V-set and immunoglobulin domain containing 4

DMD #42028

Genes more expressed in HepaRG cells (x >0.03)

ABCA12 ATP-binding cassette, sub-family A (ABC1), member 12 ACTL8 actin-like 8 AHRR aryl-hydrocarbon receptor repressor ANGPT1 angiopoietin 1 APOBEC3C apolipoprotein B mRNA editing enzyme, catalytic polypeptide-like 3C ASAM adipocyte-specific adhesion molecule BTNL8 butyrophilin-like 8 C1QL1 complement component 1, q subcomponent-like 1 CALCR calcitonin receptor CD70 CD70 molecule CDH11 cadherin 11, type 2, OB-cadherin (osteoblast) CDH18 cadherin 18, type 2 CDH19 cadherin 19, type 2 CLEC3B C-type lectin domain family 3, member B COL12A1 collagen, type XII, alpha 1 COL4A6 collagen, type IV, alpha 6 COL8A1 collagen, type VIII, alpha 1 CT45-5 cancer/testis antigen CT45-5 CXCL13 chemokine (C-X-C motif) ligand 13 (B-cell chemoattractant) CYP4B1 cytochrome P450, family 4, subfamily B, polypeptide 1 DEFB103A defensin, beta 103A DKK1 dickkopf homolog 1 (Xenopus laevis) DNER delta/notch-like EGF repeat containing EFEMP1 EGF-containing fibulin-like extracellular matrix protein 1 EGLN3 egl nine homolog 3 (C. elegans) FSTL5 follistatin-like 5 GAGE7 G antigen 7 GGT5 gamma-glutamyltransferase 5 GLI3 GLI-Kruppel family member GLI3 (Greig cephalopolysyndactyly syndrome) GPM6B glycoprotein M6B GPR87 G protein-coupled receptor 87 HOXB9 homeobox B9 HOXC9 homeobox C9 IL13RA2 interleukin 13 receptor, alpha 2 IL1RL1 interleukin 1 receptor-like 1 ITGA3 integrin, alpha 3 (antigen CD49C, alpha 3 subunit of VLA-3 receptor) KCNJ16 potassium inwardly-rectifying channel, subfamily J, member 16 KCNMB4 potassium large conductance calcium-activated channel, subfamily M, beta member 4 KLRC2 killer cell lectin-like receptor subfamily C, member 2 KRT5 keratin 5 (epidermolysis bullosa simplex, Dowling-Meara/Kobner/Weber-Cockayne types) KRT6C keratin 6C LAMA2 laminin, alpha 2 (merosin, congenital muscular dystrophy) LEPREL1 leprecan-like 1 LPHN3 latrophilin 3 LPL lipoprotein lipase DMD #42028

LUM lumican LUZP4 leucine zipper protein 4 MAGEA1 melanoma antigen family A, 1 (directs expression of antigen MZ2-E) MAGEA12 melanoma antigen family A, 12 MAGEA2B melanoma antigen family A, 2B MAGEA4 melanoma antigen family A, 4 MAGEC2 melanoma antigen family C, 2 MUC15 mucin 15, cell surface associated MYBPH myosin binding protein H NBEA neurobeachin NLGN1 neuroligin 1 NRXN3 neurexin 3 NUDT10 nudix (nucleoside diphosphate linked moiety X)-type motif 10 NXF2 nuclear RNA export factor 2 NXF5 nuclear RNA export factor 5 P704P prostate-specific P704P PCDH7 protocadherin 7 PDPN podoplanin PEG10 paternally expressed 10 PLAC8 placenta-specific 8 PLCXD3 phosphatidylinositol-specific phospholipase C, X domain containing 3 PTN pleiotrophin (heparin binding growth factor 8, neurite growth-promoting factor 1) S100A2 S100 calcium binding protein A2 SCGB1D1 secretoglobin, family 1D, member 1 SCGN secretagogin, EF-hand calcium binding protein SEMA3E sema domain, immunoglobulin domain (Ig), short basic domain, secreted, (semaphorin) 3E SLC47A2 solute carrier family 47, member 2 SOD3 superoxide dismutase 3, extracellular SOHLH2 spermatogenesis and oogenesis specific basic helix-loop-helix 2 SPANXA1 sperm protein associated with the nucleus, X-linked, family member A1 SPANXB2 SPANX family, member B2 SPANXD SPANX family, member D TEX11 testis expressed 11 TUSC3 tumor suppressor candidate 3 VCX variable charge, X-linked VCX3A variable charge, X-linked 3A WDR21C WD repeat domain 21C WISP2 WNT1 inducible signaling pathway protein 2 XAGE1D X antigen family, member 1D ZNF415 zinc finger protein 415

DMD #42028

Supplemental data

Inter-individual variability in gene expression profiles in human hepatocytes and comparison with HepaRG cells

Alexandra ROGUE, Carine LAMBERT, Catherine SPIRE, Nancy CLAUDE and André GUILLOUZO

Drug and metabolism disposition

Supplemental Table 5: Validation by RT-qPCR analysis of the microarray results in primary human hepatocytes

Microarray results q-PCR results Donor Donor Donor Donor Donor Donor Donor Donor Donor Donor Donor Donor # 1 # 2 # 3 # 4 # 5 # 6 # 1 # 2 # 3 # 4 # 5 # 6 ABCB1 0.53 1.02 0.71 0.75 1.58 1.40 0.62 0.73 0.74 1.04 1.61 1.26 ALDOB 1.67 0.90 1.41 1.22 0.39 0.41 1.54 0.75 1.12 0.74 1.08 0.77 CYP1A2 0.97 1.03 1.35 1.90 0.30 0.44 0.68 1.04 1.73 1.70 0.14 0.71 CYP2B6 1.94 0.94 0.91 0.80 0.89 0.52 1.92 0.94 1.29 0.93 0.58 0.34 CYP3A4 1.98 1.06 1.74 1.04 0.06 0.12 1.74 0.75 2.13 0.80 0.09 0.49 CYP7A1 3.91 0.81 0.87 0.36 0.01 0.05 1.29 1.46 0.95 0.88 0.82 0.60 GSTA1 1.99 1.13 1.09 0.62 0.47 0.69 1.89 1.32 0.98 0.73 0.43 0.64 KRT19 0.05 0.30 0.36 0.56 4.43 0.30 0.01 0.04 0.04 0.03 5.88 0.01 NR1I3 1.38 1.13 1.38 1.55 0.24 0.32 1.41 0.91 0.97 1.79 0.28 0.64 PPARA 0.91 1.28 1.54 0.85 0.52 0.89 0.79 1.56 1.89 0.46 0.49 0.81 SLC10A1 1.02 1.04 1.38 1.49 0.38 0.69 0.92 1.06 1.33 1.65 0.20 0.85

mRNA fold change for each gene corresponds to the ratio of mRNA expression in each primary human hepatocytes vs the mean values of primary human hepatocytes.