Xenobiotic metabolism and disposition in Human lung cell...

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Title Page

Xenobiotic metabolism and disposition in Human lung cell models:

comparison with in vivo expression profiles.

Elisabeth Courcot, Julie Leclerc, Jean-Jacques Lafitte, Eric Mensier, Sophie Jaillard,

Philippe Gosset, Pirouz Shirali, Nicolas Pottier, Franck Broly, Jean-Marc Lo-Guidice.

EA4483, Faculté de Médecine H. Warembourg, Pôle Recherche, Lille, France (EC, FB, JL,

JMLG, NP)

Service de Pneumologie et d’Oncologie Thoracique, Hôpital Calmette, CHRU, Lille, France

(JJL)

Département de Chirurgie, Polyclinique du Bois, Lille, France (EM, SJ)

Unité de Chimie Environnementale et Interactions sur le Vivant, EA4492, Université du

Littoral-Côte d’Opale, Dunkerque, France (PS)

Unité INSERM U1019, Institut Pasteur de Lille, Lille, France (PG)

DMD Fast Forward. Published on July 13, 2012 as doi:10.1124/dmd.112.046896

Copyright 2012 by the American Society for Pharmacology and Experimental Therapeutics.

This article has not been copyedited and formatted. The final version may differ from this version.DMD Fast Forward. Published on July 13, 2012 as DOI: 10.1124/dmd.112.046896

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Running title page

Running title:

Xenobiotic metabolism and disposition in Lung cells models

Corresponding author:

Lo-Guidice Jean- Marc

Faculté de Médecine – Pôle Recherche

EA4483 – Salles 31-32

1 Place de Verdun

59045 Lille cedex, France

Tel: +33 3 20 62 68 18

Fax: +33 3 20 62 68 91

E-mail: [email protected]

Number of text pages: 47

Number of tables: 4

Number of figures: 1

Number of references: 37

Number of words: Abstract: 242 words

Introduction: 764 words

Discussion: 1585 words

Abbreviations: Adenocarcinoma (AC); Aryl hydrocarbon Receptor (AhR); ATP- Binding

Cassette (ABC); Bronchial Mucosa (BM); Constitutive Androstane Receptor (CAR);

threshold Cycle (Ct); Cytochrome P450 (CYP); Human Bronchial Epithelial Cell (HBEC);

Non Small Cell Lung Cancer (NSCL); Pulmonary Parenchyma (PP); Pregnane X Receptor

(PXR); Reverse Transcription-Polymerase Chain Reaction (RT-PCR); Solute Carriers (SLC);

Squamous cell Carcinoma (SCC); TaqMan Low Density Arrays (TLDA); Xenobiotic

Metabolizing Enzyme (XME).


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Abstract

Numerous lung cell lines are currently used as in vitro models for pharmacological

and toxicological studies. However, no exhaustive report about the metabolic capacities of

these models in comparison with those of lung tissues is available. In the present study, we

used a high throughput quantitative real-time RT-PCR strategy to characterize the expression

profiles of 380 genes encoding proteins involved in the metabolism and disposition of

xenobiotics in ten commonly used lung cell lines (A549, H292, H358, H460, H727, Calu-1,

16HBE, 1 HAEO, BEAS-2B and L-132), and four primary cultures of human bronchial

epithelial cells. Expression results were then compared to those previously obtained in human

non tumoral and tumoral lung tissues. Our results revealed disparities in gene expression

between lung cell lines or when comparing lung cell lines with primary cells or lung tissues.

Primary cell cultures displayed the highest similarities with bronchial mucosa in terms of

transcript profiling and therefore appear to be the most relevant in vitro model for

investigating the metabolism and bioactivation of toxicants and drugs in bronchial epithelium.

H292 and BEAS-2B cell lines which exhibited the highest homology in gene expression

pattern with primary cells and the lowest number of dysregulated genes compared to non-

tumoral lung tissues, could be used as surrogates for toxicological and pharmacological

studies. Overall, our study should provide references for researchers to choose the most

appropriate in vitro model for analyzing the cellular effects of drugs or airborne toxicants on

the airways.


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Introduction

Lung is a target organ for inhaled chemicals and carcinogens. Several enzymatic and

non-enzymatic systems cooperate in the metabolism and disposition of these compounds.

Phase I xenobiotic-metabolizing enzymes (XMEs), in particular Cytochromes P450 (CYPs),

catalyze the first step of xenobiotic processing via oxidation, reduction or hydrolysis

reactions. Phase II XMEs conjugate xenobiotics or their phase I metabolites to hydrophilic

endogenous substrates, making molecules more suitable for elimination. In general,

biotransformation reactions are beneficial in that they help the pulmonary tissues to reduce

the potential toxicity of inhaled toxicants. Sometimes, however, XMEs transform harmless

substances into “bioactivated” metabolites which are highly reactive with endogenous

macromolecules, causing cell death and gene mutations (Castell et al., 2005). Transporters,

mainly represented by the solute carriers (SLC) and ATP- binding cassette (ABC) families,

mediate the entrance of xenobiotics into cells or facilitate the efflux of xenobiotics or their

metabolites from cells. Tight coupling between metabolism and transport processes is ensured

by ligand-activated transcription factors that control constitutive and inducible expression of

XME and transporter genes in a coordinate manner. Two major nuclear receptors, namely the

Pregnane X receptor (PXR) and Constitutive Androstane Receptor (CAR), and one member

of the family of basic helix-loop-helix transcription factors, the Aryl hydrocarbon Receptor

(AhR), are activated by xenobiotics and are therefore termed as xenosensors (Nakata et al.,

2006).

Expression profiles of XMEs, transporters and nuclear receptors define the metabolic

capacity of each tissue and may have consequences for cell defense against environmental

chemicals but also for drug response. Recently, we characterized the mRNA expression level

of 380 genes involved in the cellular processing of xenobiotics in pulmonary parenchyma

(PP), bronchial mucosa (BM), and tumoral lung tissues (Leclerc et al., 2011). These data

allowed the identification of the major XME and transporter genes expressed in PP and BM,


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and confirmed that AhR was the predominant xenosensor expressed in human lung.

Significant differences in gene expression between BM and PP, and a global decrease in gene

expression in tumoral lung tissues were also pointed out, suggesting distinct susceptibility to

xenobiotics and their toxic effects between these tissue types.

Human cell lines are still widely used to study the impact of toxicants on lung or to

test new therapeutics including anti-cancer drugs. Primary cells are also used but are more

difficult to obtain and have limited growth activity. However there is some evidence that

primary cells are the best experimental models for in vivo situations. Expression of

xenobiotic/drug- metabolizing enzymes has been extensively studied in many human hepatic

cell lines and compared with primary human hepatocytes or human liver slices. Large

variations in the expression of xenobiotic metabolizing enzymes have been observed between

hepatic cell lines and primary hepatocytes, with the complete absence or much lower

abundance of certain enzymes in hepatic cell lines (LeCluyse, 2001; Gómez-Lechón et al.,

2004; Olsavsky et al., 2007). However, although the perfect hepatoma cell line is not yet

available, the expression of many drug metabolizing genes was similar in the HepaRG cell

line and primary hepatocytes, suggesting that this cell line may be a reliable surrogate to

human hepatocytes for studies of xenobiotic metabolism and toxicology (Aninat et al., 2006;

Guillouzo et al., 2007; Hart et al., 2010).

In contrast to in vitro liver systems, the level of expression of genes involved in the

metabolism and disposition of xenobiotics in lung cell models is much less documented.

Many lung cell lines are available for toxicity studies but their metabolic capacities are not

well defined and differences in gene expression compared to lung primary cells or tissues are

very limited. The adenocarcinoma A549 cell line is probably the best characterized and the

most widely used (Foster et al., 1998; Hukkanen et al., 2000). Quantitative RT-PCR analyses

detected transcript levels for several CYP in this cell line but at levels lower than those found


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in human lung tissue (Castell et al., 2005). Moreover, few data are available about phase II

enzymes or transporters in A549 cells.

In the current study, we aimed to assess the metabolic capacities of ten commonly

used lung cell lines (A549, H292, H358, H460, H727, Calu-1, 16HBE, 1 HAEO, BEAS-2B

and L-132), and four primary cultures of human bronchial epithelial cells. The mRNA level of

almost all of genes encoding XMEs, transporters, nuclear receptors and transcription factors

involved in the cellular processing of xenobiotics was measured using a high throughput

quantitative real-time RT-PCR strategy based on TaqMan Low Density Arrays (TLDA).

Expression results were then compared to those previously obtained in human non tumoral

(bronchial mucosa and pulmonary parenchyma) and tumoral (adenocarcinoma or squamous

cell carcinoma) lung tissues.


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Materials and methods

Lung tissue samples

Twelve patients undergoing partial or complete lung resection for Non Small Cell

Lung Cancer (NSCLC) were included in this study. Informations related to each patient,

histopathology of tumor samples and transcript profiling have been previously described

(Leclerc et al., 2011). An informed consent was obtained for each patient. None of the

patients were treated with preoperative radiotherapy or chemotherapy. For each patient, three

tissue samples were collected: one from the tumor (adenocarcinoma (AC) or squamous cell

carcinoma (SCC) and two from macroscopically healthy areas of lobar bronchi (BM) and

distal pulmonary parenchyma (PP), both of which were taken remotely from the tumor. After

surgical resection, samples were immediately submerged in RNAlater™ Solution (Ambion,

Courtaboeuf, France) to avoid RNA degradation, stored at 4°C for 24 h and then at -20°C

until used. Four additional BM specimens namely P13.B, P14.B, P15.B, and P16.B, were

analyzed; they correspond to tissues samples used for primary cultures of human bronchial

epithelial cells (HBEC 1, 2, 3, and 4, respectively).

Cell culture

A549, Calu-1, H292, H358, H460, and H727 cell lines were purchased from the

American Type Culture Collection (ATCC). The immortalized bronchial epithelial cells

1HAEO and 16HBE were generous gifts from Dr P. Gosset (INSERM U1019, Lille, France).

The immortalized bronchial epithelial cells BEAS-2B and the L-132 cell line were generous

gifts from Pr P. Shirali (ULCO, EA4492, Dunkerque, France). The A549 and H358 cells were

derived from lung adenocarcinomas, the Calu-1 cells from a lung squamous cell carcinoma,

the H292 cells from a lymph node metastasis of a pulmonary mucoepidermoid carcinoma, the

H460 cells from a large cell carcinoma, the H727 cells from a carcinoid tumour, and the L-


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132 cells from human embryonic alveolar cells. Cells were cultured in 75 cm2 flasks in

standard conditions.

HBECs were derived from bronchial tissues of four patients undergoing surgery for

lung carcinomas. After surgical resection, macroscopically healthy areas of lobar bronchi

were immediately immersed in a nutrient medium containing DMEM, 1% Penicillin-

streptomycin, and 2% fungizone, then stored at 4°C until used. Bronchial segments were

rinsed twice with cold PBS and processed for mucosa isolation using a sterile scalpel. Small

pieces of BM (about 2 mm2) were used as a source of primary cell. They were placed in 9 cm2

plates coated with 0.8 % collagen G in the presence of 500 µl of a serum free medium (Small

Airway Epithelial Cell Medium, Promocell, Heidelberg, Germany) supplemented with 1%

penicillin-streptomycin and 2% fungizone. After an adherence period of 24 hours, 2 ml of

culture medium were added and were changed every 2-3 days. Epithelial cells grown from

bronchial explants reached 100% confluence in about 10 days. After trypsinization, cells were

gathered, reseeded in new 9 cm2 plates coated with collagen and cultured until confluency.

RNA Isolation

RNA extractions from lung tissues were performed as previously described (Leclerc et

al., 2011). For cell culture, 600 µl of RLT lysis buffer supplemented with 1%

mercaptoethanol was directly added to the cell dishes. Total RNAs were isolated using the

RNeasy plus Mini Kit™ (Qiagen, Courtaboeuf, France) according to the instructions of the

manufacturer. The yield of the extracted RNA was determined by measuring the optical

density at 260 nm with the BioSpec-nano spectrophotometer (Shimadzu, Champs sur Marne,

France). The purity and quality of RNA were evaluated using the Experion automated

electrophoresis station (Biorad, Marnes-la-Coquette, France). High quality RNA with RQI

(RNA Quality Indicator) greater than 9.0 were used for the study.


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cDNA synthesis

Two µg of total RNAs were retrotranscribed in single-stranded cDNAs using the High

Capacity cDNA Reverse Transcription Kit™ (Applied Biosystems, Courtaboeuf, France)

according to the manufacturer’s recommendations.

Quantitative real-time PCR

Gene expression was quantified using custom TaqMan™ Low Density Arrays (TLDA,

Applied Biosystems). This real-time PCR-based technique consists in a 384-well micro

fluidic card preloaded with sets of primers and 6-FAM labeled TaqMan MGB probes

previously selected from predesigned TaqMan™ Gene Expression Assays (Applied

Biosystems). We chose a configuration with 380 different assays, the last 4 wells being

dedicated to the control assay (in quadruplicate).

TLDA design

TLDA were configured with 380 assays for genes encoding proteins known or

suspected to be involved in the metabolism of xenobiotics, to govern the cellular entry or

efflux of these compounds and/or their metabolites, or to coordinate the metabolism and

transport processes (Leclerc et al., 2011). This set of genes comprised 137 genes of phase I

enzymes (including 56 CYPs), 69 genes of phase II enzymes, 103 genes of transporters

(including 31 ABC and 62 SLC transporters), 48 genes of nuclear receptors and transcription

factors (including coactivators and corepressors), and 23 miscellaneous genes (including 9

metallothioneins). It should be noted that some of the CYP genes analyzed in this study

encode enzymes (families CYP4 to CYP51) that are rather involved in endogenous pathways

such as the biosynthesis of bile acids and steroid hormones, the metabolism of eicosanoids,

vitamin D and retinoic acid. As they control the levels of endogenous substrates that are


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sometimes associated with tumor promotion or progression, it could be stated that these CYP

enzymes participate indirectly in environmental carcinogenesis (Nebert et al., 2006).

TLDA procedure

The TLDAs were loaded with each cDNA template mixed with 2X TaqMan™ Gene

Expression Master Mix (Applied Biosystems), according to the manufacturer’s instructions.

After centrifugation (2 x 1 min at 1 200 rpm), each reaction well contained 1 μL reaction

mixture corresponding to 1 ng of total RNA. The wells were immediately sealed with a

TLDA Sealer (Applied Biosystems) to prevent cross-contamination. 7900HT Real-Time PCR

System (Applied Biosystems) was used to perform the real-time PCR amplification. Thermal

cycling conditions were as follows: 2 min at 50 °C to activate Uracil-DNA Glycosylase

(UDG), 10 min at 94.5 °C, followed by 40 cycles of denaturation at 97 °C (30 s) and

annealing-extension at 59.7 °C (1 min).

Analysis of gene expression

The detection threshold was set at 0.3 for all genes, except 13 genes for which a

threshold at 0.3 would have led to inaccurate quantification (Leclerc et al., 2011). The

threshold cycle (Ct) values, which are the cycle number at which the fluorescence crosses the

detection threshold, were determined with the RQ Manager 1.2 software (Applied

Biosystems). The 18S rRNA was selected as the reference gene for normalization of target

gene. It has been reported as the most suitable reference genes for gene expression profiling in

normal and tumoral lung specimens (Saviozzi et al., 2006). We chose Ct value > 35 as the

cut-off for non-expressed genes. Ct values for target genes were normalized to the Ct value of

the reference gene, creating ΔCt values (Cttarget gene - Ct18S rRNA).

After ΔCt computation, ΔΔCt values were calculated for each lung cell line by

subtracting the average ΔCt of the tissue samples (BM, PP, or lung tumors) used as a


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calibrators from the ΔCt value of each lung cell model used as target sample. This enables the

calculation of the relative quantity (RQ) between the tissue samples and cells with the

formula: RQ = 2-(ΔCt of target cells - AverageΔCt of lung tissues). Genes were regarded as being

differentially expressed if they displayed at least a 4-fold difference in expression level (RQ ≥

4 or ≤ 0.25).


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Results

In order to determine the most appropriate in vitro lung cell model for toxicological

and pharmacological studies, a quantitative real-time RT-PCR strategy based on TaqMan

Low Density Arrays (TLDA) was used to characterize the mRNA expression level of 380

genes encoding proteins involved in the biodisposition of xenobiotics in 10 human lung cell

lines currently used in laboratories, and 4 primary cultures of HBEC. Results were compared

with those previously obtained for human lung tissues (Leclerc et al., 2011).

Expression profiling in primary cultures of human bronchial epithelial cells and in human

lung cell lines.

Gene expression profiles of the different lung cell models are presented in Table 1.

Expression profiling in non-tumoral and tumoral lung tissues is also described in this Table.

Out of the 380 genes that we studied, 57 genes were regarded as not expressed (Ct value

above 35) in all cultured lung cell models. Thirty-seven of these genes were also undetectable

in lung tissues. In primary cells, 140 genes (36.8 %) were considered not expressed. They

included 35.8 %, 49.3 %, and 36.9 % of genes encoding phase 1 XMEs, phase 2 XMEs, and

transporters, respectively. In lung cell lines and immortalized cells, the number of not

expressed genes varied from 138 genes in A549 cells to 192 in L-132 cells, representing 33.6

% (H292) to 56.9 % (L-132) of genes encoding phase 1 enzymes, 40.6 % (A549) to 66.7 %

(16HBE) of genes encoding phase 2 enzymes, and 35 % (Calu-1) to 47.6 % (16HBE) of genes

encoding transporters.

The number of genes that exhibited high mRNA expression levels (∆Ct above 16)

varied depending on the cellular model, ranging from 14 for the L-132 cells to 128 for the

A549 cells.

In the primary cells, 14 genes encoding phase I enzymes (AKR1A1, AKR1B1,

AKR1C1/2, ALDH18A1, ALDH1A3, ALDH2, ALDH3A2, ALDH7A1, CES2, CYP51A1,


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HSD17B10, MAOA, NQO1 and PON2) presented high mRNA levels. Most of these genes

were also highly expressed both in lung cell lines (except for L-132 and H727 cells) and in

non tumoral lung tissue samples. Moreover, some genes showing high mRNA expression

levels in BM and PP, i.e. ADH1B, CES1 and CYP4B1, were weakly or not expressed in most

models of lung cells. ADH1B was detected only in BEAS-2B cells (high level of expression);

CYP4B1 was expressed only in BEAS-2B cells and primary cells (moderate level), and in

H292 cells (low level); CES1 was detected only in A549 cells (high level), in H460 cells

(moderate level) and in H727 cells and primary cells (low level).

The phase II XME genes that exhibited the highest mRNA levels in primary cells

encode the glutathione S-transferases GSTK1, GSTO1, GSTP1, MGST1 and MGST3, the

methyltransferases COMT and TPMT, the N-acetyltransferase NAT5, the sulfotransferase

SULT2B1, and the mercaptopyruvate sulfurtransferase MPST. Apart from SULT2B1, these

genes also presented a significant level of expression in other lung cell models and lung tissue

specimens. Surprisingly, GSTA1/GSTA2 and INMT, which were among the genes with the

highest expression levels in BM and PP, respectively, were not detectable in most lung cell

models.

Concerning transporters, 13 genes, namely ABCA1, ABCB2, ATP6V0C, MVP,

SLC2A1, SLC3A2, SLC7A5, SLC7A11, SLC16A1, SLC31A1, SLC38A1, SLC38A2, and

SLC38A5, were highly expressed in lung primary cultures. ABCA1 and/or SLC38A5 exhibited

lower mRNA levels in most cell lines, as well as SLC7A5, SLC7A11, and SLC16A1 in human

lung tissues. Except for the A549 cell line, the AQP1 and/or SLCO2B1 mRNAs, which were

abundant in non tumoral lung tissues, were not detected in lung cell cultures.

As observed for the BM and PP, large amounts of transcripts of AhR and AhR

partners (i.e. AIP, ARNT, P23 (PTGES3) and HSP90) were detected in the different lung cell

models, suggesting the predominant role of this xenosensor in coordinating the expression of

XMEs and transporters in these cells. Finally, one can notice that some nuclear receptor


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mRNAs highly expressed in primary cultures, such as PPARD, RARG or VDR, were also

abundant in most cell lines.

In the four primary cultures of HBEC, most of the genes showed very similar mRNA

expression levels between individuals, as assessed by a coefficient of variation (CV) lower

than 5 % for 85.3 % of the genes. Only 8.2% of the genes exhibited high variability (CV ≥

10%) (Table 2). Interindividual variations in mRNA expression were particularly high for

GSTM1 and GSTT1 with CV= 19.8 % and 28.6 %, respectively.

Differential expression profiling between primary lung cells, lung cell lines and lung

tissues.

To reveal homologies of expression patterns among the lung cell models, a similarity

matrix was evaluated by a pairwise comparison of the samples (Table 3), in which the

Pearson’s correlation coefficient (r) was calculated based on the ΔCt obtained for each gene.

The Pearson’s correlation coefficient (r) values represent the strengths of the linear

relationship between any two sets of comparative components (a greater number indicates

higher similarity).

The highest r value between BM and lung cells was observed for the primary lung

cells (r value = 0.76), followed by the immortalized bronchial epithelial cells BEAS-2B (r =

0.72). The lowest r value between BM and cells was found for the two immortalized

bronchial epithelial cells 16HBE and 1HAEO (r = 0.61 for both cell models). The highest

similarities with pulmonary parenchyma were observed for the BEAS-2B cells (r = 0.76),

followed by the lung primary cells (r = 0.73). The two immortalized cells 16HBE (r = 0.65)

and 1HAEO (r = 0.62) showed the lowest r value. Highest similarities between tumor samples

and lung cell cultures were observed for the primary cells, with a r value of 0.82 and 0.85

when comparing with AC and SCC, respectively, and for the BEAS-2B cells, with a r value

of 0.82 and 0.79. The other lung cell models showed few differences in their r values, varying


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from 0.73 (H727 cells vs SCC) to 0.79 (H460 cells vs SCC). When comparing to the primary

cells, the highest similarities were observed for the H292 and BEAS-2B cells (r = 0.87 and

0.84, respectively). The H727 and A549 cell lines showed the lowest r values (r = 0.78).

To visualize directly the distances of gene expression patterns among lung cells and

lung tissues, unsupervised hierarchical clustering was performed with the Euclidean distance

as an input parameter in the clustering algorithm (Figure1). When considering the

dendrogramm including the totality of the 380 genes, several groups were observed (Figure

1A). The BM specimens clustered together, except for one sample. The PP samples clustered

in two distinct groups and the tumor samples exhibited more heterogeneity in their clustering.

Lung cell models clustered in three major groups. The four primary lung cells clustered

together and were close to a cluster containing the 16HBE, 1HAEO, Calu-1, BEAS-2B and

H292 cells, and to another cluster containing the H358, H727, and L-132 cells. Only the A549

cell line was found in a cluster containing mostly SCC tumor samples. When considering only

the genes encoding phase I enzymes (Figure 1B), the primary cells and most of the other lung

cell models exhibited a similar clustering, whereas the A549 cell line clustered together with

some AC and SCC tumor samples. The dendrogram obtained taking into account only the

genes encoding phase II enzymes also showed a close clustering between the A549 cell line

and an AC sample (Figure 1C). Dendrograms obtained from expression patterns of genes

encoding transporters (Figure 1D) and genes encoding nuclear receptors and transcription

factors (Figure 1E) presented similarities with the existence of a common cluster including all

the lung cell models.

Differences in mRNA levels between in vitro lung models and lung tissues were

measured for each gene. The number of genes differentially expressed (i.e. genes that exhibit

at least a 4-fold difference in expression) is described in Table 4. Among all the cells tested,


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the L-132 cell line had expression levels the most distant from those observed in vivo, since it

exhibited the highest number of differentially expressed genes compared with non tumoral

lung tissues. In comparison with BM, the primary and BEAS-2B cells showed the lowest

number of differentially expressed genes. Compared to PP, the H292 and BEAS-2B cells

showed the lowest number of differentially expressed genes.

Gene expression profiles of in vitro models were also compared with those of tumour

samples (Table 4). The primary cells exhibited the lowest number of differentially expressed

genes in comparison with AC and SCC samples.


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Discussion

Our present study provides for the first time similarities and differences between 10

lung cell lines, primary bronchial cells and lung tissues in their metabolic capacities,

measuring the expression levels of 380 genes encoding XMEs, transporters, NRs and

transcription factors regulating metabolism and transport processes. Expression analyzes were

performed using TaqMan Low Density Arrays. We previously validated this methodology for

the quantification of the expression of closely related genes whose nucleotide sequences show

high homologies (Leclerc et al., 2010 & 2011).

Our results showed differential gene expression between lung cell lines and also

highlighted disparities when comparing these cells with primary cells or lung tissues. All

cellular models tested in this study showed a significant decrease in the number of expressed

genes compared to lung tissues, which is a common feature of in vitro models derived from

other tissues (Olsavsky et al., 2007; Hart et al., 2010; Bourgine et al., 2012). Furthermore,

except for A549 cells, the number of underexpressed genes was higher than the number of

overexpressed genes. This loss or decrease of gene expression reflects the limitations of the

culture conditions that do not completely mimic the complexity of the physiological

microenvironment and its influence on gene expression and cellular phenotypes (Flaim et al.,

2005; Mees et al. 2011). Moreover, lung cell lines derived from carcinomas exhibit

tumorigenic characteristics as chromosomal alterations which can impact on their metabolic

capacities and must be considered when they are used with the aim of studying effect of

toxicants on non tumoral tissues (Kunzschughart et al., 1995; Kunz-Schughart et al. 2000).

The metabolism of most inhaled toxicants usually requires the intervention of phase I

enzymes and in particular many CYPs. The CYP1 family enzymes are involved in the

metabolic activation of procarcinogens such as polycyclic aromatic hydrocarbons and are

directly regulated by AhR (Shimada et Fujii-Kuriyama, 2004). AhR and most of its partners


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(i.e. AIP, ARNT, P23 (PTGES3) and HSP90) were as widely expressed in lung cell models as

in lung tissues. The CYP1A1 isoform that is poorly or not expressed in bronchial tissues in

basal conditions (Leclerc et al., 2010 & 2011; Willey et al., 1997; Thum et al., 2006)

exhibited higher levels of expression in most cell models. CYP1B1, another isoform of the

CYP1 family, was also upregulated in vitro, especially in the 16HBE and BEAS-2B cells. In

contrast to CYP1 enzymes, other procarcinogen activating CYPs previously reported as

highly and/or specifically expressed in bronchial mucosa, such as CYP2F1, CYP4B1 and to a

lesser extent CYP2B6, (Lanza and Yost, 2001; Baer et al., 2005; Hodgson and Rose, 2007),

are significantly underexpressed or not expressed in most lung cells. Similarly, some genes

encoding phase II enzymes and found at high level of expression in BM were markedly

downregulated (GSTA1-2 in A549 and/or primary cells) or not detected in lung cell models

(GSTA1-3). The loss of expression of some GSTs and CYPs in lung cell models should be

considered when studying the in vitro impact of inhaled toxicants.

In vitro cell-based models are also currently used in mechanistic studies of membrane

transport and the pharmaceutical screening of drug candidates. Membrane transporters are

involved in the uptake and the efflux of chemotherapeutic agents and therefore contribute to

drug resistance (Chang et al., 2011). In a previous study, mRNA expression levels of 31 drug

transporters were investigated in established cell lines (A549, Calu-3, 16HBE, BEAS-2B) and

primary cultures of lung epithelial cells, using a conventional semi-quantitative RT-PCR

methodology (Endter et al., 2009). In accordance with our results, the authors highlighted

disparities between the lung cell models. However, discrepant findings concerning the level of

expression of some genes were observed, probably because of the varying sensitivity and

specificity of the methods used to detect gene expression.

Our study revealed differences in expression profiles between lung tumors and lung

cell models. Evidence that ABC transporters play a significant role in clinical drug resistance


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has been reviewed extensively (Gottesman et al., 2002). Relatively high levels of ABCB1

(MDR1) expression have been shown in many intrinsically drug-resistant tumors. We found

low and moderate levels of ABCB1 gene expression in tumoral and non tumoral lung tissues,

respectively. Only H460 and H727 cells showed levels of ABCB1 transcript comparable to

lung tissues; the mRNA of this transporter was not detected in the other cell types. The

different members of the ABCC group are variously expressed in lung tissues. Of these,

ABCC1 (MRP1) was the first to be characterized (Cole et al., 1992). While there is significant

overlap with the substrate specificity of ABCB1, MRP1 transports a broader range of

antineoplastic or therapeutic agents (Munoz et al., 2007). Numerous studies have shown

upregulation of ABCC1 in tumors and its role in the clinical drug resistance behaviour of

several cancers. In particular, ABCC1 expression was found to be a highly significant

indicator of poor response to chemotherapy (Berger et al., 2005; Ota et al., 1995). In the

present study, we found overexpression of ABCC1 in SCC tumors and in 16HBE, A549, and

Calu-1 cells compared to non tumoral lung tissues. Among the other genes of the ABCC

subfamily, ABCC2, ABCC6 and ABCC9 were the most variously expressed in lung cell

models. ABCC2 was moderately or highly upregulated in 16HBE, A549, L-132, H460 and

H727 cells compared to other cell types and lung tissues. In tumor cell lines ABCC2 mRNA

overexpression was associated with resistance to multiple classes of anticancer drugs (Campa

et al., 2012). Regarding the ABCC6 and ABCC9 genes, while they were moderately

expressed in lung tissues, we failed to detect their mRNAs in most lung cell models.

SLCs typically mediate uptake and chemosensitivity for hydrophilic drugs. The first

report of SLC-mediated transport of anticancer drugs dealt with the antifolate drug

methotrexate, which is transported by members of the SLC19A family (SLC19A1-3)

(Goldman et al., 1985). Decrease or loss of SLC19A1 gene expression has been detected in

cancer cell lines made resistant to antifolates in vitro (Gifford et al., 2002). We observed that

SLC19A1 was downregulated only in H727 cells compared to lung tissues; it was


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overexpressed in 16HBE, 1HAE0, A549 and Calu-1 cells. In breast cancer, the lower

expression of SLC19A3 was found to be associated with resistance to doxorubicin (Liu et al.,

2003). We found that the transcript level of this transporter was low in tumoral lung tissues

and variable in lung cell models; SLC19A3 mRNAS were upregulated in 16HBE, A549, and

H460 cells but poorly expressed or undetectable in Calu-1, L-132, H727, and primary cells.

Nucleoside transporters (SLC28 and SLC29 families) are important determinants of

sensitivity to anticancer nucleoside analogs (Rauchwerger et al., 2000). Our study indicated

that the members of the SLC29 family were the predominant nucleoside transporters in lung

cell models and lung tumors; for some SLC29 subtypes, mRNA levels were highly variable

from one cell model to another, suggesting differences in chemosensitivity to anticancer

nucleoside drugs. Members of the SLCO superfamily (OATPs) transport a wide variety of

endogenous and exogenous compounds. Patients with SLCO polymorphisms have recently

been found to have altered pharmacokinetics for administered chemotherapeutic drugs

(Obaidat et al., 2012). We observed that mRNAs of the major OATPs implicated in the

transport of anticancer drugs, i.e. SLCO1A2, 1B1, and 1B3, were faintly expressed or not

detected in lung tissues and most lung cell models; only the A549 and Calu-1 cell lines

exhibited abundant transcript levels of SLCO1B3. The sensitivity of these cells to certain

antineoplastic agents should therefore be specific since SLCO1B3 has been identified as the

most efficient transporter for the taxane derivative drug, docetaxel (Baker et al., 2009).

In conclusion, none of the lung cell models tested in our study exactly reflects gene

expression profiles observed in fresh tissues. However, our results indicate that primary

airway epithelial cell cultures appear to be the most relevant experimental model since they

displayed the highest homology in expression pattern and the lowest number of dysregulated

genes compared to BM. Improvements of culture conditions, as previously discussed for

primary hepatocytes with the change of extra-cellular matrix or the use of new three-


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dimensional in vitro models ( Kim et al., 2010; Lang et al., 2011), could allow primary airway

epithelial cells to present gene expression profiles that accurately reflect those of bronchial

tissue, and to be used with full confidence for toxicological and pharmacological studies. It

should be noted that the interindividual variability of expression observed for some genes in

primary cells may affect the reproducibility of experiments. In our study, the H292 and

BEAS-2B cell lines exhibited the highest similarities with primary cells (86.7 % and 84.4 %,

respectively) and the lowest number of dysregulated genes compared to non-tumoral lung

tissues. Moreover, BEAS-2B cells showed high correlation coefficients with BM and PP.

These data suggest that H292 and BEAS-2B cells could therefore be used as surrogates for

investigating the metabolism and bioactivation of toxicants and drugs in bronchial epithelium.

The A549 cell line is probably the best characterized and the most widely used for

metabolism-related toxicity studies (Castell et al., 2005). Our hierarchical cluster analyses

indicate that these cells share common patterns of expression with some lung tumor samples,

especially when considering only phase I or phase II enzymes. Furthermore, A549 cells

showed correlation coefficients with lung tissues and primary cells among the lowest, and

exhibited the highest number of overexpressed genes compared to lung tissues. As a

consequence, the A549 cell line could express metabolic capabilities very different from those

observed in vivo in lung tissues and thus would not correspond to the most suitable and

realistic in vitro model.


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Acknowlegments

The authors thank Dr. Billaut-Laden Ingrid for useful advices and comments. Authorship Contributions Participated in research design: Lo-Guidice, Pottier and Broly.

Conducted experiments: Courcot and Leclerc.

Contributed new reagents or analytic tools: Lafitte, Mensier, Jaillard, Gosset and Shirali.

Perfomed data analysis: Courcot, Leclerc and Lo-Guidice.

Wrote or contributed to the writing of the manuscript: Courcot and Lo-Guidice.


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Footnotes

This work was supported by the Institut de Recherche en Environnement Industriel (IRENI) ;

the Université de Lille 2 ; and the Conseil Régional du Nord-Pas-de-Calais.


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Legends for figures

Figure 1: Unsupervised hierarchical clustering. A: complete data set (380 genes), ∆Cts

range from 7.63 to 30.5; B: phase I enzymes, ∆Cts range from 7.63 to 30.5; C: phase II

enzymes, ∆Cts range from 7.63 to 30.5; D: transporters, ∆Cts range from 10.13 to 30.5; E:

nuclear receptors and transcription factors, ∆Cts range from 8.92 to 30.5.

Bronchial mucosa samples: P01.B to P16.B. Pulmonary parenchyma samples: P01.P to P12.P.

Tumor samples: P01.T to P12.T.


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Table 1

Expression levels of 380 genes involved in xenobiotic metabolism and disposition in 10 lung

cell lines, primary cultures of HBEC and lung tissues.

Not detectable (-, ΔCt>26); very low (…, 26≥ΔCt>24); low (+, 24≥ΔCt>20); moderate (++,

20≥ΔCt>16); high (+++, ΔCt≤16); variable expression (+/-, detectable or not detectable); the

cut-off for mRNA levels was arbitrarily determined. BM: bronchial mucosa; PP: pulmonary

parenchyma; AC: adenocarcinoma; SCC: squamous cell carcinoma.

Genes Lung cell models Lung tissues

16HBE 1HAE0 A549 BEAS-2B Calu-1 L-132 H292 H358 H460 H727 HBEC BM PP SCC AC

Phase I enzymes

AADAC - - +++ - + - . . . - + - - + ++ + +

ABP1 - - - - - - + + - ++ + - + + + ++

ADH1A* - - - - - - - - - - - - - - -

ADH1B - - - ++ - - - - - - - +++ +++ ++ ++

ADH1C - - - . . . - - - + - - - ++ + + +

ADH4 - - - - - - - - - - - + - - -

ADH5 ++ ++ ++ ++ ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

ADH6 - - - - - - - - - - - ++ - - -

ADH7 - - - - - - - - - - ++ +++ - ++ -

ADHFE1 + + + ++ + - + + + + + ++ ++ ++ ++

AKR1A1 +++ ++ + +++ +++ +++ ++ +++ ++ +++ ++ ++ + +++ +++ +++ +++

AKR1B1 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

AKR1B10 - + +++ + + - + + +++ + ++ ++ - +++ +

AKR1C1/2 - - +++ + ++ ++ + . . . +++ + ++ + ++ ++ +++ ++

AKR1C3 - - +++ ++ ++ ++ + + +++ ++ ++ ++ ++ +++ ++

AKR1C4 - - - - - - - - - . . . - - - - -

AKR1CL1 - - + - - - - - - - - + - + +

AKR1CL2 ++ - +++ ++ ++ - ++ ++ + - + ++ ++ ++ ++

AKR1D1 - - - - - - . . . . . . - - - - - - -

AKR6A3 - - - - - - - - - - - + ++ + +

AKR6A5 ++ ++ +++ ++ ++ ++ ++ ++ ++ + + ++ +++ ++ ++


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AKR6A9 - - - + + - + . . . - - - + + + +

AKR7A2 +++ ++ + +++ ++ ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

AKR7A3 ++ + + + ++ . . . + + + ++ + + ++ + + ++

AKR7L - - - - - - - - - . . . - - - - -

ALDH16A1 + + + + + . . . + + + - + + + + +

ALDH18A1 +++ ++ + +++ +++ +++ ++ +++ ++ +++ ++ ++ + +++ ++ +++ +++

ALDH1A1 - - +++ - + - . . . - +++ ++ ++ +++ +++ ++ ++

ALDH1A2 - + - - - - + - - + - ++ ++ + +

ALDH1A3 +++ ++ + +++ +++ +++ ++ +++ +++ + + ++ + +++ ++ ++ ++

ALDH1B1 +++ ++ +++ ++ ++ ++ ++ ++ ++ + ++ ++ ++ ++ ++

ALDH1L1 ++ + + ++ - - ++ + + - + ++ + + +

ALDH2 - ++ +++ +++ ++ ++ +++ + ++ ++ ++ + +++ +++ +++ +++

ALDH3A1 + - +++ +++ ++ + ++ + +++ - ++ +++ + ++ +

ALDH3A2 +++ ++ +++ +++ +++ ++ +++ +++ +++ ++ ++ + +++ +++ +++ +++

ALDH3B1 +++ ++ +++ +++ +++ ++ +++ ++ +++ + ++ +++ +++ ++ +++

ALDH3B2 - + - - - - + . . . - - ++ + - + -

ALDH4A1 +++ ++ + +++ +++ +++ + ++ ++ ++ + ++ ++ ++ ++ ++

ALDH5A1 ++ ++ ++ ++ + + ++ ++ ++ + + ++ ++ ++ ++

ALDH6A1 ++ ++ + ++ +++ +++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

ALDH7A1 +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ + ++ ++ ++ ++

ALDH8A1 - - - - - - - . . . - - - + + + +

ALDH9A1 +++ ++ +++ +++ +++ ++ +++ +++ +++ ++ ++ +++ +++ ++ +++

AOC2 + ++ ++ - + + - + + + + + + + +

AOC3 - + + - + . . . . . . + + . . . + ++ +++ ++ ++

AOF1 +++ ++ +++ ++ +++ ++ ++ ++ ++ + ++ +++ ++ ++ ++

AOF2 +++ ++ + +++ +++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

AOX1 ++ + ++ ++ +++ - + + ++ + ++ ++ ++ + ++

BCHE - - + - - - - - ++ + - ++ ++ + +

CBR1 +++ ++ + +++ +++ ++ ++ ++ ++ ++ + ++ ++ ++ +++ ++

CBR3 ++ + ++ ++ ++ + . . . + + - + ++ + ++ +

CBR4 ++ ++ ++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

CES1 - - +++ - - - - - ++ + + +++ +++ +++ +++

CES2 ++ ++ ++ ++ ++ + ++ ++ ++ + ++ + ++ ++ ++ ++

CES3 ++ ++ ++ + + + + + + . . . + ++ ++ + ++

CES4 - - - - - - - - - - - + + + -


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CES7* - - - - - - - - - - - - - - -

CYP1A1 - ++ + . . . + + + + - + ++ - - - -

CYP1A2* - - - - - - - - - - - - - - -

CYP1B1 +++ ++ +++ +++ +++ +++ ++ ++ +++ ++ ++ ++ +++ ++ +++

CYP2A6 - - - - - - . . . - - - - - - - -

CYP2A7 - - + . . . + - + . . . - - - ++ ++ + +

CYP2A13 - - - - - - + - - - - ++ - - -

CYP2B6 - - - - . . . - + - - + - ++ ++ + ++

CYP2C8 - - - - - - - - - - - + - - -

CYP2C9 - - + - - - - - - - + ++ + - +

CYP2C18 - - + - - - - - - - ++ ++ + + +

CYP2C19 - - - - - - - - - - - + + + +

CYP2D6 - - - - - - + - - - - + - + +

CYP2E1 + + - - + - + + + + ++ ++ ++ ++ ++

CYP2F1 - - - - - - - - - - - +++ + - -

CYP2J2 ++ ++ + - + - ++ ++ . . . - ++ ++ + + ++

CYP2R1 - ++ ++ + ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

CYP2S1 ++ ++ +++ ++ ++ + ++ ++ + + ++ ++ ++ +++ ++

CYP2U1 ++ ++ ++ ++ +++ + ++ ++ ++ + ++ ++ ++ ++ ++

CYP2W1 - - - - + - + - - - + ++ - + -

CYP3A4* - - - - - - - - - - - - - - -

CYP3A5 - - ++ - - - + - - ++ + + ++ - +

CYP3A7 - - - - - - - - - - - - + - -

CYP3A43* - - - - - - - - - - - - - - -

CYP4A11/22 - - - + - - - - - - + / - - - - -

CYP4B1 - - - ++ - - + - - - ++ +++ +++ + ++

CYP4F2* - - - - - - - - - - - - - - -

CYP4F3 + - + - - - . . . - - - - + ++ + +

CYP4F8* - - - - - - - - - - - - - - -

CYP4F11 - ++ +++ ++ + + ++ - +++ + ++ ++ + ++ +

CYP4F12 - + ++ + + - + - - + + ++ ++ + +

CYP4F22 - + - - - - - - - . . . + + + + +

CYP4V2 ++ + ++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

CYP4X1 - + - ++ - - + + + - + +++ ++ ++ ++

CYP4Z1 - - - + - - - - - - - ++ + - +


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CYP5A11 - + +++ + ++ + - + + + + ++ ++ ++ ++

CYP7A1* - - - - - - - - - - - - - - -

CYP7B1 ++ - ++ + - - + + - - + ++ ++ ++ ++

CYP8A1 ++ - - ++ ++ - + - - - - ++ +++ ++ ++

CYP8B1 - - - - - - - - - - - + + + +

CYP11B1* - - - - - - - - - - - - - - -

CYP11B2* - - - - - - - - - - - - - - -

CYP17A1 - - - - - - - - - - - - + - +

CYP19A1 - - - - . . . - - . . . - - - - - + -

CYP20A1 +++ ++ ++ ++ ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

CYP21A2 - . . . - + . . . - + - - - - + + - +

CYP24A1 +++ ++ +++ - +++ - ++ + - - ++ ++ - ++ ++

CYP26A1 - + ++ - - - + + - - - ++ - ++ +

CYP26B1 + + +++ - ++ - + + - - + ++ ++ ++ ++

CYP26C1* - - - - - - - - - - - - - - -

CYP27A1 - - - ++ ++ - - - - - + ++ +++ ++ ++

CYP27B1 ++ + ++ ++ ++ . . . ++ ++ ++ ++ ++ + ++ ++ ++

CYP27C1 +++ ++ ++ + + . . . - ++ - - ++ + - + +

CYP39A1 + - + ++ + . . . + + + + + ++ ++ + +

CYP46A1 - - - - . . . - - - - - - - - - -

CYP51A1 +++ ++ + +++ +++ +++ ++ ++ ++ ++ ++ ++ + ++ ++ ++ ++

DHRS2 +++ ++ ++ + ++ . . . ++ +++ + + - - - + +

DHRS4 +++ ++ + +++ ++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

DHRS9 - - ++ - . . . - + . . . - + ++ +++ ++ ++ ++

DPYD +++ ++ ++ ++ +++ + ++ ++ ++ - + +++ +++ ++ +++

EPHX1 +++ ++ +++ +++ +++ ++ ++ ++ +++ ++ ++ +++ +++ +++ +++

EPHX2 ++ ++ +++ ++ + + ++ ++ ++ ++ ++ ++ ++ ++ ++

ESD +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ ++ ++ ++ ++

FMO1 - - - - - - - - - - - + + ++ ++

FMO2 - - - + - - - - - - - +++ +++ ++ ++

FMO3 - - - + - - - - - - + / - ++ ++ ++ ++

FMO4 + + + + + - + + + . . . + ++ ++ ++ +

FMO5 + + ++ + + + + ++ + ++ + +++ +++ ++ ++

HSD17B10 +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ ++ + +++ +++ +++ +++

MAOA ++ ++ ++ +++ +++ + +++ ++ ++ ++ ++ + +++ +++ +++ +++


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MAOB - + ++ ++ + + . . . + - - + ++ +++ ++ ++

NQO1 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ ++ +++ +++

NQO2 +++ ++ +++ ++ +++ ++ ++ ++ +++ ++ ++ ++ ++ ++ ++

PAOX ++ + ++ ++ ++ - ++ + + + ++ ++ + ++ ++

PON1 - - + - - - - - - - - - + - +

PON2 +++ ++ +++ +++ +++ ++ +++ ++ ++ ++ ++ + ++ +++ +++ +++

PON3 ++ + +++ + + - ++ + + + + + ++ + ++

SPR +++ ++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

SUOX ++ ++ ++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

XDH ++ + ++ + + - ++ + - - ++ ++ + + ++

Phase II enzymes

AANAT* - - - - - - - - - - - - - - -

AS3MT ++ ++ ++ ++ ++ - ++ + ++ + + ++ ++ ++ ++

BAAT - - ++ - - - - . . . - - - - - - +

COMT +++ ++ + +++ +++ +++ ++ ++ +++ ++ ++ ++ + ++ +++ +++ ++

GGT1 + + +++ - + . . . ++ ++ +++ + ++ ++ ++ ++ ++

GLYAT - . . . - - + - - - - - - - - - -

GNMT - - - + - - - - - - - + + - -

GSTA1 - - + - - - - - - - + +++ ++ ++ +

GSTA2 - - + - - - - - - - - +++ + + . . .

GSTA3 - - - - - - - - - - - ++ + - -

GSTA4 ++ + ++ ++ ++ + + ++ ++ ++ ++ ++ +++ ++ ++

GSTA5* - - - - - - - - - - - - - - -

GSTK1 +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ + +++ +++ +++ +++

GSTM1 - - - - ++ - - - + - + / - - - - -

GSTM2 - - ++ ++ ++ - + + ++ + + ++ ++ ++ ++

GSTM3 - ++ ++ ++ ++ ++ + + +++ + ++ ++ ++ ++ ++

GSTM4 ++ ++ ++ ++ ++ ++ ++ + ++ + + ++ ++ ++ ++

GSTM5 - - - - + - - - + - - ++ ++ + +

GSTO1 +++ ++ + +++ +++ +++ ++ +++ ++ +++ ++ + ++ + ++ +++ +++ ++

GSTO2 ++ ++ + ++ + - ++ ++ ++ ++ ++ ++ + ++ +

GSTP1 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

GSTT1 +++ ++ - - - + ++ ++ ++ ++ + + ++ ++ +

GSTT2/2B ++ ++ + + ++ ++ + ++ + + . . . + ++ ++ ++ ++

GSTZ1 ++ ++ + +++ ++ ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++


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HNMT - - ++ + +++ + ++ ++ ++ ++ + +++ +++ ++ +++

INMT - - - + - - - - - . . . - ++ +++ + ++

MGST1 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ ++ + +++ +++ +++ +++

MGST2 ++ ++ +++ +++ ++ ++ +++ ++ +++ ++ ++ +++ ++ ++ ++

MGST3 +++ ++ +++ +++ +++ ++ +++ ++ +++ ++ + ++ + +++ +++ +++ +++

MPST +++ ++ + +++ +++ +++ ++ +++ ++ +++ ++ ++ + ++ +++ +++ ++

NAT1 + + + + + - + + - . . . - + - + -

NAT2 - - - - . . . - - - - - - - - - -

NAT5 +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ ++ + +++ ++ +++ +++

NNMT ++ ++ +++ ++ ++ ++ +++ - + ++ + ++ ++ +++ ++ +++

PNMT - - - - - - - . . . - + - + + - -

SULT1A1 - + - . . . - . . . - - - - - + - - -

SULT1A2 - + - + - - + . . . - - + + ++ + +

SULT1A3/4 ++ ++ ++ ++ ++ + ++ + + + ++ ++ ++ ++ ++

SULT1B1 - - - - ++ - - - - - + + + + +

SULT1C2 - - + - + - - - - + - - + - ++

SULT1C3* - - - - - - - - - - - - - - -

SULT1C4 - - - - - - - - - - - ++ ++ + +

SULT1E1 - - - + - - + + - - + ++ + + -

SULT2A1* - - - - - - - - - - - - - - -

SULT2B1 +++ + +++ - - - ++ ++ - . . . ++ + ++ ++ ++ ++

SULT4A1 - ++ - - - + - - - - + + - + -

SULT6B1 - - - - - - - - + - - - - - -

TPMT +++ ++ + +++ +++ +++ ++ ++ ++ ++ ++ ++ + ++ ++ ++ +++

TST +++ ++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

UGT1A1 - + ++ - - . . . - - . . . + + ++ + ++ +

UGT1A10 - - - - - - - - - - + / - ++ - ++ +

UGT1A4 - - - - - - - - - - - + - ++ . . .

UGT1A5 - - - - - - - - - - - + - + +

UGT1A6 - ++ ++ - - +++ - - - - ++ ++ - ++ +

UGT1A7 - - +++ - - - - - - - - ++ - ++ +

UGT1A8 - - ++ - - - - - - - + / - + - + -

UGT1A9 - - ++ - - - - - . . . - - + - + -

UGT2A1 - - - - - - - - - - - ++ - - -

UGT2A3 - - ++ - - - - - - - - - - - -


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UGT2B10 - - + - . . . - - - - . . . - - - + -

UGT2B11 - - ++ - - - - - . . . - - + + + +

UGT2B15 - - + - - - - . . . - . . . - + - + +

UGT2B17 - - - - - - - + - - - + - + +

UGT2B28 - - + - - - - - - - - + - + -

UGT2B4 - - + - - - - - - - - - + - -

UGT2B7 - - ++ - - - - - - + - - - - -

UGT3A1* - - - - - - - - - - - - - - -

UGT3A2 - + - ++ - - + - - - - + - - +

UGT8 - - - - +++ ++ - ++ ++ + - ++ + ++ ++

Transporters

ABCA1 +++ ++ +++ ++ +++ + ++ + ++ + ++ + ++ +++ +++ +++

ABCA2 ++ ++ ++ ++ ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

ABCA3 +++ ++ +++ ++ + ++ ++ + ++ ++ + ++ +++ ++ +++

ABCA4 - - ++ - + + + ++ . . . - + + + + +

ABCA7 ++ ++ ++ ++ + + ++ ++ ++ ++ ++ ++ ++ ++ ++

ABCA8 - - ++ ++ + - . . . - ++ - - ++ ++ + +

ABCB1 - - - - - - - - + ++ - ++ ++ + +

ABCB10 +++ ++ +++ +++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

ABCB11 - - - - - - - - - - + / - + - - -

ABCB2 +++ ++ + +++ +++ +++ ++ +++ ++ +++ ++ ++ + +++ +++ +++ +++

ABCB3 +++ ++ + ++ ++ +++ ++ +++ ++ ++ + ++ ++ ++ ++ ++

ABCB4 - - - - - - - - - + - + + + +

ABCB5* - - - - - - - - - - - - - - -

ABCB6 +++ ++ +++ +++ +++ ++ ++ ++ +++ ++ ++ ++ ++ ++ ++

ABCB7 +++ ++ + +++ +++ +++ ++ ++ ++ +++ ++ ++ ++ ++ ++ ++

ABCB8 +++ ++ +++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

ABCB9 +++ ++ ++ ++ ++ + ++ ++ ++ + ++ + + ++ ++

ABCC1 +++ ++ +++ ++ +++ ++ ++ ++ ++ + ++ ++ ++ +++ ++

ABCC2 ++ + +++ + + ++ + + +++ ++ + + + + +

ABCC3 +++ ++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ +++

ABCC4 ++ ++ + +++ +++ +++ ++ + ++ ++ + ++ ++ ++ ++ ++

ABCC5 ++ ++ ++ ++ ++ + + + + + ++ ++ ++ ++ ++

ABCC6 - - + + + - + - - . . . + / - ++ ++ + ++

ABCC8* - - - - - - - - - - - - - - -


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ABCC9 - - - - ++ - - - ++ - + ++ ++ + ++

ABCC10 +++ ++ ++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

ABCC11 - - + - - - - - . . . - - - - - -

ABCC12* - - - - - - - - - - - - - - -

ABCD4 ++ ++ ++ ++ ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

ABCG2 +++ ++ +++ . . . ++ ++ ++ + ++ - + ++ ++ + +

ABCG8* - - - - - - - - - - - - - - -

SLC1A1 - ++ ++ ++ ++ + ++ ++ + + ++ ++ ++ + ++

SLC1A2 - - + - + - . . . - - - . . . ++ + + +

SLC1A3 +++ ++ - + ++ ++ +++ - + - ++ ++ ++ ++ ++

SLC1A6 +++ ++ + - - - - - - - + - - - - -

SLC1A7* - - - - - - - - - - - - - - -

SLC2A1 +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ + ++ + ++ ++ +++ ++

SLC3A1 - - ++ - + - - - - - - - - - -

SLC3A2 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

SLC5A4* - - - - - - - - - - - - - - -

SLC6A3 - + - - - - - - - - - - - + +

SLC6A4 - - - - - - - - - - - + ++ + +

SLC7A5 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + ++ ++ +++ ++

SLC7A6 +++ ++ + +++ +++ +++ ++ ++ ++ ++ + ++ ++ ++ ++ ++

SLC7A7 - - ++ . . . + - + . . . - + + ++ ++ ++ ++

SLC7A8 + + + ++ + . . . + - + + ++ ++ ++ +++ ++

SLC7A11 +++ ++ + +++ ++ +++ ++ +++ ++ +++ ++ ++ + ++ + ++ ++

SLC10A1* - - - - - - - - - - - - - - -

SLC10A2* - - - - - - - - - - - - - - -

SLC15A1 - - - - - - - - - + + + - + +

SLC15A2 + - - - . . . - + - - - ++ ++ ++ + ++

SLC16A1 +++ ++ + +++ +++ +++ ++ +++ + ++ ++ ++ + ++ ++ ++ ++

SLC18A2 - - - - - - - - - . . . - ++ ++ + +

SLC19A1 +++ ++ + +++ ++ +++ ++ ++ ++ ++ + ++ ++ ++ ++ ++

SLC19A2 ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

SLC19A3 ++ + ++ + . . . . . . + + ++ - - + ++ + +

SLC22A1 + + ++ - + . . . + - - - + + + + +

SLC22A11 - - + - - - - - - + - - - - -

SLC22A12* - - - - - - - - - - - - - - -


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SLC22A16 - - - - - - - - - - - + - - -

SLC22A2* - - - - - - - - - - - - - - -

SLC22A3 + . . . +++ ++ + - - - - + + + ++ + +

SLC22A4 ++ ++ ++ ++ ++ + + + + + + ++ + + +

SLC22A5 +++ ++ +++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

SLC22A6* - - - - - - - - - - - - - - -

SLC22A7* - - - - - - - - - - - - - - -

SLC22A8* - - - - - - - - - - - - - - -

SLC22A9* - - - - - - - - - - - - - - -

SLC25A13 +++ ++ +++ +++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

SLC28A1* - - - - - - - - - - - - - - -

SLC28A2 - - - - - - - . . . - - - + - - -

SLC28A3 - - - - - - + - - - + + + + +

SLC29A1 +++ ++ + +++ +++ +++ ++ ++ ++ ++ ++ ++ ++ +++ ++ +++

SLC29A2 +++ ++ ++ ++ + + ++ ++ + + + + + ++ ++

SLC29A3 ++ ++ +++ + ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

SLC29A4 ++ ++ +++ + ++ . . . + ++ + ++ ++ + + ++ ++

SLC31A1 +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ + +++ +++ +++ +++

SLC38A1 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

SLC38A2 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

SLC38A5 - + - ++ ++ ++ + + ++ + ++ + ++ ++ ++ ++

SLC47A1 + + +++ +++ ++ ++ ++ + ++ - - + ++ ++ ++

SLC47A2 - - - + . . . - - + - - + - - + -

SLCO1A2 - - - - - - + - - + - + + + -

SLCO1B1 - - + - + - - - - - - - - - -

SLCO1B3 - - +++ - +++ + . . . - - - + + - + -

SLCO1C1* - - - - - - - - - - - - - - -

SLCO2A1 ++ ++ + - - . . . + + ++ - ++ + ++ +++ ++ ++

SLCO2B1 - - ++ - . . . - - - - + - ++ +++ ++ +++

SLCO3A1 ++ ++ + ++ ++ ++ + ++ ++ + ++ ++ ++ ++ ++ ++

SLCO4A1 +++ ++ + ++ ++ +++ ++ ++ ++ +++ ++ + ++ ++ ++ ++ ++

SLCO4C1 - - + + . . . - - + - + + ++ ++ + ++

SLCO5A1 - - ++ - - - - + ++ - + / - + + + ++

SLCO6A1* - - - - - - - - - - - - - - -

AQP1 - - - + - ++ - - - - - +++ +++ ++ +++


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AQP7 - . . . - - - - - - - - - + + - -

AQP9 - - - - - - - - - - - + ++ + ++

ATP6V0C +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

ATP7A ++ ++ +++ ++ ++ ++ + ++ ++ + ++ ++ ++ ++ ++

ATP7B ++ ++ ++ ++ ++ + ++ - + + ++ ++ ++ ++ ++

KCNK9* - - - - - - - - - - - - - - -

MVP +++ ++ +++ +++ +++ ++ +++ +++ +++ ++ ++ + +++ +++ +++ +++

VDAC2 ++ ++ ++ ++ ++ + ++ + ++ ++ ++ ++ ++ ++ ++

VDAC3 +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ ++ ++ ++ ++

Nuclear receptors

AHR +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

AHRR + - - - + - + - - - - - - - -

AIP +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ + ++ ++ +++ ++ +++

ARNT +++ ++ +++ +++ +++ ++ ++ ++ ++ ++ ++ +++ +++ +++ +++

ARNT2 - ++ +++ + ++ + ++ . . . + + + ++ ++ ++ ++

CREBBP +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ + +++ +++ +++ +++

EP300 +++ ++ + +++ +++ +++ ++ ++ ++ ++ ++ ++ + +++ +++ +++ +++

ESR1 ++ + - - . . . - ++ - + - - + + + +

ESR2 - - - - . . . - - . . . - - - + + + +

FOXA2 - + +++ - ++ - - ++ - ++ ++ ++ ++ + ++

FOXO1 ++ + ++ ++ + + ++ + ++ ++ ++ ++ ++ ++ ++

HIF1A +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ ++ + +++ +++ +++ +++

HIF3A - - - ++ - - - . . . - - + / - ++ ++ + ++

HNF4A - - +++ - - + + - - ++ - + - - +

HSP90AA1 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

KEAP1 +++ ++ + +++ +++ +++ ++ +++ ++ +++ ++ ++ ++ ++ +++ +++

NCOA1 +++ ++ + +++ +++ +++ ++ ++ ++ ++ ++ ++ +++ +++ +++ +++

NCOA2 ++ ++ +++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

NCOA3 +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ + +++ +++ +++ +++

NCOR1 +++ ++ + +++ +++ +++ ++ +++ +++ ++ ++ ++ + +++ +++ +++ +++

NCOR2 +++ ++ +++ ++ +++ ++ +++ ++ ++ ++ ++ ++ +++ ++ +++

NFE2L2 +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

NR0B2 - - - - - - - - - + - - ++ - +

NR1H2 +++ ++ +++ ++ ++ + ++ ++ ++ + ++ ++ ++ ++ ++

NR1H3 ++ ++ ++ ++ ++ + ++ + ++ ++ + ++ ++ ++ ++


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NR1H4 - - ++ - - - - - - - - - + - -

NR1I2 - - - - . . . - + - - - - + + - +

NR1I3* - - - - - - - - - - - - - - -

NR3C1 +++ ++ + +++ +++ +++ ++ +++ ++ ++ ++ ++ ++ +++ ++ +++

NR3C2 - + - ++ ++ - + + - + ++ ++ ++ + ++

NR5A2 ++ + +++ - - - + + - - - ++ ++ + ++

PPARA ++ ++ + ++ ++ + + + + + ++ ++ ++ ++ ++

PPARD +++ ++ + ++ +++ +++ ++ +++ ++ ++ ++ ++ + ++ ++ ++ ++

PPARG +++ ++ +++ ++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

PPARGC1A - - - ++ + + ++ + ++ ++ + ++ ++ + +

PPARGC1B ++ ++ ++ ++ + + + + + - ++ ++ ++ ++ ++

PPRC1 +++ ++ + +++ ++ +++ +++ ++ ++ ++ + ++ ++ ++ ++ ++

PTGES3 +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

RARA +++ ++ + +++ ++ +++ ++ ++ +++ ++ + ++ ++ +++ ++ ++

RARB - - +++ + - - ++ ++ ++ ++ ++ ++ ++ ++ ++

RARG +++ ++ + ++ +++ +++ ++ +++ +++ ++ + ++ + ++ ++ +++ ++

RXRA +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ ++ + +++ +++ +++ +++

RXRB +++ ++ ++ +++ +++ ++ ++ ++ ++ ++ ++ ++ ++ ++ ++

RXRG - - - - - - - - - + - + ++ + +

THRA ++ ++ +++ +++ +++ ++ ++ ++ ++ ++ ++ ++ +++ ++ ++

THRB +++ ++ ++ +++ ++ + ++ + + + ++ ++ ++ ++ ++

TRIP11 +++ ++ + +++ +++ +++ ++ ++ ++ ++ ++ ++ +++ +++ ++ +++

VDR +++ ++ ++ ++ ++ ++ ++ ++ + + ++ + ++ ++ ++ +++

Other genes

BLMH +++ ++ +++ ++ ++ ++ ++ - ++ ++ ++ ++ ++ ++ ++

CRABP1 - + + - - + - - + + - ++ - + +

CRABP2 +++ ++ ++ ++ +++ + +++ +++ + ++ ++ + ++ ++ ++ +++

CYB5A - - - + + - + . . . - - - - + - +

GZMA - - - - - - - - - - - ++ ++ ++ ++

GZMB - + - - - - - - - - - ++ ++ ++ ++

MT1A ++ - +++ + ++ + - - +++ + + ++ ++ + ++

MT1B - - - - - - - + - - - - - - -

MT1F ++ ++ ++ ++ + - ++ ++ + + + ++ ++ ++ ++

MT1H* - - - - - - - - - - - - - - -

MT1M - - - ++ ++ - - - - - + ++ ++ + +


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MT1X +++ ++ + +++ +++ +++ ++ +++ +++ ++ ++ ++ + +++ +++ +++ ++

MT2A +++ ++ + +++ ++ +++ ++ +++ +++ ++ ++ ++ + ++ +++ ++ ++

MT3 - + - + - - - - - + - + - - -

MT4* - - - - - - - - - - - - - - -

MTHFR ++ ++ ++ ++ ++ + ++ ++ ++ ++ ++ ++ ++ ++ ++

POR +++ ++ + +++ +++ +++ ++ +++ +++ ++ ++ ++ + +++ +++ +++ +++

RBP1 - - ++ ++ - - ++ + - ++ ++ + ++ ++ ++ ++

RBP2 - - - - - - - - - - - - + - -

STX2 ++ ++ +++ +++ +++ ++ ++ + ++ ++ ++ ++ ++ ++ ++

TP53 +++ ++ + +++ +++ - ++ +++ - ++ + ++ ++ ++ ++ ++

TXN +++ ++ + +++ +++ +++ +++ +++ +++ +++ ++ + ++ + +++ +++ +++ +++

TXN2 +++ ++ + +++ +++ +++ ++ +++ +++ +++ ++ ++ + +++ +++ +++ +++

* Not detectable in all models


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Table 2

Genes exhibiting high interindividual variability (CV >10%) in primary cultures of HBEC.

Interindividual variability in gene expression is evaluated by calculation of the coefficient of

variation (CV = ∆Ct standard deviation / mean ∆Ct).

Genes Minimum ΔCt Maximum ΔCt Coefficient of variation

PhaseI enzymes

CYP4B1 17.09 23.85 15.41

CYP2W1 20.14 28.09 14.46

CYP11A1 22.04 28.91 13.83

CYP4A11/22 22.07 30.53 13.78

ALDH3B2 17.29 23.01 12.17

DHRS2 21.97 28.71 12.13

ALDH1A2 22.07 28.09 11.61

ALDH1A3 10.41 13.85 11.61

CYP26B1 18.49 24.55 11.49

ALDH3A1 15.75 19.96 11.16

FMO3 23.29 28.91 10.88

CYP4F11 15.04 19.14 10.38

ADH7 16.31 20.72 10.27

Phase II enzymes

GSTT1 17.34 30.53 28.58

GSTM1 20.80 30.53 19.82

INMT 21.62 28.91 15.11

UGT1A10 22.52 30.53 14.66

GSTT2/2B 17.48 23.78 13.44

UGT1A8 23.10 30.53 12.28

SULT2B1 13.03 16.93 10.89

Transporters

ABCA4 20.08 28.09 15.02

SLC7A5 11.68 14.83 13.06

SLCO4A1 16.41 21.86 12.85

SLC7A11 13.14 17.04 12.81

ABCC6 22.98 28.91 10.75

ABCB11 22.33 27.98 10.70

SLCO5A1 22.71 28.91 10.52


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Nuclear receptors and other genes

ARNT2 19.93 26.64 14.69

FOXA2 17.29 22.57 13.65

HIF3A 21.25 28.71 12.34

MT1X 12.01 15.71 12.61


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Table 3

Pearson’s correlation coefficient between lung cell lines, primary cultures of HBEC and lung

tissues.

The correlation matrix was calculated on the basis of ΔCt values. The numbers represent the

pairwise Pearson’s correlation coefficient r values. BM: bronchial mucosa; PP: pulmonary

parenchyma; AC: adenocarcinoma; SCC: squamous cell carcinoma.

A549 AC BEAS-2B Calu-1 H292 H358 H460 H727 HBEC SCC L-132 BM PP 16HBE 1HAEO

A549 1.000

AC 0.731 1.000

BEAS-2B 0.729 0.818 1.000

Calu-1 0.788 0.779 0.843 1.000

H292 0.775 0.776 0.853 0.833 1.000

H358 0.749 0.751 0.806 0.825 0.841 1.000

H460 0.811 0.756 0.825 0.819 0.805 0.787 1.000

H727 0.757 0.745 0.730 0.742 0.762 0.764 0.773 1.000

HBEC 0.783 0.820 0.844 0.837 0.867 0.821 0.807 0.778 1.000

SCC 0.766 0.933 0.790 0.770 0.775 0.749 0.788 0.730 0.851 1.000

L-132 0.758 0.740 0.828 0.825 0.814 0.786 0.846 0.769 0.806 0.761 1.000

BM 0.650 0.878 0.724 0.663 0.682 0.645 0.672 0.631 0.761 0.898 0.625 1.000

PP 0.621 0.942 0.764 0.694 0.690 0.656 0.673 0.666 0.727 0.849 0.651 0.864 1.000

16HBE 0.753 0.747 0.827 0.831 0.867 0.843 0.792 0.736 0.815 0.745 0.832 0.613 0.648 1.000

1HAEO 0.744 0.733 0.821 0.818 0.866 0.810 0.785 0.757 0.828 0.746 0.865 0.614 0.621 0.897 1.000


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Table 4

Number of genes differentially expressed between lung cell models and lung tissues.

Relative quantities (RQ) were calculated based on the comparative threshold cycle method

(RQ = 2-∆∆Ct), with BM (bronchial mucosa), PP (pulmonary parenchyma), AC

(adenocarcinoma) or SCC (squamous cell carcinoma) as calibrators. Only the genes that

exhibit at least a 4-fold difference in expression (RQ > 4 or < 0.25) were considered.

16HBE 1HAEO A549 BEAS-2B Calu-1 L-132 H292 H358 H460 H727 HBEC

Nb of Overexpressed genes/BM 92 41 112 27 62 8 24 14 23 20 21

Nb of Underexpressed genes/BM 128 147 89 132 134 233 138 173 167 220 137

Total 220 188 201 159 196 241 162 187 190 240 158

Nb of Overexpressed genes/PP 85 44 115 32 58 10 27 18 21 18 33

Nb of Underexpressed genes/PP 107 123 73 112 105 213 114 148 137 193 119

Total 192 167 188 144 163 223 141 166 158 211 152

Nb of Overexpressed genes/SCC 107 38 134 40 65 6 35 13 24 19 22

Nb of Underexpressed genes/SCC 105 111 52 102 101 210 105 129 128 179 87

Total 212 149 186 142 166 216 140 142 152 198 109

Nb of Overexpressed genes/AC 97 47 131 35 63 6 32 20 18 19 32

Nb of Underexpressed genes/AC 99 119 55 101 107 209 105 136 132 186 99

Total 196 166 186 136 170 215 137 156 150 205 131


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Xenobiotic metabolism and disposition in Human lung cell...

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