gene expression profiling of systems involved in the...

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Gene expression profiling of systems involved in the metabolism

and the disposition of xenobiotics: comparison between human

intestinal biopsies and colon cell lines.

Joanna Bourgine, Ingrid Billaut-Laden, Mélanie Happillon, Jean-Marc Lo-Guidice, Vincent

Maunoury, Michel Imbenotte, Franck Broly

Equipe d’accueil EA4483, Faculté de Médecine Pôle Recherche, Université Lille Nord de

France, Place de Verdun, 59045 Lille, France (JB, IBL, MH, JMLG, MI, FB)

Département de Gastroentérologie, Hôpital Claude Huriez, CHRU, Lille, France (VM)

DMD Fast Forward. Published on January 4, 2012 as doi:10.1124/dmd.111.042465

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 January 4, 2012 as DOI: 10.1124/dmd.111.042465

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Running title page

Running title: Xenobiotic metabolism and disposition in human intestine.

Corresponding author: Joanna Bourgine

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

Email: [email protected]

Number of Text pages: 17

Number of Tables: 5

Number of Supplemental Tables: 3

Number of Figures: 2

Number of References: 40

Words in Abstract: 248

Words in Introduction: 536

Words in Discussion: 1641

Abbreviations: ABC, ATP-binding cassette; Ct, threshold cycle; CYP, cytochrome P450; NR,

nuclear receptor; PCA, principal component analysis; PPIA, peptidylpropyl isomerase A;

RPLP0, 60S acidic ribosomal protein P0; RT-PCR, reverse transcription-polymerase chain

reaction; SLC, solute carrier; TLDA, TaqMan Low Density Array; XME, xenobiotic-

metabolizing enzyme.


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Abstract

Intestinal cell lines are used as in vitro models for pharmacological and toxicological studies.

However, a general report of the gene expression spectrum of proteins that are involved in the

metabolism and the disposition of xenobiotics in these in vitro systems is not currently

available. To fill this information gap, we systematically characterized the expression profile

of 377 genes encoding xenobiotic-metabolizing enzymes, transporters, nuclear receptors and

transcription factors in intestinal mucosa (ileum, ascending colon, transverse colon,

descending colon and rectum) from 5 healthy subjects and in 5 commonly used intestinal cell

lines (Caco-2, C2BBe1, HT29, T84 and FHC). For this, we performed a quantitative real-time

RT-PCR analysis using TaqMan Low Density Arrays (TLDA) and analyzed the results by

different statistical approaches, Spearman’s correlation coefficients, hierarchical clustering

and principal component analysis (PCA). A large variation in gene expression spectra was

observed between intestinal cell lines and intestinal tissues. Both hierarchical clustering and

PCA showed that two distinct clusters are visible, of which one corresponds to all cultured

cell lines, and the other to all intestinal biopsies. The best agreement between human tissue

and the representative cell line was observed for human colonic tissues and HT29 and T84.

Altogether, these data demonstrated that gene expression profiling represent a new valuable

tool for investigating in vitro and in vivo expression level correlation. This study has pointed

out interesting expression profiles for various colon cell lines, which will be useful for

choosing the appropriate in vitro model for pharmacological and toxicological studies.


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Introduction

Intestine is the primary site for ingested xenobiotics, including toxicants, carcinogens and

drugs. Three different groups of proteins are involved in the metabolism and disposition of

these compounds: enzymes, transporters and nuclear factors. Phase I xenobiotic-metabolizing

enzymes (XME) catalyze the first step of xenobiotic processing, referred to as xenobiotic

functionalization; they catalyze oxidation, reduction, hydrolysis, cyclization, and

decyclization reactions. The cytochrome P450 (CYP) enzyme superfamily, for example, plays

a dominant role in Phase I biotransformation. Phase II XME conjugate xenobiotics or their

phase I metabolites to glutathione, sulfate, glucuronide, methyl or acetyl moieties, making

molecules more hydrophilic and, consequently, more suitable for elimination. Transporters,

mainly of the solute carrier (SLC) and of the ATP-binding cassette (ABC) families, mediate

the influx of xenobiotics into cells or facilitate the efflux of xenobiotics or phase II

metabolites from cells. Tight coupling between phase I XME, phase II XME and transporters

is ensured by nuclear receptors (NR), which are ligand-activated transcription factors that

control constitutive and inducible expression of numerous genes, including XME and

transporter genes, in a coordinated manner (Nakata et al., 2006). Three major NRs (AhR,

PXR and CAR) are activated by xenobiotics and are therefore termed as xenosensors (Nakata

et al., 2006).

To better understand xenobiotic metabolic pathways, efficacies or toxicities, the establishment

of a reliable research model system remains a key challenge. During past decades, primary

intestinal cell cultures have been obtained from the small intestine (Perreault and Beaulieu,

1998; Aldhous et al., 2001) or from the colon (Baten et al., 1992; Fonti et al., 1994; Deveney

et al., 1996; Grossmann et al., 2003; Mohammadpour, 2005), but a rapid loss of the

differentiated characteristics of cells was observed. As consequences, these primary cell


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models could be utilized only for short-term toxicity studies. Intestinal cell lines, such as

Caco-2, C2BBe1, HT29, T84 and FHC are the most widely used in vitro models for

pharmacological and toxicological studies. These cell lines present several advantages

including their availability, growth rate, homogeneous cell population and reproducibility.

However, they are not fully representative of the tissues. For example, a large variation in

expression levels of drug metabolizing enzymes observed between cell lines and primary

culture (Guo et al., 2011).

Recently, many research groups have studied gene expression in human intestinal cells

(Taipalensuu et al., 2001; Nakamura et al., 2002; Sun et al., 2002; Pfrunder et al., 2003;

Anderle et al., 2004; van Erk et al., 2005; Seithel et al., 2006; Hilgendorf et al., 2007). To our

knowledge, there is no complete report available comparing intestinal cell lines with both

human ileum and colon, especially for systems involved in the metabolism and the disposition

of xenobiotics. Such informations would enhance our ability to predict potential

pharmacological and toxicological consequences of xenobiotic exposure in the intestinal

mucosa and would facilitate the data translation to the in vivo situation.

The aim of the present study was to investigate, using TaqMan Low Density Arrays (TLDA),

the expression profile of 377 genes encoding proteins that are involved in the metabolism and

the disposition of xenobiotics in five cell lines (Caco-2 and HT29 differentiated or not,

C2BBe1, T84 and FHC) and in intestinal mucosa from 5 different segments (ileum, ascending

colon, transverse colon, descending colon and rectum).


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Materials and methods

Tissues. Human tissues were obtained after written informed consent, in agreement with the

local ethics committee. Fresh biopsies were obtained from five healthy subjects of both

genders (aged 32-55) undergoing endoscopy. These patients were referred to the endoscopy

center because of abdominal cramp and diarrhea with unknown cause, irritable bowel

syndrome, polyp surveillance, obstipation and anemia of unknown cause. They had no

mucosal inflammation upon endoscopic and histologic examination. Biopsies were taken

from 5 different intestinal areas (ileum, ascending colon, transverse colon, descending colon

and rectum) using a standard biopsy forceps. Informations on age, sex and location of

biopsies are listed in Table 1. To preserve the RNA, intestinal specimens were immediately

placed in RNAlater (Ambion, Austin, TX), at 4°C for 16 hours, then stored at -20°C until

used.

Cell Cultures. Culture media and additives were obtained from Invitrogen (Cergy-Pontoise,

France). Caco-2, C2BBe1, HT29, T84 and FHC cells were purchased from The American

Type Culture Collection (Manassas, VA) (Table 2). Human colon carcinoma cell lines Caco-

2, C2BBe1 and HT29 were cultured in DMEM supplemented with 10% fetal calf serum, 2

mM L-glutamine, 100 units/mL penicillin G and 100 µg/mL streptomycin, as well as 1% non-

essential amino acid solution for the Caco-2 cell line and 10 µg/mL transferrin for the

C2BBe1 cell line. The human carcinoma cell line T84 derived from a lung metastasis of a

colon carcinoma was cultivated in DMEM : F12 (1:1) supplemented with 5% fetal calf serum,

2 mM L-glutamine, 100 units/mL penicillin G and 100 µg/mL streptomycin. The foetal

human colon cell line FHC was cultured in DMEM : F12 (1 : 1) supplemented with 10% fetal

calf serum, 10 ng/mL cholera toxin, 5 µg/mL ITS, 100 ng/mL hydrocortisone, 10 mM

HEPES, 100 units/mL penicillin G and 100 µg/mL streptomycin. All cultures were


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maintained at 37°C in 5% CO2. The passage number was 4 for all experiments performed in

each cell type (starting passage was determined as passage 1 after receipt from ATCC). Cells

were seeded into 6-well plates at 5 × 105 cells per well and grown to confluence (for 5 cell

lines) or to 14 days post-confluence (for differentiation of Caco-2 and HT29 cells) before the

RNA was isolated.

RNA Isolation. Before extraction, intestinal biopsies were homogenized in Buffer RLT Plus

(Qiagen, Courtaboeuf, France) supplemented with 1% β-mercaptoethanol, using a

gentleMACS™ Dissociator (Miltenyi Biotec, Paris, France). Cell lines were washed two

times with PBS, and lysed in an appropriate volume of Buffer RLT Plus supplemented with

1% β-mercaptoethanol. Total RNAs from biopsies or cell lines were extracted using the

RNeasy Plus Mini Kit™ (Qiagen), according to the manufacturer’s instructions. Elution was

performed with 50 µL RNase-Free water. RNAs were then precipitated for 12 h at -20°C by

addition of 3M sodium acetate/ice cold 100% ethanol (0.1V/2.5V). After centrifugation and

washing with 70% ethanol (200 µL), pellets were re-suspended in 10 µL RNase-Free water.

RNA concentration was determined using the BioSpec-nano (Shimadzu, Champs-sur-Marne,

France). The quality of RNA was evaluated using Experion RNA StdSens chips on an

Experion electrophoresis system (Bio-Rad laboratories, Hercules, CA).

cDNA Synthesis. Two µg of total RNAs were retrotranscribed into 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 data were obtained using TaqMan Low Density

Arrays (TLDA) (Applied Biosystems) which are 384-well micro fluidic cards preloaded with

sets of primers and 6-FAM labelled Taqman MGB probes that enables to perform 384

simultaneous real-time PCR runs and which has been used for gene expression profiling in


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several studies (Leclerc et al., 2010; Kodani et al., 2011). We chose a configuration with 379

different assays loaded in simplicate (listed in Tables 3, 4 and Supplemental Tables 1, 2 and

3), the last 5 wells being dedicated to other assays not detailed in this study.

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 (2x1 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. The real-time PCR

amplification was performed using an Applied Biosystems Prism 7900HT sequence detection

system with the following thermal cycler conditions: 2 min at 50°C and 10 min at 94.5°C,

followed by 40 cycles of 30 s at 97°C and 1 min at 59.7°C.

Relative Expression Analysis. The detection threshold was set at 0.3 for all genes, except 7

genes for which a threshold at 0.3 would have led to inaccurate quantification (AKR7L: 0.2,

ALDH16A1: 0.2, ALDH5A1: 0.1, CES2: 0.1, GSTM1: 0.1, PNMT: 0.2 and PON1: 0.1). The

threshold cycle (Ct) values were determined with the RQ Manager 1.2 software (Applied

Biosystems). We chose Ct value > 35 as the cutoff for non-expressed genes. Each Ct value

was normalized to the average Ct of the two endogenous controls, 60S acidic ribosomal

protein P0 (RPLP0) and peptidylpropyl isomerise A (PPIA), to correct for any tube-to-tube

variations in reverse transcription efficiencies and amount of total RNA added to each

reaction. The comparative ∆∆Ct method was used to calculate relative quantifications of gene

expression.

Data Analysis. Statistical analyses were performed using SPSS 17.0 (SPSS, Inc., Chicago, IL,

USA). Spearman’s correlation coefficients of all the ΔCt means values were calculated

between cell lines and intestinal segments. After ΔCt computation, unsupervised hierarchical


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clustering was performed with the Euclidean distance as an input parameter in the clustering

algorithm.

Principal component analysis (PCA), a standard, non-parametric tool that reduces a complex

data set to a lower dimension, was used for comparisons between different tissues and cell

lines. This analysis was carried out using ΔCt values. Two-dimensional plots were made,

using principal component 1 and 2 as axes.

An arbitrary classification system designating expression levels as high (ΔCt<6), moderate

(6≤ΔCt<10), and low levels (ΔCt ≥10), was applied to the data throughout the article.


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Results

In the current study, gene expression of 206 XMEs (137 phase I and 69 phase II enzymes),

102 transporters (including 30 ABC and 62 SLC transporters), 48 nuclear receptors and

transcription factors (including coactivators and corepressors) and 21 miscellaneous genes

(including 9 metallothioneins) was quantified in RNA samples from intestinal mucosa and

intestinal cell lines, using custom TaqMan™ Low Density Arrays (TLDA). Genes from each

cell lines were evaluated in comparison to expression levels of biopsies from 5 donors.

Expression level of systems involved in the metabolism and the disposition of xenobiotics in

intestinal biopsies

Gene expression profiles of intestinal biopsies (Table 1) were analyzed using TLDA. 21.7%

of genes were not detected (Ct>35) in RNA preparations from ileum and approximately 28%

from colon. Some families of genes were poorly expressed in the intestine. For example, 29

out of 54 (53.7%) CYPs genes and 21 out of 62 (33.9%) SLC genes were not detected in

transverse colon (Supplemental Table 1). 9.3% of genes encoding CYPs were expressed at

low levels (10≤ΔCt<14), 22.2% at moderate levels (6≤ΔCt<10) and 14.8% at high levels

(ΔCt<6) in transverse colon. We next calculated the relative abundance of each genes using

gene expression levels measured in transverse colon biopsies as references (Table 3 and

Supplemental Table 2). Approximate abundances of genes expressed in transverse colon

biopsies are listed as “Expression Value” in Table 3 and Supplemental Table 2, using

housekeeping genes RPLP0 and PPIA as references and expression value of each genes was

defined using the following equations:

ΔCt = [(Ct of target gene) - (average Ct of (RPLP0 and PPIA))] [1]

E=2-ΔCt*10 000 [2]


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The “Expression Value” implies the relative mRNA expression abundance of a gene,

arbitrarily assuming an expression level of the housekeeping genes RPLP0 and PPIA being

10000 copies. The Table 3 and Supplemental Table 2 is intended to provide very general

information about the gene expression in human transverse colon biopsies, in which the large

inter-individual variability of gene expression levels in human populations is certainly under-

represented.

Expression of 46 genes was significantly higher (at least 4 fold higher) and expression of 6

genes (CYP2E1, CYP2W1, DHRS9, UGT2B10, SLC16A1, and THRB) was significantly lower

(at least 4 fold lower) in ileum biopsies than in transverse colon biopsies (Table 3). In

descending colon biopsies, only CYP3A4 gene was significantly more expressed than in

transverse colon biopsies, and SLC6A4 gene was significantly less expressed. Expression of 7

genes (ALDH1A2, CYP2W1, CYP3A4, GSTT1, SULT1C2, SLC15A1 and SLC28A2) was

significantly higher in rectal biopsies than in transverse colon biopsies (Table 3 and

Supplemental Table 1) and expression of 12 genes (CYP2B6, CYP2C9, SLC6A4,

UGT2B17…) was significantly lower in rectal biopsies than in transverse colon biopsies

(Table 3). The most abundantly expressed genes in intestinal tissues were XMEs such as

UGT2B17, MAOA, GSTP1, MGST1 and CES2 (Table 3).

Expression level of systems involved in the metabolism and the disposition of xenobiotics in

intestinal cell lines

Gene expression profiles of 5 intestinal cell lines are described in Table 4 and Supplemental

Table 3. The relative abundance of each gene detected in each cell line was calculated, using

gene expression levels measured in transverse colon biopsies as references (Table 4).


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A higher proportion of genes was not detected in each cell line, with 31.8%, 29.2%, 32.4%,

40.8%, 41.1%, 42.4% and 42.4% of genes in Caco-2, differentiated Caco-2, C2BBe1, FHC,

HT29, differentiated HT29 and T84 cell lines, respectively.

Strikingly, several critical Phase I enzymes, such as CYP3A4, CYP7B1, ADH1B and BCHE

were not detected in any of the cell lines. Nevertheless, the ADH1B and CYP3A4 were found

to be weakly expressed in differentiated Caco-2 and HT29 cells, respectively (Table 4).

Among the expressed genes, between 18 and 44 genes, depending on the cell line, were barely

detectable with a relative abundance less than 5% of those in colon biopsies. CES2, one of

key Phase I enzymes, falls into this category. In all cell lines, abundances for the majority of

expressed genes were at a similar level (25%-400%) to colon biopsies. In addition, a few

genes have much higher abundances (~4-591 times higher) in cell lines. For example,

CYP26B1 was expressed over 250 times more in FHC cells than in colon biopsies. Notably,

although not detected in colon biopsies, several genes were found to be expressed in different

cell lines, such as CYP1A1 in Caco-2 (differentiated or not), C2BBe1, FHC and T84, making

these cell lines as potential surrogate tools for investigation of related XMEs (Supplemental

Table 3). Similarly, the relative abundances for Phase II XMEs, transporters and RNs are

listed for different intestinal cell lines compared to colon biopsies in the Table 4.

Differencies and Similarities between intestinal biopsies and intestinal Cell Lines.

Differences and similarities in gene expression patterns among intestinal cell lines and

intestinal biopsies are pronounced as indicated by the relative abundances of drug

metabolizing genes in different cells. To reveal similarities of gene expression patterns among

these cells, a similarity matrix was evaluated by a pairwise comparison of the samples (Table

5), in which the Spearman’s correlation coefficient (rs) was calculated based on the ΔCt

obtained for each gene. Generally, similarities among intestinal biopsies isolated from the


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different donors (with rs values between 0.914-0.992) were higher than the similarities among

the different intestinal cell lines (with rs values between 0.703-0.980).

Among these 5 intestinal cell lines, the highest rs value of 0.980 was observed between Caco-

2 and C2BBe1, while the lowest rs value of 0.703 was found between differentiated Caco-2

and HT29. More importantly, the similarities between intestinal cell lines and the intestinal

biopsies were lower with rs values between 0.620-0.783. The highest similarity (rs = 0.783)

was observed between T84 cells and ascending colon biopsies while the lowest similarity (rs

= 0.620) was observed between FHC cells and ileal biopsies (Table 5). Interestingly, in terms

of gene expression levels, the most often used intestinal cell lines HT29 and Caco-2 were

relatively different from the intestinal biopsies with rs values between 0.672 and 0.747 (Table

5).

To visualize directly the distances of gene expression patterns among different intestinal cell

lines and intestinal biopsies, a hierarchical cluster analysis (HCA) was performed. Figure 1

shows a dendrogram of 4 clusters based on their gene expression levels. Two major clusters

were clearly separated, one consisted of 5 intestinal cell lines and the other consisted of

intestinal biopsies. In the cell line cluster, HT29 and T84 profiles were separated from those

of other cells (Caco-2, C2BBe1 and FHC). In the intestinal biopsy cluster, profiles of ileal

biopsies were separated from profiles of colon biopsies, except for ileal biopsy from patient 2.

Furthermore, similarities and differences in gene expression levels between intestinal biopsies

and intestinal cell lines were further illustrated by principal component analysis (PCA). The

plot shown in Figure 2 is a simple scatter plot of the first two principal components (PC). PC1

and PC2 explain 42.2% and 16.49% of the total variation, respectively. Distance of separation

between clusters is indicative of degree of similarity on a gene level; a greater distance is

equivalent to reduced similarity. Along PC1, two distinct clusters were visible, one

corresponds to all cultured cell lines, and the other to all intestinal biopsies. In the cluster of


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the cell lines, two sub-clusters exist along PC2 corresponding to profiles from HT29 together

with T84 cells, and Caco-2 together with C2BBe1 cells. PC1 was negatively correlated with

the expression of SLC7A11, SLC7A5, AHRR and CRABP2, and positively correlated with

ADH1B, ADH5, AOC3, CES2, FMO5, NAT2, UGT2B17, ABCC8, SLC18A2, SLC22A5,

NCOR1, RXRG, GZMA and GZMB, for example. PC2 was negatively correlated with the

expression of GSTT1, TBXAS1, SLC38A5 and SLCO5A1, and positively correlated with

AKR1D1, AKR1E2, ALDH7A1, ABCA3, ABCC9, SLC1A3, SLC29A4, CRABP1 and AIP, for

example.


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Discussion

This study provides an overview of gene expression profiles of phase I and phase II XMEs,

transporters, NRs and transcription factors in human intestinal tissues, as well as in intestinal

cell lines.

Expression analysis was carried out using a real-time quantitative RT-PCR strategy based on

TaqMan Low Density Arrays (TLDA). This biotechnology allows to measure simultaneously

mRNA expression of 380 genes for a single sample, and is considered as one of the most

robust, sensible, reproducible and reliable techniques for high throughput screening in

functional genomics. On the basis of a careful and extensive review of the literature and of

human genome sequence data bases, we identified 377 genes known or suspected to code for

XME, xenobiotic transporters or nuclear factors involved in xenobiotic cellular processing.

Many genes, such as CYP, ADH, FMO, UGT, GST and MT, are clustered in the same

chromosomal regions and their nucleotide and amino acid sequences show high homology.

The high specificity of the TaqMan primers and probe sets enables discrimination among

closely related members of gene families.

RNA expression data do not always correlate with the expression of encoded protein. To fully

align mRNA data with protein expression profiles, a protein expression analysis of all the

proteins would be necessary. However, quantification of all proteins remains a major

technical challenge in proteomics, and, until this issue is solved, quantitative mRNA analysis

is the most viable alternative. Consequently, we used mRNA profiles to estimate the

expression patterns of the 377 proteins investigated in this study.

Quantification with RT-PCR technology uses housekeeping genes as a reference. There has

recently been vigorous debate in the literature about how best to achieve this and about which

housekeeping genes are suitable (Tricarico et al., 2002; Dydensborg et al., 2006; Said et al.,


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2009). The principle for choice of internal reference genes is that they should be unregulated

in all samples of interest and their amplification behavior should be comparable to that of the

genes of interest. If not all these prerequisites are taken into consideration, it could well be

impossible to build a relative expression analysis on one single reference gene.

The optimal internal reference gene for the comparison over all samples was determined using

the GeNorm algorithm software (Vandesompele et al., 2002). A panel of 16 potentially

suitable housekeeping genes was analyzed for 8 cDNA sample (data not shown). As RPLP0

and PPIA mRNA displayed the smallest coefficients of variation between tissues and between

patients (CVRPLP0 < 1.89%, CVPPIA < 2.1%), they were selected as reference genes for

normalization of target gene data in this study. Although the coefficient of variation looked

best for 18S mRNA, it was decided to exclude 18S mRNA, since it had Ct values around 10,

making it clearly different from the target genes, which had Ct values between 20 and 40. The

maximal-fold intrinsic variance in the sample set was low, which allows quantitative

comparison between all samples included in the analysis.

In this study, mRNA expression profiles of 377 genes encoding proteins that are involved in

the metabolism and the disposition of xenobiotics were investigating for the first time in

biopsies from 5 different intestinal areas (ileum, ascending colon, transverse colon,

descending colon and rectum). Apart from cytochromes P450 (Obach et al., 2001; Bergheim

et al., 2005; Zhang et al., 2007), there are very limited data available on other genes expressed

in human intestinal tissues (Kaminsky and Zhang, 2003; Anderle et al., 2004; Hilgendorf et

al., 2007). Hierarchical clustering revealed that profiles of ileal biopsies were separated from

profiles of colon biopsies. Many genes, encoding XMEs (i.e. AADAC, CBR1, CYP2C9,

CYP2D6, CYP3A4, FMO1, GSTA1, SULT1E1, SULT2A1…) and transporters (i.e. ABCC2,

ABCG8, SLC10A2, SLC15A1, SLC28A1, SLC6A4…), were over-expressed in the small


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intestine compared to colon, indicating major differences in the metabolism and disposition of

xenobiotics, between these two tissues (Table 3). This can be explained by different functions

of these two segments. Indeed, while the small intestine function comprises the major part of

the digestion processes, wherein most of the food gets absorbed, the large intestine function in

digestion mostly pertains to absorption of water and excretion of solid wastes through the

anus.

Furthermore, hierarchical clustering revealed that the gene expression profile of ileal biopsy

from patient 2 was separated from profiles of ileal biopsies from patients 1 and 5. The

variability of gene expression among humans is largely attributed to genetic and

environmental factors. Genetic polymorphisms, including single nucleotide polymorphism

(SNP), copy number variation (CNV), and insertion and deletion variations, contribute greatly

to gene expression profiles, drug metabolisms, and clinical impacts. In addition,

environmental factors such as exogenous inducers, inhibitors and/or intestinal disorders may

produce more heterogeneous gene expression and xenobiotic responses. Wojtal et al. (2009)

observed a statistically significant increased in expression of SLC15A1 mRNA, in ileum and

colon of inflammatory bowel disease (IBD) patients. The intestinal SLC mRNA levels are

dysregulated in IBD patients, which may be linked to the inflammatory status of the affected

tissue (Wojtal et al., 2009).

In the current study, similarities and differences in gene expression levels, between intestinal

biopsies and 5 intestinal cell lines, were observed using Spearman rank correlation

coefficient, principal component analysis, and hierarchical clustering analysis. These

similarity comparison analyses suggest that intestinal cell lines only partially reflect the gene

expression characteristics of intestinal tissues, indicating their limitations as surrogate cell

models for human intestinal epithelial cells in toxicological and pharmacological studies.


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This could be partly explained by the tumoral origin of the cell lines. Four of the five cell

lines directly originate from colon cancer (Caco-2, C2BBe1, HT29 and T84). And the FHC

cell line, which has been established from fetal colonic mucosa, exhibits tumorigenic

phenotype (Soucek et al., 2010). Chromosomal aberrations including gene amplification, gene

deletion and heteroploidy are common events in carcinogenesis, which introduces gene

dosage differences between normal cells and transformed cell lines.

Furthermore, in comparison with the in vivo situation with influences from different

neighbouring cells, (neuro)endocrine regulators and blood flow, the in vitro model is

relatively simple. Although this is ideal for specific research questions, it complicates the

translatability of in vitro results to in vivo situations. In addition, cell culture environments,

such as the composition of the culture medium and the oxygen concentration, can alter gene

expression profiles in cell lines (Warabi et al., 2004; Brunet De La Grange et al., 2006).

Above all, it is not clear if cells in culture retain gene expression profiles of their in vivo

counterparts. A study regarding the gene expression patterns in 60 human cancer cell lines,

including colon cancer cell lines, revealed that the tissue from which the cells are derived is

the main factor accounting for the variation in gene expression (Ross et al., 2000).

To avoid all these changes in the expression profile, it would be preferable to use primary

cultures for toxicological studies. Primary cultures have been described in other tissues, such

as liver (LeCluyse, 2001) or kidney (Brown et al., 2008), as having a genetic profile similar to

native tissue. However, primary human cells have high variability, short life spans, and

limited availability. Moreover, primary cultures of human intestinal epithelial cells are

difficult to obtain to date. Consequently, intestinal cell lines, which are relatively easy to

maintain in culture, are widely used for transport and toxicity studies of xenobiotics and

therapeutic agents.


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Caco-2 cells were derived from a human colon adenocarcinoma, and they differentiate

spontaneously in vitro under standard culture conditions thereby exhibiting enterocyte-like

structural and functional characteristics. In differentiated state, they mimic typical

characteristics of the human small intestinal epithelium, like a well-developed brush border

with associated enzymes such as alkaline phosphatase and sucrase isomaltase. Nevertheless,

the Caco-2 cell model is different from the small intestine in several aspects, and their

phenotype is dependent on the time in culture (Mehran et al., 1997; Engle et al., 1998).

Interestingly, our results reveal a relatively good correlation between Caco-2 cells and human

colon with a Spearman’s correlation coefficient of 0.7.

The HT29 cell line is also of human colon adenocarcinoma origin, and is described as in vitro

model of normal epithelial cells since they can reversibly display some structural and

functional features resembling those of human normal mature intestinal epithelial cells

(Andoh et al., 2001). Comalada et al. had observed that a confluent culture of HT29

(differentiated culture) showed characteristics of normal epithelial cell (Comalada et al.,

2006). For the expression of our 377 genes, differentiated HT29 cells and human colonic

tissues don’t appear to differ significantly (rs=0.75).

Up to now, Caco-2 and HT29 cell lines have proved to be the best models for studies of

intestinal absorption and toxicity of xenobiotics. Nevertheless, studies have shown that

several proteins, including transporters, are over- or under-expressed in those cell lines, in

comparison to human intestinal tissues (Calcagno et al., 2006; Seithel et al., 2006; Hilgendorf

et al., 2007; Lenaerts et al., 2007). It needs to be considered by scientists using these cell lines

to prevent misinterpretation of in vitro obtained findings when translating them to the in vivo

situation. Our results showed that the best agreement between human tissue and the

representative cell line was observed for human colonic tissues and HT29 and T84 for

expression of 206 XMEs, 102 transporters, 48 nuclear receptors and transcription factors and


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21 miscellaneous. And the large gap observed on the PCA between the HT29 cluster and the

Caco-2 cluster suggests this latter cell line seems not to be the best in vitro model for

toxicological and pharmacological studies.

In conclusion, this study was designed to compare expression profiles of widely used

intestinal cell models with their in vivo counterparts. PCA and hierarchical clustering analysis

revealed that gene expression of intestinal biopsies differed considerably with that of

intestinal epithelial cell lines. Expression profiles of colon cell lines will be useful for

choosing the appropriate model system for toxicological and pharmacological studies.


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Acknowledgments

We thank Dr. Julie Leclerc for her scientific and technical contribution. We are grateful to Dr.

Bruno Lefebvre for a final proof-reading assistance.


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Authorship contributions

Participated in research design: Broly F and Lo-Guidice JM.

Conducted experiments: Bourgine J, Billaut-Laden I and Happillon M.

Contributed new reagents or analytic tools: Maunoury V, Broly F and Lo-Guidice JM.

Performed data analysis: Bourgine J and Billaut-Laden I.

Wrote or contributed to the writing of the manuscript: Bourgine J, Billaut-Laden I, Lo-

Guidice JM and Imbenotte M.


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Footnotes

This work was supported by the Centre Hospitalier Régional et Universitaire (CHRU) de

Lille, the Université de Lille 2, the Fonds européen de développement régional (FEDER), the

Institut de Recherche en Environnement Industriel (IRENI) and the Conseil Régional du Nord

Pas-de-Calais.


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Legends for figures

Figure 1 Hierarchical clustering of colon cell lines and intestinal biopsies. The

dendrogram represents the relationship of gene expression profiles. The lengths of the arms

are proportional to the similarities of gene expression profiles, with shorter arms indicating

closer relationships. After ΔCt computation, this clustering analysis identified two distinct

clusters based on the similarity of their gene expression profiles, separating colon cell lines

and intestinal biopsies.

Figure 2 Principal component analysis of gene expression profiles generated from five

colon cell lines (Caco-2, C2BBe1, HT29, T84 and FHC) and intestinal biopsies from five

segments (ileum, ascending colon, transverse colon, descending colon and rectum). Samples

are labelled with different symbols. Closed symbols are colon cell lines, while open symbols

are intestinal biopsies. For the XMEs genes, transporters genes, nuclear receptors and

transcription factors genes, the relative contribution of the ΔCt variance is shown by two

major principal components (PC1 and PC2) plotted in two dimensions.


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Tables

Table 1 Description and origin of human intestinal biopsies.

Patient Age

(years) Sex

Location of biopsies

Ileum Ascending

colon

Transverse

colon

Descending

colon Rectum

1 32 Male X X X X X

2 55 Male X

3 52 Male X X X

4 48 Female X X X

5 48 Male X X X


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Table 2 Description and origin of human colon cell lines

Cell line Origin Derived from

Purchased from

ATCC at

passage number

Caco-2 Caucasian male, 72 years Colorectal adenocarcinoma 18

C2BBe1 Caucasian male, 72 years Colorectal adenocarcinoma 47

HT29 Caucasian female, 44 years Colorectal adenocarcinoma 128

T84 Male, 72 years Colorectal carcinoma, metastatic site (lung) 53

FHC 13 weeks gestation Normal colon 16


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Table 3 Relative abundance of XMEs, transporters, nuclear receptors and transcription

factors whose expression levels vary in ileum or along the colon. Percent are expressed

compared to transverse colon expression value (for each gene transverse colon expression is

baseline (=100%)).

Assay ID Gene name Expression

valuea in TC I (%) CA (%) CD (%) R (%)

Phase I enzymes

Hs00175631_m1 ABP1 2384 191 84 93 96

Hs00605175_m1 ADH1B 224 87 77 95 180

Hs00817827_m1 ADH1C 2688 39 88 55 53

Hs00923466_m1 ADH4 9 140 99 82 70

Hs00605185_m1 ADH5 123 131 82 83 86

Hs00167423_m1 ADH6 70 138 84 67 42

Hs00329084_m1 ADHFE1 30 73 59 99 108

Hs00195992_m1 AKR1A1 660 214 92 89 94

Hs00252524_m1 AKR1B10 1400 191 103 58 32

Hs00413886_m1 AKR1C1;AKR1C2 52 73 74 68 58

Hs00366267_m1 AKR1C3 1091 187 112 69 48

Hs00230170_m1 AKR1E2 55 51 67 106 65

Hs00761005_s1 AKR7A2 181 129 107 85 115

Hs00792041_gH AKR7A3 909 207 87 68 56

Hs00292269_m1 ALDH16A1 3 82 70 ND 105

Hs00913261_m1 ALDH18A1 1415 92 76 95 57

Hs00167445_m1 ALDH1A1 380 217 111 71 59


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Hs00167476_m1 ALDH1A3 32 260 49 78 109

Hs00377718_m1 ALDH1B1 160 70 94 87 65

Hs00201836_m1 ALDH1L1 137 26 64 35 23

Hs00355914_m1 ALDH2 2059 112 106 71 60

Hs00964880_m1 ALDH3A1 76 31 114 39 47

Hs00166066_m1 ALDH3A2 1078 107 90 65 62

Hs00167488_m1 ALDH3B1 82 302 99 80 103

Hs00186689_m1 ALDH4A1 38 74 116 70 76

Hs00153566_m1 ALDH5A1 55 129 73 68 86

Hs00194421_m1 ALDH6A1 364 108 92 67 69

Hs00609622_m1 ALDH7A1 410 71 81 69 59

Hs00355924_m1 ALDH9A1 420 125 86 75 83

Hs00186647_m1 AOC3 77 85 67 111 173

Hs00154079_m1 AOX1 3 147 106 162 201

Hs00163746_m1 BCHE 5 134 40 97 155

Hs00156323_m1 CBR1 231 411 133 70 71

Hs00275607_m1 CES1 67 77 100 60 72

Hs00187279_m1 CES2 3486 203 78 84 93

Hs00227775_m1 CES3 1100 64 72 82 72

Hs00164383_m1 CYP1B1 19 71 32 62 32

Hs00219866_m1 CYP26B1 12 112 216 59 53

Hs01026016_m1 CYP27A1 383 137 57 65 60

Hs03044634_m1 CYP2B6 363 110 70 26 11

Hs01595322_mH CYP2C18 171 519 155 52 17

Hs00426380_m1 CYP2C19 19 658 147 73 9


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Hs00426397_m1 CYP2C9 17 1351 132 56 ND

Hs00559370_m1 CYP2E1 3 ND 59 108 94

Hs00951113_m1 CYP2J2 264 354 86 89 129

Hs01379776_m1 CYP2R1 64 127 89 122 101

Hs00258076_m1 CYP2S1 212 171 74 107 144

Hs00766273_m1 CYP2U1 36 321 75 92 111

Hs00214994_m1 CYP2W1 3 ND ND 209 1426

Hs00213201_m1 CYP39A1 11 120 80 167 287

Hs00430021_m1 CYP3A4 4 11292 74 639 932

Hs00241417_m1 CYP3A5 172 156 42 76 79

Hs01680107_m1 CYP4F11 4 566 66 100 323

Hs00430602_g1 CYP4F12 188 110 100 88 54

Hs00426608_m1 CYP4F2 56 1510 54 52 30

Hs01389878_m1 CYP4V2 64 299 101 115 133

Hs00380077_m1 CYP4X1 3 115 108 90 135

Hs00426415_m1 CYP51A1 325 122 108 74 106

Hs00191385_m1 CYP7B1 14 62 57 86 152

Hs00949075_m1 DHRS4 235 223 100 95 88

Hs00608375_m1 DHRS9 1529 19 116 59 31

Hs00559279_m1 DPYD 141 173 74 86 86

Hs01116807_m1 EPHX1 434 71 63 63 70

Hs00157403_m1 EPHX2 581 213 101 80 89

Hs00382667_m1 ESD 330 73 85 83 84

Hs00157614_m1 FMO4 73 117 80 61 53

Hs00356233_m1 FMO5 809 151 76 94 110


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Hs00400708_m1 KDM1B 390 63 70 78 81

Hs00165140_m1 MAOA 4777 160 88 78 85

Hs00168533_m1 MAOB 94 567 80 78 69

Hs00168547_m1 NQO1 1382 38 81 50 29

Hs00168552_m1 NQO2 43 120 48 117 93

Hs00382210_m1 PAOX 28 168 96 71 47

Hs00165563_m1 PON2 604 90 70 89 103

Hs00412993_m1 PON3 7 232 123 133 156

Hs00919949_m1 PTGIS 9 86 73 87 208

Hs00268403_m1 SPR 398 62 75 76 85

Hs00166578_m1 SUOX 111 73 102 72 62

Hs00233423_m1 TBXAS1 114 87 74 80 115

Hs00166010_m1 XDH 408 259 97 97 154

Phase II enzymes

Hs00221125_m1 AS3MT 12 95 56 103 101

Hs00980756_m1 GGT1 177 265 119 111 122

Hs00275575_m1 GSTA1 63 3268 127 115 151

Hs00155308_m1 GSTA4 46 118 87 94 175

Hs02341469_m1 GSTM1 7 44 ND 51 39

Hs00168307_m1 GSTM3 51 136 97 87 97

Hs00426432_m1 GSTM4 216 164 88 73 73

Hs00757076_m1 GSTM5 20 72 44 94 114

Hs00818731_m1 GSTO1 258 177 97 95 106

Hs00826661_m1 GSTO2 40 76 66 71 77

Hs00168310_m1 GSTP1 4243 79 80 73 82


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Hs00184475_m1 GSTT1 21 89 100 67 954

Hs00199373_m1 HNMT 698 49 72 78 56

Hs00198941_m1 INMT 5 181 75 172 280

Hs00220393_m1 MGST1 3534 53 95 68 40

Hs00182064_m1 MGST2 739 129 86 80 96

Hs01058946_m1 MGST3 2578 102 87 75 62

Hs00560401_m1 MPST 2249 128 104 83 60

Hs00377717_m1 NAT1 3 73 86 80 ND

Hs00605099_m1 NAT2 54 123 96 95 51

Hs02340929_g1 SULT1A2 215 175 90 85 56

Hs00413970_m1 SULT1A3;SULT1A4 25 133 96 154 68

Hs00234899_m1 SULT1B1 1190 97 66 73 58

Hs00169044_m1 SULT1C2 1 232 156 353 1976

Hs00198159_m1 SULT1C4 3 295 134 296 307

Hs00190268_m1 SULT2B1 30 502 111 43 18

Hs00361812_m1 TST 2719 60 94 64 56

Hs02511055_s1 UGT1A1 261 378 39 62 36

Hs02516990_s1 UGT1A10 2279 71 82 57 35

Hs01655285_s1 UGT1A4 33 96 58 83 39

Hs01374521_s1 UGT1A5 32 122 51 72 34

Hs01592477_m1 UGT1A6 7 212 90 70 51

Hs02517015_s1 UGT1A7 242 39 45 78 42

Hs01592482_m1 UGT1A8 1043 72 88 68 35

Hs02516855_sH UGT1A9 91 47 47 75 41

Hs00226904_m1 UGT2A3 813 183 84 75 74


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Hs02556282_s1 UGT2B10 6 19 29 95 37

Hs01894900_gH UGT2B11 4 152 121 152 70

Hs00854486_sH UGT2B17 9575 112 102 59 24

Hs00426592_m1 UGT2B7 19 654 65 187 167

Transporters

Hs01059122_m1 ABCA1 385 37 65 73 62

Hs00242232_m1 ABCA2 43 74 69 86 105

Hs00975530_m1 ABCA3 12 182 91 134 169

Hs01105117_m1 ABCA7 40 86 114 100 65

Hs00992371_m1 ABCA8 138 64 62 98 109

Hs00184491_m1 ABCB1 175 217 44 96 90

Hs01085315_m1 ABCB10 213 118 82 85 69

Hs00184824_m1 ABCB11 122 <5 25 31 8

Hs00240956_m1 ABCB4 7 135 76 128 128

Hs00180568_m1 ABCB6 69 151 92 85 76

Hs00608640_m1 ABCB9 35 100 85 71 40

Hs00219905_m1 ABCC1 64 78 86 61 62

Hs00375716_m1 ABCC10 67 146 106 117 97

Hs00358656_m1 ABCC3 637 62 84 71 61

Hs00195260_m1 ABCC4 111 51 49 87 72

Hs00981089_m1 ABCC5 42 73 92 100 108

Hs00184566_m1 ABCC6 39 339 109 148 128

Hs00245340_m1 ABCD4 98 140 83 93 88

Hs01053787_m1 ABCG2 1030 152 64 75 39

Hs02880035_m1 ABCG8 4 1403 109 52 ND


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Hs00166067_m1 AQP1 111 360 80 93 180

Hs00163707_m1 ATP7A 34 105 72 98 106

Hs00245438_m1 MVP 2642 155 127 117 100

Hs00166561_m1 SLC10A2 5 8539 21 37 ND

Hs00192639_m1 SLC15A1 14 2612 35 237 684

Hs00221539_m1 SLC15A2 15 80 98 113 369

Hs00161826_m1 SLC16A1 2611 20 84 53 22

Hs00161858_m1 SLC18A2 10 105 62 99 85

Hs00953345_m1 SLC19A1 124 149 66 70 32

Hs00949693_m1 SLC19A2 58 75 72 133 87

Hs00375596_m1 SLC19A3 57 76 63 87 55

Hs00188172_m1 SLC1A1 432 251 93 81 36

Hs00188193_m1 SLC1A3 11 48 65 107 142

Hs00427554_m1 SLC22A1 3 34 80 112 ND

Hs00222691_m1 SLC22A3 3 175 164 ND ND

Hs00268200_m1 SLC22A4 20 335 61 123 138

Hs00929869_m1 SLC22A5 379 91 82 70 56

Hs00185185_m1 SLC25A13 300 78 89 71 69

Hs00188407_m1 SLC28A2 29 2868 111 137 1050

Hs00223220_m1 SLC28A3 2 150 26 ND 287

Hs01085706_m1 SLC29A1 56 83 84 89 125

Hs00155426_m1 SLC29A2 26 45 97 87 108

Hs00983219_m1 SLC29A3 56 64 90 62 100

Hs00542001_m1 SLC29A4 21 171 68 119 193

Hs00197884_m1 SLC2A1 198 45 95 68 108


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Hs00977268_g1 SLC31A1 505 153 70 68 90

Hs01562168_m1 SLC38A1 1979 50 83 65 79

Hs01012028_m1 SLC38A5 125 45 71 86 85

Hs00165789_m1 SLC3A1 167 284 66 99 19

Hs00374243_m1 SLC3A2 336 112 66 83 86

Hs00217320_m1 SLC47A1 20 73 79 80 71

Hs00169010_m1 SLC6A4 25 1608 75 23 ND

Hs00204928_m1 SLC7A11 17 61 66 79 141

Hs00185826_m1 SLC7A5 17 130 158 63 77

Hs00909952_m1 SLC7A7 41 675 74 105 74

Hs00794796_m1 SLC7A8 188 120 65 77 122

Hs00200670_m1 SLCO2B1 194 126 70 76 73

Hs00203184_m1 SLCO3A1 27 59 67 80 125

Hs00249583_m1 SLCO4A1 36 73 84 124 123

Hs00698884_m1 SLCO4C1 11 202 111 95 98

Hs00229597_m1 SLCO5A1 22 63 70 97 131

Hs00388682_m1 TAP1 788 117 94 89 72

Hs00241060_m1 TAP2 190 145 81 96 85

Nuclear receptors and transcription factors

Hs00610222_m1 AIP 281 97 70 78 63

Hs00208298_m1 ARNT2 16 148 75 130 157

Hs00231733_m1 CREBBP 530 98 60 84 91

Hs00230938_m1 EP300 622 90 64 77 84

Hs00230957_m1 ESR2 11 36 101 59 75

Hs00232764_m1 FOXA2 52 55 61 114 259


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Hs01054576_m1 FOXO1 127 76 65 69 89

Hs00541709_m1 HIF3A 7 91 94 187 232

Hs00604435_m1 HNF4A 2650 92 77 82 73

Hs00743767_sH HSP90AA1 2627 126 98 91 83

Hs00186661_m1 NCOA1 655 119 61 86 104

Hs00896106_m1 NCOA2 170 119 75 87 101

Hs00196955_m1 NCOR2 212 98 74 108 110

Hs00222677_m1 NR0B2 4 2231 87 117 238

Hs00173195_m1 NR1H2 71 144 102 101 95

Hs00172885_m1 NR1H3 137 104 78 66 43

Hs00231968_m1 NR1H4 115 546 179 56 10

Hs00243666_m1 NR1I2 576 114 75 89 53

Hs00353740_m1 NR3C1 122 216 90 118 142

Hs01031809_m1 NR3C2 431 85 70 97 89

Hs00187067_m1 NR5A2 452 138 73 96 98

Hs00231882_m1 PPARA 97 119 91 69 78

Hs00602622_m1 PPARD 536 58 127 87 76

Hs01115513_m1 PPARG 998 37 89 75 41

Hs00173304_m1 PPARGC1A 198 65 59 89 83

Hs00370186_m1 PPARGC1B 184 72 93 74 114

Hs00209379_m1 PPRC1 81 61 75 83 96

Hs00940446_m1 RARA 162 153 100 87 83

Hs00233407_m1 RARB 23 80 78 47 50

Hs01559234_m1 RARG 50 60 98 117 171

Hs01067640_m1 RXRA 1352 76 84 77 65


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Hs00232774_m1 RXRB 155 133 104 100 105

Hs00199455_m1 RXRG 13 105 59 93 121

Hs00268470_m1 THRA 287 116 81 75 79

Hs00230861_m1 THRB 160 25 18 139 128

Hs01045840_m1 VDR 1651 81 71 78 81

Other genes

Hs00171635_m1 CRABP1 7 151 43 110 74

Hs00275636_m1 CRABP2 3 94 90 210 130

Hs00196206_m1 GZMA 134 90 52 63 41

Hs00188051_m1 GZMB 7 78 98 64 47

Hs00831826_s1 MT1A 49 127 32 115 150

Hs00744661_sH MT1F 496 150 66 107 98

Hs00823168_g1 MT1H 6 101 34 75 107

Hs00828387_g1 MT1M 280 111 38 145 166

Hs00745167_sH MT1X 1606 98 52 78 71

Hs02379661_g1 MT2A 487 106 49 91 98

Hs00359394_g1 MT3 6 51 146 149 125

Hs00287016_m1 POR 595 173 81 81 73

Hs00161252_m1 RBP1 46 80 74 53 53

Hs00188160_m1 RBP2 7 9275 130 116 114

Hs00153349_m1 TP53 197 63 75 68 97

Hs00828652_m1 TXN 3791 70 82 105 103

I, Ileum; AC, Ascending Colon; TC, Transverse Colon; DC, Descending Colon; R, Rectum.

aExpression value is a relative number calculated based on the assumption that the average expression level

of two housekeeping genes RPLP0 and PPIA is 10 000 copies.


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Table 4 Relative abundance of XMEs, transporters, nuclear receptors and transcription

factors expressed in colon cell lines and transverse colon biopsies. Percent are expressed

compared to transverse colon expression value (for each gene transverse colon expression is

baseline (=100%)). 106 genes are not expressed in transverse colon biopsies and are not

represented in this table (for further details see Supplemental Table 3).

Assay ID Gene name Expression

valuea in TC

Caco-2

(%)

Caco-2

D14

(%)

C2BBe1

(%)

FHC

(%)

HT29

(%)

HT29

D14

(%)

T84

(%)

Phase I enzymes

Hs00175631_m1 ABP1 2384 <5 <5 <5 ND <5 16 <5

Hs00605175_m1 ADH1B 224 ND <5 ND ND ND ND ND

Hs00817827_m1 ADH1C 2688 <5 <5 ND ND <5 ND <5

Hs00923466_m1 ADH4 9 55 357 113 ND ND ND ND

Hs00605185_m1 ADH5 123 22 51 35 28 20 57 21

Hs00167423_m1 ADH6 70 26 25 16 ND <5 7 <5

Hs00329084_m1 ADHFE1 30 ND ND ND 49 ND ND ND

Hs00195992_m1 AKR1A1 660 34 36 32 61 27 88 43

Hs00739326_m1 AKR1B1 270 132 78 227 454 ND ND 6

Hs00252524_m1 AKR1B10 1400 <5 <5 <5 <5 23 9 <5

Hs00413886_m1 AKR1C1; AKR1C2 52 284 2366 284 57 50 64 14

Hs00366267_m1 AKR1C3 1091 45 95 11 <5 14 63 10

Hs00230170_m1 AKR1E2 55 420 785 436 70 16 75 145

Hs00761005_s1 AKR7A2 181 61 60 103 89 48 150 42

Hs00792041_gH AKR7A3 909 <5 <5 <5 <5 14 75 19

Hs00292269_m1 ALDH16A1 3 152 32 94 141 56 112 68

Hs00913261_m1 ALDH18A1 1415 90 76 65 42 26 67 45


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Hs00167445_m1 ALDH1A1 380 108 272 94 688 145 313 139

Hs00167476_m1 ALDH1A3 32 19 6 22 816 77 25 85

Hs00377718_m1 ALDH1B1 160 69 41 66 77 22 17 64

Hs00201836_m1 ALDH1L1 137 <5 7 ND ND <5 14 ND

Hs00355914_m1 ALDH2 2059 23 19 26 26 6 34 36

Hs00964880_m1 ALDH3A1 76 30 12 36 <5 54 16 63

Hs00166066_m1 ALDH3A2 1078 32 21 46 13 22 25 38

Hs00167488_m1 ALDH3B1 82 88 302 83 531 56 599 33

Hs00186689_m1 ALDH4A1 38 185 80 193 187 337 309 89

Hs00153566_m1 ALDH5A1 55 143 105 212 13 9 42 47

Hs00194421_m1 ALDH6A1 364 37 61 33 30 6 25 25

Hs00609622_m1 ALDH7A1 410 137 143 161 86 24 77 62

Hs00355924_m1 ALDH9A1 420 34 60 41 70 23 27 59

Hs00186647_m1 AOC3 77 <5 5 <5 <5 ND 12 ND

Hs00154079_m1 AOX1 3 33 110 70 2647 ND ND ND

Hs00163746_m1 BCHE 5 ND ND ND ND ND ND ND

Hs00156323_m1 CBR1 231 37 42 49 56 20 24 31

Hs00154295_m1 CBR3 3 ND ND ND 124 ND ND 342

Hs00379036_m1 CBR4 120 35 32 50 56 14 34 21

Hs00275607_m1 CES1 67 248 1017 444 13 ND ND ND

Hs00187279_m1 CES2 3486 <5 <5 <5 <5 <5 <5 <5

Hs00227775_m1 CES3 1100 <5 <5 <5 ND <5 <5 <5

Hs00164383_m1 CYP1B1 19 16 12 18 12 275 592 74

Hs00221087_m1 CYP20A1 152 49 28 78 75 11 20 31

Hs00219866_m1 CYP26B1 12 ND ND ND 25465 ND ND ND

Hs01026016_m1 CYP27A1 383 41 50 35 11 <5 8 ND

Hs00168017_m1 CYP27B1 11 680 739 880 201 226 465 167


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Hs03044634_m1 CYP2B6 363 <5 <5 <5 ND <5 7 12

Hs01595322_mH CYP2C18 171 <5 <5 <5 ND <5 ND <5

Hs00426380_m1 CYP2C19 19 10 54 29 ND ND ND ND

Hs00426397_m1 CYP2C9 17 <5 9 12 ND ND ND ND

Hs00559370_m1 CYP2E1 3 ND 29 18 56 ND 77 ND

Hs00951113_m1 CYP2J2 264 5 7 <5 ND <5 <5 37

Hs01379776_m1 CYP2R1 64 92 116 60 <5 31 72 78

Hs00258076_m1 CYP2S1 212 88 103 97 40 19 74 89

Hs00766273_m1 CYP2U1 36 18 27 13 228 11 38 28

Hs00214994_m1 CYP2W1 3 3863 16470 1306 30 183 769 ND

Hs00213201_m1 CYP39A1 11 ND ND ND 108 25 95 61

Hs00430021_m1 CYP3A4 4 ND ND ND ND ND 196 ND

Hs00241417_m1 CYP3A5 172 10 17 16 ND 21 170 16

Hs01680107_m1 CYP4F11 4 ND ND ND ND 58 195 382

Hs00430602_g1 CYP4F12 188 <5 6 ND ND <5 15 <5

Hs00426608_m1 CYP4F2 56 <5 16 ND ND ND <5 <5

Hs01389878_m1 CYP4V2 64 15 15 8 57 7 23 11

Hs00380077_m1 CYP4X1 3 489 267 184 ND ND ND ND

Hs00426415_m1 CYP51A1 325 196 378 178 191 51 165 216

Hs00191385_m1 CYP7B1 14 ND ND ND ND ND ND ND

Hs00949075_m1 DHRS4 235 16 11 16 47 17 36 23

Hs00608375_m1 DHRS9 1529 <5 <5 <5 ND <5 <5 5

Hs00559279_m1 DPYD 141 <5 <5 5 15 5 18 ND

Hs01116807_m1 EPHX1 434 42 61 43 66 46 111 17

Hs00157403_m1 EPHX2 581 25 35 18 <5 <5 <5 9

Hs00382667_m1 ESD 330 85 117 103 96 54 63 41

Hs00157614_m1 FMO4 73 13 13 11 <5 <5 6 <5


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Hs00356233_m1 FMO5 809 <5 <5 <5 <5 <5 8 <5

Hs00189576_m1 HSD17B10 668 98 48 138 94 63 83 214

Hs00186308_m1 KCNAB2 66 50 181 50 42 23 94 89

Hs00323448_m1 KDM1A 130 150 152 192 144 143 348 147

Hs00400708_m1 KDM1B 390 25 22 31 38 26 27 94

Hs00165140_m1 MAOA 4777 <5 <5 <5 14 <5 17 <5

Hs00168533_m1 MAOB 94 11 14 <5 ND 27 28 46

Hs00168547_m1 NQO1 1382 56 42 73 154 71 92 166

Hs00168552_m1 NQO2 43 257 97 252 192 113 132 178

Hs00382210_m1 PAOX 28 51 79 43 22 19 28 6

Hs00165563_m1 PON2 604 77 94 92 111 29 36 58

Hs00412993_m1 PON3 7 795 965 601 66 75 230 399

Hs00919949_m1 PTGIS 9 96 395 70 75 ND ND ND

Hs00268403_m1 SPR 398 56 34 71 34 29 36 47

Hs00166578_m1 SUOX 111 47 44 53 39 17 44 63

Hs00233423_m1 TBXAS1 114 ND ND ND 27 48 48 38

Hs00166010_m1 XDH 408 <5 <5 <5 ND <5 <5 ND

Phase II enzymes

Hs00221125_m1 AS3MT 12 840 608 948 247 ND ND ND

Hs00241349_m1 COMT 92 187 228 167 309 218 625 114

Hs00980756_m1 GGT1 177 25 26 39 71 21 79 73

Hs00275575_m1 GSTA1 63 25 133 338 12 <5 ND ND

Hs00155308_m1 GSTA4 46 145 214 137 322 52 72 21

Hs00210861_m1 GSTK1 830 21 30 31 30 26 88 25

Hs02341469_m1 GSTM1 7 ND ND ND 1172 ND ND ND

Hs00265266_g1 GSTM2 34 ND <5 <5 268 ND ND ND

Hs00168307_m1 GSTM3 51 54 66 80 1156 ND ND 160


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Hs00426432_m1 GSTM4 216 14 14 21 51 <5 9 14

Hs00757076_m1 GSTM5 20 ND ND ND 662 ND ND ND

Hs00818731_m1 GSTO1 258 300 180 312 228 97 246 60

Hs00826661_m1 GSTO2 40 <5 <5 <5 ND 79 217 84

Hs00168310_m1 GSTP1 4243 287 236 311 121 101 121 ND

Hs00184475_m1 GSTT1 21 ND ND ND 194 271 683 260

Hs01041668_m1 GSTZ1 76 28 22 23 18 22 34 23

Hs00199373_m1 HNMT 698 35 36 50 46 11 29 13

Hs00198941_m1 INMT 5 95 16 125 2535 <5 ND ND

Hs00220393_m1 MGST1 3534 21 16 30 58 25 20 97

Hs00182064_m1 MGST2 739 61 61 53 <5 18 51 27

Hs01058946_m1 MGST3 2578 62 60 44 29 <5 17 28

Hs00560401_m1 MPST 2249 29 36 25 23 10 29 11

Hs00211492_m1 NAA20 376 76 84 133 88 73 118 134

Hs00377717_m1 NAT1 3 189 64 213 55 19 ND 46

Hs00605099_m1 NAT2 54 <5 <5 ND ND ND ND ND

Hs00196287_m1 NNMT 27 8 9 9 4866 166 321 ND

Hs02340929_g1 SULT1A2 215 ND ND <5 ND ND <5 <5

Hs00413970_m1 SULT1A3;

SULT1A4 25 49 31 56 79 18 35 43

Hs00234899_m1 SULT1B1 1190 <5 <5 <5 ND ND ND <5

Hs00169044_m1 SULT1C2 1 310 2934 779 ND ND ND 402

Hs00198159_m1 SULT1C4 3 5543 5244 320 50 ND ND ND

Hs00190268_m1 SULT2B1 30 <5 ND ND ND 627 1598 447

Hs00740082_mH TPMT 1355 13 14 18 16 6 5 50

Hs00361812_m1 TST 2719 <5 <5 <5 7 <5 16 6

Hs02511055_s1 UGT1A1 261 <5 <5 9 <5 <5 <5 7


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Hs02516990_s1 UGT1A10 2279 ND <5 <5 ND 46 31 <5

Hs01655285_s1 UGT1A4 33 <5 ND 6 ND <5 ND <5

Hs01374521_s1 UGT1A5 32 ND ND <5 ND <5 ND 5

Hs01592477_m1 UGT1A6 7 1233 374 816 13 790 389 2993

Hs02517015_s1 UGT1A7 242 ND ND <5 ND <5 <5 <5

Hs01592482_m1 UGT1A8 1043 ND ND ND ND 54 43 <5

Hs02516855_sH UGT1A9 91 ND ND ND ND <5 ND <5

Hs00226904_m1 UGT2A3 813 <5 38 <5 <5 <5 <5 <5

Hs02556282_s1 UGT2B10 6 8 75 17 ND ND ND ND

Hs01894900_gH UGT2B11 4 57 95 67 ND ND ND ND

Hs00854486_sH UGT2B17 9575 <5 <5 <5 ND ND ND ND

Hs00426592_m1 UGT2B7 19 68 184 47 ND 9 ND ND

Hs00409961_m1 UGT8 449 48 81 50 <5 39 62 30

Transporters

Hs01059122_m1 ABCA1 385 17 20 12 45 <5 13 <5

Hs00242232_m1 ABCA2 43 27 52 23 34 62 206 60

Hs00975530_m1 ABCA3 12 1121 1267 885 122 <5 57 7

Hs01105117_m1 ABCA7 40 34 11 32 27 77 242 31

Hs00992371_m1 ABCA8 138 ND ND ND 272 ND ND ND

Hs00184491_m1 ABCB1 175 23 18 5 15 ND ND 23

Hs01085315_m1 ABCB10 213 88 111 107 75 26 37 61

Hs00184824_m1 ABCB11 122 ND ND ND ND ND ND <5

Hs00240956_m1 ABCB4 7 ND ND ND ND ND ND ND

Hs00180568_m1 ABCB6 69 465 717 775 566 137 305 175

Hs00188776_m1 ABCB7 286 55 90 77 48 43 77 94

Hs00185159_m1 ABCB8 71 58 29 71 71 80 115 42

Hs00608640_m1 ABCB9 35 34 44 31 41 38 109 55


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Hs00219905_m1 ABCC1 64 54 55 87 524 85 108 164

Hs00375716_m1 ABCC10 67 122 102 113 146 49 63 82

Hs00358656_m1 ABCC3 637 <5 16 7 33 32 77 21

Hs00195260_m1 ABCC4 111 181 84 202 531 109 147 55

Hs00981089_m1 ABCC5 42 53 71 54 59 14 16 60

Hs00184566_m1 ABCC6 39 85 101 99 27 ND 15 16

Hs00245340_m1 ABCD4 98 39 39 48 35 20 82 36

Hs01053787_m1 ABCG2 1030 8 8 20 17 13 21 <5

Hs02880035_m1 ABCG8 4 ND ND ND ND ND ND ND

Hs00166067_m1 AQP1 111 <5 <5 <5 <5 8 197 ND

Hs00798308_sH ATP6V0C 1571 86 92 115 99 39 71 63

Hs00163707_m1 ATP7A 34 18 38 23 76 49 87 83

Hs00163739_m1 ATP7B 115 184 158 234 39 20 70 14

Hs00245438_m1 MVP 2642 7 16 8 32 9 43 24

Hs00166561_m1 SLC10A2 5 ND 82 22 ND ND ND ND

Hs00192639_m1 SLC15A1 14 286 578 443 8 ND ND 12

Hs00221539_m1 SLC15A2 15 14 35 35 9 ND 15 ND

Hs00161826_m1 SLC16A1 2611 20 23 27 17 11 12 25

Hs00161858_m1 SLC18A2 10 ND ND ND ND ND ND ND

Hs00953345_m1 SLC19A1 124 212 117 294 636 84 149 87

Hs00949693_m1 SLC19A2 58 297 385 360 158 120 191 140

Hs00375596_m1 SLC19A3 57 282 327 386 8 <5 13 <5

Hs00188172_m1 SLC1A1 432 72 55 47 62 34 136 15

Hs00188193_m1 SLC1A3 11 7090 3896 9444 175 ND ND ND

Hs00427554_m1 SLC22A1 3 44 60 71 ND ND ND 58

Hs00222691_m1 SLC22A3 3 ND ND ND ND 30 208 453

Hs00268200_m1 SLC22A4 20 5 <5 11 17 6 42 5


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Hs00929869_m1 SLC22A5 379 9 8 13 8 <5 9 8

Hs00185185_m1 SLC25A13 300 155 111 201 50 47 59 73

Hs00188407_m1 SLC28A2 29 ND ND ND ND ND ND ND

Hs00223220_m1 SLC28A3 2 44 ND 42 ND 473 425 60

Hs01085706_m1 SLC29A1 56 382 432 493 150 170 415 614

Hs00155426_m1 SLC29A2 26 335 399 241 25 168 259 204

Hs00983219_m1 SLC29A3 56 126 140 131 40 28 86 27

Hs00542001_m1 SLC29A4 21 909 985 698 132 50 5780 115

Hs00197884_m1 SLC2A1 198 904 1045 1071 769 311 956 93

Hs00977268_g1 SLC31A1 505 107 95 100 81 34 52 44

Hs01562168_m1 SLC38A1 1979 80 59 98 53 35 38 62

Hs01089954_m1 SLC38A2 574 228 257 204 910 58 157 77

Hs01012028_m1 SLC38A5 125 <5 5 <5 48 119 137 306

Hs00165789_m1 SLC3A1 167 <5 14 6 <5 <5 73 11

Hs00374243_m1 SLC3A2 336 694 608 579 351 113 194 189

Hs00217320_m1 SLC47A1 20 <5 13 ND ND ND ND ND

Hs00169010_m1 SLC6A4 25 192 530 139 43 ND ND 17

Hs00204928_m1 SLC7A11 17 510 732 880 7078 1471 1603 694

Hs00185826_m1 SLC7A5 17 4697 1833 7991 3588 1669 2217 3128

Hs00938056_m1 SLC7A6 71 851 405 1107 416 146 119 210

Hs00909952_m1 SLC7A7 41 1702 3500 1153 73 37 103 61

Hs00794796_m1 SLC7A8 188 158 153 184 35 <5 <5 166

Hs00194554_m1 SLCO2A1 384 <5 5 <5 <5 ND ND ND

Hs00200670_m1 SLCO2B1 194 137 330 170 8 <5 <5 12

Hs00203184_m1 SLCO3A1 27 <5 15 <5 7 16 30 140

Hs00249583_m1 SLCO4A1 36 589 563 695 6 379 342 1009

Hs00698884_m1 SLCO4C1 11 103 271 26 ND ND ND ND


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Hs00229597_m1 SLCO5A1 22 ND ND ND ND 27 57 55

Hs00388682_m1 TAP1 788 6 12 <5 51 6 55 89

Hs00241060_m1 TAP2 190 20 24 23 141 31 141 142

Hs00748551_s1 VDAC2 49 63 67 102 80 25 37 43

Hs00366592_m1 VDAC3 337 56 33 57 85 12 14 46

Nuclear receptors and transcription factors

Hs00169233_m1 AHR 1189 53 81 54 53 40 99 90

Hs00610222_m1 AIP 281 153 350 184 116 57 192 67

Hs01121918_m1 ARNT 385 34 50 47 60 15 34 33

Hs00208298_m1 ARNT2 16 ND ND ND 21 ND ND ND

Hs00231733_m1 CREBBP 530 58 62 65 54 28 36 61

Hs00230938_m1 EP300 622 54 41 43 41 19 18 29

Hs00230957_m1 ESR2 11 ND ND ND ND ND ND ND

Hs00232764_m1 FOXA2 52 163 123 207 <5 85 189 179

Hs01054576_m1 FOXO1 127 25 71 32 <5 18 27 15

Hs00153153_m1 HIF1A 785 60 43 64 185 29 37 60

Hs00541709_m1 HIF3A 7 544 1285 661 812 ND ND ND

Hs00604435_m1 HNF4A 2650 64 73 73 <5 6 16 31

Hs00743767_sH HSP90AA1 2627 102 67 134 71 52 42 131

Hs00202227_m1 KEAP1 299 75 63 96 108 45 64 94

Hs00186661_m1 NCOA1 655 34 55 54 27 8 19 26

Hs00896106_m1 NCOA2 170 55 51 47 43 20 64 33

Hs00180722_m1 NCOA3 292 113 120 156 86 27 42 55

Hs00196920_m1 NCOR1 1404 20 21 27 28 16 24 24

Hs00196955_m1 NCOR2 212 97 140 130 101 56 108 153

Hs00232352_m1 NFE2L2 2150 47 49 63 105 24 32 47

Hs00222677_m1 NR0B2 4 140 290 42 ND 1220 7206 414


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Hs00173195_m1 NR1H2 71 35 58 36 88 28 128 42

Hs00172885_m1 NR1H3 137 49 144 49 27 41 206 36

Hs00231968_m1 NR1H4 115 <5 24 ND ND <5 14 ND

Hs00243666_m1 NR1I2 576 ND ND ND ND ND <5 12

Hs00353740_m1 NR3C1 122 40 96 43 261 ND ND ND

Hs01031809_m1 NR3C2 431 ND <5 ND ND <5 <5 ND

Hs00187067_m1 NR5A2 452 21 72 25 <5 <5 7 9

Hs00231882_m1 PPARA 97 26 89 25 37 10 48 32

Hs00602622_m1 PPARD 536 10 17 12 24 12 27 26

Hs01115513_m1 PPARG 998 18 35 16 14 20 41 31

Hs00173304_m1 PPARGC1A 198 ND ND ND ND <5 ND 8

Hs00370186_m1 PPARGC1B 184 21 29 41 <5 7 10 25

Hs00209379_m1 PPRC1 81 126 127 212 160 102 101 158

Hs00832847_gH PTGES3 961 79 66 116 78 75 106 153

Hs00940446_m1 RARA 162 58 82 49 45 33 77 23

Hs00233407_m1 RARB 23 82 238 82 7 ND ND ND

Hs01559234_m1 RARG 50 70 57 61 173 333 641 163

Hs01067640_m1 RXRA 1352 42 70 43 73 33 59 24

Hs00232774_m1 RXRB 155 54 59 50 89 53 99 45

Hs00199455_m1 RXRG 13 ND ND ND ND ND ND ND

Hs00268470_m1 THRA 287 48 77 46 38 26 82 29

Hs00230861_m1 THRB 160 64 186 101 97 <5 15 26

Hs00188542_m1 TRIP11 326 38 33 32 52 15 16 36

Hs01045840_m1 VDR 1651 7 9 12 9 <5 8 36

Other genes

Hs00171635_m1 CRABP1 7 5537 7360 5629 24 ND ND ND

Hs00275636_m1 CRABP2 3 3798 7852 19011 1556 59109 181154 527


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Hs00196206_m1 GZMA 134 ND ND ND ND ND ND ND

Hs00188051_m1 GZMB 7 ND ND ND ND ND ND ND

Hs00831826_s1 MT1A 49 48 39 35 65 28 29 8

Hs00744661_sH MT1F 496 24 49 13 <5 <5 <5 <5

Hs00823168_g1 MT1H 6 ND ND ND ND ND ND ND

Hs00828387_g1 MT1M 280 <5 <5 ND 21 ND ND ND

Hs00745167_sH MT1X 1606 5 12 <5 39 <5 <5 <5

Hs02379661_g1 MT2A 487 8 12 <5 99 <5 <5 <5

Hs00359394_g1 MT3 6 ND ND ND ND 16 349 ND

Hs00293639_s1 MTHFR 67 55 51 35 33 33 47 16

Hs00287016_m1 POR 595 100 118 98 53 44 126 79

Hs00161252_m1 RBP1 46 16 12 7 <5 ND ND 35

Hs00188160_m1 RBP2 7 2071 4790 3311 17 ND ND ND

Hs00153349_m1 TP53 197 <5 <5 <5 51 55 53 <5

Hs00828652_m1 TXN 3791 76 47 65 95 70 72 79

Hs00429399_g1 TXN2 1121 43 42 44 43 22 31 24

ND, not detected; TC, Transverse Colon.

aExpression value is a relative number calculated based on the assumption that the average expression level

of two housekeeping genes RPLP0 and PPIA is 10 000 copies.


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Table 5 Spearman’s correlation coefficient between colon cell lines and intestinal

biopsies.

Caco-2 Caco-2

D14 C2BBe1 FHC HT29

HT29

D14 T84 Ileum AC TC DC R

Caco-2 1,000

Caco-2 D14 0,968 1,000

C2BBe1 0,980 0,955 1,000

FHC 0,837 0,798 0,839 1,000

HT29 0,758 0,715 0,756 0,738 1,000

HT29 D14 0,729 0,703 0,724 0,711 0,957 1,000

T84 0,792 0,750 0,786 0,750 0,884 0,856 1,000

Ileum 0,672 0,682 0,680 0,620 0,679 0,694 0,708 1,000

AC 0,711 0,708 0,715 0,692 0,747 0,758 0,783 0,940 1,000

TC 0,701 0,700 0,706 0,685 0,737 0,743 0,774 0,937 0,991 1,000

DC 0,708 0,704 0,713 0,695 0,741 0,750 0,777 0,937 0,988 0,992 1,000

R 0,706 0,702 0,709 0,704 0,735 0,744 0,772 0,914 0,967 0,971 0,980 1,000

I, Ileum; AC, Ascending Colon; TC, Transverse Colon; DC, Descending Colon; R, Rectum.

The correlation matrix was calculated based on the averaged ΔCt of two technical replicates for colon cell lines

and three biological replicates for intestinal biopsies. The numbers are the pairwise Spearman’s correlation

coefficient (rs) values that represent the strengths of the linear relationship between any two sets of comparative

components (rs=0 no correlation, rs=1 perfect correlation).


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