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Formaldehyde-induced gene expression in F344 rat nasal

respiratory epithelium

Susan D. Hester a,c,*, Gina B. Benavides b, Lawrence Yoonb,Kevin T. Morgan b, Fei Zou d, William Barry d, Douglas C. Wolfa

a

US Environmental Protection Agency, Research Triangle Park, NC, USAb GlaxoSmithKline, Inc., Research Triangle Park, NC, USA

c Department of Pathology and Laboratory Medicine, University of North Carolina, Chapel Hill, NC, USAd Department of Biostatistics, School of Public Health, University of North Carolina, Chapel Hill, NC, USA

Received 17 October 2002; received in revised form 24 December 2002; accepted 2 January 2003

Abstract

Formaldehyde (FA), an occupational and environmental toxicant used extensively in the manufacturing of many

household and personal use products, is known to induce squamous cell carcinomas in the nasal turbinates of rats and

mice and squamous metaplasia in monkey noses. Tissue responses to FA include a dose dependent epithelialdegeneration, respiratory cell hypertrophy, and squamous metaplasia. The primary target for FA-induced toxicity in

both rodents and monkeys is the respiratory nasal epithelium. FA increases nasal epithelial cell proliferation and

DNA/protein crosslinks (DPX) that are associated with subsequent nasal cancer development. To address the acute

effects of FA exposure that might contribute to known pathological changes, cDNA gene expression analysis was used.

Two groups of male F344 rats received either 40 ul of distilled water or FA (400 mM) instilled into each nostril. Twenty-

four hours following treatment, nasal epithelium was recovered from which total RNA was used to generate cDNA

probes. Significance analysis of microarrays (SAM) hybridization data using ClontechTM Rat Atlas 1.2 arrays revealed

that 24 of the 1185 genes queried were significantly up-regulated and 22 genes were significantly downregulated. Results

for ten of the differentially expressed genes were confirmed by quantitative real time RT PCR. The identified genes with

FA-induced change in expression belong to the functional gene categories xenobiotic metabolism, cell cycle, apoptosis,

and DNA repair. These data suggest that multiple pathways are dysregulated by FA exposure, including those involved

in DNA synthesis/repair and regulation of cell proliferation. Differential gene expression profiles may pro vide clues

that could be used to define mechanisms involved in FA-induced nasal cancer.

# 2003 Elsevier Science Ireland Ltd. All rights reserved.

Keywords: Gene expression; F344 rat; cDNA array; Nasal epithelium; Rodent nasal cancer; Formaldehyde

Abbreviations: FA, formaldehyde; DPX, DNA/protein crosslink; Min, minute; mg, microgram; mM, millimolar; 8C, centrifuge; ml,

milliliter.

Supplementary data associated with this article can be found at doi:10.1016/S0300-483X(03)00008-8

* Corresponding author. Tel.: /1-919-541-1320; fax: /1-919-541-0694.

E-mail address: [email protected] (S.D. Hester).

Toxicology 187 (2003) 13/24

www.elsevier.com/locate/toxicol

0300-483X/03/$ - see front matter # 2003 Elsevier Science Ireland Ltd. All rights reserved.

doi:10.1016/S0300-483X(03)00008-8
mailto:[email protected]:[email protected]:[email protected]

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1. Introduction

Formaldehyde (FA) is a common environmental

contaminant found in tobacco smoke, paint,garments, medicinal and industrial products, and

is a component of diesel and gasoline exhaust

(Flyvholm and Andersen, 1993; Quievryn and

Zhitkovich, 2000). Although there is limited evi-

dence that FA is a human carcinogen, it is well

known that FA induces tumors in rodents. FA

exposure leads to the formation of DNA/protein

crosslinks (DPX), a major form of DNA damage

and the presence of DPX have been used as a

measure of delivered dose (Heck and Casanova,

1999; Heck et al., 1990).FA is also cytotoxic in the rodent nose, inducing

sustained increases in cell turnover (proliferation)

at concentrations that induce tumors (Monticello

et al., 1991b; Morgan et al., 1986). Lesions

primarily develop in the epithelium lining the nasal

septum and the ventral meatus of the turbinates.

The types of lesions following an acute 24 h nasal

instillation of 400 mM FA were squamous meta-

plasia, ulceration, hyperplasia, and goblet cell

hypertrophy, which were observed at 3 weeks

post treatment (St. Clair et al., 1990). These lesionsoccurred only in respiratory and transitional

epithelium lining the anterior nasal passages of

the rat nose. This suggests that respiratory and

transitional epitheliums are more susceptible to

FA damage than the other epithelial types present

in the nose.

In addition to DPX, FA can readily react with

DNA and RNA by forming cross-links that

connect bases exclusively through exocyclic amino

groups (Chaw et al., 1980; Kennedy et al., 1996;

Takahashi and Hashimoto, 2001). FA is known to

induce regenerative proliferation (Monticello etal., 1991a,b) and may alter apoptosis (Szende et

al., 1995, 1998; Tyihak et al., 2001). An alteration

in the balance between cell growth and cell death

may contribute to the development of squamous

cell carcinoma in the rat nose. Biologically based

risk-assessment models (CIIT, 1999) have been

proposed which integrate levels of cell prolifera-

tion, cell death, and mutation rates associated with

FA treatment (Andersen et al., 1992; Conolly and

Andersen, 1993). These models reflect a mathe-

matical approach based on the two-stage model of

cancer development proposed by Moolgavkar et

al. (1988). The model used to assess human risk to

environmental pollutants, states that any agentthat alters cell division or rates of cell differentia-

tion will cause an increase in the number of

susceptible cells and thus, an increase in a cancer-

ous outcome. To date, only cell proliferation and

DPX data have driven FA cancer risk assessments.

The endpoints needed to complete the model,

namely cell death rates associated with FA ex-

posure, have yet to be reported. The assessment of

cell death in the epithelia lining the nasal turbi-

nates poses a unique challenge because the lining is

only one to two cells thick. If a respiratory cellunderwent apoptosis it would immediately slought

off and, therefore, go undetected. Conventional

methods to quantitate cell death would not be

accurate. Since measurements of death rates of the

nasal epithelium following FA exposure are not

feasible, we chose to evaluate gene expression

profiles to gauge whether acute changes in activity

of genes that control apoptosis were induced by

FA.

The evaluation of respiratory tract toxicity

following exposure to chemicals inv

olv

es deliv

er-ing the agent to animals by inhalation. This is a

natural route of entry in the exposed animal and is

a preferred method to introduce toxicants to the

respiratory tract. However, this method cannot

always be used because of cost and the need of

specialized equipment. Alternatively, direct instil-

lation of the test substance to the respiratory tract

has been employed in many studies (Evans and

Hastings, 1992; Jeffrey et al., 2002; Wagner et al.,

2001). The advantages of direct instillation are that

the chemical is delivered to the target site (respira-

tory cells lining the nasal cavity) and it is arelatively simple procedure to carry out without

requiring special equipment. An acute dose of a

chemical in aqueous solution can be infused with

relative ease and little stress to the animal.

Although there are distinct differences in distribu-

tion, clearance, and retention of chemicals when

administered by nasal instillation versus inhala-

tion, nasal instillation can be a useful and rela-

tively inexpensive method for investigating specific

questions involving respiratory toxicants.

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The concentration of FA used in our study

induces regenerative cell proliferation, but is not

high enough to produce necrosis. St. Clair et al.,

(1990), using nasal instillation of 400 mM FAshowed increased cell proliferation of respiratory

epithelium with minimal cytotoxicity. Since the

present study represents the first look at global

gene expression changes following FA exposure, a

simple design of two groups of animals (control

and treated) was utilized. For review of experi-

mental design decisions and interpretation of gene

expression data from toxicogenomic experiments

see (Hamadeh et al., 2002). In the present study, a

single concentration and time point were used to

examine transcriptional changes associated withacute FA exposure.

2. Materials and methods

2.1. Animal dosing

Rats were maintained in plastic cages (two per

cage) with filter purified tap water and feed ad

libitum. On day of treatment, 40 ml aliquots of

water or FA (400 mM) were instilled into eachnostril using a pipette.

2.2. Epithelial cell extraction from anterior rat

noses

Eight 60-day-old F344 male rats (Charles River

Laboratory, Raleigh, NC) were euthanized by

receiving CO2 asphyxiation and nasal respiratory

cells were recovered and processed as previously

described (Hester et al., 2002). Briefly, TrizolTM

reagent was instilled into each nostril through

polyethylene tubing and incubated for 10 min.Using a syringe attached to the tubing, the cellular

TrizolTM solution was removed, placed in a micro-

fuge tube, and immediately frozen in liquid nitro-

gen for subsequent total RNA isolation and

quantitation.

2.3. Total RNA extraction

Total RNA was extracted from respiratory cells

as previously reported (Hester et al., 2002). Briefly,

phase separation was carried out after thawing the

cellular/TrizolTM samples in a warm water bath

(65/70 8C) for 10 min. Chloroform was added to

each sample and tubes were shaken followed by10 000/gcentrifugation at 8 8C for 20 min. The

phenol/chloroform phase separates to the bottom

and the upper aqueous phase contains the RNA,

which was precipitated using ice cold isopropyl

alcohol followed by centrifugation at 10 000/g

for 20 min. The isopropyl supernatant was re-

moved leaving the RNA pellet. The RNA was

resuspended with 75% alcohol, mixed by inversion,

then centrifuged at 10 000/g for 30 min. RNA

was dissolved in 100 ml of DEPC water and heated

at 70 8C for 3 min with intermittent vortexing.The RNA solution was then transferred to silico-

nized Eppendorf tubes and the concentration

(absorbance at 260 nm; 1A260 unit of single

stranded RNA/40 mg/ml) was adjusted to 2 mg/

ml with diethylene pyrocarbonate (DEPC) water.

2.4. Electrophoresis of the RNA

5 mg of the resultant RNA sample was loaded

into a denaturing 1% agarose gel containing FAaccording to the protocol described inLehrach et

al. (1977) for electrophoresis. Observation of

rRNA subunit bands at 18S and 28S indicate the

presence of intact RNA.

3. Synthesis and labeling of cDNA

About 5 mg total RNA was used to generate a

probe for hybridizations as described in Hester etal. (2002). Briefly, seven (four control and three

treated) cDNA probes were generated by reverse

transcribing the RNA with primers in the presence

of 33P. Unincorporated label was removed on a

MicrospinTM Sepharose G-50 gel filtration column

(Amersham Pharmacia Biotech, Piscataway, NJ).

For hybridization of the labeled product, 250 000

Cerenkovcpm were used. ClontechTM software was

used to analyze gene expression levels from the

hybridization membranes.

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4. Real-time quantitative PCR

Quantification of mRNA was done using Mo-

lecular Probes Ribogreen RNA Quantificationkit. To prevent amplification of genomic DNA

sequences, all RNA samples were treated with

DNase I and diluted to 10 ng/ul. Taqman probes

were labeled with FAM (carboxyfluorescein) as

the reporter dye on the 5? position and TAMRA

(carboxytetramethylrhodamine) as the quencher

dye on the 3? position. cDNA was made using

moloney murine leukemia virus (MMuLV) reverse

transcriptase. All reactions were carried out in a

single tube reaction setup on an ABI PRISM 7700

sequence detection system (Applied Biosystems,Inc). The following temperature profile was used:

30 min at 48 8C for reverse transcription and 10

min at 95 8C for reverse transcription inactivation

and AmpliTaq Gold activation, 40 cycles of 15 s at

94 8C and 1 min at 60 8C. To check for possible

contamination in the reaction mix, no template

control (NTC) wells without RNA were used. The

cycle threshold Ct (i.e. ten times the standard

deviation of the mean baseline emission calculated

during PCR cycles 3 to 15) was used to calculate

relativ

e amounts of target RNA. The delta Ctmethod was used to calculate relative fold expres-

sion levels, as described by Applied Biosystems.

Primers and probes for ten rat genes (aldr, b2mg,

calp, cof, czsod, p38mapk, gst, nmor, sc1, waf1)

were purchased from Keystone Biosource (Camar-

illo, CA). Final concentration of all primers were

900 nM and probes were at 200 nM.

After the reaction was complete, a graph of

fluorescent intensity versus cycle number was

created using the above software. For each gene

assayed, a Ct is placed at the intersection of the

linear portion of the curve, which reflects theexponential amplification. Samples, which do not

reach the threshold line, are considered not above

background. The average Ct for each gene is

calculated by subtracting the Ct of the sample

RNA from the control RNA for the same time

measurement. This value is known as the delta Ct

and reflects the relative expression of the treated

sample compared with control and becomes the

exponent in the calculation for amplification

240ct, equivalent to fold change in expression.

When the delta Ct is negative, the final calculation

is negative, and is interpreted as down regulation

of that gene.

5. Statistical analysis of microarray data

The mean and variance of the Adjusted signal

intensity (ASI) were calculated and plotted (Fig. 1)

for each gene across the control and FA-treated

samples. There is a clear trend that the variation in

expression of a gene increased along with the

intensity of the gene. Therefore, intensities were

log (base 2) transformed to stabilize the variation

across intensity levels. Next, the data was globallynormalized within each membrane by first sub-

tracting the median intensity and then scaling by

the median absolute difference (MAD); normal-

izing by the median and MAD for each membrane

is more robust against extreme values than by the

classical measures, mean and standard deviation.

Once the data were normalized, statistically sig-

nificant, differentially expressed genes were ob-

tained using the statistical software, SAM

(significance analysis of microarrays) (Tusher et

al., 2001). Because of the large number of genesincorporated into microarray experiments, adjust-

ing for multiple testing is necessary when assessing

statistical significance. Few experiments have en-

ough power to detect significance with a stringent

Bonferroni correction when the number of com-

parisons is large. In SAM, the effect of multiple

comparisons is controlled through the false dis-

covery rate (FDR; Benjamini and Hochberg,

1995), which is defined as the expected proportion

of false positives among the rejected hypotheses;

for example, an FDR of 5% in testing differential

gene expression would indicate that about 5% ofthe identified genes were spurious. Through a

permutation scheme, SAM estimates the FDR

for a set of genes whose test statistics deviate

from their expected value by more than a given

threshold level; by adjusting the threshold level

one can achieve a desired FDR. Due to the

limitation in sample size of our data, threshold

levels were chosen that resulted in FDRs of 11.3

and 5.3% as the nearest approximations of 10 and

5%, respectively.


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6. Results

6.1. SAM analysis of gene expression

The ASI were obtained from the image analysis

for 1185 genes from four control and three FA-

treated samples. The data were first transformed

and normalized as described in Section 5, SAM

was then used to identify a set of genes that were

differentially expressed across treated and control

samples. By setting a threshold level of 0.187,

SAM predicted a FDR of 11.3% for 46 signifi-

cantly altered genes; 24 genes increased in expres-

sion due to FA treatment and 22 genes decreasedin expression (Fig. 2). Among the genes listed in

Tables 1 and 2,the fold change in raw intensities

ranged from 6.1 to 2.4 (Table 1) among up-

regulated genes and 10/2.5 in the down-regulated

genes (Table 2). By setting a more stringent

threshold level of 0.232 we obtain a set of 14

significant genes with FDR 5.3%. This set of genes

corresponded to the top 13 up-regulated genes in

Table 1 and the most down-regulated gene in

Table 2.

Genes listed in Table 1 were statistically eval-

uated and sorted from the highest test statistic

value to the lowest. Ten of the most highly

expressed genes for FA-treated animals included

NMDA receptor, inducible nitric oxide synthase,

macrophage inflammatory protein 1 alpha and 2,

Wilms tumor protein, tumor necrosis factor

ligand, methyl-CpG binding protein 2, GABA

receptor, Fos-responsive gene 1, and presomato-

trophin. Of the 24 significantly up-regulated genes

six were receptors, six were involved in extracel-

lular cell signaling, and four were oncogene/tumor

suppressor genes suggesting pathways that could

be affected by FA treatment. In contrast, in Table2, of the 22 genes significantly down-regulated,

five were involved in ion channel regulation and

four were involved in protein turnover which

suggests that an early response to FA treatment

may be impaired ion channel function and inter-

ruption of protein processing. Many phase I and

phase II genes regulating xenobiotic metabolism

and oxidative stress, the family of cytochrome

P450 and glutathione, respectively, were altered in

treated versus control.

Fig. 1. Distribution of the raw intensities for each gene. The variation in intensities across treatment (gray triangles) and control

samples (black circles) is plotted against the mean intensity for all 1185 genes. It is e vident, that the variation observed within each gene

was dependent on the average intensity. Despite the smaller sample size, the variability observed in the treatment group (n/3) was

smaller on average, than in the control group (n/4).


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7. Comparison of atlas rat toxicology II array and

real-time PCR data

A subset of ten genes with a range of expression

levels from high to low were selected for quanti-

tative real-time PCR analysis to validate the

direction of gene expression observed on the

microarrays. These ten genes included aldehyde

dehydrogenase (aldr), calpactin (calp), cofillin

(cof), copper/zinc superoxide dismutase (czsod),p38 map kinase (p38mapk), gluthione (gst),

NAD(p)H quinone oxidoreductase (nmor), so-

dium chloride 1 (sc1), and p21 waf1/CIP 1

(cyclin-dependent protein kinase inhibitor)

(waf1). Fig. 3 displays gene expression changes

present in both the Atlas Toxicology II arrays and

TaqManTM assays. Ten genes were confirmed but

arrays under-estimated, on average, the true

expression differences as revealed by quantitative

RT-PCR. Eight of the ten TaqManTM confirmed

genes on the array were estimated as increased

signal and one gene, copper/zinc superoxide

dismutase (CZSOD), showed a reduced signal.

7.1. Apoptosis gene expression

Fig. 4 shows gene expression levels of nine

apoptosis genes assayed in the FA and controlgroups. None of these genes were defined as

statistically different. However, there

was a general trend of less apoptotic gene expres-

sion levels in the FA group compared with control.

The nine genes were representative of three of the

major apoptosis-regulating pathways including

receptor-mediated (Fas-L), caspase (Caspase 3),

and the mitochondrial-associated bcl2 family of

genes (bcl2-x, bcl2-associated oncogene, BCLX,

BAD).

Fig. 2. Identification of differentially expressed genes. Using SAM, the observed test statistic is plotted against the statistic expected by

chance for 1185 genes. Genes that were expressed higher in the FA-treated samples appear on the positi ve side of the x -axis. At the

threshold,D/0.187 (drawn as dashed lines) SAM predicts 46 genes (24 positive and 22 negative) as being differentially expressed. The

FDR was estimated as 11.3%.


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Table 1

24 significantly up-regulated genes

Gene

ID

Treatmenta Controla Fold

change

Test-sta-

tistic

Family Description

D11c 0.658 0.580 6.086 1.794 Receptors N-methyl-D-aspartate receptor subtype 2B (NMDAR2B; NR2B

epsilon 2B (GRIN2B)

A08f 0.116 0.759 3.856 1.415 Immune Inducible nitric oxide synthase (INOS); type II NOS (NOS2)

E02k 0.251 0.906 5.763 1.404 Extrac/sign Macrophage inflammatory protein 1 alpha (Small inducible cyt

D14k 0.154 0.673 3.536 1.281 Extrac/sign Macrophage inflammatory protein 2 (MIP2)

A10f 0.331 1.200 3.785 1.157 Onco/tumo Wilms tumor protein homolog 1 (WT1)

E02m 0.184 1.009 3.804 1.144 Extrac/sign Tumor necrosis factor (ligand) superfamily, member 6 (apoptosi

antigen ligand)

A06l 0.390 0.368 2.950 1.117 Tx fact/dBP Methyl-CpG-binding protein 2 (MECP2)

D10d 1.115 1.937 4.938 1.083 Receptors Gamma-aminobutyric-acid receptor alpha 2 subunit (GABA(A

D01l 0.153 0.790 2.641 0.991 Receptors Fos-responsive gene 1

E03j 0.697 1.393 3.207 0.988 Extrac/sign Presomatotropin

D07m 0.534 1.201 2.904 0.987 Receptors Somatostatin receptor 3 (SSTR3; SS3R)

A09e 0.463 1.144 2.900 0.986 Immune 34A transformation-associated protein; TAP-related matrix me

stromelysin 2 (SL2); transin 2

D14f 0.626 1.270 2.866 0.985 Extrac/sign Nerve growth factor 8A (VGF8A)

D12i 0.674 0.060 2.371 0.914 Receptors Metabotropic glutamate receptor 6 (GRM6; MGLUR6)

E02n 1.025 1.631 3.513 0.897 Extrac/sign Brain natriuretic peptide (BNP); 5-kDa cardiac natriuretic pept

A11a 0.852 0.195 2.456 0.887 Onco/tumo F os-like antigen 1

E03d 0.616 1.345 3.680 0.886 Extrac/sign Follicle-stimulating hormone beta subunit

F12h 0.076 0.654 2.404 0.880 Recept by

act

Adenosine A2A receptor (ADORA2A)

A11h 0.882 0.307 2.236 0.878 Onco/tumo Neogenin; DCC netrin receptor-related protein; immunoglobul

former tumor suppressor protein candidate

A11g 0.439 1.110 2.590 0.869 Onco/tumo Deleted in colcorectal cancer (rat homolog)

D05m 0.762 1.376 2.633 0.868 Receptors 5-hydroxytryptamine (serotonin) receptor 5A

B01a 0.331 0.361 2.364 0.853 Stress res Cytochrome P450 1b1C05b 0.005 0.591 2.454 0.852 Metab pat Acetyl-CoA carboxylase (ACAC; ACC); biotin carboxylase

A05b 0.651 1.420 2.599 0.839 Cell sur ag NK lymphocyte receptor; NKR-P1B

Sample means are calculated from the normalized data. Fold Change is calculated from the raw data.a Mean signal intensities.

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Table 2

Tenty-two significantly down-regulated genes

Gene

ID

Treatmenta Controla Fold

change

Test-sta-

tistic

Family Description

E09m /2.352 /1.356 9.701 /1.439 Mod/

transd

Phosphorylase B kinase gamma subunit

F07j /2.284 /1.318 7.999 /1.159 Prot turnov Proprotein convertase subtilisin/kexin type 2

B04i /1.910 /1.004 4.272 /1.124 Ion chann Sodium channel protein 6 (SCP6)

F06l /0.568 0.208 3.312 /1.094 Prot turnov Secretory granule neuroendocrine, protein 1 (7B2 protein)

E14n /2.357 /1.499 4.625 /1.060 Mod/

transd

Ras-related protein RAB26

C07g /0.238 0.369 2.489 /1.026 Metab pat Cytochrome P450 IVA8 (CYP4A8); P450-KP1; P450-PP1

B14i /1.969 /1.206 3.533 /1.012 Traff/target Fatty acid-binding protein 9 (FABP9); testis lipid-binding protei

protein (PERF15)

A07k /1.286 /0.503 3.385 /0.951 Cell cycle Cyclin-dependent kinase 4 inhibitor 2B (CDKN2B); p14-INK4B

C05d /0.768 /0.009 2.846 /0.940 Metab pat Brain long-chain fatty acid-CoA ligase (LACS); acyl-CoA synth

B12i /2.448 /1.692 12.641 /0.936 Extra matr Myelin-associated glycoprotein

B13h /1.514 /0.787 2.926 /0.934 Traff/target Gastric intrinsic factor

B10m /1.566 /0.986 2.488 /0.928 Ion chann Aquaporin 3 (AQP3); 31.4-kDa water channel protein

F07i /1.658 /0.824 2.900 /0.927 Prot turnov Dipeptidyl peptidase IV (DPPIV; DPP4); bile canaliculus domain

B01i /0.087 0.632 3.000 /0.918 Stress res Plasma glutathione peroxidase (GSHPX-P; GPX3); selenoprotei

B13k /0.994 /0.399 2.531 /0.917 Traff/target Syntaxin binding protein 1

E14l 0.212 0.819 2.656 /0.903 Mod/

transd

Ras-related protein RAB16

F09j /1.498 /0.809 3.393 /0.884 Prot turnov Interleukin 1beta converting enzyme

C11k /2.197 /1.352 2.802 /0.872 Translation Ribosomal protein S19

B02d /1.803 /1.065 2.853 /0.871 Ion chann Solute carrier family 2 A2 (gkucose transporter, type 2)

B10n /1.537 /0.829 3.079 /0.869 Ion chann Synaptic vesicle amine transporter (SVAT); monoamine transport

(VAT2)

B02j /1.621 /0.972 2.617 /0.866 Ion chann Neuronal acetylcholine receptor protein alpha 6 subunit (NACH

receptor nicotinic alpha polipeptide 6 (CHRNA6)C08c /1.596 /0.973 2.855 /0.854 Metab pat Cytochrome P-450 2C23, arachidonic acid epoxygenase

Sample means are calculated from the normalized data. Fold change is calculated from the raw data. For down-regulated genes, fold c

over treated.a Mean signal intensities.

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Fig. 3. Comparison of TaqManTM to ClontechTM array results. A subset of ten genes was verified using quantitative real time PCR.

Nine of the ten gene expression values were in good agreement. One gene value, calpactin, was under-estimated on the array compared

with the TaqManTM result.

Fig. 4. Apoptosis Genes. Mean expression levels of nine genes involved in regulating apoptosis. Seven of the nine genes on the FA-

treated group showed reduced expression values compared with control group; AO1g-Annexin V, B13c-Annexin I, C12h-Bcl2-

associated death promoter (BAD), C12i-Bcl2-associated X protein (BAX), C12j-Bcl2 associated oncogene, BCL2-L, C12k-BCL2,

C12m activator of apoptosis (HRK), FO9i- Caspase 3, and EO2m-Fas-ligand.


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8. Discussion

FA induces squamous metaplasia leading to

squamous cell carcinoma after 12 months orlonger of exposure. In the present study, we

evaluated the acute response of epithelial cells 24

h after FA treatment. Our results indicated that

the expression levels of genes in several functional

categories were altered, including those participat-

ing in xenobiotic metabolism, cell cycle regulation,

DNA synthesis and repair, oncogene, and apop-

tosis. Xenobiotic metabolism genes showed a

general trend towards increased expression. Un-

expectedly, two cytochrome P450 family members

were down-regulated, cytochrome P450 IVA8, andcytochrome P450 2C23, genes which are usually

involved in metabolizing FA (Dahl and Hadley,

1991).

Genes were considered differentially expressed if

they exceeded the calculated threshold of 0.187,

with up-regulated genes falling on the positive side

and down regulated genes appearing in the nega-

tive quadrant (Fig. 2). However, gene expression

changes, which were not statistically significant

cannot be considered to be irrelevant but rather

not included in this analysis. For example, genesexpressed at low levels in the FA-treated group

that exhibit a small change in expression could still

be responsible for a large biologic effect, especially

if their gene products control critical pathways

such as cell growth or cell death.

Seven of the nine genes regulating apoptosis

showed less expression in the FA group compared

with the control group, however, none of these

genes were identified as being statistically differ-

ent. This result may be interpreted as a negative

finding, however, the effect of FA exposure on

respiratory epithelium is unknown. Therefore, anyinformation of changes in gene expression levels

after FA treatment is both novel and informative.

The post-treatment changes in gene expression

levels may well be subtle ones rather than large

changes. In addition, the respiratory cell may be

responding to acute FA exposure by altering

metabolism preferentially to deal with the acute

toxicity of this chemical. Just as changes in

reparative cell proliferation secondary to FA

treatment require time to develop, changes in

apoptosis gene expression may require longer

exposures over time to saturate the detoxifying

capacity of the nasal cell. So perhaps the optimum

time-frame to observe apoptosis gene expressionchanges would certainly be longer than 24 h as it

takes 4 days to 6 weeks of continuous exposure for

increased cell proliferation to occur (Monticello et

al., 1991a).

FA is a potent respiratory irritant and is capable

of stimulating a number of receptors related to the

trigeminal nerve and localized in the nasal epithe-

lium (Babiuk et al., 1985; Cassee et al., 1996). In

the present study, seven of the 24 significantly up-

regulated genes (Table 1) were classified as recep-

tors. Stimulation of these receptors represent oneof many defense mechanisms of the rodent re-

spiratory tract (Babiuk et al., 1985). Other protec-

tive mechanisms include a decrease in minute

ventilation, local cellular metabolism the muco-

ciliary apparatus, and DNA repair (Swenberg et

al., 1983). Chemicals that can induce these protec-

tive mechanisms are considered to be sensory

irritants because they can stimulate the trigeminal

nerve fibers, cause a burning sensation, and

diminish respiratory rates (Alarie, 1973). Interest-

ingly, the gene expression data in this report showthat four of the seven most highly expressed genes

were neuropeptides including NMDAR2B, sero-

tonin 5A, GABA(A), and metabotrophic gluta-

mate receptor which could reflect a response to

sensory irritation caused by FA.

In summary, there were more up-regulated

genes in the FA treated group than down-regu-

lated genes. Some genes, such as cell receptors, are

reported for the first time to have changed

expression in FA-exposed respiratory cells lining

the nasal turbinates, which is consistent with the

phenotypic response of these cells. Several geno-mic techniques, including subtractive hybridiza-

tion, array based comparative genomic

hybridization (aCGH), mRNA differential display

and serial analysis of gene expression (SAGE) are

being utilized to identify gene expression profiles

which could account for differentially expressed

genes after chemical or xenobiotic treatment.

From the results reported here, it is clear that

multiple genetic changes are induced after FA

exposure. Genetic events that account for progres-


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sion from squamous metaplasia to squamous cell

carcinoma are yet to be identified. Genes playing

more significant roles in common or overlapping

pathways are candidates to be assessed andanalyzed further over time. Results of the above

experiments hold the promise of revealing critical

gene interactions, which may aid in the discovery

of potential molecular events operative in the

pathogenic transition of epithelium exposed to

FA. Once gene pathways are identified, the next

key step will be to conduct bioassays that could

validate gene expression changes and will reinforce

insights provided by the gene profiling experi-

ments.

Acknowledgements

This manuscript has been reviewed and ap-

proved for publication by the Environmental

Protection Agency and does not necessarily reflect

the views of the agency. Mention of trade names or

commercial products does not constitute endorse-

ments or recommendations for use. Special thanks

to Dr. Jeffrey Ross, Dr. Julian Preston, Dr. David

Threadgill, Dr. Donald Delkar, and Dr. MarilaCordeiro-Stone for review and advice of this

manuscript.

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