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Carcinogenesis Advance Access originally published online on November 3, 2005
Carcinogenesis 2006 27(3):646-655; doi:10.1093/carcin/bgi255
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Carcinogenesis vol.27 no.3 © Oxford University Press 2005; all rights reserved.

Modulation of gene expression and DNA adduct formation in HepG2 cells by polycyclic aromatic hydrocarbons with different carcinogenic potencies

Yvonne C.M. Staal, Marcel H.M. van Herwijnen, Frederik J. van Schooten and Joost H.M. van Delft *

Department of Health Risk Analysis and Toxicology, Maastricht University, The Netherlands

* To whom correspondence should be addressed Email: j.vandelft@grat.unimaas.nl


   Abstract
Top
 Abstract
Introduction
 Materials and methods
 Results
 Discussion
 Conclusion
 References
 
Polycyclic aromatic hydrocarbons (PAHs) can occur in relatively high concentrations in the air, and many PAHs are known or suspected carcinogens. In order to better understand differences in carcinogenic potency between PAHs, we investigated modulation of gene expression in human HepG2 cells after 6 h incubation with varying doses of benzo[a]pyrene (B[a]P), benzo[b]fluoranthene (B[b]F), fluoranthene (FA), dibenzo[a,h]anthracene (DB[a,h]A), 1-methylphenanthrene (1-MPA) or dibenzo[a,l]pyrene (DB[a,l]P), by using cDNA microarrays containing 600 toxicologically relevant genes. Furthermore, DNA adduct levels induced by the compounds were assessed with 32P-post-labeling, and carcinogenic potency was determined by literature study. All tested PAHs, except 1-MPA, induced gene expression changes in HepG2 cells, although generally no dose–response relationship could be detected. Clustering and principal component analysis showed that gene expression changes were compound specific, since for each compound all concentrations grouped together. Furthermore, it showed that the six PAHs can be divided into three groups, first FA and 1-MPA, second B[a]P, B[b]F and DB[a,h]A, and third DB[a,l]P. This grouping corresponds with the carcinogenic potencies of the individual compounds. Many of the modulated genes are involved in biological pathways like apoptosis, cholesterol biosynthesis and fatty acid synthesis. The order of DNA adduct levels induced by the PAHs was: B[a]P >> DB[a,l]P > B[b]F > DB[a,h]A > 1-MPA ≥ FA. When comparing the expression change of individual genes with DNA adduct levels, carcinogenic potency or Ah-receptor antagonicity (the last two were taken from literature), several highly correlated genes were found, of which CYP1A1, PRKCA, SLC22A3, NFKB1A, CYP1A2 and CYP2D6 correlated with all parameters. Our data indicate that discrimination of high and low carcinogenic PAHs by gene expression profiling is feasible. Also, the carcinogenic PAHs induce several pathways that were not affected by the least carcinogenic PAHs.

Abbreviations: B[a]P, benzo[a]pyrene; B[b]F, benzo[b]fluoranthene; DB[a,h]A, dibenzo[a,h]anthracene; DB[a,l]P, dibenzo[a,l]pyrene; EROD assay, 7-ethoxyresorufin-O-deethylase assay; FA, fluoranthene; FAS, fatty acid synthase; IEF, induction equivalency factor; 1-MPA, 1-methylphenanthrene; PAH, Polycyclic aromatic hydrocarbons; PEF, potency equivalency factor; TEF, toxic equivalency factor


   Introduction
Top
 Abstract
 Introduction
Materials and methods
 Results
 Discussion
 Conclusion
 References
 
Polycyclic aromatic hydrocarbons (PAHs) occur in the environment owing to incomplete combustion of organic fuels and cover a wide range of different compounds. Exposure to some of these compounds is known to cause cancer in mice and is also suspected to be carcinogenic in humans (1–5). Although PAHs have similar structural properties, their carcinogenic potency can differ greatly. Despite that some PAHs occur in low concentrations in the environment, they can substantially contribute to the carcinogenic risk of exposure to environmental PAH mixtures. At the same time, other PAHs that occur in high concentrations in the environment are regarded as non-carcinogenic (1,2,6,7). PAHs can be carcinogenic because of their interaction with DNA and cause mutations in oncogenes or tumor suppressor genes and, thereby, initiate tumor formation (8).

PAHs are metabolically activated by Cytochrome P450 enzymes or by peroxidases to reactive intermediates that can damage DNA by covalently binding (9). The formation of DNA adducts by PAHs has been shown both in vitro (10) as well as in vivo (4,11). The DNA adduct forming potency differs between the compounds (8) and has been shown to correlate with carcinogenic potency (12). Ross et al. (11) suggested that time-integrated DNA adduct levels are a better predictor for carcinogenicity of PAHs than DNA adduct levels at a certain time point.

Some PAHs are known to activate the Aromatic hydrocarbon receptor (Ah-receptor) (13–15) and, thereby, upregulate the expression and activity of several biotransformation enzymes, including CYP1A1 and CYP1A2 (16–18). The ability to bind to the Ah-receptor has been suggested to reflect tumor promoting activity of PAHs (19). Changes in the expression of genes regulated downstream of Ah-receptor binding could be considered representative for the tumor promoting potency of a PAH. The ability to bind to the Ah-receptor and induce CYP1A1 and CYP1A2 also affects the DNA binding potency of these compounds and has been suggested to determine the genotoxicity of PAHs (20).

The toxic equivalency factor (TEF) approach is mostly used to compare the carcinogenicity of PAHs. The TEF estimates the toxicity of a compound, relative to another compound, in case of PAHs mostly to benzo[a]pyrene (B[a]P). Although based on limited information and multiple endpoints in cancer development (21,22), several authors have estimated a TEF for PAHs (23,24). Another ranking for carcinogenicity of PAHs is developed by Collins et al. (25), who estimated a potency equivalency factor (PEF) for PAHs relative to B[a]P and based these factors on bioassay data. According to the authors, PEF is an estimation of the carcinogenic activity rather than a true carcinogenic potency.

For a better understanding of the differences in carcinogenic potency between PAHs and ultimately to improve carcinogenic risk assessment of PAHs, more knowledge is required about the biological and cellular effects induced by these compounds. To our opinion, information about alterations in gene expression following exposure of cells to a PAH might be highly valuable for risk assessment. By gene expression profiling using DNA microarray technologies, early biological changes induced by a compound on a cellular system can be investigated. Indeed this technology has proven to yield mechanistic information about the mode-of-action of the compounds (26,27). Furthermore, different classes of carcinogens can be discriminated from each other at gene expression level, as they induce different gene expression patterns (28,29).

The aim of the current study was to investigate the changes in gene expression patterns in response to several PAHs, which may help further understand the mechanism of carcinogenesis of these compounds. Therefore, we exposed human hepatoma cells (HepG2) to six PAHs selected on their diverge environmental occurrence and their range in carcinogenic potency. These were B[a]P, benzo[b]fluoranthene (B[b]F), fluoranthene (FA), dibenzo[a,h]anthracene (DB[a,h]A), dibenzo[a,l]pyrene (DB[a,l]P) and 1-methylphenanthrene (1-MPA). HepG2 cells are metabolic competent, which is important for the metabolic activation of PAHs (30,31) and the cells express similar biotransformation enzymes as human liver (32,33). These cells are a suitable model for human liver and are useful to study regulation of drug-metabolizing enzymes on gene level (34). Cells were exposed to different concentrations of the PAHs and the effects at gene expression were studied in relation to their carcinogenic, DNA binding and Ah-receptor binding potencies.


   Materials and methods
Top
 Abstract
 Introduction
 Materials and methods
Results
 Discussion
 Conclusion
 References
 
Chemicals
B[a]P (purity 97%, CAS no. 50-32-8), B[b]F (purity 98%, CAS no. 205-99-2), FA (purity 99%, CAS no. 206-44-0), DB[a,h]A (purity 97%, CAS no. 53-70-3) and DB[a,l]P (purity 99.6%, CAS no. 191-30-0) were obtained from Sigma-Aldich (Zwijndrecht, The Netherlands). 1-MPA, (purity 99%, CAS no. 832-69-9) was obtained from LGC Promchem (Teddington, UK). All chemicals were dissolved in DMSO.

Cell culture and treatment
HepG2 cells were cultured in minimal essential medium (MEM) supplemented with 1% non-essential amino acids, 1% sodium-pyruvate, 2% penicillin/streptomycin and 10% fetal bovine serum (FBS) (all from Gibco BRL, Breda, The Netherlands) in T25 culture flasks at 37°C and 5% CO2. One day before treatment, cell cultures at 70–80% confluency were harvested and cells were undiluted divided among new culture flasks, in order to obtain a homogeneous cell population for each treatment. The next day, the medium was replaced with fresh medium containing 3, 10 or 30 µM of a PAH or a vehicle control (DMSO, 0.1%). The cells were exposed during 6 h, and two independent experiments were conducted. After exposure, media was removed and 1 ml Trizol (Gibco BRL, Breda, The Netherlands) was immediately added to the cells.

RNA isolation and cDNA synthesis
RNA was isolated from the Trizol solutions according to the producer's manual and purified with the RNeasy mini kit (Qiagen Westburg, Leusden, The Netherlands). RNA quantity was measured on a spectrophotometer and quality was determined on a BioAnalyzer (Agilent Technologies, Breda, The Netherlands). Only RNA samples that showed clear 18S and 28S peaks were used for labeling and hybridization.

Every RNA sample was reverse transcribed into cDNA in quadruplicate with amino allyl labeled dUTP (Sigma-Aldrich, St Louis, MO) and subsequently labeled with one of the four dyes, namely Cy3, Cy5, Alexa 488 and Alexa 594. Four instead of two dyes were applied in order to reduce the variation (four related samples are on one array instead of three) and the number of arrays [as described by Staal et al. (35)].

Microarray hybridizations
Targets were hybridized on the Human-600 Microarray (PHASE-1 Molecular Toxicology, Santa Fe, NM), containing 597 sequence verified cDNA clones from human genes, representing a number of toxicologically relevant, as well as control, genes, each printed in quadruplicate. On every array, four samples were simultaneously hybridized, each with a different fluorophore. Hybridization and washing was done according to the producers' manual as previously described (35). The hybridization design is shown in Table I.


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  		Table I. Labeling and hybridization of RNA from cells exposed to the shown PAH concentration

 
Microarray data analysis and data mining
The microarray slides were scanned on a ScanArrayExpress (Perkin Elmer life sciences, Boston, MA). All four channels were scanned at 100% laser power and adjusted photo multiplier tube (PMT) gain, such that the signal of the highest fluorescent spots is just below the maximum measurable level. The images (10 µ resolution; 16 bit tiff) were processed with ImaGene 5.0 software (Biodiscovery, Los Angeles, CA) to quantify spot signals. Abnormal spots were manually and automatically flagged and not included in the data analysis.

Data from ImaGene were transported to GeneSight software version 4.1.5 (Biodiscovery) for transformations, normalizations and analyses. For each spot, background was subtracted; flagged spots and spots with a net expression level <5 were omitted. Data were log (base 2) transformed and expression difference between exposed and control was calculated. Data normalization was done by LOWESS. Data of replicate spots were combined while omitting outliers (>2 SD). Samples from each biological replicate were hybridized twice, thereby providing four hybridizations per PAH concentration (two biological replicates with two technical replicates for each replicate). Significantly modulated genes were found by a t-test between gene expression differences of each PAH concentration compared (four replicates) with self-hybridizations (four replicates) of the control samples labeled with the same dyes at P < 0.05. A Holm's correction of the P-values was used to reduce false positives in these multiple tests.

Pathway analysis was done by the use of GenMAPP version 2.0 beta (Gladstone Institutes, University of California, San Fransisco, CA) and local maps from GenMAPP (human std 20040614). For each compound all modulated genes were included in the analysis. Pathways, with a Z-score >2.0 and >1 modulated gene, were assumed to be affected by the PAH.

DNA adduct analysis
After removal of the aqueous phase during RNA isolation using Trizol, the remaining phases were used for DNA isolation according to manufacturer's protocol. DNA adduct levels were determined according to the procedure originally described by Reddy and Randerath (36) with modifications described by Godschalk et al. (37). By including samples with known DNA adduct levels (1 adduct per 106, 107 or 108 nt), DNA adduct levels were quantified (detection limit 1 adduct/108 nt).

Adduct spots on the chromatograms were located and quantified using a phosphor imager (FLA-3000, Fuji, Paris, France) and AIDA/2D densometry software.

Correlation analysis
For correlation with carcinogenic potency, we used TEF values proposed by Nisbet and LaGoy (23) for B[a]P, B[b]F, FA and DB[a,h]A. We complemented these with the PEF values proposed by Collins et al. (25) for DB[a,l]P and estimated a TEF for 1-MPA based on IARC data (1,2) according to the method proposed by Nisbet and LaGoy (23). The resulting TEF values were; 1.0 for B[a]P, 0.1 for B[b]F, 0.001 for FA and 1-MPA, 5.0 for DB[a,h]A and 10 for DB[a,l]P. For correlation with Ah-receptor antagonicity, induction equivalency factor (IEF) values determined by Machala et al. (13) were used. We used the values after 6 h exposure and calculated the values relative to B[a]P. They were 1 for B[a]P, 0.37 for B[b]F, 0 for FA, 12.99 for DB[a,h]A and 0.05 for DB[a,l]P.

After log (base 2) transformation, DNA adduct levels, TEF and IEF were correlated with the expression changes of genes differentially expressed by at least one concentration of one compound. Since after log transformation, DNA adduct formation, TEF and IEF were normally distributed (according to the Kolmogorov–Smirnov test in SPSS, P < 0.05), Pearson correlation coefficients of gene expression were calculated using SPSS for windows 11.5 (SPSS, Chicago, IL).


   Results
Top
 Abstract
 Introduction
 Materials and methods
 Results
Discussion
 Conclusion
 References
 
Gene expression modulation
All PAHs, except 1-MPA, induced statistically significant gene expression changes. Figure 1 shows for each compound expression changes of the genes, which were significantly modulated by that compound at least one concentration. Several genes were modulated by many compounds, for example CYP1A1, CYP1A2, VMP1, IGFBP1 and HIST1H2AL. B[a]P modulated the highest number of genes, namely 36, and B[b]F, DB[a,h]A, DB[a,l]P and FA modulated 18, 31, 16 and 3 genes, respectively. For most genes and compounds, no dose dependent effect on gene expression is observed. Only for DB[a,l]P a dose–response relation could be seen for most genes. Names, abbreviations, GenBank accession nos and gene expression differences of the 62 modulated genes are listed in Table II. Additional data files are available at http://fdgwgratsrv0401.unimaas.nl/data.


Figure 1
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  		Fig. 1. Genes significantly modulated by a PAH for at least one of the concentrations of (A), B[a]P; (B), DB[a,h]A; (C), B[b]F; (D), DB[a,l]P and (E), FA. Significant modulations (compared with self-hybridizations) are indicated with an asterix. Standard deviation is indicated as error bars.

 

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  		Table II. List of modulated genes, their abbreviations, full names and GenBank accession

 
Hierarchical clustering of the PAH treatments, using the 62 genes that were modulated by at least one treatment is shown in Figure 2. The data shows that for each compound all concentrations induce similar responses, since for each compound the three concentrations are close together on the dendogram. This indicates that compound-specific gene expression profiles are induced. Also, differences and similarities between the compounds on gene expression patterns can be observed. FA and 1-MPA, which affect only a small number of genes, induce similar gene expression changes as they group closely together. Furthermore, B[a]P, B[b]F and DB[a,h]A induce gross similar gene expression changes. DB[a,l]P is found to have a different gene expression profile compared with the other compounds, but higher in the dendogram, it groups with B[a]P, B[b]F and DB[a,h]A and not with FA and 1-MPA. This figure also shows the dendograms for the genes. Most noteworthy is that all induced cytochrome P450 genes (CYP1A1, CYP1A2, CYP2D6 and CYP2E1) and IGFBP1 respond similar to all treatments and different from all other genes.


Figure 2
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  		Fig. 2. Hierarchical clustering of PAH treatments and genes, using the 62 that were significantly modulated by at least one of the treatments (see Table II). Clustering with average cluster linkage and Euclidean distance metric was used.

 
Differences in treatment related responses are also visualized by principal component analysis (Figure 3). Comparable with clustering data, this again shows that for each PAH the three dose levels are close together implying similar response on gene level. It also shows discrimination of the PAHs indicating the presence of PAH-specific gene expression profiles.


Figure 3
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  		Fig. 3. Principal component analysis of all PAH treatments using the 62 genes that were significantly modulated by at least one of the treatments (see Table II). B[a]P is shown in red, B[b]F in green, FA in dark blue, DB[a,h]A in blue, DB[a,l]P in pink and 1-MPA in yellow.

 
Pathway analysis
Pathway analysis by GenMAPP of the significantly modulated genes per compound revealed several affected pathways for most compounds. An overview is shown in Table III. Modulation of gene expressions suggests that apoptosis was induced by DB[a,l]P and DB[a,h]A, cholesterol biosynthesis was inhibited by B[a]P and B[b]F and fatty acid synthesis was inhibited by B[a]P and DB[a,l]P. Furthermore, some other pathways appear affected by one of the six compounds.


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  		Table III. Affected pathways in response to PAH treatment as revealed by analysis with GenMAPP

 
DNA adduct formation
DNA adduct levels were measured by 32P-postlabeling in the same samples as used for gene expression profiling. Results are summarized in Table IV. B[a]P exposure results in the highest number of DNA adducts (up to 1.9 adducts/105 nt), and FA and 1-MPA DNA adduct levels were not detected (detection limit 1 adduct/108 nt). No dose–response relations could be detected.


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  		Table IV. DNA adduct levels in HepG2 cells exposed to PAHs

 
Correlation studies
DNA adduct levels for all compounds and all concentrations were correlated with the expression changes of all 62 modulated genes. Significant correlations coefficients with an R2 > 0.4 are shown in Table V. The expression of several genes showed significant correlation with DNA adduct levels, for instance that of CYP1A1 (R = 0.818, P < 0.001).


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  		Table V. Pearson correlation analysis of gene expression changes and DNA adduct levels for all tested PAHs and doses

 
Expression changes of significantly modulated genes were also correlated with a parameter for carcinogenic potency, TEF, and for Ah-receptor binding potency, IEF. Both parameters are based on literature data (see Materials and methods). Since for every compound we hardly observed dose–response relations in gene expression changes, the same TEF and IEF value was used for all concentrations. Significant correlation coefficients with R2 > 0.4 are shown in Tables VI and VII. CYP1A1, PRKCA, SLC22A3, NFKB1A, CYP1A2 and CYP2D6 appeared to correlate with all parameters, and several other genes correlated with one or two parameters.


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  		Table VI. Pearson correlation analysis of gene expression changes and TEF for all tested PAHs and doses

 

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  		Table VII. Pearson correlation analysis of gene expression changes and IEF for all tested PAHs and doses

 

   Discussion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
Conclusion
 References
 
Differential gene expression
As modulation of gene expression in human liver cells, i.e. HepG2 cells, might reveal a toxic outcome (38), we studied this after exposure of the cells to several PAHs and related gene expression differences to parameters for genotoxicity, carcinogenic potency and Ah-receptor binding potency. Based on a diverse carcinogenicity and abundance in the air, we used B[a]P, B[b]F, FA, DB[a,l]P, DB[a,h]P and 1-MPA to study the effects on gene expression in HepG2 cells.

All tested PAHs, except 1-MPA, were able to modulate gene expression at concentrations up to 30 µM. However, a clear dose-response was not observed. Only DB[a,l]P showed a dose–response relation in gene expression difference for many genes. This indicates that in general a maximum induction was already achieved at the lowest concentration. The fact that DNA adducts also show no clear dose–response relations suggests that saturation of metabolism of the PAH compounds is responsible for the absence of dose–response effects on gene expression. However, Bláha et al. (39) did not find a maximum induction level in the CALUX assay at concentrations similar to those we tested. Also, in liver and lung slices a dose–response was seen up to 80 µM (40). The difference with our results could be due to a different cell system.

Of all 600 genes on the microarray, 62 genes were found modulated by one or more compounds. Principal component and hierarchical clustering analysis using these 62 genes show that for each compound the response on gene expression profiles is grossly independent of the concentration, as all concentrations of a single compound are grouped closely together. This indicates that each compound induces a unique gene expression profile in HepG2 cells. Moreover, in the hierarchical clustering at the next higher level, the compounds are grouped into carcinogenic (B[a]P, B[b]F, DB[a,h]A and DB[a,l]P) and non-carcinogenic (FA and 1-MPA). Furthermore, the most carcinogenic PAH (DB[a,l]P) is separated from the less carcinogenic compounds (B[a]P, B[b]F and DB[a,h]A). Taken into account that we examined only six PAHs, our results suggest the possibility to discriminate carcinogenic from non-carcinogenic PAHs, based on gene expression profiles.

Pathway analysis
Pathway analysis by GenMAPP revealed that several pathways appeared to be affected by the PAHs (Table III). According to the modulated gene expression, apoptosis was induced by DB[a,h]A and DB[a,l]P. We did not find induction of the apoptotic pathway in our experiments by B[a]P, although B[a]P and several other PAHs have been shown to induce apoptosis in in vitro cell systems (20,41,42). This could be due to the relative short exposure time of 6 h.

Modulated gene expression suggests an inhibition of cholesterol synthesis by B[a]P and B[b]F. It has been shown that the cholesterol content and the cholesterol biosynthesis are elevated in proliferating normal tissue and in tumors (43) and are suggested to be an indicator for neoplasmatic growth (44). Since decreased cholesterol synthesis has been shown to inhibit cell growth (43), our results suggest a cell growth reduction by B[a]P and B[b]F in HepG2 cells, which may allow the cell to recover from damage by PAHs. However, it is unclear whether PAHs indeed affect cholesterol synthesis.

Exposure to B[a]P or DB[a,l]P leads to an inhibition of genes involved in fatty acid synthesis. It has been reported that tumorigenic tissue expresses a higher level of fatty acid synthase (FAS) than normal tissue (45,46). Also, it has been shown that inhibition of FAS will result in apoptosis in human cancer cells (46,47). This would suggest that B[a]P and DB[a,l]P induce a protective response by inhibition of fatty acid synthesis. In literature we did not find a relation between PAH exposure and fatty acid synthesis pathway. However, Iwano et al. (48) previously studied the effect of 3-methylcholanthrene on the expression of several genes in HepG2 cells and found a downregulation of FASN and SCD. These enzymes are involved in fatty acid synthesis and are also downregulated in our study.

Furthermore, the Wnt signaling pathway was downregulated in response to DB[a,l]P. Genes involved in Wnt signaling (APC, ß-catenin and AXIN1) are often mutated in human cancers (49,50). As downregulation of AXIN1 by DB[a,l]P is involved in this pathway, and as AXIN1 is a tumor suppressor gene (49), this would suggest a tumorigenic potency of DB[a,l]P. However, no data on the influence of PAHs on the Wnt signaling pathway are known from literature.

The two pathways affected by B[a]P, G protein signaling and nucleotide metabolism, could not be related to carcinogenicity based on literature data.

Taken together, the affected pathways are generally involved in defense mechanisms, which protect against cancer. An upregulation of apoptosis would eliminate damaged cells, and by inhibiting the cell cycle and cholesterol biosynthesis, the damage due to the PAHs could be repaired. Other pathways such as fatty acid synthesis would suggest a less neoplastic phenotype of the cells after exposure to PAHs, which could be a defense mechanism of the cell against carcinogenic compounds.

DB[a,h]A and DB[a,l]P are the most carcinogenic of all tested compounds, and both are also the only two that induce apoptosis. This suggests that induction of apoptosis is related to high carcinogenic potency. Other affected pathways do not seem to relate with carcinogenicity of the PAHs. As FA and 1-MPA modulate only a few or no genes significantly, they affect no biological pathways.

DNA adduct formation
PAHs have been shown to form DNA adducts in several tissues, including skin, lung and liver (10,40,51,52). The order of DNA adduct levels induced by the PAHs in HepG2 cells is B[a]P >> DB[a,l]P > B[b]F > DB[a,h]A > 1-MPA ≥ FA. This differs from the order found in several other studies, namely DB[a,h]P > DB[a,h]A > B[a]P > B[b]F (10,40,51,52). This difference could be due to the difference in tissue (lung versus liver), in model system (in vivo versus in vitro), in species (rat or mouse versus human) or exposure time. However, Topinka et al. (10) also found that in rat hepatocytes B[a]P induced higher DNA adduct levels than B[b]F, and Segerback and Vodicka (52) found the same order of DNA adduct levels as we did, for B[a]P, B[b]F, DB[a,h]A and FA in DNA directly exposed to the PAHs in the presence of rat S9-mix.

Correlation studies
We correlated the 62 genes that were modulated by at least one concentration of one compound with DNA adduct formation, TEF and IEF and found that several genes gave a high correlation coefficient. Some genes correlated with all three parameters tested, namely CYP1A1, PRKCA, SLC22A3, NFKB1A, CYP1A2 and CYP2D6. Although these genes might be used for qualitative carcinogenic risk assessment of PAHs, they are not specific for either one of the parameters. The other correlating genes might be important for a single biological function or effect, like DNA adduct levels or Ah-receptor antagonicity. Sjorgen et al. (19) related several parameters, for example Ah-receptor binding, 7-ethoxyresorufin-O-deethylase (EROD) assay data, Ames test data and carcinogenicity of PAHs and found that the affinity of PAHs to bind to the Ah-receptor correlates with carcinogenic potency of the compounds.

As expected, we found significant correlation between IEF and the gene expression of the modulated cytochome P450 enzymes. These enzymes are also involved in the metabolism of PAHs and they are known to be induced via the Ah-receptor following exposure to PAHs (14,18). Also, we found a correlation between DNA adduct formation and expression of GADD45, which can be explained by the DNA damage induced by the PAHs. Pathway analysis of the significantly correlating genes revealed only pathways involved in metabolism, which is probably due to the highly correlating cytochrome P450 enzymes.


   Conclusion
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Conclusion
References
 
Our data indicate that qualitative cancer risk prediction of PAH by gene expression profiling is feasible, i.e. the discrimination of carcinogenic PAH from non-carcinogenic PAH. This may help in the characterization of risks of other PAHs for which carcinogenic potency is unknown. Additionally, some genes appeared to correlate with all three carcinogenic parameters, indicating a relationship between the expression of these genes and carcinogenicity of PAHs.


   Acknowledgments
 
The research was carried out as part of the AMBIPAH project (mechanism-based approaches to improved cancer risk assessment of ambient air polycyclic aromatic hydrocarbons), funded by the European Union (No. QLRT-2001-02402).

Conflict of Interest Statement: None declared.


   References
Top
 Abstract
 Introduction
 Materials and methods
 Results
 Discussion
 Conclusion
 References
 

  1. International Agency for Research on Cancer. (1983) Polynuclear aromatic compounds, Part 1, Chemical, environmental and experimental data. IARC Monogr. Eval. Carcinog. Risk Chem. Hum., 32, 1–453.[Medline]
  2. International Agency for Research on Cancer. (1973) Certain polycyclic aromatic hydrocarbons and heterocyclic compounds. IARC Monogr. Eval. Carcinog. Risk Chem. Hum., 3, 1–271.[Medline]
  3. Wang,J.S. and Busby,W.F. Jr (1993) Induction of lung and liver tumors by fluoranthene in a preweanling CD-1 mouse bioassay. Carcinogenesis, 14, 1871–1874.[Abstract/Free Full Text]
  4. Nesnow,S., Mass,M.J., Ross,J.A., Galati,A.J., Lambert,G.R., Gennings,C., Carter,W.H. Jr and Stoner,G.D. (1998) Lung tumorigenic interactions in strain A/J mice of five environmental polycyclic aromatic hydrocarbons. Environ. Health Perspect., 106 (Suppl 6), 1337–1346.[Medline]
  5. Boffetta,P., Jourenkova,N. and Gustavsson,P. (1997) Cancer risk from occupational and environmental exposure to polycyclic aromatic hydrocarbons. Cancer Causes Control, 8, 444–472.[CrossRef][ISI][Medline]
  6. Ciganek,M., Neca,J., Adamec,V., Janosek,J. and Machala,M. (2004) A combined chemical and bioassay analysis of traffic-emitted polycyclic aromatic hydrocarbons. Sci. Total Environ., 334–335, 141–148.
  7. Kuo,C.Y., Cheng,Y.W., Chen,C.Y. and Lee,H. (1998) Correlation between the amounts of polycyclic aromatic hydrocarbons and mutagenicity of airborne particulate samples from Taichung City, Taiwan. Environ. Res., 78, 43–49.[Medline]
  8. Cavalieri,E.L. and Rogan,E.G. (1995) Central role of radical cations in metabolic activation of polycyclic aromatic hydrocarbons. Xenobiotica, 25, 677–688.[ISI][Medline]
  9. Melendez-Colon,V.J., Luch,A., Seidel,A. and Baird,W.M. (1999) Cancer initiation by polycyclic aromatic hydrocarbons results from formation of stable DNA adducts rather than apurinic sites. Carcinogenesis, 20, 1885–1891.[Abstract/Free Full Text]
  10. Topinka,J., Schwarz,L.R., Kiefer,F., Wiebel,F.J., Gajdos,O., Vidova,P., Dobias,L., Fried,M., Sram,R.J. and Wolff,T. (1998) DNA adduct formation in mammalian cell cultures by polycyclic aromatic hydrocarbons (PAH) and nitro-PAH in coke oven emission extract. Mutat. Res., 419, 91–105.[ISI][Medline]
  11. Ross,J.A., Nelson,G.B., Wilson,K.H., Rabinowitz,J.R., Galati,A., Stoner,G.D., Nesnow,S. and Mass,M.J. (1995) Adenomas induced by polycyclic aromatic hydrocarbons in strain A/J mouse lung correlate with time-integrated DNA adduct levels. Cancer Res., 55, 1039–1044.[Abstract/Free Full Text]
  12. Brookes,P. and Lawley,P.D. (1964) Evidence for the binding of polynuclear aromatic hydrocarbons to the nucleic acids of mouse skin: relation between carcinogenic power of hydrocarbons and their binding to deoxyribonucleic acid. Nature, 202, 781–784.[CrossRef][Medline]
  13. Machala,M., Vondracek,J., Blaha,L., Ciganek,M. and Neca,J.V. (2001) Aryl hydrocarbon receptor-mediated activity of mutagenic polycyclic aromatic hydrocarbons determined using in vitro reporter gene assay. Mutat. Res., 497, 49–62.[ISI][Medline]
  14. Jones,J.M. and Anderson,J.W. (1999) Relative potencies of PAHs and PCBs based on the response of human cells. Environ. Toxicol. Pharmacol., 7, 19–26.[Medline]
  15. Tsuchiya,Y., Nakajima,M., Itoh,S., Iwanari,M. and Yokoi,T. (2003) Expression of aryl hydrocarbon receptor repressor in normal human tissues and inducibility by polycyclic aromatic hydrocarbons in human tumor-derived cell lines. Toxicol. Sci., 72, 253–259.[Abstract/Free Full Text]
  16. Chaloupka,K., Steinberg,M., Santostefano,M., Rodriguez,L.V., Goldstein,L. and Safe,S. (1995) Induction of Cyp1a-1 and Cyp1a-2 gene expression by a reconstituted mixture of polynuclear aromatic hydrocarbons in B6C3F1 mice. Chem. Biol. Interact., 96, 207–221.[CrossRef][ISI][Medline]
  17. Shimada,T. and Fujii-Kuriyama,Y. (2004) Metabolic activation of polycyclic aromatic hydrocarbons to carcinogens by cytochromes P450 1A1 and 1B1. Cancer Sci., 95, 1–6.[CrossRef][Medline]
  18. Shimada,T., Inoue,K., Suzuki,Y. et al. (2002) Arylhydrocarbon receptor-dependent induction of liver and lung cytochromes P450 1A1, 1A2, and 1B1 by polycyclic aromatic hydrocarbons and polychlorinated biphenyls in genetically engineered C57BL/6J mice. Carcinogenesis, 23, 1199–1207.[Abstract/Free Full Text]
  19. Sjogren,M., Ehrenberg,L. and Rannug,U. (1996) Relevance of different biological assays in assessing initiating and promoting properties of polycyclic aromatic hydrocarbons with respect to carcinogenic potency. Mutat. Res., 358, 97–112.[CrossRef][ISI][Medline]
  20. Solhaug,A., Refsnes,M., Lag,M., Schwarze,P.E., Husoy,T. and Holme,J.A. (2004) Polycyclic aromatic hydrocarbons induce both apoptotic and anti-apoptotic signals in Hepa1c1c7 cells. Carcinogenesis, 25, 809–819.[Abstract/Free Full Text]
  21. Delistraty,D. (1997) Toxic equivalency factor approach for risk assessment of polycyclic aromatic hydrocarbons. Toxicol. Environ. Chem., 64, 81–108.
  22. Reeves,W.R., Barhoumi,R., Burghardt,R.C., Lemke,S.L., Mayura,K., McDonald,T.J., Phillips,T.D. and Donnelly,K.C. (2001) Evaluation of methods for predicting the toxicity of polycyclic aromatic hydrocarbon mixtures. Environ Sci Technol, 35, 1630–1636.[Medline]
  23. Nisbet,I.C. and LaGoy,P.K. (1992) Toxic equivalency factors (TEFs) for polycyclic aromatic hydrocarbons (PAHs). Regul. Toxicol. Pharmacol., 16, 290–300.[CrossRef][ISI][Medline]
  24. Bostrom,C.E., Gerde,P., Hanberg,A., Jernstrom,B., Johansson,C., Kyrklund,T., Rannug,A., Tornqvist,M., Victorin,K. and Westerholm,R. (2002) Cancer risk assessment, indicators, and guidelines for polycyclic aromatic hydrocarbons in the ambient air. Environ. Health Perspect., 110 (Suppl 3), 451–488.[Medline]
  25. Collins,J.F., Brown,J.P., Alexeeff,G.V. and Salmon,A.G. (1998) Potency equivalency factors for some polycyclic aromatic hydrocarbons and polycyclic aromatic hydrocarbon derivatives. Regul Toxicol Pharmacol, 28, 45–54.[CrossRef][ISI][Medline]
  26. de Longueville,F., Atienzar,F.A., Marcq,L. et al. (2003) Use of a low-density microarray for studying gene expression patterns induced by hepatotoxicants on primary cultures of rat hepatocytes. Toxicol. Sci., 75, 378–392.[Abstract/Free Full Text]
  27. Guerreiro,N., Staedtler,F., Grenet,O., Kehren,J. and Chibout,S.D. (2003) Toxicogenomics in drug development. Toxicol. Pathol., 31, 471–479.[CrossRef][ISI][Medline]
  28. Hu,T., Gibson,D.P., Carr,G.J., Torontali,S.M., Tiesman,J.P., Chaney,J.G. and Aardema,M.J. (2004) Identification of a gene expression profile that discriminates indirect-acting genotoxins from direct-acting genotoxins. Mutat. Res., 549, 5–27.[ISI][Medline]
  29. van Delft,J.H., van Agen,E., van Breda,S.G., Herwijnen,M.H., Staal,Y.C. and Kleinjans,J.C. (2004) Discrimination of genotoxic from non-genotoxic carcinogens by gene expression profiling. Carcinogenesis, 25, 1265–1276.[Abstract/Free Full Text]
  30. Lehr,R.E. and Jerina,D.M. (1977) Metabolic activations of polycyclic hydrocarbons. Structure-activity relationships. Arch. Toxicol., 39, 1–6.[CrossRef][ISI][Medline]
  31. Vaca,C., Tornqvist,M., Rannug,U., Lindahl-Kiessling,K., Ahnstrom,G. and Ehrenberg,L. (1992) On the bioactivation and genotoxic action of fluoranthene. Arch. Toxicol., 66, 538–545.[CrossRef][ISI][Medline]
  32. Knasmuller,S., Parzefall,W., Sanyal,R. et al. (1998) Use of metabolically competent human hepatoma cells for the detection of mutagens and antimutagens. Mutat. Res., 402, 185–202.[ISI][Medline]
  33. Natarajan,A.T. and Darroudi,F. (1991) Use of human hepatoma cells for in vitro metabolic activation of chemical mutagens/carcinogens. Mutagenesis, 6, 399–403.[Abstract/Free Full Text]
  34. Wilkening,S., Stahl,F. and Bader,A. (2003) Comparison of primary human hepatocytes and hepatoma cell line Hepg2 with regard to their biotransformation properties. Drug Metab. Dispos., 31, 1035–1042.[Abstract/Free Full Text]
  35. Staal,Y.C.M., van Herwijnen,M.H.M., van Schooten,F.J. and van Delft,J.H.M. (2005) Application of four dyes in gene expression analyses by microarrays. BMC Genomics, 6, 101.[CrossRef][Medline]
  36. Reddy,M.V. and Randerath,K. (1986) Nuclease P1-mediated enhancement of sensitivity of 32P-postlabeling test for structurally diverse DNA adducts. Carcinogenesis, 7, 1543–1551.[Abstract/Free Full Text]
  37. Godschalk,R.W., Maas,L.M., Van Zandwijk,N., van 't Veer,L.J., Breedijk,A., Borm,P.J., Verhaert,J., Kleinjans,J.C. and van Schooten,F.J. (1998) Differences in aromatic-DNA adduct levels between alveolar macrophages and subpopulations of white blood cells from smokers. Carcinogenesis, 19, 819–825.[Abstract/Free Full Text]
  38. Burczynski,M.E., McMillian,M., Ciervo,J., Li,L., Parker,J.B., Dunn,R.T., 2nd, Hicken,S., Farr,S. and Johnson,M.D. (2000) Toxicogenomics-based discrimination of toxic mechanism in HepG2 human hepatoma cells. Toxicol. Sci., 58, 399–415.[Abstract/Free Full Text]
  39. Blaha,L., Kapplova,P., Vondracek,J., Upham,B. and Machala,M. (2002) Inhibition of gap-junctional intercellular communication by environmentally occurring polycyclic aromatic hydrocarbons. Toxicol. Sci., 65, 43–51.[Abstract/Free Full Text]
  40. Harrigan,J.A., Vezina,C.M., McGarrigle,B.P., Ersing,N., Box,H.C., Maccubbin,A.E. and Olson,J.R. (2004) DNA adduct formation in precision-cut rat liver and lung slices exposed to benzo(a)pyrene. Toxicol. Sci., 77, 307–314.[Abstract/Free Full Text]
  41. Chen,S., Nguyen,N., Tamura,K., Karin,M. and Tukey,R.H. (2003) The role of the Ah receptor and p38 in benzo[a]pyrene-7,8-dihydrodiol and benzo[a]pyrene-7,8-dihydrodiol-9,10-epoxide-induced apoptosis. J. Biol. Chem., 278, 19526–19533.[Abstract/Free Full Text]
  42. Pliskova,M., Vondracek,J., Vojtesek,B., Kozubik,A. and Machala,M. (2005) Deregulation of cell proliferation by polycyclic aromatic hydrocarbons in human breast carcinoma MCF-7 cells reflects both genotoxic and nongenotoxic events. Toxicol. Sci., 83, 246–256.[Abstract/Free Full Text]
  43. Rao,K.N. (1995) The significance of the cholesterol biosynthetic pathway in cell growth and carcinogenesis (review). Anticancer Res., 15, 309–314.[ISI][Medline]
  44. Venturini,I., Amedei,R., Modonesi,G., Cosenza,R., Miglioli,L., Cioni,G. and Zeneroli,M.L. (1999) May plasma cholesterol level be considered a neoplastic marker in liver disease from cirrhosis to hepatocellular carcinoma? Ital. J. Gastroenterol. Hepatol., 31, 61–65.[ISI][Medline]
  45. Pizer,E.S., Jackisch,C., Wood,F.D., Pasternack,G.R., Davidson,N.E. and Kuhajda,F.P. (1996) Inhibition of fatty acid synthesis induces programmed cell death in human breast cancer cells. Cancer Res., 56, 2745–2747.[Abstract/Free Full Text]
  46. Kuhajda,F.P. (2000) Fatty-acid synthase and human cancer: new perspectives on its role in tumor biology. Nutrition, 16, 202–208.[CrossRef][ISI][Medline]
  47. Zhou,W., Simpson,P.J., McFadden,J.M., Townsend,C.A., Medghalchi,S.M., Vadlamudi,A., Pinn,M.L., Ronnett,G.V. and Kuhajda,F.P. (2003) Fatty acid synthase inhibition triggers apoptosis during S phase in human cancer cells. Cancer Res., 63, 7330–7337.[Abstract/Free Full Text]
  48. Iwano,S., Nukaya,M., Saito,T., Asanuma,F. and Kamataki,T. (2005) A possible mechanism for atherosclerosis induced by polycyclic aromatic hydrocarbons. Biochem Biophys. Res. Commun., 335, 220–226.[CrossRef][ISI][Medline]
  49. Kikuchi,A. (2003) Tumor formation by genetic mutations in the components of the Wnt signaling pathway. Cancer Sci., 94, 225–229.[CrossRef][Medline]
  50. Giles,R.H., van Es,J.H. and Clevers,H. (2003) Caught up in a Wnt storm: Wnt signaling in cancer. Biochim. Biophys. Acta., 1653, 1–24.[Medline]
  51. Arif,J.M., Smith,W.A. and Gupta,R.C. (1999) DNA adduct formation and persistence in rat tissues following exposure to the mammary carcinogen dibenzo[a,l]pyrene. Carcinogenesis, 20, 1147–1150.[Abstract/Free Full Text]
  52. Segerback,D. and Vodicka,P. (1993) Recoveries of DNA adducts of polycyclic aromatic hydrocarbons in the 32P-postlabelling assay. Carcinogenesis, 14, 2463–2469.[Abstract/Free Full Text]
Received September 30, 2005; accepted October 26, 2005.


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