Chemical carcinogens may cause a multitude of effects inside cells, thereby affecting transcript levels of genes by direct activation of transcription factors (TF) or indirectly through the formation of DNA damage. As the temporal profiles of these responses may be profoundly different, examining time-dependent changes may provide new insights in TF networks related to cellular responses to chemical carcinogens. Therefore, we investigated in human hepatoma cells gene expression changes caused by benzo[a]pyrene at 12 time points after exposure, in relation to DNA adduct and cell cycle. Temporal profiles for functional gene sets demonstrate both early and late effects in up- and downregulation of relevant gene sets involved in cell cycle, apoptosis, DNA repair, and metabolism of amino acids and lipids. Many significant transcription regulation networks appeared to be around TF that are proto-oncogenes or tumor suppressor genes. The time series analysis tool Short Time-series Expression Miner (STEM) was used to identify time-dependent correlation of pathways, gene sets, TF networks, and biological parameters. Most correlations are with DNA adduct levels, which is an early response, and less with the later responses on G1 and S phase cells. The majority of the modulated genes in the Reactome pathways can be regulated by several of these TF, e.g., 73% by nuclear factor-kappa B and 34-42% by c-MYC, SRF, AP1, and E2F1. All these TF can also regulate one or more of the others. Our data indicate that a complex network of a few TF is responsible for the majority of the transcriptional changes induced by BaP. This network hardly changes over time, despite that the transcriptional profiles clearly alter, suggesting that also other regulatory mechanisms are involved.

Polycyclic aromatic hydrocarbons (PAHs) cover a wide range of structurally related compounds which differ greatly in their carcinogenic potency. PAH exposure usually occurs through mixtures rather than individual compounds. Therefore, we assessed whether the effects of binary PAH mixtures on gene expression, DNA adduct formation, apoptosis and cell cycle are additive compared with the effects of the individual compounds in human hepatoma cells (HepG2). Equimolar and equitoxic mixtures of benzo[a]pyrene (B[a]P) with either dibenzo[a,l]pyrene (DB[a,l]P), dibenzo[a,h]anthracene (DB[a,h]A), benzo[b]fluoranthene (B[b]F), fluoranthene (FA) or 1-methylphenanthrene (1-MPA) were studied. DB[a,l]P, B[a]P, DB[a,h]A and B[b]F dose-dependently increased apoptosis and blocked cells cycle in S-phase. PAH mixtures showed an additive effect on apoptosis and on cell cycle blockage. DNA adduct formation in mixtures was higher than expected based on the individual compounds, indicating a synergistic effect of PAH mixtures. Equimolar mixtures of B[a]P and DB[a,l]P (0.1, 0.3 and 1.0 microM) were assessed for their effects on gene expression. Only at 1.0 microM, the mixture showed antagonism. All five compounds were also tested as a binary mixture with B[a]P in equitoxic concentrations. The combinations of B[a]P with B[b]F, DB[a,h]A or FA showed additivity, whereas B[a]P with DB[a,l]P or 1-MPA showed antagonism. Many individual genes showed additivity in mixtures, but some genes showed mostly antagonism or synergism. Our results show that the effects of binary mixtures of PAHs on gene expression are generally additive or slightly antagonistic, suggesting no effect or decreased carcinogenic potency, whereas the effects on DNA adduct formation show synergism, which rather indicates increased carcinogenic potency.

The EU-EuroMix project adopted the strategy of the European Food Safety Authority (EFSA) for cumulative risk assessment, which limits the number of chemicals to consider in a mixture to those that induce a specific toxicological phenotype. These so-called cumulative assessment groups (CAGs) are refined at several levels, including the target organ and specific phenotype. Here, we explore the zebrafish embryo as a test model for quantitative evaluation in one such CAG, skeletal malformations, through exposure to test compounds 0–120 hpf and alcian blue cartilage staining at 120 hpf, focusing on the head skeleton. Reference compounds cyproconazole, flusilazole, metam, and thiram induced distinctive phenotypes in the head skeleton between the triazoles and dithiocarbamates. Of many evaluated parameters, the Meckel’s–palatoquadrate (M–PQ) angle was selected for further assessment, based on the best combination of a small confidence interval, an intermediate maximal effect size and a gentle slope of the dose–response curve with cyproconazole and metam. Additional test compounds included in the CAG skeletal malformations database were tested for M–PQ effects, and this set was supplemented with compounds associated with craniofacial malformations or cleft palate to accommodate otherwise organized databases. This additional set included hexaconazole, all-trans-retinoic acid, AM580, CD3254, maneb, pyrimethanil, imidacloprid, pirimiphos-methyl, 2,4-dinitrophenol, 5-fluorouracil, 17alpha-ethynylestradiol (EE2), ethanol, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), PCB 126, methylmercury, boric acid, and MEHP. Most of these compounds produced a dose–response for M–PQ effects. Application of the assay in mixture testing was provided by combined exposure to cyproconazole and TCDD through the isobole method, supporting that in this case the combined effect can be modeled through concentration addition.

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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 (32)P-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.

Two general mechanisms are implicated in chemical carcinogenesis. The first involves direct damage to DNA, referred to as genotoxic (GTX), to which the cell responds by repair of the damages, arrest of the cell cycle or induction of apoptosis. The second is non-DNA damaging, non-genotoxic (NGTX), in which a wide variety of cellular processes may be involved. Therefore, it can be hypothesized that modulation of the underlying gene expression patterns is profoundly distinct between GTX and NGTX carcinogens, and thus that expression profiling is applicable for classification of chemical carcinogens as GTX or NGTX. We investigated this hypothesis by analysing modulation of gene expression profiles induced by 20 chemical carcinogens in HepG2 cells with application of cDNA microarrays that contain 597 toxicologically relevant genes. In total, 22 treatments were included, divided in two sets. The training set consisted of 16 treatments (nine genotoxins and seven non-genotoxins) and the validation set of six treatments (three and three). Class discrimination models based on Pearson correlation analyses for the 20 most discriminating genes were developed with data from the training set, where after the models were tested with all data. Using all data, the correctness for classification of the carcinogens from the training set was clearly better than that for the validation set, namely 81 and 33%, respectively. Exclusion of the treatments that had only marginal effects on the expression profiles, improved the discrimination for the training and validation sets to 92 and 100% correctness, respectively. Exclusion of the gene expression signals that were hardly altered also improved classification, namely to 94 and 80%. Therefore, our study proves the principle that gene expression profiling can discriminate carcinogens with major differences in their mode of actions, namely genotoxins versus non-genotoxins.

BackgroundCurcumin is a spice and a coloring food compound with a promising role in colon cancer prevention. Curcumin protects against development of colon tumors in rats treated with a colon carcinogen, in colon cancer cells curcumin can inhibit cell proliferation and induce apoptosis, it is an anti-oxidant and it can act as an anti-inflammatory agent. The aim of this study was to elucidate mechanisms and effect of curcumin in colon cancer cells using gene expression profiling.MethodsGene expression changes in response to curcumin exposure were studied in two human colon cancer cell lines, using cDNA microarrays with four thousand human genes. HT29 cells were exposed to two different concentrations of curcumin and gene expression changes were followed in time (3, 6, 12, 24 and 48 hours). Gene expression changes after short-term exposure (3 or 6 hours) to curcumin were also studied in a second cell type, Caco-2 cells.ResultsGene expression changes (>1.5-fold) were found at all time points. HT29 cells were more sensitive to curcumin than Caco-2 cells. Early response genes were involved in cell cycle, signal transduction, DNA repair, gene transcription, cell adhesion and xenobiotic metabolism. In HT29 cells curcumin modulated a number of cell cycle genes of which several have a role in transition through the G2/M phase. This corresponded to a cell cycle arrest in the G2/M phase as was observed by flow cytometry. Functional groups with a similar expression profile included genes involved in phase-II metabolism that were induced by curcumin after 12 and 24 hours. Expression of some cytochrome P450 genes was downregulated by curcumin in HT29 and Caco-2 cells. In addition, curcumin affected expression of metallothionein genes, tubulin genes, p53 and other genes involved in colon carcinogenesis.ConclusionsThis study has extended knowledge on pathways or processes already reported to be affected by curcumin (cell cycle arrest, phase-II genes). Moreover, potential new leads to genes and pathways that could play a role in colon cancer prevention by curcumin were identified.

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