From multi-omics integration towards novel genomic interaction networks to identify key cancer cell line characteristics.

Cancer is a complex disease where cancer cells express epigenetic and transcriptomic mechanisms to promote tumor initiation, progression, and survival. To extract relevant features from the 2019 Cancer Cell Line Encyclopedia (CCLE), a multi-layer nonnegative matrix factorization approach is used. We used relevant feature genes and DNA promoter regions to construct genomic interaction network to study gene-gene and gene-DNA promoter methylation relationships. Here, we identified a set of gene transcripts and methylated DNA promoter regions for different clusters, including one homogeneous lymphoid neoplasms cluster. In this cluster, we found different methylated transcription factors that affect transcriptional activation of EGFR and downstream interactions. Furthermore, the hippo-signaling pathway might not function properly because of DNA hypermethylation and low gene expression of both LATS2 and YAP1. Finally, we could identify a potential dysregulation of the CD28-CD86-CTLA4 axis. Characterizing the interaction of the epigenome and the transcriptome is vital for our understanding of cancer cell line behavior, not only for deepening insights into cancer-related processes but also for future disease treatment and drug development. Here we have identified potential candidates that characterize cancer cell lines, which give insight into the development and progression of cancers.

Circulating microRNAs as potential biomarkers for psychiatric and neurodegenerative disorders.

Circulating microRNAs (cimiRNAs) are a class of non-encoding RNAs found in bodily fluids such as blood, cerebrospinal fluid (CSF) and tears. CimiRNAs have been implicated as promising biomarkers for central nervous system (CNS) disorders because they are actively secreted as messengers and are profoundly involved in fine-tuning of developmental and differentiation processes. Furthermore, they are attractive biomarkers because they are extremely stable, tissue enriched and can be determined in a quantitative manner. This review aims to provide a comprehensive assessment on the current progress regarding the potential value of cimiRNAs as CNS biomarkers. Within this framework five CNS disorders are explored which share a common pathological hallmark namely cognitive impairment. The CNS disorders include Major depression disorder (MDD), Bipolar disorder (BD), Schizophrenia (SZ), Alzheimer's disease (AD) and Parkinson disease (PD). The similarities and differences between altered cimiRNAs in the different disorders are described. The miR-29 family, miR-34a-5p and miR-132-3p are discussed as common dysregulated cimiRNAs found in the CNS disorders. Furthermore, it is shown that the type of bodily fluid used for measuring cimiRNAs is important as inconsistencies in cimiRNAs expression directions are found when comparing CSF, blood cell-free and blood cell-bound samples.

DynOVis: a web tool to study dynamic perturbations for capturing dose-over-time effects in biological networks.

BACKGROUND: The development of high throughput sequencing techniques provides us with the possibilities to obtain large data sets, which capture the effect of dynamic perturbations on cellular processes. However, because of the dynamic nature of these processes, the analysis of the results is challenging. Therefore, there is a great need for bioinformatics tools that address this problem. RESULTS: Here we present DynOVis, a network visualization tool that can capture dynamic dose-over-time effects in biological networks. DynOVis is an integrated work frame of R packages and JavaScript libraries and offers a force-directed graph network style, involving multiple network analysis methods such as degree threshold, but more importantly, it allows for node expression animations as well as a frame-by-frame view of the dynamic exposure. Valuable biological information can be highlighted on the nodes in the network, by the integration of various databases within DynOVis. This information includes pathway-to-gene associations from ConsensusPathDB, disease-to-gene associations from the Comparative Toxicogenomics databases, as well as Entrez gene ID, gene symbol, gene synonyms and gene type from the NCBI database. CONCLUSIONS: DynOVis could be a useful tool to analyse biological networks which have a dynamic nature. It can visualize the dynamic perturbations in biological networks and allows the user to investigate the changes over time. The integrated data from various online databases makes it easy to identify the biological relevance of nodes in the network. With DynOVis we offer a service that is easy to use and does not require any bioinformatics skills to visualize a network.

The idiosyncratic drug-induced gene expression changes in HepG2 cells.

The inflammatory stress has been associated with an increase in susceptibility to idiosyncratic drug-induced liver injury (DILI). However, the molecular mechanisms of this inflammation-associated idiosyncratic drug hepatotoxicity remain unknown. We exposed HepG2 cells with high and low doses of three idiosyncratic (I) and three non-idiosyncratic (N) compounds, in the presence (I+ and N+) or absence (I- and N-) of a cytokine mix for 6, 12 and 24 h. To investigate the genome-wide expression patterns, microarray was performed using the Agilent 4×44K Whole Human Genome chips. The data presented in this DIB include the expression of genes participating in the ceramide metabolism, ER stress, apoptosis and cell survival pathways. The functions of these genes were illustrated in our associated article (Jiang et al., 2017) [1]. Raw and normalized gene expression data are available through NCBI GEO (accession number GSE102006).

Inferring transcription factor activity from microarray data reveals novel targets for toxicological investigations.

Transcription factors (TFs) are important modulators of the inducible portion of the transcriptome, and therefore relevant in the context of exposure to exogenous compounds. Current approaches to predict the activity of TFs in biological systems are usually restricted to a few entities at a time due to low-throughput techniques targeting a limited fraction of annotated human TFs. Therefore, high-throughput alternatives may help to identify new targets of mechanistic and predictive value in toxicological investigations. In this study, we inferred the activity multiple TFs using publicly available microarray data from primary human hepatocytes exposed to hundreds of chemicals and evaluated these molecular profiles using multiple correspondence analysis. Our results demonstrate that the lowest dose and latest exposure time (24h) in a subset of chemicals generates a signature indicative of carcinogenicity possibly due to DNA-damaging properties. Furthermore, profiles from the earliest exposure time (2h) and highest dose creates clusters of chemicals implicated in the development of diverse forms of drug-induced liver injury (DILI). Both approaches yielded a number of TFs with similar activity across groups of chemicals, including TFs known in toxicological responses such as AhR, NFE2L2 (Nrf2), NF-κB and PPARG. FOXM1, IRF1 and E2F4 were some of the TFs identified that may be relevant in genotoxic carcinogenesis. SMADs (SMAD1, SMAD2, SMAD5) and KLF5 were identified as some of potentially new TFs whose inferred activities were linked to acute and progressive outcomes in DILI. In conclusion this study offers a novel mechanistic approach targeting TF activity during chemical exposure.

Omics-based identification of the combined effects of idiosyncratic drugs and inflammatory cytokines on the development of drug-induced liver injury.

The mechanisms of idiosyncratic drug-induced hepatotoxicity remain largely unclear. It has demonstrated that the drug idiosyncrasy is potentiated in the context of inflammation and intracellular ceramides may play a role in this process. To study the mechanisms, HepG2 cells were co-treated with high and low doses of three idiosyncratic (I) and three non-idiosyncratic (N) compounds, with (I+ and N+) or without (I- and N-) a cytokine mix. Microarray, lipidomics and flow cytometry were performed to investigate the genome-wide expression patterns, the intracellular ceramide levels and the induction of apoptosis. We found that all I+ treatments significantly influenced the immune response- and response to stimulus-associated gene ontology (GO) terms, but the induction of apoptotic pathways, which was confirmed by flow cytometry, only appeared to be induced after the high-dose treatment. The ceramide signaling-, ER stress-, NF-kB activation- and mitochondrial activity-related pathways were biologically involved in apoptosis induced by the high-dose I+. Additionally, genes participating in ceramide metabolism were significantly altered resulting in a measurable increase in ceramide levels. The increases in ceramide concentrations may induce ER stress and activate the JNK pathway by affecting the expression of the related genes, and eventually trigger the mitochondria-independent apoptosis in hepatocytes. Overall, our study provides a potential mechanism to explain the role of inflammation in idiosyncratic drug reactions.

Cell line-specific oxidative stress in cellular toxicity: A toxicogenomics-based comparison between liver and colon cell models.

Imbalance between high reactive oxygen species formation and antioxidant capacity in the colon and liver has been linked to increased cancer risk. However, knowledge about possible cell line-specific oxidative stress-mechanisms is limited. To explore this further, gene expression data from a human liver and colon cell line (HepG2/Caco-2), both exposed to menadione and H2O2 at six time points (0.5-1-2-4-8 and 24h) were compared in association with cell cycle distribution. In total, 3164 unique- and 1827 common genes were identified between HepG2 and Caco-2 cells. Despite the higher number of unique genes, most oxidative stress-related genes such as CAT, OGG1, NRF2, NF-κB, GCLC, HMOX1 and GSR were differentially expressed in both cell lines. However, cell-specific regulation of genes such as KEAP1 and GCLM, or of the EMT pathway, which are of pathophysiological importance, indicates that oxidative stress induces different transcriptional effects and outcomes in the two selected cell lines. In addition, expression levels and/or -direction of common genes were often different in HepG2 and Caco-2 cells, and this led to very diverse downstream effects as confirmed by correlating pathways to cell cycle changes. Altogether, this work contributes to obtaining a better molecular understanding of cell line-specific toxicity upon exposure to oxidative stress-inducing compounds.

Prediagnostic transcriptomic markers of Chronic lymphocytic leukemia reveal perturbations 10 years before diagnosis.

BACKGROUND: B-cell lymphomas are a diverse group of hematological neoplasms with differential etiology and clinical trajectories. Increased insights in the etiology and the discovery of prediagnostic markers have the potential to improve the clinical course of these neoplasms. METHODS: We investigated in a prospective study global gene expression in peripheral blood mononuclear cells of 263 incident B-cell lymphoma cases, diagnosed between 1 and 17 years after blood sample collection, and 439 controls, nested within two European cohorts. RESULTS: Our analyses identified only transcriptomic markers for specific lymphoma subtypes; few markers of multiple myeloma (N = 3), and 745 differentially expressed genes in relation to future risk of chronic lymphocytic leukemia (CLL). The strongest of these associations were consistently found in both cohorts and were related to (B-) cell signaling networks and immune system regulation pathways. CLL markers exhibited very high predictive abilities of disease onset even in cases diagnosed more than 10 years after blood collection. CONCLUSIONS: This is the first investigation on blood cell global gene expression and future risk of B-cell lymphomas. We mainly identified genes in relation to future risk of CLL that are involved in biological pathways, which appear to be mechanistically involved in CLL pathogenesis. Many but not all of the top hits we identified have been reported previously in studies based on tumor tissues, therefore suggesting that a mixture of preclinical and early disease markers can be detected several years before CLL clinical diagnosis.

Baseline and genotoxic compound induced gene expression profiles in HepG2 and HepaRG compared to primary human hepatocytes.

Efforts are put into developing toxicogenomics-based toxicity testing methods using in vitro human cell models for improving human risk assessment/replacing animal models. Human in vitro liver models include HepG2, HepaRG and primary human hepatocytes (PHH). Studies on comparability/applicability of these cell types mainly focus on assessing baseline biotransformation capacities/cytochrome P450-inducibility, but compound-induced gene expression profiles are at least as important. Therefore, we compared baseline and aflatoxin B1- and benzo(α)pyrene-induced gene expression profiles in HepG2, HepaRG and PHH (11-13 donors). At baseline, all liver models differ from each other with respect to whole genome gene expression levels. PHH show profound inter-individual differences, and are most similar to HepaRG. After compound exposure, induced gene expression profiles are more similar between cell models, especially for benzo(α)pyrene. Pathways involved in compound metabolism are induced in all 3 models, while others are more pronounced in a specific cell model. Examples are transcriptomic modifications of carbohydrate-related genes (HepaRG) and of receptor-related genes (PHH) after benzo(α)pyrene exposure, and of cell cycle-related genes (HepG2) after aflatoxin B1 exposure. PHH gene expression responses are the most heterogeneous. In conclusion, at base line level PHH are more similar to HepaRG than to HepG2, but for toxicogenomics applications both cell lines perform equally well in comparison to PHH.

Time series analysis of oxidative stress response patterns in HepG2: a toxicogenomics approach.

Oxidative stress plays an important role in chemically induced liver injury, however, our insight into molecular responses to different oxygen radicals is fragmentary. Since these cellular responses will differ over time, examining time-dependent changes in gene expression, and correlating these with markers for oxidative stress, may provide new insights into responses to oxidants. We used the human hepatoma cell line HepG2 to investigate the effects of oxidative stress on the transcriptome level by micro-arrays at seven time points (0.5, 1, 2, 4, 6, 8 and 24h) following exposure to the oxidants menadione, hydrogen peroxide and tert-butyl hydroperoxide including the effects on cell cycle and apoptosis by flow cytometry, protein carbonyl formation by spectrophotometry and oxidative DNA damage by FPG-comet. In total, 3429 genes were differentially expressed, including 136 genes that were significantly modified by all oxidants. Time-dependent biological pathway analysis showed that these genes were particularly involved in inflammatory responses, cell cycle processes and glutathione signaling. These responses were confirmed and supported by phenotypic anchoring to the different cellular endpoints. In addition, using an innovative temporal analysis we established an oxidative stress-related gene expression time cluster. Altogether, this study provides new insights in temporal oxidative stress mechanisms and demonstrates sequential cellular responses that may contribute to a better hazard identification and the mechanisms of toxicological responses in the liver induced by oxidative stress.

Benzo[a]pyrene-induced transcriptomic responses in primary hepatocytes and in vivo liver: toxicokinetics is essential for in vivo-in vitro comparisons.

The traditional 2-year cancer bioassay needs replacement by more cost-effective and predictive tests. The use of toxicogenomics in an in vitro system may provide a more high-throughput method to investigate early alterations induced by carcinogens. Recently, the differential gene expression response in wild-type and cancer-prone Xpa (-/-) p53 (+/-) primary mouse hepatocytes after exposure to benzo[a]pyrene (B[a]P) revealed downregulation of cancer-related pathways in Xpa (-/-) p53 (+/-) hepatocytes only. Here, we investigated pathway regulation upon in vivo B[a]P exposure of wild-type and Xpa (-/-) p53 (+/-) mice. In vivo transcriptomics analysis revealed a limited gene expression response in mouse livers, but with a significant induction of DNA replication and apoptotic/anti-apoptotic cellular responses in Xpa (-/-) p53 (+/-) livers only. In order to be able to make a meaningful in vivo-in vitro comparison we estimated internal in vivo B[a]P concentrations using DNA adduct levels and physiologically based kinetic modeling. Based on these results, the in vitro concentration that corresponded best with the internal in vivo dose was chosen. Comparison of in vivo and in vitro data demonstrated similarities in transcriptomics response: xenobiotic metabolism, lipid metabolism and oxidative stress. However, we were unable to detect cancer-related pathways in either wild-type or Xpa (-/-) p53 (+/-) exposed livers, which were previously found to be induced by B[a]P in Xpa (-/-) p53 (+/-) primary hepatocytes. In conclusion, we showed parallels in gene expression responses between livers and primary hepatocytes upon exposure to equivalent concentrations of B[a]P. Furthermore, we recommend considering toxicokinetics when modeling a complex in vivo endpoint with in vitro models.

Compound-specific effects of diverse neurodevelopmental toxicants on global gene expression in the neural embryonic stem cell test (ESTn).

Alternative assays for developmental toxicity testing are needed to reduce animal use in regulatory toxicology. The in vitro murine neural embryonic stem cell test (ESTn) was designed as an alternative for neurodevelopmental toxicity testing. The integration of toxicogenomic-based approaches may further increase predictivity as well as provide insight into underlying mechanisms of developmental toxicity. In the present study, we investigated concentration-dependent effects of six mechanistically diverse compounds, acetaldehyde (ACE), carbamazepine (CBZ), flusilazole (FLU), monoethylhexyl phthalate (MEHP), penicillin G (PENG) and phenytoin (PHE), on the transcriptome and neural differentiation in the ESTn. All compounds with the exception of PENG altered ESTn morphology (cytotoxicity and neural differentiation) in a concentration-dependent manner. Compound induced gene expression changes and corresponding enriched gene ontology biological processes (GO-BP) were identified after 24h exposure at equipotent differentiation-inhibiting concentrations of the compounds. Both compound-specific and common gene expression changes were observed between subsets of tested compounds, in terms of significance, magnitude of regulation and functionality. For example, ACE, CBZ and FLU induced robust changes in number of significantly altered genes (≥ 687 genes) as well as a variety of GO-BP, as compared to MEHP, PHE and PENG (≤ 55 genes with no significant changes in GO-BP observed). Genes associated with developmentally related processes (embryonic morphogenesis, neuron differentiation, and Wnt signaling) showed diverse regulation after exposure to ACE, CBZ and FLU. In addition, gene expression and GO-BP enrichment showed concentration dependence, allowing discrimination of non-toxic versus toxic concentrations on the basis of transcriptomics. This information may be used to define adaptive versus toxic responses at the transcriptome level.

A transcriptomics-based in vitro assay for predicting chemical genotoxicity in vivo.

The lack of accurate in vitro assays for predicting in vivo toxicity of chemicals together with new legislations demanding replacement and reduction of animal testing has triggered the development of alternative methods. This study aimed at developing a transcriptomics-based in vitro prediction assay for in vivo genotoxicity. Transcriptomics changes induced in the human liver cell line HepG2 by 34 compounds after treatment for 12, 24, and 48 h were used for the selection of gene-sets that are capable of discriminating between in vivo genotoxins (GTX) and in vivo nongenotoxins (NGTX). By combining transcriptomics with publicly available results for these chemicals from standard in vitro genotoxicity studies, we developed several prediction models. These models were validated by using an additional set of 28 chemicals. The best prediction was achieved after stratification of chemicals according to results from the Ames bacterial gene mutation assay prior to transcriptomics evaluation after 24h of treatment. A total of 33 genes were selected for discriminating GTX from NGTX for Ames-positive chemicals and 22 for Ames-negative chemicals. Overall, this method resulted in 89% accuracy and 91% specificity, thereby clearly outperforming the standard in vitro test battery. Transcription factor network analysis revealed HNF3a, HNF4a, HNF6, androgen receptor, and SP1 as main factors regulating the expression of classifiers for Ames-positive chemicals. Thus, the classical bacterial gene mutation assay in combination with in vitro transcriptomics in HepG2 is proposed as an upgraded in vitro approach for predicting in vivo genotoxicity of chemicals holding a great promise for reducing animal experimentations on genotoxicity.

Comparison of phenotypic and transcriptomic effects of false-positive genotoxins, true genotoxins and non-genotoxins using HepG2 cells.

The conventional in vitro assays for genotoxicity assessment of chemicals are characterised by a high false-positive rate, thus failing to correctly predict their in vivo genotoxic effects. This study aimed to identify the cellular mechanisms induced by the false-positive genotoxins quercetin, 8-Hydroxyquinoline and 17-beta oestradiol in comparison to true genotoxins and non-genotoxins, by combining in vitro phenotypic parameters with transcriptomics data from HepG2 cells. The effects of these compounds on the phosphorylation of H2AX, cell cycle distribution and whole genome gene expression following treatment for 12, 24 and 48 h were compared with the effects of true genotoxins [benzo[a]pyrene and aflatoxin B1] and non-genotoxins (2,3,7,8-tetrachlorodibenzodioxin, cyclosporin A and ampicillin C). Quercetin induced similar phenotypic effects as true genotoxins and to some extent similar gene expression alterations. Different gene expression changes were also observed, including the up-regulation of DNA repair-related genes. 8-Hydroxyquinoline and 17-beta oestradiol showed no similarities to the true genotoxins at both the phenotypic and the transcriptomic level. In a classification approach, classifiers were selected to discriminate between genotoxins and non-genotoxins. Subsequent analysis for the false-positive compounds showed quercetin to be predicted as genotoxic and 8-hydroxyquinoline and 17-beta oestradiol as non-genotoxic. Our results support that transcriptomics analysis of compound effects in HepG2 leads to similar results with phenotypic analysis and provides additional mechanistic information. Therefore, combined evaluation of gene expression alterations and relevant functional end points using HepG2 cells may contribute to the better understanding of modes-of-action of chemicals and the correct evaluation of their genotoxic properties.

Transcriptomic network analysis of micronuclei-related genes: a case study.

Mechanistically relevant information on responses of humans to xenobiotic exposure in relation to chemically induced biological effects, such as micronuclei (MN) formation can be obtained through large-scale transcriptomics studies. Network analysis may enhance the analysis and visualisation of such data. Therefore, this study aimed to develop a 'MN formation' network based on a priori knowledge, by using the pathway tool MetaCore. The gene network contained 27 genes and three gene complexes that are related to processes involved in MN formation, e.g. spindle assembly checkpoint, cell cycle checkpoint and aneuploidy. The MN-related gene network was tested against a transcriptomics case study associated with MN measurements. In this case study, transcriptomic data from children and adults differentially exposed to ambient air pollution in the Czech Republic were analysed and visualised on the network. Six genes from the network, i.e. BAX, DMNT1, PCNA, HIC1, p21 and CDC20, were retrieved. Based on these six genes and in combination with p53 and IL-6, a dedicated network was created. This dedicated network is possibly suited for the development of a reporter gene assay that could be used to screen populations complementary to the current MN test assay. In conclusion, we have shown that network analysis of transcriptomics data in relation to the formation of MN is possible and provides a novel mechanistic hypothesis by indicating which genes are regulated and influence others.

Gene expression profiling in primary mouse hepatocytes discriminates true from false-positive genotoxic compounds.

Well-established in vitro methods for testing the genotoxic potency of chemicals--such as the Ames/Salmonella test, the mouse lymphoma assay, the micronucleus test and the chromosomal aberration test--show a high false-positive rate for predicting in vivo genotoxicity and carcinogenicity. Thus, there is a need for more reliable in vitro assays. We investigated whether gene expression profiling in metabolically competent primary mouse hepatocytes is capable of discriminating true genotoxic (GTX) compounds from false-positive genotoxic (FP-GTX) compounds. Sandwich-cultured primary hepatocytes from male C57Bl6 mice were treated for 24 and 48 h with five true GTX and five FP-GTX compounds. Whole genome gene expression modifications were analysed by means of Affymetrix mouse genome 430 2.0 microarrays. Filtered genes were used for hierarchical clustering and class prediction methods. Classifiers were generated by prediction analysis of microarray using a leave-one-compound-out method and selecting the genes that were common to the 10 training sets. For the training compounds, all but one were correctly classified. Validation of the classification model with five new compounds resulted in a 100% correct classification at 24 h and 80% at 48 h. The generated classifiers were mostly involved in metabolic and biosynthetic processes, immune responses and apoptosis. Applying genes whose expression change correlates with γH2AX foci, a measure for DNA damage, did not improve the classification. The present study shows that gene expression profiling in primary mouse hepatocytes is capable of discriminating between true GTX and FP-GTX compounds.

A pro-inflammatory genotype predisposes to Barrett's esophagus.

INTRODUCTION: Severity of mucosal inflammation is shown to be associated with Barrett's esophagus (BE) development in animals. It has therefore been postulated that a strong pro-inflammatory host response predisposes to BE. AIM: To determine the impact of cytokine gene polymorphisms on the development of BE. METHODS: The multiplex SNaPshot method was used to determine interleukin (IL)-12B (A+1188C), IL-10 (C-592A, C-819T, A-1082G), IL-8 (A-251T), IL-6 (G-174C) and IL-2 (G-330T) gene polymorphisms in 255 patients with BE and 247 patients with reflux esophagitis (RE). RESULTS: The presence of the IL-12B C-allele, which is associated with increased IL-12p70 expression, was more frequently observed in BE than in RE patients [odds ratio (OR) 1.8; 95% confidence interval (CI) 1.2-2.7; P = 0.007). The risk of BE was increased in patients in whom the IL-12B C-allele coincided with a hiatal hernia (OR 2.9; 95% CI 1.32-6.58; P = 0.008). The IL-10(-1082) GG genotype, which is associated with higher IL-10 levels, was also associated with a decreased risk of BE when it was associated with the IL-12B C-allele, indicating IL-10-dependent down-regulation of IL-12p70 expression. A combination of the IL-12B AA genotype and the IL-10 AA or AG genotypes was associated with RE (OR 1.4; 95% CI 1.05-1.85; P = 0.011). CONCLUSION: A genetic profile predisposing to a strong pro-inflammatory host response, mediated by IL-12p70 and partially dependent on IL-10, is associated with BE. This risk further increases when this genotype coincides with a hiatal hernia, suggesting that exposure to gastroesophageal reflux in the presence of a pro-inflammatory genetic background is a driving force in the development of BE.

A sandwich-cultured rat hepatocyte system with increased metabolic competence evaluated by gene expression profiling.

A rapid decline of cytochrome P450 (CYP450) enzyme activities remains a drawback of rat hepatocyte-based in vitro cultures. Consequently, judgment of the toxic potential of compounds that need bioactivation by CYP450s may not be adequate using this model. In the present study, an improved hepatocyte-based in vitro system was developed with special focus on metabolic competence. Therefore, a mixture of CYP450 inducers, phenobarbital, dexamethasone and beta-naphthoflavone, was added to culture medium of sandwich-cultured rat hepatocytes. The resulting modified model was evaluated by comparing its genome-wide expression profiles with liver and a standard model without the inducer mixture. Metabolic capacity for CYP450 enzymes showed that the modified model resembled more closely the in vivo situation. Gene expression results revealed large differences between in vivo and both in vitro models. The slight differences between the two sandwich models were predominantly represented by gene expression changes in CYP450s. Importantly, in the modified model, expression ratios of the phase I and the majority of phase II genes more closely resembled liver in vivo. The CYP450 enzyme activities corresponded with gene expression data. In conclusion, for toxicological applications using sandwich-cultured hepatocytes, the modified model may be preferred.

Genome-wide differential gene expression in children exposed to air pollution in the Czech Republic.

The Teplice area in the Czech Republic is a mining district where elevated levels of air pollution including airborne carcinogens, have been demonstrated, especially during winter time. This environmental exposure can impact human health; in particular children may be more vulnerable. To study the impact of air pollution in children at the transcriptional level, peripheral blood cells were subjected to whole genome response analysis, in order to identify significantly modulated biological pathways and processes as a result of exposure. Using genome-wide oligonucleotide microarrays, we investigated differential gene expression in children from the Teplice area (n=23) and compared them with children from the rural control area of Prachatice (n=24). In an additional approach, individual gene expressions were correlated with individual peripheral blood lymphocyte micronuclei frequencies, in order to evaluate the linkage of individual gene expressions with an established biomarker of effect that is representative for increased genotoxic risk. Children from the Teplice area showed a significantly higher average micronuclei frequency than Prachatice children (p=0.023). For considerable numbers of genes, the expression differed significantly between the children from the two areas. Amongst these genes, considerable numbers of genes were observed to correlate significantly with the frequencies of micronuclei. The main biological process that appeared significantly affected overall was nucleosome assembly. This suggests an effect of air pollution on the primary structural unit of the condensed DNA. In addition, several other pathways were modulated. Based on the results of this study, we suggest that transcriptomic analysis represents a promising biomarker for environmental carcinogenesis.

[Relationship between the composition of fine dust particles in the air and lung function in school children]. / Relatie tussen de samenstelling van fijn stofin de lucht en de longfunctie van schoolkinderen.

OBJECTIVE: To determine whether or not there is a relationship between the lung function of school children and the ability of fine dust particles in the air to generate radicals. DESIGN: Descriptive. METHOD: Six primary schools in locations with different traffic volumes were selected in Maastricht, the Netherlands. Air samples were taken in these schools over a period of 4 days; the concentration of fine dust was measured in the 6 pooled samples. Lung function tests were performed in children in the age of 8-13 and their parents filled out a questionnaire on the state of their children's health. RESULTS: An average of 66% of the children (184 girls and 158 boys, with an average age of 10 years (range: 8-13 years)) participated. The average FEV1 for the children from the 6 schools was not related with the total amount of fine dust particles in the air. However, a lower average FEV1 was associated with a higher radical-generating capacity in the air samples. No direct association was observed between the radical-generating capacity of the dust and the traffic intensity. CONCLUSION: There was a clear relationship between lung function and the radical-generating capacity of fine dust in the air. On the basis of these findings future guidelines could be based on chemical properties of the fine dust particles and not exclusively on the quantity of fine dust.