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.

ABSTRACT:Primary human and rat hepatocyte cultures are well established in vitro systems used in toxicological studies. However, whereas transgenic mouse models provide an opportunity for studying mechanisms of toxicity, mouse primary hepatocyte cultures are less well described. The potential usefulness of a mouse hepatocyte-based in vitro model was assessed in this study by investigating time-dependent competence for xenobiotic metabolism and gene expression profiles. Primary mouse hepatocytes, isolated using two-step collagenase perfusion, were cultured in a collagen sandwich configuration. Gene expression profiles and the activities of various cytochrome P450 (P450) enzymes were determined after 0, 42, and 90 h in culture. Principal component analysis of gene expression profiles shows that replicates per time point are similar. Gene expression levels of most phase I biotransformation enzymes decrease to approximately 69 and 57% of the original levels at 42 and 90 h, respectively, whereas enzyme activities for most of the studied P450s decrease to 59 and 34%. The decrease for phase II gene expression is only to 96 and 92% of the original levels at 42 and 90 h, respectively. Pathway analysis reveals initial effects at the level of proteins, external signaling pathways, and energy production. Later effects are observed for transcription, translation, membranes, and cell cycle-related gene sets. These results indicate that the sandwich-cultured primary mouse hepatocyte system is robust and seems to maintain its metabolic competence better than that of the rat hepatocyte system.

Assessing the potential carcinogenicity of chemicals for humans represents an ongoing challenge. Chronic rodent bioassays predict human cancer risk at only limited reliability and are simultaneously expensive and long lasting. In order to seek for alternatives, the ability of a transcriptomics-based primary mouse hepatocyte model to classify carcinogens by their modes of action was evaluated. As it is obvious that exposure will induce a cascade of gene expression modifications, in particular, the influence of exposure time in vitro on discriminating genotoxic (GTX) carcinogens from nongenotoxic (NGTX) carcinogens class discrimination was investigated. Primary mouse hepatocytes from male C57Bl6 mice were treated for 12, 24, 36, and 48 h with two GTX and two NGTX carcinogens. For validation, two additional GTX compounds were studied at 24 and 48 h. Immunostaining of gammaH2AX foci was applied in order to phenotypically verify DNA damage. It confirmed significant induction of DNA damage after treatment with GTX compounds but not with NGTX compounds. Whole-genome gene expression modifications were analyzed by means of Affymetrix microarrays. When using differentially expressed genes from data sets normalized by Robust Multi-array Average, the two classes and various compounds were better separated from each other by hierarchical clustering when increasing the treatment period. Discrimination of GTX and NGTX carcinogens by Prediction Analysis of Microarray improved with time and resulted in correct classification of the validation compounds. The present study shows that gene expression profiling in primary mouse hepatocytes is promising for discriminating GTX from NGTX compounds and that this discrimination improves with increasing treatment period.

Background Nitrate is converted to nitrite in the human body and subsequently can react with amines and amides in the gastrointestinal tract to form N-nitroso compounds (NOCs), which are known to be carcinogenic in animals. Humans can be exposed to nitrate via consumption of drinking water and diet, especially green leafy vegetables and cured meat. The contribution of nitrate from drinking water in combination with meat intake has not been investigated thoroughly. Therefore, in the present pilot study, we examined the effect of nitrate from drinking water, and its interaction with the consumption of white and processed red meat, on the endogenous formation of NOCs, taking into account the intake of vitamin C, a nitrosation inhibitor. Methods Twenty healthy subjects were randomly assigned to two groups consuming either 3.75 g/kg body weight (maximum 300 g per day) processed red meat or unprocessed white meat per day for two weeks. Drinking water nitrate levels were kept low during the first week (< 1.5 mg/L), whereas in week 2, nitrate levels in drinking water were adjusted to the acceptable daily intake level of 3.7 mg/kg bodyweight. At baseline, after 1 and 2 weeks, faeces and 24 h urine samples were collected for analyses of nitrate, apparent total N-nitroso compounds (ATNC), compliance markers, and genotoxic potential in human colonic Caco-2 cells. Results Urinary nitrate excretion was significantly increased during the high drinking water nitrate period for both meat types. Furthermore, levels of compliance markers for meat intake were significantly increased in urine from subjects consuming processed red meat (i.e. 1-Methylhistidine levels), or unprocessed white meat (i.e. 3-Methylhistidine). ATNC levels significantly increased during the high drinking water nitrate period, which was more pronounced in the processed red meat group. Genotoxicity in Caco-2 cells exposed to faecal water resulted in increased genotoxicity after the interventions, but results were only significant in the low drinking water nitrate period in subjects consuming processed red meat. Furthermore, a positive correlation was found between the ratio of nitrate/vitamin C intake (including drinking water) and the level of ATNC in faecal water of subjects in the processed red meat group, but this was not statistically significant. Conclusions Drinking water nitrate significantly contributed to the endogenous formation of NOC, independent of the meat type consumed. This implies that drinking water nitrate levels should be taken into account when evaluating the effect of meat consumption on endogenous formation of NOC. Trial registration Dutch Trialregister: 29707. Registered 19th of October 2018. Retrospectively registered.

Microarray technology is being used increasingly to study gene expression of biological systems on a large scale. Both interlaboratory and interplatform differences are known to contribute to variability in microarray data. In this study we have investigated data from different platforms and laboratories on the transcriptomic profile of HepG2 cells exposed to benzo(a)pyrene (BaP). RNA samples generated in two different laboratories were analyzed using both Agilent oligonucleotide microarrays and Cancer Research UK (CR-UK) cDNA microarrays. Comparability of the expression profiles was assessed at various levels including correlation and overlap between the data, clustering of the data and affected biological processes. Overlap and correlation occurred, but it was not possible to deduce whether choice of platform or interlaboratory differences contributed more to the data variation. Principal component analysis (PCA) and hierarchical clustering of the expression profiles indicated that the data were most clearly defined by duration of exposure to BaP, suggesting that laboratory and platform variability does not mask the biological effects. Real-time quantitative PCR was used to validate the two array platforms and indicated that false negatives, rather than false positives, are obtained with both systems. All together these results suggest that data from similar biological experiments analyzed on different microarray platforms can be combined to give a more complete transcriptomic profile. Each platform gives a slight variation in the BaP-gene expression response and, although it cannot be stated which is more correct, combining the two data sets is more informative than considering them individually.