Abstract Chronic exposure to aflatoxin B1 (AFB1) has, in certain regions in the world, been strongly associated with hepatocellular carcinoma (HCC) development. AFB1 is a very potent hepatotoxic and ...carcinogenic mycotoxin which is frequently reported as a food contaminant. Epigenetic modifications provoked by environmental exposures, such as AFB1, may create a persistent epigenetic footprint. Deregulation of epigenetic mechanisms has actually been reported in HCC patients following AFB1 exposure; however, no attempts have yet been made to investigate early effects on the epigenome level which may be persistent on longer term, thereby possibly initiating carcinogenic events. In this study, we aim to identify methyl DNA-mRNA-interactions representative for a persistent epigenetic footprint associated with the early onset of AFB1-induced HCC. For this, primary human hepatocytes were exposed to 0.3 μM of AFB1 for 5 days. Persistent epigenetic effects were measured 3 days after terminating the carcinogenic exposure. Whole genome DNA methylation changes and whole genome transcriptomic analysis were analyzed applying microarray technologies, and cross-omics interactions were evaluated. Upon combining transcriptomics data with results on DNA methylation, a range of persistent hyper- and hypo-methylated genes was identified which also appeared affected on the transcriptome level. For six of the hypo-methylated and up-regulated genes, namely TXNRD1, PCNA, CCNK, DIAPH3, RAB27A and HIST1H2BF, a clear role in carcinogenic events could be identified. This study is the first to report on a carcinogen-induced persistent impact on the epigenetic footprint in relation with the transcriptome which could be indicative for the early onset of AFB1-related development of HCC.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
The liver is the primary site for the metabolism and detoxification of many compounds, including pharmaceuticals. Consequently, it is also the primary location for many adverse reactions. As the ...liver is not readily accessible for sampling in humans; rodent or cell line models are often used to evaluate potential toxic effects of a novel compound or candidate drug. However, relating the results of animal and in vitro studies to relevant clinical outcomes for the human in vivo situation still proves challenging. In this study, we incorporate principles of transfer learning within a deep artificial neural network allowing us to leverage the relative abundance of rat in vitro and in vivo exposure data from the Open TG-GATEs data set to train a model to predict the expected pattern of human in vivo gene expression following an exposure given measured human in vitro gene expression. We show that domain adaptation has been successfully achieved, with the rat and human in vitro data no longer being separable in the common latent space generated by the network. The network produces physiologically plausible predictions of human in vivo gene expression pattern following an exposure to a previously unseen compound. Moreover, we show the integration of the human in vitro data in the training of the domain adaptation network significantly improves the temporal accuracy of the predicted rat in vivo gene expression pattern following an exposure to a previously unseen compound. In this way, we demonstrate the improvements in prediction accuracy that can be achieved by combining data from distinct domains.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
In clinical trials, animal and cell line models are often used to evaluate the potential toxic effects of a novel compound or candidate drug before progressing to human trials. However, relating the ...results of animal and in vitro model exposures to relevant clinical outcomes in the human in vivo system still proves challenging, relying on often putative orthologs. In recent years, multiple studies have demonstrated that the repeated dose rodent bioassay, the current gold standard in the field, lacks sufficient sensitivity and specificity in predicting toxic effects of pharmaceuticals in humans. In this study, we evaluate the potential of deep learning techniques to translate the pattern of gene expression measured following an exposure in rodents to humans, circumventing the current reliance on orthologs, and also from in vitro to in vivo experimental designs. Of the applied deep learning architectures applied in this study the convolutional neural network (CNN) and a deep artificial neural network with bottleneck architecture significantly outperform classical machine learning techniques in predicting the time series of gene expression in primary human hepatocytes given a measured time series of gene expression from primary rat hepatocytes following exposure in vitro to a previously unseen compound across multiple toxicologically relevant gene sets. With a reduction in average mean absolute error across 76 genes that have been shown to be predictive for identifying carcinogenicity from 0.0172 for a random regression forest to 0.0166 for the CNN model (p < 0.05). These deep learning architecture also perform well when applied to predict time series of in vivo gene expression given measured time series of in vitro gene expression for rats.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Differentiated human bronchial epithelial cells in air liquid interface cultures (ALI-PBEC) represent a promising alternative for inhalation studies with rodents as these 3D airway epithelial tissue ...cultures recapitulate the human airway in multiple aspects, including morphology, cell type composition, gene expression and xenobiotic metabolism. We performed a detailed longitudinal gene expression analysis during the differentiation of submerged primary human bronchial epithelial cells into ALI-PBEC to assess the reproducibility and inter-individual variability of changes in transcriptional activity during this process. We generated ALI-PBEC cultures from four donors and focussed our analysis on the expression levels of 362 genes involved in biotransformation, which are of primary importance for toxicological studies. Expression of various of these genes (e.g., GSTA1, ADH1C, ALDH1A1, CYP2B6, CYP2F1, CYP4B1, CYP4X1 and CYP4Z1) was elevated following the mucociliary differentiation of airway epithelial cells into a pseudo-stratified epithelial layer. Although a substantial number of genes were differentially expressed between donors, the differences in fold changes were generally small. Metabolic activity measurements applying a variety of different cytochrome p450 substrates indicated that epithelial cultures at the early stages of differentiation are incapable of biotransformation. In contrast, mature ALI-PBEC cultures were proficient in the metabolic conversion of a variety of substrates albeit with considerable variation between donors. In summary, our data indicate a distinct increase in biotransformation capacity during differentiation of PBECs at the air–liquid interface and that the generation of biotransformation competent ALI-PBEC cultures is a reproducible process with little variability between cultures derived from four different donors.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Arsenic is an established human carcinogen, but the mechanisms through which it contributes to for instance lung cancer development are still unclear. As arsenic is methylated during its metabolism, ...it may interfere with the DNA methylation process, and is therefore considered to be an epigenetic carcinogen. In the present study, we hypothesize that arsenic is able to induce DNA methylation changes, which lead to changes in specific gene expression, in pathways associated with lung cancer promotion and progression. A549 human adenocarcinoma lung cells were exposed to a low (0.08 µM), intermediate (0.4 µM) and high (2 µM) concentration of sodium arsenite for 1, 2 and 8 weeks. DNA was isolated for whole-genome DNA methylation analyses using NimbleGen 2.1 M deluxe promoter arrays. In addition, RNA was isolated for whole-genome transcriptomic analysis using Affymetrix microarrays. Arsenic modulated DNA methylation and expression levels of hundreds of genes in a dose-dependent and time-dependent manner. By combining whole-genome DNA methylation and gene expression data with possibly involved transcription factors, a large molecular interaction network was created based on transcription factor-target gene pairs, consisting of 216 genes. A tumor protein p53 (
TP53
) subnetwork was identified, showing the interactions of
TP53
with other genes affected by arsenic. Furthermore, multiple other new genes were discovered showing altered DNA methylation and gene expression. In particular, arsenic modulated genes which function as transcription factor, thereby affecting target genes which are known to play a role in lung cancer promotion and progression.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Direct comparison of the hepatoma cell lines HepG2 and HepaRG has previously been performed by only evaluating a limited set of genes or proteins. In this study, we examined the whole-genome gene ...expression of both cell lines before and after exposure to the genotoxic (GTX) carcinogens aflatoxin B1 and benzoapyrene and the nongenotoxic (NGTX) carcinogens cyclosporin A, 17β-estradiol, and 2,3,7,8-tetrachlorodibenzo-para-dioxin for 12 and 48 h. Before exposure, this analysis revealed an extensive network of genes and pathways, which were regulated differentially for each cell line. The comparison of the basal gene expression between HepG2, HepaRG, primary human hepatocytes (PHH), and liver clearly showed that HepaRG resembles PHH and liver the most. After exposure to the GTX and NGTX carcinogens, for both cell lines, common pathways were found that are important in carcinogenesis, for example, cell cycle regulation and apoptosis. However, also clear differences between exposed HepG2 and HepaRG were observed, and these are related to common metabolic processes, immune response, and transcription processes. Furthermore, HepG2 performs better in discriminating between GTX and NGTX carcinogens. In conclusion, these results have shown that HepaRG is a more suited in vitro liver model for biological interpretations of the effects of exposure to chemicals, whereas HepG2 is a more promising in vitro liver model for classification studies using the toxicogenomics approach. Although, it should be noted that only five carcinogens were used in this study.
•Toxic doses of acetaminophen (APAP) boost the formation of mitochondrial reactive oxygen species (ROS).•Toxic doses of APAP disrupt the expression of many genes encoding the subunits of electron ...transport chain (ETC) complexes, and reduce the expression of SOD2, a mitochondria-specific antioxidant enzyme.•Toxic doses of APAP reduce the ATP yield of human liver cells.
Acetaminophen (APAP) overdosage results in hepatotoxicity, but the underlying molecular mechanisms are still not completely understood. In the current study, we focused on mitochondrial-specific oxidative liver injury induced by APAP exposure. Owning to genetic polymorphisms in the CYP2E1 gene or varying inducibility by xenobiotics, the CYP2E1 mRNA level and protein activity vary extensively among individuals. As CYP2E1 is a known ROS generating enzyme, we chose HepG2 to minimize CYP2E1-induced ROS formation, which will help us better understand the APAP induced mitochondrial-specific hepatotoxicity in a subpopulation with low CYP2E1 activity. HepG2 cells were exposed to a low and toxic dose (0.5 and 10mM) of APAP and analyzed at four time points for genome-wide gene expression. Mitochondria were isolated and electron spin resonance spectroscopy was performed to measure the formation of mitochondrial ROS. The yield of ATP was measured to confirm the impact of the toxic dose of APAP on cellular energy production. Our results indicate that 10mM APAP significantly influences the expression of mitochondrial protein-encoding genes in association with an increase in mitochondrial ROS formation. Additionally, 10mM APAP affects the expression of genes encoding the subunits of electron transport chain (ETC) complexes, which may alter normal mitochondrial functions by disrupting the assembly, stability, and structural integrity of ETC complexes, leading to a measurable depletion of ATP, and cell death. The expression of mitochondrium-specific antioxidant enzyme, SOD2, is reduced which may limit the ROS scavenging ability and cause imbalance of the mitochondrial ROS homeostasis. Overall, transcriptome analysis reveals the molecular processes involved in the observed APAP-induced increase of mitochondrial ROS formation and the associated APAP-induced oxidative stress.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UL, UM, UPCLJ, UPUK
5-Fluorouracil (5-FU) is a widely used chemotherapeutical that induces acute toxicity in the small and large intestine of patients. Symptoms can be severe and lead to the interruption of cancer ...treatments. However, there is limited understanding of the molecular mechanisms underlying 5-FU-induced intestinal toxicity. In this study, well-established 3D organoid models of human colon and small intestine (SI) were used to characterize 5-FU transcriptomic and metabolomic responses. Clinically relevant 5-FU concentrations for in vitro testing in organoids were established using physiologically based pharmacokinetic simulation of dosing regimens recommended for cancer patients, resulting in exposures to 10, 100 and 1000 µM. After treatment, different measurements were performed: cell viability and apoptosis; image analysis of cell morphological changes; RNA sequencing; and metabolome analysis of supernatant from organoids cultures. Based on analysis of the differentially expressed genes, the most prominent molecular pathways affected by 5-FU included cell cycle, p53 signalling, mitochondrial ATP synthesis and apoptosis. Short time-series expression miner demonstrated tissue-specific mechanisms affected by 5-FU, namely biosynthesis and transport of small molecules, and mRNA translation for colon; cell signalling mediated by Rho GTPases and fork-head box transcription factors for SI. Metabolomic analysis showed that in addition to the effects on TCA cycle and oxidative stress in both organoids, tissue-specific metabolic alterations were also induced by 5-FU. Multi-omics integration identified transcription factor E2F1, a regulator of cell cycle and apoptosis, as the best key node across all samples. These results provide new insights into 5-FU toxicity mechanisms and underline the relevance of human organoid models in the safety assessment in drug development.
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EMUNI, FIS, FZAB, GEOZS, GIS, IJS, IMTLJ, KILJ, KISLJ, MFDPS, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, SBMB, SBNM, UKNU, UL, UM, UPUK, VKSCE, ZAGLJ
Gefitinib is a tyrosine kinase inhibitor (TKI) that selectively inhibits the epidermal growth factor receptor (EGFR), hampering cell growth and proliferation. Due to its action, gefitinib has been ...used in the treatment of cancers that present abnormally increased expression of EGFR. However, side effects from gefitinib therapy may occur, among which diarrhoea is most common, that can lead to interruption of the planned therapy in the more severe cases. The mechanisms underlying intestinal toxicity induced by gefitinib are not well understood. Therefore, this study aims at providing insight into these mechanisms based on transcriptomic responses induced in vitro. A 3D culture of healthy human colon and small intestine (SI) organoids was exposed to 0.1, 1, 10 and 30 µM of gefitinib, for a maximum of three days. These drug concentrations were selected using physiologically-based pharmacokinetic simulation considering patient dosing regimens. Samples were used for the analysis of viability and caspase 3/7 activation, image-based analysis of structural changes, as well as RNA isolation and sequencing via high-throughput techniques. Differential gene expression analysis showed that gefitinib perturbed signal transduction pathways, apoptosis, cell cycle, FOXO-mediated transcription, p53 signalling pathway, and metabolic pathways. Remarkably, opposite expression patterns of genes associated with metabolism of lipids and cholesterol biosynthesis were observed in colon versus SI organoids in response to gefitinib. These differences in the organoids' responses could be linked to increased activated protein kinase (AMPK) activity in colon, which can influence the sensitivity of the colon to the drug. Therefore, this study sheds light on how gefitinib induces toxicity in intestinal organoids and provides an avenue towards the development of a potential tool for drug screening and development.
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IZUM, KILJ, NUK, PILJ, PNG, SAZU, UL, UM, UPUK
Arsenic (As) contamination in groundwater is responsible for numerous adverse health outcomes among millions of people. Epigenetic alterations are among the most widely studied mechanisms of As ...toxicity. To understand how As exposure alters gene expression through epigenetic modifications, a systematic genome-wide study was designed to address the impact of multiple important single nucleotide polymorphisms (SNPs) related to As exposure on the methylome of drinking water As-exposed rural subjects from Pakistan. Urinary As levels were used to stratify subjects into low, medium and high exposure groups. Genome-wide DNA methylation was investigated using MeDIP in combination with NimbleGen 2.1 M Deluxe Promotor arrays. Transcriptome levels were measured using Agilent 8 × 60 K expression arrays. Genotyping of selected SNPs (As3MT, DNMT1a, ERCC2, EGFR and MTHFR) was measured and an integrated genetic risk factor for each respondent was calculated by assigning a specific value to the measured genotypes based on known risk allele numbers. To select a representative model related to As exposure we compared 9 linear mixed models comprising of model 1 (including the genetic risk factor), model 2 (without the genetic risk factor) and models with individual SNPs incorporated into the methylome data. Pathway analysis was performed using ConsensusPathDB. Model 1 comprising the integrated genetic risk factor disclosed biochemical pathways including muscle contraction, cardio-vascular diseases, ATR signaling, GPCR signaling, methionine metabolism and chromatin modification in association with hypo- and hyper-methylated gene targets. A unique pathway (direct P53 effector) was found associated with the individual DNMT1a polymorphism due to hyper-methylation of CSE1L and TRRAP. Most importantly, we provide here the first evidence of As-associated DNA methylation in relation with gene expression of ATR, ATF7IP, TPM3, UBE2J2. We report the first evidence that integrating SNPs data with methylome data generates a more representative epigenome profile and discloses a better insight in disease risks of As-exposed individuals.
•Analysis of global blood methylome changes associated with As exposure via drinking water.•Integrating As-related SNPs with epigenome data yielded refined methylome profiles.•Novel As-related signaling and disease pathways found associated with As exposure.•Evidence of As-induced interplay between DNA methylation and gene expression.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP