Can systems toxicology identify common biomarkers of non-genotoxic carcinogenesis?

Impacts of Environmental Pollution on Brain Tumorigenesis

Pollutants consist of several components, known as direct or indirect mutagens, that can be associated with the risk of tumorigenesis. The increased incidence of brain tumors, observed more frequently in industrialized countries, has generated a deeper interest in examining different pollutants that could be found in food, air, or water supply. These compounds, due to their chemical nature, alter the activity of biological molecules naturally found in the body. The bioaccumulation leads to harmful effects for humans, increasing the risk of the onset of several pathologies, including cancer. Environmental components often combine with other risk factors, such as the individual genetic component, which increases the chance of developing cancer. The objective of this review is to discuss the impact of environmental carcinogens on modulating the risk of brain tumorigenesis, focusing our attention on certain categories of pollutants and their sources.

The selected epigenetic effects of phthalates: DBP, BBP and their metabolites: MBP, MBzP on human peripheral blood mononuclear cells (In Vitro)

Phthalates are classified as non-genotoxic carcinogens. These compounds do not cause direct DNA damage but may induce indirect DNA lesions leading to cancer development. In the presented paper we have studied the effect of di-n-butyl phthalate (DBP), butylbenzyl phthalate (BBP), and their metabolites, such as mono-n-butyl phthalate (MBP) and monobenzyl phthalate (MBzP) on selected epigenetic parameters in human peripheral blood mononuclear cells (PBMCs). The cells were incubated with tested phthalates at 0.001, 0.01 and 0.1 μg/mL for 24 h. Next, global DNA methylation, methylation in the promoter regions of tumor suppressor genes (P16, TP53) and proto-oncogenes (BCL2, CCND1) were assessed as well as the expression profile of the indicated genes was analysed. The obtained results have revealed significant reduction of global DNA methylation level in PBMCs exposed to BBP, MBP and MBzP. Phthalates changed methylation pattern of the tested genes, decreased expression of P16 and TP53 genes and increased the expression of BCL2 and CCND1. In conclusion, our results have shown that the examined phthalates disturbed the processes of methylation and expression of tumor suppressor genes (P16, TP53) and protooncogenes (BCL2, CCND1) in human PBMCs.

Effects of the tributyltin on the blood parameters, immune responses and thyroid hormone system in zebrafish

Tributyltin (TBT) is a widely used organotin compound around the world and was frequently detected in surface waters, which would pose risk to aquatic organisms. However, the mechanisms of TBT-induced toxicity is not full clear. The present study investigated the effects of the tributyltin (TBT) on the blood parameters, immune responses and thyroid hormone system in zebrafish. Fish were exposed to sublethal concentrations of TBT (10 ng/L, 100 ng/L and 300 ng/L) for 6 weeks. The effects of long-term exposure to TBT on blood parameters (NH3, ammonia; GLU, glucose; TP, total proteins; CK, creatine kinase; ALT, alanine aminotransferase; AST, aspartate aminotransferase), immune responses (Lys, lysozyme; IgM, immunoglobulin M) and some indexes related thyroid hormone system (T3, 3,5,3'-triiodothyronine; T4, thyroxine) were measured in zebrafish, as well as the expression of genes related to immune responses and thyroid hormone system. Based on the results, the physiological-biochemical responses was significantly enhanced with an increase in TBT concentration, reflected by the abnormal blood indices, dysregulation of endocrine system and immunotoxicity in zebrafish under TBT stress. The present study greatly extends our understanding of adverse effects of TBT on aquatic organisms.

Identification of Time-Invariant Biomarkers for Non-Genotoxic Hepatocarcinogen Assessment

Non-genotoxic hepatocarcinogens (NGHCs) can only be confirmed by 2-year rodent studies. Toxicogenomics (TGx) approaches using gene expression profiles from short-term animal studies could enable early assessment of NGHCs. However, high variance in the modulation of the genes had been noted among exposure styles and datasets. Expanding from our previous strategy in identifying consensus biomarkers in multiple experiments, we aimed to identify time-invariant biomarkers for NGHCs in short-term exposure styles and validate their applicability to long-term exposure styles. In this study, nine time-invariant biomarkers, namely A2m, Akr7a3, Aqp7, Ca3, Cdc2a, Cdkn3, Cyp2c11, Ntf3, and Sds, were identified from four large-scale microarray datasets. Machine learning techniques were subsequently employed to assess the prediction performance of the biomarkers. The biomarker set along with the Random Forest models gave the highest median area under the receiver operating characteristic curve (AUC) of 0.824 and a low interquartile range (IQR) variance of 0.036 based on a leave-one-out cross-validation. The application of the models to the external validation datasets achieved high AUC values of greater than or equal to 0.857. Enrichment analysis of the biomarkers inferred the involvement of chronic inflammatory diseases such as liver cirrhosis, fibrosis, and hepatocellular carcinoma in NGHCs. The time-invariant biomarkers provided a robust alternative for NGHC prediction.

Environmental co-exposure to TBT and Cd caused neurotoxicity and thyroid endocrine disruption in zebrafish, a three-generation study in a simulated environment

Although the coexistence of heavy metals and environmental hormones always occur in aquatic environment, the information of the combined impacts remains unclear. To explore the multi-generational toxicity of cadmium (Cd) and tributyltin (TBT), adult zebrafish (Danio rerio) (F0) were exposed to different treated groups (100 ng/l Cd, 100 ng/l TBT and their mixture) for 90 d, with their offspring (F1 and F2) subsequently reared in the same exposure solutions corresponding to their parents. Both developmental neurotoxicity and thyroid disturbances were examined in the three (F0, F1, and F2) generations. Our results showed that co-exposure to Cd and TBT induced the developmental neurotoxicity in F1 and F2 generations, reflected by the significant lower levels of neurotransmitters (dopamine and serotonin) and the inhibited acetylcholinesterase (AChE) activities. And the thyroid endocrine disruption were observed in the two-generations larval offspring by parental exposure to Cd and/or TBT, including the significantly decreasing levels of thyroid hormones and the down-regulated the expression of genes involved in the hypothalamus-pituitary-thyroid axis, compared to the control. Additional, the embryonic toxicity and growth inhibition were also determined in the fish larvae. Overall, this study examined the impacts of parental co-exposure to Cd and TBT, with regard to developmental inhibition, nervous system damage and endocrine disruption, which highlighted that co-exposure influences are complicated and need to be considered for accurate environmental risk assessment.

Identification of consensus biomarkers for predicting non-genotoxic hepatocarcinogens

The assessment of non-genotoxic hepatocarcinogens (NGHCs) is currently relying on two-year rodent bioassays. Toxicogenomics biomarkers provide a potential alternative method for the prioritization of NGHCs that could be useful for risk assessment. However, previous studies using inconsistently classified chemicals as the training set and a single microarray dataset concluded no consensus biomarkers. In this study, 4 consensus biomarkers of A2m, Ca3, Cxcl1, and Cyp8b1 were identified from four large-scale microarray datasets of the one-day single maximum tolerated dose and a large set of chemicals without inconsistent classifications. Machine learning techniques were subsequently applied to develop prediction models for NGHCs. The final bagging decision tree models were constructed with an average AUC performance of 0.803 for an independent test. A set of 16 chemicals with controversial classifications were reclassified according to the consensus biomarkers. The developed prediction models and identified consensus biomarkers are expected to be potential alternative methods for prioritization of NGHCs for further experimental validation.

Identifying the causative proteins of similar side effect pairs to explore the common molecular basis of these side effects

Drug side effects, or adverse drug reactions (ADRs), have become a major public health concern and often cause drug development failure and withdrawal. Some ADRs always occur concomitantly. Therefore, identifying these ADRs and their common molecular basis can better promote their prevention and treatment. In this paper we predicted the potential proteins for ADR pairs with similar mechanisms based on three layers of information: (i) the drug co-occurrence between a pair of ADRs; (ii) the correlation between a protein and an ADR pair based on the co-occurrence of drugs and (iii) the interaction between these proteins within the protein-protein interaction (PPI) network. The methods of randomization and functional annotation are used to investigate and analyze the relation between causative proteins and similar ADR pairs. The prediction accuracy of the relation between similar ADR pairs and related proteins reached 80%, and it increases with the number of drugs shared by the ADR pairs. From the ADR network made of single ADRs from predicted similar ADR pairs, we found that some ADRs are involved in multiple ADR pairs. The functional analysis of these ADR-related proteins suggests that a similar molecular basis is shared by multiple ADR pairs containing the same ADR, and these ADR pairs are almost caused by the same drug sets. The results of this study are reliable and provide a theoretical basis for the better prevention and treatment of ADRs that always occur concomitantly.

Changes of c-Myc and DNMT1 mRNA and protein levels in the rat livers induced by dibutyl phthalate treatment

We investigated the relationship between dibutyl phthalate (DBP)-induced hypomethylation of the c-Myc promoter region (as evident in our early study) and the expression of c-Myc and DNMT1 genes (at messenger RNA (mRNA) and protein level) in the rat liver. Male Wistar rats received DBP in 1, 3, or 14 daily doses of 1800 mg kg−1 body weight. Levels of DNMT1, c-Myc mRNA, and proteins were detected using real-time polymerase chain reaction and Western blot analysis, respectively. Our findings indicate that DBP caused an increase in mRNA levels of c-Myc at all time points. The results showed that protein levels of c-Myc in rat liver also increased significantly by DBP treatment, which were more pronounced at last time point (after 14 doses). Furthermore, overexpression of DNMT1gene have been found after one dose of DBP, which was confirmed at the protein level by Western blot analysis. Reduced levels of DNMT1mRNA and proteins (3 and 14 doses) were coordinated with depletion DNA synthesis (reported previously). Based on our previous results and those presented here, the following conclusion could be drawn: (1) DBP exerted biological activity through epigenetic modulation of c-Myc gene expression; (2) it seems possible that DBP-induced active demethylation of c-Myc gene through mechanism(s) linked to generation of reactive oxygen species by activated c-Myc; and (3) control of DNA replication was not directly dependent on c-Myc transcriptional activity and we attribute this finding to DNMT1gene expression which was tightly coordinated with DNA synthesis.

Construction of a computable network model for DNA damage, autophagy, cell death, and senescence

Towards the development of a systems biology-based risk assessment approach for environmental toxicants, including tobacco products in a systems toxicology setting such as the “21st Century Toxicology”, we are building a series of computable biological network models specific to non-diseased pulmonary and cardiovascular cells/tissues which capture the molecular events that can be activated following exposure to environmental toxicants. Here we extend on previous work and report on the construction and evaluation of a mechanistic network model focused on DNA damage response and the four main cellular fates induced by stress: autophagy, apoptosis, necroptosis, and senescence. In total, the network consists of 34 sub-models containing 1052 unique nodes and 1538 unique edges which are supported by 1231 PubMed-referenced literature citations. Causal node-edge relationships are described using the Biological Expression Language (BEL), which allows for the semantic representation of life science relationships in a computable format. The Network is provided in .XGMML format and can be viewed using freely available network visualization software, such as Cytoscape.

Human environments: definition, scope, and the role of toxicology

This chapter is a brief introduction to the subject matter of the volume including the complexity and definition of human environments. Exposure to complex mixtures and the problem of interactions are considered as well as the important role of toxicology in environmental and human health, including risk analysis, risk management, and risk communication.

Predicting drug side-effects by chemical systems biology

New approaches to predicting ligand similarity and protein interactions can explain unexpected observations of drug inefficacy or side-effects.