Research toward the development of a biologically based dose response assessment for inorganic arsenic carcinogenicity: a progress report

Low-Dose Arsenic Trioxide Modulates the Differentiation of Mouse Embryonic Stem Cells

Arsenic (As) is a well-known environmental pollutant, while arsenic trioxide (ATO) has been proven to be an effective treatment for acute promyelocytic leukemia, however, the mechanism underlying its dual effects is not fully understood. Embryonic stem cells (ESCs) exhibit properties of stemness and serve as a popular model to investigate epigenetic modifiers including environmental pollutants. Herein, the effects of low-dose ATO on differentiation were evaluated in vitro using a mouse ESCs (mESCs) cell line, CGR8. Cells treated with 0.2-0.5 μM ATO for 3-4 days had slight inhibition of proliferation with elevation of apoptosis, but obvious alterations of differentiation by morphological checking and alkaline phosphatase (AP) staining. Moreover, ATO exposure significantly decreased the mRNA expression of the stemness maintenance genes including Oct4, Nanog, and Rex-1 ( P < 0.01), whereas obviously increased some tissue-specific differentiation marker genes such as Gata4, Gata-6, AFP, and IHH. These alterations were consistent with the differentiation phenotype induced by retinoic acid (RA) and the expression patterns of distinct pluripotency markers such as SSEA-1 and Oct4. Furthermore, low-dose ATO led to a quantitative increase in Caspase 3 (CASP3) activation and subsequent cleavage of Nanog around 27 kDa, which corresponded with the mouse Nanog cleaved by CASP3 in a tube cleavage assay. Taken together, we suggest that low-dose ATO exposure will induce differentiation, other than apoptosis, of ESCs, such effects might be tuned partially by ATO-induced CASP3 activation and Nanog cleavage coupling with other differentiation related genes involved. The present findings provide a preliminary action mechanism of arsenic on the cell fate determination.

Human health implications, risk assessment and remediation of As-contaminated water: A critical review

Arsenic (As) is a naturally occurring metalloid and Class-A human carcinogen. Exposure to As via direct intake of As-contaminated water or ingestion of As-contaminated edible crops is considered a life threatening problem around the globe. Arsenic-laced drinking water has affected the lives of over 200 million people in 105 countries worldwide. Limited data are available on various health risk assessment models/frameworks used to predict carcinogenic and non-carcinogenic health effects caused by As-contaminated water. Therefore, this discussion highlights the need for future research focusing on human health risk assessment of individual As species (both organic and inorganic) present in As-contaminated water. Various conventional and latest technologies for remediation of As-contaminated water are also reviewed along with a discussion of the fate of As-loaded waste and sludge.

In silico toxicology: computational methods for the prediction of chemical toxicity

Determining the toxicity of chemicals is necessary to identify their harmful effects on humans, animals, plants, or the environment. It is also one of the main steps in drug design. Animal models have been used for a long time for toxicity testing. However, in vivo animal tests are constrained by time, ethical considerations, and financial burden. Therefore, computational methods for estimating the toxicity of chemicals are considered useful. In silico toxicology is one type of toxicity assessment that uses computational methods to analyze, simulate, visualize, or predict the toxicity of chemicals. In silico toxicology aims to complement existing toxicity tests to predict toxicity, prioritize chemicals, guide toxicity tests, and minimize late-stage failures in drugs design. There are various methods for generating models to predict toxicity endpoints. We provide a comprehensive overview, explain, and compare the strengths and weaknesses of the existing modeling methods and algorithms for toxicity prediction with a particular (but not exclusive) emphasis on computational tools that can implement these methods and refer to expert systems that deploy the prediction models. Finally, we briefly review a number of new research directions in in silico toxicology and provide recommendations for designing in silico models. WIREs Comput Mol Sci 2016, 6:147-172. doi: 10.1002/wcms.1240 For further resources related to this article, please visit the WIREs website.

Assessing the cancer risk associated with arsenic-contaminated seafood

Tens of millions of people worldwide ingest excessive amounts of arsenic (As) through drinking water and food. The dietary intake of seafood is the major As exposure route in humans and can cause As-related adverse health effects including cancers. The aim of this study was to quantify potential cancer risks of As exposure for children and adults through seafood consumption. By coupling the age-specific physiologically based pharmacokinetic (PBPK) model and a Weibull-based dose-response function, a more accurate estimate of urinary arsenic metabolites could be achieved to better characterize potential cancer risks. The simulation results show that the proportion of inorganic As, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) in human urine are estimated to total 6.7, 26.9, and 66.4% for children, and 6.2, 27.4, and 66.4% for adults, respectively. The estimated median cumulative cancer incidence ratios were respectively 2.67x10(-6) and 3.83x10(-6) for children and adults, indicating a low cancer risk for local residents exposed to As through the consumption of seafood. However, it is necessary to incorporate other exposure routes into the model to make it more realistic. The methodology proposed here can not only be applied to calculate the concentrations of As metabolites in urine, but also to provide a direct estimation of adverse health effects caused by the calculated internal concentrations.

Tissue-level modeling of xenobiotic metabolism in liver: An emerging tool for enabling clinical translational research

This review summarizes some of the recent developments and identifies critical challenges associated with in vitro and in silico representations of the liver and assesses the translational potential of these models in the quest of rationalizing the process of evaluating drug efficacy and toxicity. It discusses a wide range of research efforts that have produced, during recent years, quantitative descriptions and conceptual as well as computational models of hepatic processes such as biotransport and biotransformation, intra- and intercellular signal transduction, detoxification, etc. The above mentioned research efforts cover multiple scales of biological organization, from molecule-molecule interactions to reaction network and cellular and histological dynamics, and have resulted in a rapidly evolving knowledge base for a "systems biology of the liver." Virtual organ/organism formulations represent integrative implementations of particular elements of this knowledge base, usually oriented toward the study of specific biological endpoints, and provide frameworks for translating the systems biology concepts into computational tools for quantitative prediction of responses to stressors and hypothesis generation for experimental design.

Arsenic-induced carcinogenesis--oxidative stress as a possible mode of action and future research needs for more biologically based risk assessment

Exposure to inorganic arsenic (iAs) induces cancer in human lungs, urinary bladder, skin, kidney, and liver, with the majority of deaths from lung and bladder cancer. To date, cancer risk assessments for iAs have not relied on mechanistic data, as we have lacked sufficient understanding of arsenic's pharmacokinetics and mode(s) of carcinogenic action (MOA). Furthermore, while there are vast amounts of toxicological data on iAs, relatively little of it has been collected using experimental designs that efficiently support development of biologically based dose-response (BBDR) models and subsequently risk assessment. This review outlines an efficient approach to the development of a BBDR model for iAs that would reduce uncertainties in its cancer risk assessment. This BBDR-based approach is illustrated by using oxidative stress as the carcinogenic MOA for iAs but would be generically applicable to other MOAs. Six major research needs that will facilitate BBDR model development for arsenic-induced cancer are (1) MOA research, which is needed to reduce the uncertainty in risk assessment; (2) development and integration of the pharmacodynamic component (MOA) of the BBDR model; (3) dose-response and extrapolation model selection; (4) the determination of internal human speciated arsenical concentrations to improve physiologically based pharmacokinetic (PBPK) models; (5) animal models of arsenic carcinogenesis; and (6) the determination of the low dose human relationship for death from cancer, particularly in lungs and urinary bladder. The major parts of the BBDR model are arsenic exposure, a physiologically based pharmacokinetic model, reactive species, antioxidant defenses, oxidative stress, cytotoxicity, growth factors, transcription factors, DNA damage, chromosome damage, cell proliferation, mutation accumulation, and cancer. The BBDR model will need to be developed concurrently with data collection so that model uncertainties can be identified and addressed through an iterative process of targeted additional research.

Risk assessment practice for essential metals

This article addresses the content of the workshop, including a panel discussion relevant to delineation of a path forward in relation to risk assessment of essential metals. The state of the art of risk assessment and associated issues for essential metals are outlined initially, followed by brief illustration by the case studies considered at the workshop (i.e., copper, zinc, and manganese). Approaches for the future testing strategies of essential metals are discussed in terms of options to increase efficiency and accuracy of assessments. Subsequently, recommendations for pragmatic next steps to advance progress and facilitate uptake by the regulatory risk assessment community are presented.

Analysis of genomic dose-response information on arsenic to inform key events in a mode of action for carcinogenicity

A comprehensive literature search was conducted to identify information on gene expression changes following exposures to inorganic arsenic compounds. This information was organized by compound, exposure, dose/concentration, species, tissue, and cell type. A concentration-related hierarchy of responses was observed, beginning with changes in gene/protein expression associated with adaptive responses (e.g., preinflammatory responses, delay of apoptosis). Between 0.1 and 10 microM, additional gene/protein expression changes related to oxidative stress, proteotoxicity, inflammation, and proliferative signaling occur along with those related to DNA repair, cell cycle G2/M checkpoint control, and induction of apoptosis. At higher concentrations (10-100 microM), changes in apoptotic genes dominate. Comparisons of primary cell results with those obtained from immortalized or tumor-derived cell lines were also evaluated to determine the extent to which similar responses are observed across cell lines. Although immortalized cells appear to respond similarly to primary cells, caution must be exercised in using gene expression data from tumor-derived cell lines, where inactivation or overexpression of key genes (e.g., p53, Bcl-2) may lead to altered genomic responses. Data from acute in vivo exposures are of limited value for evaluating the dose-response for gene expression, because of the transient, variable, and uncertain nature of tissue exposure in these studies. The available in vitro gene expression data, together with information on the metabolism and protein binding of arsenic compounds, provide evidence of a mode of action for inorganic arsenic carcinogenicity involving interactions with critical proteins, such as those involved in DNA repair, overlaid against a background of chemical stress, including proteotoxicity and depletion of nonprotein sulfhydryls. The inhibition of DNA repair under conditions of toxicity and proliferative pressure may compromise the ability of cells to maintain the integrity of their DNA.

Inhibition by methylated organo-arsenicals of the respiratory 2-oxo-acid dehydrogenases

Inorganic arsenic that is ingested through drinking water or inhalation is metabolized by biological methylation pathways into organoarsenical metabolites. It is now becoming understood that this metabolism that was formerly considered to be detoxification may contribute as much or more to increasing the toxicity of arsenic. One proposed mode of the toxic action of arsenic and its organoarsenic metabolites is through its binding to proteins and inactivating their enzymatic activity. The classic case has been considered the affinity of the proximal 1,3 sulfhydryl groups of the lipoic acid cofactor of the pyruvate dehydrogenase complex for arsenic. A 2:1 stoichiometry of sulfhydryl to arsenic groups has been measured in proteins and arsenical complexes can be synthesized using free D,L-lipoic acid. The relative importance of this site for arsenic binding has come in to question through the use of methylating bifunctional arsenic complexes that suggested the methylation of an active site histidine may also be important, and the suggestion that arsenic inhibits the pyruvate dehydrogenase complex indirectly by elevating mitochondrial hydrogen peroxide generation. In order to separate the effects of direct trivalent arsenite toxicity from that of hydrogen peroxide and activated oxygen, we studied the inhibition of the PDH complex under conditions that did not generate hydrogen peroxide but did expose the lipoic acid group in its reduced state to arsenicals. We also studied the effects of arsenicals in the inhibition of the α-ketoglutarate dehydrogenase complex. We found that only trivalent arsenical compounds inhibited the activity of both dehydrogenase complexes and only when the lipoic acid was in its reduced form. Arsenite inhibited both enzyme complexes approximately equivalently while monomethylarsenite inhibited the PDH complex to a greater extent than the KGDH complex - although both complexes were very sensitive to inhibition by this complex. Dimethylarsenite inhibition of both complexes was only observed with longer pre-incubation periods. Cumulative inhibition by the reduced arsenical was observed for all complexes indicating a binding mode of inhibition that is dependent upon lipoic acid being in its reduced state.