Biochemical effects of copper nanomaterials in human hepatocellular carcinoma (HepG2) cells.

In dose-response and structure-activity studies, human hepatic HepG2 cells were exposed for 3 days to nano Cu, nano CuO or CuCl2 (ions) at doses between 0.1 and 30 ug/ml (approximately the no observable adverse effect level to a high degree of cytotoxicity). Various biochemical parameters were then evaluated to study cytotoxicity, cell growth, hepatic function, and oxidative stress. With nano Cu and nano CuO, few indications of cytotoxicity were observed between 0.1 and 3 ug/ml. In respect to dose, lactate dehydrogenase and aspartate transaminase were the most sensitive cytotoxicity parameters. The next most responsive parameters were alanine aminotransferase, glutathione reductase, glucose 6-phosphate dehydrogenase, and protein concentration. The medium responsive parameters were superoxide dismutase, gamma glutamyltranspeptidase, total bilirubin, and microalbumin. The parameters glutathione peroxidase, glutathione reductase, and protein were all altered by nano Cu and nano CuO but not by CuCl2 exposures. Our chief observations were (1) significant decreases in glucose 6-phosphate dehydrogenase and glutathione reductase was observed at doses below the doses that show high cytotoxicity, (2) even high cytotoxicity did not induce large changes in some study parameters (e.g., alkaline phosphatase, catalase, microalbumin, total bilirubin, thioredoxin reductase, and triglycerides), (3) even though many significant biochemical effects happen only at doses showing varying degrees of cytotoxicity, it was not clear that cytotoxicity alone caused all of the observed significant biochemical effects, and (4) the decreased glucose 6-phosphate dehydrogenase and glutathione reductase support the view that oxidative stress is a main toxicity pathway of CuCl2 and Cu-containing nanomaterials.

Biochemical effects of some CeO2, SiO2, and TiO2 nanomaterials in HepG2 cells.

The potential mammalian hepatotoxicity of nanomaterials was explored in dose-response and structure-activity studies in human hepatic HepG2 cells exposed to between 10 and 1000 µg/ml of five different CeO2, three SiO2, and one TiO2-based particles for 3 days. Various biochemical parameters were then evaluated to study cytotoxicity, cell growth, hepatic function, and oxidative stress. Few indications of cytotoxicity were observed between 10 and 30 µg/ml. In the 100 to 300 µg/ml exposure range, a moderate degree of cytotoxicity was often observed. At 1000 µg/ml exposures, all but TiO2 showed a high degree of cytotoxicity. Cytotoxicity per se did not seem to fully explain the observed patterns of biochemical parameters. Four nanomaterials (all three SiO2) decreased glucose 6-phosphate dehydrogenase activity with some significant decreases observed at 30 µg/ml. In the range of 100 to 1000 µg/ml, the activities of glutathione reductase (by all three SiO2) and glutathione peroxidase were decreased by some nanomaterials. Decreased glutathione concentration was also found after exposure to four nanomaterials (all three nano SiO2 particles). In this study, the more responsive and informative assays were glucose 6-phosphate dehydrogenase, glutathione reductase, superoxide dismutase, lactate dehydrogenase, and aspartate transaminase. In this study, there were six factors that contribute to oxidative stress observed in nanomaterials exposed to hepatocytes (decreased glutathione content, reduced glucose 6-phosphate dehydrogenase, glutathione reductase, glutathione peroxidase, superoxide dismutase, and increased catalase activities). With respect to structure-activity, nanomaterials of SiO2 were more effective than CeO2 in reducing glutathione content, glucose 6-phosphate dehydrogenase, glutathione reductase, and superoxide dismutase activities.

Metabolomic effects of CeO2, SiO2 and CuO metal oxide nanomaterials on HepG2 cells.

BACKGROUND: To better assess potential hepatotoxicity of nanomaterials, human liver HepG2 cells were exposed for 3 days to five different CeO2 (either 30 or 100 µg/ml), 3 SiO2 based (30 µg/ml) or 1 CuO (3 µg/ml) nanomaterials with dry primary particle sizes ranging from 15 to 213 nm. Metabolomic assessment of exposed cells was then performed using four mass spectroscopy dependent platforms (LC and GC), finding 344 biochemicals. RESULTS: Four CeO2, 1 SiO2 and 1 CuO nanomaterials increased hepatocyte concentrations of many lipids, particularly free fatty acids and monoacylglycerols but only CuO elevated lysolipids and sphingolipids. In respect to structure-activity, we now know that five out of six tested CeO2, and both SiO2 and CuO, but zero out of four TiO2 nanomaterials have caused this elevated lipids effect in HepG2 cells. Observed decreases in UDP-glucuronate (by CeO2) and S-adenosylmethionine (by CeO2 and CuO) and increased S-adenosylhomocysteine (by CuO and some CeO2) suggest that a nanomaterial exposure increases transmethylation reactions and depletes hepatic methylation and glucuronidation capacity. Our metabolomics data suggests increased free radical attack on nucleotides. There was a clear pattern of nanomaterial-induced decreased nucleotide concentrations coupled with increased concentrations of nucleic acid degradation products. Purine and pyrimidine alterations included concentration increases for hypoxanthine, xanthine, allantoin, urate, inosine, adenosine 3',5'-diphosphate, cytidine and thymidine while decreases were seen for uridine 5'-diphosphate, UDP-glucuronate, uridine 5'-monophosphate, adenosine 5'-diphosphate, adenosine 5'-monophophate, cytidine 5'-monophosphate and cytidine 3'-monophosphate. Observed depletions of both 6-phosphogluconate, NADPH and NADH (all by CeO2) suggest that the HepG2 cells may be deficient in reducing equivalents and thus in a state of oxidative stress. CONCLUSIONS: Metal oxide nanomaterial exposure may compromise the methylation, glucuronidation and reduced glutathione conjugation systems; thus Phase II conjugational capacity of hepatocytes may be decreased. This metabolomics study of the effects of nine different nanomaterials has not only confirmed some observations of the prior 2014 study (lipid elevations caused by one CeO2 nanomaterial) but also found some entirely new effects (both SiO2 and CuO nanomaterials also increased the concentrations of several lipid classes, nanomaterial induced decreases in S-adenosylmethionine, UDP-glucuronate, dipeptides, 6-phosphogluconate, NADPH and NADH).

Differential Genomic Effects of Six Different TiO2 Nanomaterials on Human Liver HepG2 Cells.

Human HepG2 cells were exposed to six TiO2 nanomaterials (with dry primary particle sizes ranging from 22 to 214 nm, either 0.3, 3, or 30 µg/mL) for 3 days. Some of these canonical pathways changed by nano-TiO2 in vitro treatments have been already reported in the literature, such as NRF2-mediated stress response, fatty acid metabolism, cell cycle and apoptosis, immune response, cholesterol biosynthesis, and glycolysis. But this genomic study also revealed some novel effects such as protein synthesis, protein ubiquitination, hepatic fibrosis, and cancer-related signaling pathways. More importantly, this genomic analysis of nano-TiO2 treated HepG2 cells linked some of the in vitro canonical pathways to in vivo adverse outcomes: NRF2-mediated response pathways to oxidative stress, acute phase response to inflammation, cholesterol biosynthesis to steroid hormones alteration, fatty acid metabolism changes to lipid homeostasis alteration, G2/M cell checkpoint regulation to apoptosis, and hepatic fibrosis/stellate cell activation to liver fibrosis.

Differential Genomic Effects on Signaling Pathways by Two Different CeO2 Nanoparticles in HepG2 Cells.

To investigate genomic effects, human liver hepatocellular carcinoma (HepG2) cells were exposed for three days to two different forms of nanoparticles both composed of CeO2 (0.3, 3 and 30 µg/mL). The two CeO2 nanoparticles had dry primary particle sizes of 8 nanometers {(M) made by NanoAmor} and 58 nanometers {(L) made by Alfa Aesar} and differ in various other physical-chemical properties as well. The smaller particle has stronger antioxidant properties, probably because it has higher Ce3+ levels on the particle surface, as well as more surface area per unit weight. Nanoparticle M showed a normal dose-response pattern with 363, 633 and 1273 differentially expressed genes (DEGs) at 0.3, 3 and 30 µg/mL, respectively. In contrast, nanoparticle L showed a puzzling dose-response pattern with the most DEGs found in the lowest exposure group with 1049, 303 and 323 DEGs at 0.3, 3 and 30 µg/mL, respectively. This systems biological genomic study showed that the major altered pathways by these two nano cerium oxides were protein synthesis, stress response, proliferation/cell cycle, cytoskeleton remodeling/actin polymerization and cellular metabolism. Some of the canonical pathways affected were mTOR signaling, EIF2 signaling, fatty acid activation, G2/M DNA damage checkpoint regulation, glycolysis and protein ubiquitination. These two CeO2 nanoparticles differed considerably in their genomic effects. M is more active than L in respect to altering the pathways of mitochondrial dysfunction, acute phase response, apoptosis, 14-3-3 mediated signaling, remodeling of epithelial adherens junction signaling, actin nucleation by ARP-WASP complex, altered TCA cycle and elevated fatty acid concentrations by metabolomics. However, L is more active than M in respect to the pathways of NRF2-mediated stress response and hepatic fibrosis/hepatic stellate cell activation. One major difference in the cell response to nano M and L is that nano M caused the Warburg effect while nano L did not.

Differential genomic effects of four nano-sized and one micro-sized CeO2 particles on HepG2 cells.

The objective of this research was to perform a genomics study of five cerium oxide particles, 4 nano and one micrometer-sized particles which have been studied previously by our group with respect to cytotoxicity, biochemistry and metabolomics. Human liver carcinoma HepG2 cells were exposed to between 0.3 to 300 ug/ml of CeO2 particles for 72 hours and then total RNA was harvested. Fatty acid accumulation was observed with W4, X5, Z7 and less with Q but not Y6. The gene expression changes in the fatty acid metabolism genes correlated the fatty acid accumulation we detected in the prior metabolomics study for the CeO2 particles named W4, Y6, Z7 and Q, but not for X5. In particular, the observed genomics effects on fatty acid uptake and fatty acid oxidation offer a possible explanation of why many CeO2 particles increase cellular free fatty acid concentrations in HepG2 cells. The major genomic changes observed in this study were sirtuin, ubiquitination signaling pathways, NRF2-mediated stress response and mitochondrial dysfunction. The sirtuin pathway was affected by many CeO2 particle treatments. Sirtuin signaling itself is sensitive to oxidative stress state of the cells and may be an important contributor in CeO2 particle induced fatty acid accumulation. Ubiquitination pathway regulates many protein functions in the cells, including sirtuin signaling, NRF2 mediated stress, and mitochondrial dysfunction pathways. NRF2-mediated stress response and mitochondrial were reported to be altered in many nanoparticles treated cells. All these pathways may contribute to the fatty acid accumulation in the CeO2 particle treated cells.

Effects of Silver Nanoparticles and Silver Nitrate on mRNA and microRNA Expression in Human Hepatocellular Carcinoma Cells (HepG2).

In order to understand toxicity of nano silver, human hepatocellular carcinoma (HepG2) cells were treated either with silver nitrate (AgNO3) or with nano silver capped with glutathione (Ag-S) at various concentration. Differentially expressed genelists for mRNA and microRNA were obtained through Illumina RNA sequencing and DEseq data analyses. Both treatments showed non-linear dose response relationships for mRNA and microRNA. Gene expression analysis showed signaling pathways common to both nano Ag-S and AgNO3, such as cell cycle regulation, DNA damage response and cancer related pathways. But, nano Ag-S caused signaling pathway changes that were not altered by AgNO3 such as NRF2-mediated oxidative stress response inflammation, cell membrane signaling, and cell proliferation. Nano Ag-S also affected p53 signaling, survival, apoptosis, tissue repair, lipid synthesis, angiogenesis, liver fibrosis and tumor development. Several of the pathways affected by nano Ag-S are hypothesized as major contributors to nanotoxicity. MicroRNA target filter analysis revealed additional affected pathways that were not reflected in the mRNA expression response alone, including DNA damage signaling, genomic stability, ROS, cell cycle, ubiquitination, DNA methylation, cell proliferation and fibrosis for AgNO3; and cell cycle regulation, P53 signaling, cell proliferation, survival, apoptosis, tissue repair and so on for nano Ag-S. These pathways may be mediated by microRNA repression of protein translation.Our study clearly showed that the addition of microRNA profiling increased the numbers of signaling pathways discovered that affected by the treatments on HepG2 cells and gave US a better picture of the effects of these reagents in the cells.

Effects of Copper Nanoparticles on mRNA and Small RNA Expression in Human Hepatocellular Carcinoma (HepG2) Cells.

With the advancement of nanotechnology, nanoparticles are widely used in many different industrial processes and consumer products. Copper nanoparticles (Cu NPs) are among the most toxic nanomaterials. We investigated Cu NPs toxicity in Human Hepatocellular carcinoma (HepG2) cells by examining signaling pathways, and microRNA/mRNA interactions. We compared the effects of exposures to Cu NPs at various concentrations and CuCl2 was used as a control. The number of differentially expressed mRNA did not follow a linear dose-response relationship for either Cu NPs or CuCl2 treatments. The most significantly altered genes and pathways by Cu NPs exposure were NRF2 (nuclear factor erythroid 2 related factor 2)-mediated oxidative stress response, protein ubiquitination, Tumor protein p53 (p53), phase I and II metabolizing enzymes, antioxidant proteins and phase III detoxifying gene pathways.Messenger RNA-microRNA interaction from MicroRNA Target Filter Analyses revealed more signaling pathways altered in Cu NPs treated samples than transcriptomics alone, including cell proliferation, DNA methylation, endoplasmic reticulum (ER) stress, apoptosis, autophagy, reactive oxygen species, inflammation, tumorigenesis, extracellular matrix/angiogenesis and protein synthesis. In contrast, in the control (CuCl2) treated samples showed mostly changes in inflammation mainly through regulation of the Nuclear Factor Kappa-light-chain-enhancer of Activated B-cells (NFκB). Further, some RNA based parameters that showed promise as biomarkers of Cu NPs exposure including both well and lesser known genes: heme oxygenase 1 (HMOX1), heat shock protein, c-Fos proto-oncogene, DNA methyltransferases, and glutamate-cysteine ligase modifier subunit (GCLM, part of the glutathione synthesis pathway). The differences in signaling pathways altered by the Cu NPs and CuCl2 treatments suggest that the effects of the Cu NPs were not the results of nanomaterial dissolution to soluble copper ions.

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.

Biochemical Effects of Silver Nanomaterials in Human Hepatocellular Carcinoma (HepG2) Cells.

In dose-response and structure-activity studies, human hepatic HepG2 cells were exposed to between 0.01 and 300 ug/ml of different silver nanomaterials and AgNO3 for 3 days. Treatment chemicals included a custom synthesized rod shaped nano Ag, a glutathione capped nano Ag, polyvinylpyrrolidone (PVP) capped nano Ag (75 nm) from Nanocomposix and AgNO3. Various biochemical parameters were then evaluated to study cytotoxicity, cell growth, hepatic function and oxidative stress. Few indications of cytotoxicity were observed between 0.1 ug/ml and 6 ug/ml of any nano Ag. At 10 ug/ml and above, Ag containing nanomaterials caused a moderate to severe degree of cytotoxicity in HepG2 cells. Lactate dehydrogenase and aspartate transaminase activity alterations were the most sensitive cytotoxicity parameters. Some biochemical parameters were altered by exposures to both nano Ag and AgNO3 (statistically significant increases in alkaline phosphatase, gamma glutamyltranspeptidase, glutathione peroxidase and triglycerides; in contrast both glutathione reductase and HepG2 protein concentration were both decreased). Three parameters were significantly altered by nano Ag but not by AgNO3 (decreases in glucose 6-phosphate dehydrogenase and thioredoxin reductase and increases in catalase). Cytotoxicity per se did not appear to fully explain the patterns of biological responses observed. Some of the observations with the three nano Ag (increases in alkaline phosphatase, catalase, gamma glutamyltranspeptidase, as well as decreases in glucose 6-phosphate dehydrogenase and glutathione reductase) are in the same direction as HepG2 responses to other nanomaterials composed of TiO2, CeO2, SiO2, CuO and Cu. Therefore, these biochemical responses may be due to micropinocytosis of nanomaterials, membrane damage, oxidative stress and/or cytotoxicity. Decreased G6PDH (by all three nano Ag forms) and GRD activity (only nano Ag R did not cause decreases) support and are consistent with the oxidative stress theory of Ag nanomaterial action.

Oncogene expression profiles in K6/ODC mouse skin and papillomas following a chronic exposure to monomethylarsonous acid.

We have previously observed that a chronic drinking water exposure to monomethylarsonous acid [MMA(III)], a cellular metabolite of inorganic arsenic, increases tumor frequency in the skin of keratin VI/ornithine decarboxylase (K6/ODC) transgenic mice. To characterize gene expression profiles predictive of MMA(III) exposure and mode of action of carcinogenesis, skin and papilloma RNA was isolated from K6/ODC mice administered 0, 10, 50, and 100 ppm MMA(III) in their drinking water for 26 weeks. Following RNA processing, the resulting cRNA samples were hybridized to Affymetrix Mouse Genome 430A 2.0 GeneChips(R). Micoarray data were normalized using MAS 5.0 software, and statistically significant genes were determined using a regularized t-test. Significant changes in bZIP transcription factors, MAP kinase signaling, chromatin remodeling, and lipid metabolism gene transcripts were observed following MMA(III) exposure as determined using the Database for Annotation, Visualization and Integrated Discovery 2.1 (DAVID) (Dennis et al., Genome Biol 2003;4(5):P3). MMA(III) also caused dose-dependent changes in multiple Rho guanine nucleotide triphosphatase (GTPase) and cell cycle related genes as determined by linear regression analyses. Observed increases in transcript abundance of Fosl1, Myc, and Rac1 oncogenes in mouse skin support previous reports on the inducibility of these oncogenes in response to arsenic and support the relevance of these genomic changes in skin tumor induction in the K6/ODC mouse model.

Measurement of oxidative stress parameters using liquid chromatography-tandem mass spectroscopy (LC-MS/MS).

There is increasingly intense scientific and clinical interest in oxidative stress and the many parameters used to quantify the degree of oxidative stress. However, there remain many analytical limitations to currently available assays for oxidative stress markers. Recent improvements in software, hardware, and instrumentation design have made liquid chromatography and tandem mass spectroscopy (LC-MS/MS) methods optimal choices for the determination of many oxidative stress markers. In particular, LC-MS/MS often provides the advantages of higher specificity, higher sensitivity, and the capacity to determine multiple analytes (e.g. 4-11 oxidative stress markers per LC run) when compared to other available methods, such as gas chromatography-MS, immunoassays, spectrophotometric or fluorometric assays. LC-MS/MS methods are also compatible with cleanup and sample preparation methods including prior solid phase extraction or automated two dimensional LC/LC chromatography followed by MS/MS. LC-MS/MS provides three analytical filtering functions: (1) the LC column provides initial separation as each analyte elutes from the column. (2) The first MS dimension isolates ions of a particular mass-to-charge (m/z) ratio. (3) The selected precursor ion is fragmented into product ions that provide structural information about the precursor ion. Quantitation is achieved based on the abundances of the product ions. The sensitivity limits for LC-MS/MS usually lie within the range of fg-pg of analyte per LC on-column injection. In this article, the present capabilities of LC-MS/MS are briefly presented and some specific examples of the strengths of these LC-MS/MS assays are discussed. The selected examples include methods for isoprostanes, oxidized proteins and amino acids, and DNA biomarkers of oxidative stress.

Evidence against the nuclear in situ binding of arsenicals--oxidative stress theory of arsenic carcinogenesis.

A large amount of evidence suggests that arsenicals act via oxidative stress in causing cancer in humans and experimental animals. It is possible that arsenicals could bind in situ close to nuclear DNA followed by Haber-Weiss type oxidative DNA damage. Therefore, we tested this hypothesis by using radioactive (73)As labeled arsenite and vacuum filtration methodology to determine the binding affinity and capacity of (73)As arsenite to calf thymus DNA and Type 2A unfractionated histones, histone H3, H4 and horse spleen ferritin. Arsenicals are known to release redox active Fe from ferritin. At concentrations up to about 1 mM, neither DNA nor any of the three proteins studied, Type II-A histones, histone H3, H4 or ferritin, bound radioactive arsenite in a specific manner. Therefore, it appears highly unlikely that initial in situ binding of trivalent arsenicals, followed by in situ oxidative DNA damage, can account for arsenic's carcinogenicity. This experimental evidence (lack of arsenite binding to DNA, histone Type II-A and histone H3, H4) does not rule out other possible oxidative stress modes of action for arsenic such as (a) diffusion of longer lived oxidative stress molecules, such as H(2)O(2) into the nucleus and ensuing oxidative damage, (b) redox chemistry by unbound arsenicals in the nucleus, or (c) arsenical-induced perturbations in Fe, Cu or other metals which are already known to oxidize DNA in vitro and in vivo.

The role of protein binding of trivalent arsenicals in arsenic carcinogenesis and toxicity.

Three of the most plausible biological theories of arsenic carcinogenesis are protein binding, oxidative stress and altered DNA methylation. This review presents the role of trivalent arsenicals binding to proteins in arsenic carcinogenesis. Using vacuum filtration based receptor dissociation binding techniques, the lifetimes of unidentate (<1s), bidentate (1-2min) and tridentate (1-2h) arsenite containing peptide binding complexes were estimated. According to our experimental data some of the protein targets to which arsenite may bind in vivo include tubulin, poly(ADP-ribose)polymerase (PARP-1), thioredoxin reductase, estrogen receptor-alpha, arsenic(+3)methyltransferase and Keap-1. Arsenite binding to tubulin can lead to several of the genetic effects observed after arsenic exposures (aneuploidy, polyploidy and mitotic arrests). Among many other possible arsenite binding sites are rat hemoglobin, the DNA repair enzyme xeroderma pigmentosum protein A (XPA), and other C2H2, C3H and C4 zinc finger proteins including members of the steroid receptor superfamily (e.g. glucocorticoid receptor). Macromolecules to which arsenite does not bind to include calf thymus DNA, mixed Type II-A histones and bovine H3/H4 histone. Although all six tested arsenicals released iron from ferritin, radioactive arsenite did not bind to the protein horse ferritin.

Tissue levels of arsenicals and skin tumor response following administration of monomethylarsonous acid and arsenite to K6/ODC mice.

The effects of monomethylarsonous acid (MMA[III]) and arsenite, administered in drinking water on tissue levels of arsenicals, cytogenetics, and mouse skin tumorigenicity were determined. A low-methionine diet modified the pattern of arsenical tissue concentrations and decreased the tissue arsenical concentrations, particularly in kidney and urinary bladder, less so in liver, and had little effect in the lungs. In mice given 75 ppm arsenite and a low-methionine diet, the urinary bladder tissue levels were only 29%, 26%, and 38% of the inorganic arsenic (iAs), MMA, and dimethylarsinic acid (DMA) concentrations found in mice eating the control diet. In K6/ODC transgenic mice that consumed a normal diet (Purina 5002), a 26-week drinking water exposure to 10 ppm arsenite resulted in 5% of the treated animals having squamous skin tumors. Exposure to 10, 50, 75, or 150 ppm MMA(III) caused 5%, 6.7%, 5%, or 0% tumor-bearing animals. A low-methionine diet did not markedly change the incidence of skin tumors--10 ppm arsenite led to 10% tumors. With a low-methionine diet, 10 and 50 ppm, MMA(III) caused 5% and 6.7% tumor-bearing animals. In comparing the frequency of tumors in the concurrent control groups (1/70, 1.4%) with the frequency of tumors in the pooled arsenical-treated responsive groups (8/122, 6.6%), there is an excess of 6 mouse skin tumors observed in the pooled arsenical-responsive treatment groups compared to the expected number of tumors based on frequency of tumors observed in concurrent control mice. In summary, studies with MMA(III) and arsenite-treated K6/ODC transgenic mice showed (1) a low-methionine diet substantially altered mouse tissue arsenical levels and (2) numerically elevated incidence of mouse skin tumors following arsenical exposures.

Folate deficiency enhances arsenic effects on expression of genes involved in epidermal differentiation in transgenic K6/ODC mouse skin.

Chronic arsenic exposure in humans is associated with cancers of the skin, lung, bladder and other tissues. There is evidence that folate deficiency may increase susceptibility to arsenic effects, including skin lesions. K6/ODC mice develop skin tumors when exposed to 10ppm sodium arsenite for 5 months. In the current study, K6/ODC mice maintained on either a folate deficient or folate sufficient diet were exposed to 0, 1, or 10ppm sodium arsenite in the drinking water for 30 days. Total RNA was isolated from skin samples and gene expression analyzed using Affymetrix Mouse 430 2.0 GeneChips. Data from 24 samples, with 4 mice in each of the 6 treatment groups, were RMA normalized and analyzed by two-way ANOVA using GeneSpring. Top gene ontology (GO) categories for genes responding significantly to both arsenic treatment and folate deficiency include nucleotide metabolism and cell organization and biogenesis. For many of these genes, folate deficiency magnifies the response to arsenic treatment. In particular, expression of markers of epidermal differentiation, e.g., loricrin, small proline rich proteins and involucrin, was significantly reduced by arsenic in the folate sufficient animals, and reduced further or at a lower arsenic dose in the folate deficient animals. In addition, expression of a number of epidermal cell growth/proliferation genes and cellular movement genes was altered. These results indicate that arsenic disrupts the normal balance of cell proliferation and differentiation, and that folate deficiency exacerbates these effects, consistent with the view that folate deficiency is a nutritional susceptibility factor for arsenic-induced skin tumorigenesis.

An integrated pharmacokinetic and pharmacodynamic study of arsenite action 2. Heme oxygenase induction in mice.

Heme oxygenase (HO) is the rate-limiting enzyme in heme degradation and its activity has a significant impact on intracellular heme pools. Rat studies indicate that HO induction is a sensitive, dose-dependent response to arsenite (As(III)) exposure in both liver and kidney. The objective of this study was to evaluate the relationship of HO induction to administered As(III) dose, and concentrations of inorganic arsenic (iAs) in tissues and urine. Levels of iAs, mono- (MMA) and dimethylated arsenic (DMA) as well as HO activity were determined in liver, lung and kidney over time in female B6C3F1 mice given a single oral dose of 0, 1, 10, 30 or 100 micromol/kg As(III). Increased HO activity was a time and dose-dependent response in liver and kidney, but not in lung. Activity peaked in the 4-6 h time range in liver and kidney with the responsiveness in liver being approximately 2- to 3-fold greater than kidney. The lowest observed effect levels (LOELs) in this study for HO induction are 30 and 100 micromol/kg, respectively, in liver and kidney. The predominant form of arsenic (As) was iAs in liver at all doses, whereas DMA was the predominant form of As in kidney at all doses. Three- to four-fold higher levels of iAs were achieved in liver compared to kidney. MMA was the least abundant form of As in liver and kidney, never exceeding more than 20% of the total As present. The concentration of iAs in tissue or urine demonstrated the strongest correlation with HO activity in both liver and kidney. Results of this study suggest that HO induction is a biomarker of effect that is specific for tissue iAs because a high, but nontoxic, acute dose of DMA (5220 micromol/kg) did not induce HO in mice. Thus, HO induction has potential for use as a biomarker of effect for inorganic arsenic exposure and may be used as an indicator response to further the development of a biologically-based dose response model for As.

A critique of the use of hormesis in risk assessment.

There are severe problems and limitations with the use of hormesis as the principal dose-response default assumption in risk assessment. These problems and limitations include: (a) unknown prevalence of hormetic dose-response curves; (b) random chance occurrence of hormesis and the shortage of data on the repeatability of hormesis; (c) unknown degree of generalizability of hormesis; (d) there are dose-response curves that are not hormetic, therefore hormesis cannot be universally generalized; (e) problems of post hoc rather than a priori hypothesis testing; (f) a possible large problem of 'false positive' hormetic data sets which have not been extensively replicated; (g) the 'mechanism of hormesis' is not understood at a rigorous scientific level; (h) in some cases hormesis may merely be the overall sum of many different mechanisms and many different dose-response curves - some beneficial and some toxic. For all of these reasons, hormesis should not now be used as the principal dose-response default assumption in risk assessment. At this point, it appears that hormesis is a long way away from common scientific acceptance and wide utility in biomedicine and use as the principal default assumption in a risk assessment process charged with ensuring public health protection.

Pharmacokinetic and Genomic Effects of Arsenite in Drinking Water on Mouse Lung in a 30-Day Exposure.

The 2 objectives of this subchronic study were to determine the arsenite drinking water exposure dependent increases in female C3H mouse liver and lung tissue arsenicals and to characterize the dose response (to 0, 0.05, 0.25, 1, 10, and 85 ppm arsenite in drinking water for 30 days and a purified AIN-93M diet) for genomic mouse lung expression patterns. Mouse lungs were analyzed for inorganic arsenic, monomethylated, and dimethylated arsenicals by hydride generation atomic absorption spectroscopy. The total lung mean arsenical levels were 1.4, 22.5, 30.1, 50.9, 105.3, and 316.4 ng/g lung tissue after 0, 0.05, 0.25, 1, 10, and 85 ppm, respectively. At 85 ppm, the total mean lung arsenical levels increased 14-fold and 131-fold when compared to either the lowest noncontrol dose (0.05 ppm) or the control dose, respectively. We found that arsenic exposure elicited minimal numbers of differentially expressed genes (DEGs; 77, 38, 90, 87, and 87 DEGs) after 0.05, 0.25, 1, 10, and 85 ppm, respectively, which were associated with cardiovascular disease, development, differentiation, apoptosis, proliferation, and stress response. After 30 days of arsenite exposure, this study showed monotonic increases in mouse lung arsenical (total arsenic and dimethylarsinic acid) concentrations but no clear dose-related increases in DEG numbers.