Abstract

Inorganic arsenic (Asi) is a known human bladder carcinogen. The objective of this study was to examine the concentration dependence of the genomic response to Asi in the urinary bladders of mice. C57BL/6J mice were exposed for 1 or 12 weeks to arsenate in drinking water at concentrations of 0.5, 2, 10, and 50 mg As/l. Urinary bladders were analyzed using gene expression microarrays. A consistent reversal was observed in the direction of gene expression change: from predominantly decreased expression at 1 week to predominantly increased expression at 12 weeks. These results are consistent with evidence from in vitro studies of an acute adaptive response that is suppressed on longer exposure due to downregulation of Fos. Pathways with the highest enrichment in gene expression changes were associated with epithelial-to-mesenchymal transition, inflammation, and proliferation. Benchmark dose (BMD) analysis determined that the lowest median BMD values for pathways were above 5 mg As/l, despite the fact that pathway enrichment was observed at the 0.5 mg As/l exposure concentration. This disparity may result from the nonmonotonic nature of the concentration-responses for the expression changes of a number of genes, as evidenced by the much fewer gene expression changes at 2 mg As/l compared with lower or higher concentrations. Pathway categories with concentration-related gene expression changes included cellular morphogenesis, inflammation, apoptosis/survival, cell cycle control, and DNA damage response. The results of this study provide evidence of a concentration-dependent transition in the mode of action for the subchronic effects of Asi in mouse bladder cells in the vicinity of 2 mg Asi/l.

There is strong evidence from epidemiological studies in a number of locations around the world that chronic exposures to high concentrations (on the order of 0.5 mg As/l) of inorganic arsenic (Asi) in drinking water are associated with an increased risk of cancer in human populations (National Research Council [NRC], 1999). However, there is less certainty regarding the potential for carcinogenicity at the much lower concentrations (below 0.1 mg As/l) found in other areas of the world including the United States (Abernathy et al., 1996; Snow et al., 2005). A number of recent epidemiological studies in the United States and other countries, including Taiwan, have reported that the incidence of bladder, lung, and liver tumors did not increase with chronic exposure to low concentrations (below 0.1 mg As/l) of inorganic arsenic in drinking water (Baastrup et al., 2008; Bates et al., 1995; Chen et al., 2009; Chiou et al., 2001; Ferreccio et al., 2000; Guo, 2003; Han et al., 2009; Heck et al., 2009; Karagas et al., 2004; Lamm et al., 2004, 2007; Meliker et al., 2007; Mostafa et al., 2008; Steinmaus et al., 2003), although some of these studies have suggested a possible interaction with smoking at these concentrations.

Asi is clastogenic, producing chromosomal aberrations, but does not produce point mutations at single gene loci, suggesting the possibility of a nonlinear dose-response (Clewell et al., 1998). Although chronic exposure to Asi alone has only infrequently been associated with tumors in animal studies (Ng et al., 1999; Tokar et al., 2011; Waalkes et al., 2004), it has repeatedly been shown to act as a comutagen in vitro (Wiencke and Yager, 1992; Yager and Wiencke, 1993) and as a cocarcinogen in vivo (Burns et al., 2004; Tokar et al., 2010). Moreover, Asi has been shown to inhibit a number of DNA repair processes (Hu et al., 1998; Li and Rossman, 1989; Lynn et al., 1997; Sykora and Snow, 2008; Yager and Wiencke, 1997), providing a possible explanation for its observed comutagenicity and cocarcinogenicity.

Paradoxically, arsenic trioxide has been shown to be an effective antineoplastic agent for acute promyelocytic leukemia and multiple myeloma (Berenson and Yeh, 2006; Zheng et al., 2005), although it has been suggested that Asi chemotherapy could entail procarcinogenic side effects (Soucy et al., 2003). Antitumorigenic activity of Asi has also been reported in animal studies (Ahlborn et al., 2009; Gentry et al., 2005). While there is currently no completely satisfactory description of the modes of action for the procarcinogenic and anticarcinogenic effects of Asi, they appear to involve alterations of cell cycle control, replication, and differentiation (Hu et al., 2002; Salnikow and Cohen, 2002; Snow et al., 2001). It has been suggested that the biological effects of Asi may result, at least in part, from the avidity with which the trivalent arsenic species—arsenite (AsIII) and the trivalent methylated metabolites, monomethylarsonous acid (MMAIII), and dimethylarsinous acid (DMAIII)—bind to vicinal dithiols in cellular proteins (Kitchin and Wallace, 2005).

Based on data for the concentration-response of selected genes and proteins in short-term in vitro studies (Snow et al., 2001, 2005; Sykora and Snow, 2008), which include evidence of reversals in the direction of expression change between low and high concentrations, it has been suggested that the cellular responses at submicromolar concentrations are adaptive (protective), whereas those at higher concentrations are toxic. Prior to the current study, a review of the literature was conducted on studies of genomic responses to Asi exposure, to evaluate the available evidence regarding the concentration—and time-response relationship for Asi gene interactions (Gentry et al., 2010). A consistent, concentration-related hierarchy of responses was observed in vitro across cells from different species and tissues, beginning with changes in gene/protein expression associated with adaptive responses (e.g., preinflammatory responses, delay of apoptosis) at concentrations between 0.005 and 0.1μM. Between 0.1 and 10μM, additional gene/protein expression changes related to oxidative stress, proteotoxicity, inflammation, and proliferative signaling were observed along with changes related to DNA repair, cell cycle G2/M checkpoint control, and induction of apoptosis. At higher concentrations (10–100μM), changes in apoptotic genes dominated, consistent with the chemotherapeutic activity of Asi for some tumors. Some differences were noted between the results of studies with primary cells and cell lines. Data from acute in vivo exposures were found to be of little value for evaluating the dose-response for gene expression, due to the transient, variable, and uncertain nature of tissue exposure in these studies.

One of the key areas of data insufficiency identified in the Gentry et al. (2010), review was the lack of studies that characterized the concentration-response for the interactions of Asi with cellular control genes over longer periods of exposure. One in vitro study (Hu et al., 2002) compared acute (24 h) and chronic (10–20 weeks) exposures of human GM847 fibroblasts to arsenite. Intriguingly, the DNA binding activities of the Ap-1 and Nf-kb transcription factors were increased after acute exposure but decreased after chronic exposure. Similarly, Fos and Jun protein levels were increased acutely but decreased after chronic treatment. The purpose of the current study was to attempt to provide in vivo confirmation of these in vitro observations by examining the genomic concentration-response in the urinary bladder of mice exposed to arsenate in drinking water over a period of up to 12 weeks. The urinary bladder was chosen because the association between drinking water exposures to Asi and internal tumors in the human is strongest for bladder cancer (NRC, 1999). Arsenate is the primary Asi species in most drinking water originating from surface water (NRC 1999), and systemic exposure to arsenite is similar following dosing with either arsenite or arsenate (Vahter, 2002). The experimental animal selected for the study, the female C57BL/6 mouse, has been used in many of the recent Asi tumor studies (summarized in Gentry et al., 2005), including a 26-month exposure to arsenate in drinking water at 0.5 mg As/l, which produced tumors in multiple tissues (Ng et al., 1999). The arsenate drinking water concentrations in the current study span the range of concentrations used in these previous studies.

MATERIALS AND METHODS

Chemical and animals.

Sodium arsenate was obtained from Sigma Chemical Co. (St Louis, MO). All other chemicals used as standards and analytical reagents are as reported in Kenyon et al. (2008). Forty-five day-old-female C57BL/6 mice were obtained from Charles River Laboratories (Raleigh, NC) and held for 2 weeks before commencing studies. The animals were maintained according to the guidelines in the National Institutes of Health (NIH) “Guide to the Care and Use of Laboratory Animals” within an Association for Assessment and Accreditation of Laboratory Animal Care accredited animal facility. All animal use and procedures were conducted under an Institutional Animal Care and Use Committee–approved protocol. Animals were housed in polycarbonate shoebox cages (5 per cage) with hardwood chip bedding and were provided with Rodent Chow (Purina, St Louis, MO) containing < 1 mg As/kg. The room was kept on a 12/12-h light/dark cycle and at a temperature of 22 ± 1°C and humidity of 50 ± 10%.

Treatment and analytical chemistry.

Mice (n = 10 per group) received 0.5, 2, 10, or 50 mg As/l in the form of arsenate in their drinking water ad libitum for up to 12 weeks. Within each exposure group and time point (1 or 12 weeks), mice were randomized into groups (n = 5) for tissues to be allocated to either arsenical determinations (Kenyon et al., 2008) or gene expression measurements. Control animals were given distilled deionized water only. Randomly collected water samples as well as commercial diet were analyzed for total arsenic by neutron activation analysis at North Carolina State University. Water consumption was measured throughout the study period, and mice were weighed weekly. One day before the end of the study, mice (n = 4 cages with 2–3 mice per cage per exposure level) were placed in Nalgene metabolism cages (Nalge Co., Rochester, NY), and urine was collected under refrigeration (∼4°C) for 24 h. The animals were maintained on the same diet and arsenate exposure level while in the metabolism cages. Mice were housed two to three per cage to accumulate sufficient urine for analysis of metabolites, and urine samples were stored at −70° C until analysis by hydride generation atomic absorption spectrometry (HG-AAS) as described in Kenyon et al. (2008). Following urine collection, mice were killed by exsanguination under CO2 anesthesia. Blood, liver, lung, kidney, skin, and urinary bladder were harvested immediately, flash frozen in liquid nitrogen, and stored at −70° C until analysis by HG-AAS using U.S. Environmental Protection Administration Method 1632A as reported in Kenyon et al. (2008). Urinary bladders from the other five mice per exposure level and time point were harvested and preserved in RNAlater (Ambion, Austin, TX) for subsequent gene expression analysis. The bladder weights (mean and SD) were 0.016 ± 0.004 g.

Gene expression microarray measurements.

Gene expression microarray analysis was performed on five mice per concentration at each time point (1 and 12 weeks of exposure). Total RNA was isolated from the bladder tissue using Trizol reagent (Invitrogen, Carlsbad, CA). The isolated RNA was further purified using RNeasy columns (Qiagen, Valencia, CA) and the integrity of the RNA verified spectrophotometrically and with the Agilent 2100 Bioanalyzer (Palo Alto, CA). RNA yields were 11.2 ± 2.8 μg with 260:280 ratios of 1.94 ± 0.04 and RNA Integrity Numbers (RINs) of 9.2 ± 0.7 (individual sample data are presented in the Supplementary materials). Double-stranded Complementary DNA (cDNA) was synthesized from 5 μg of total RNA using the One-Cycle cDNA synthesis kit (Affymetrix, Santa Clara, CA). Biotin-labeled cRNA was transcribed from the cDNA using the GeneChip IVT Labeling Kit (Affymetrix). Fifteen ug of labeled cRNA was fragmented and hybridized to Affymetrix Mouse Genome 430 2.0 microarrays. The hybridized arrays were washed using the GeneChip Fluidics Station 450 and scanned using a GeneChip 3000 scanner. The gene expression data have been deposited in the National Center for Biotechnology Information Gene Expression Omnibus.

Statistical analysis of microarray data.

Microarray data were preprocessed using the robust multiarray average method with a log base 2 (log2) transformation (Irizarry et al., 2003). The basic statistical analysis of the gene expression changes were performed using ANOVA with contrasts between each chemical concentration and the associated control group at each time point. Probability values were adjusted for multiple comparisons using a q value (Benjamini and Hochberg, 1995). Significant changes in gene expression were defined as q value < 0.05 and ±1.5-fold change. The ANOVA analysis and associated contrasts were performed using Partek Genomics Suite (version 6.4). Gene enrichment analysis was conducted using the GeneGo pathway maps and process networks in the Metacore database (version 6.2, GeneGo, St Joseph, MI). The enrichment p values were calculated based on a hypergeometric distribution and significant enrichment was defined as a false discovery corrected p value < 0.05.

Benchmark dose analysis of microarray data.

Benchmark dose (BMD) analysis of the gene expression data was performed as described previously (Thomas et al., 2007; Yang et al., 2007), with the modifications described below. Briefly, the probe sets on the microarray were fit as continuous data to a series of four different dose response models—linear, 2° polynomial, 3° polynomial, and power models. Each model was run assuming constant variance and the benchmark response (BMR) factor was set to 1.349 multiplied by the SD in the control animals. To derive this value, a normal distribution was assumed for control animals, and it was assumed, a priori, that the transcriptional response would occur in either tail, with a 1% chance of that occurring in the absence of exposure (0.5% in each tail). A BMR of 1.349 represents the shift in the mean transcriptional response of the control distribution such that the treated distribution contains 11% in a single tail, i.e. a 10% increase over the assumed background rate of response. For model selection, a nested likelihood ratio test was performed on the linear, 2° polynomial, and 3° polynomial models. If the more complex model provided a significantly improved fit (p < 0.05), the more complex model was selected. If the more complex model did not provide a significantly improved fit (p ≥ 0.05), the simpler model was selected (Posada and Buckley, 2004). The Akaike information criterion (AIC) for the selected polynomial model was then compared with the AIC for the power model. The model with the lowest AIC (Akaike, 1973) was selected as the final model, and a BMD and benchmark dose lower confidence limit (BMDL) was calculated. To avoid model extrapolation, probe sets with a BMD value greater than the highest dose were removed from further analysis. Probe sets that had a BMD less than the highest dose were converted into unique genes based on their NCBI Entrez Gene ID. When two or more probe sets were associated with a single gene, the BMDs and BMDLs for the individual probe sets were averaged to obtain a single BMD and BMDL. The Entrez Gene identifiers were then matched to their corresponding GeneGo pathway maps. Pathways with less than three genes were excluded from the analysis.

RESULTS

Arsenic Concentrations in Urine

The concentrations of the various arsenic compounds in the urine and bladders of animals exposed to arsenate for 12 weeks in this study have been reported previously (Kenyon et al., 2008). As expected, the metabolite pentavalent dimethylarsinic acid (DMAV) was the arsenical excreted in the highest proportion at all dose levels (about 80%, based on Table 1, Kenyon et al., 2008). Arsenate was excreted in the second highest proportion, ranging from 7 to 14%. At the highest dose, the concentration of DMAV in urine was 800uM. Mean urine arsenite concentrations ranged from 1.24 μg/l (0.05μM) to 1224 μg/l (16μM).

TABLE 1

Median BMD Values (mg As/l) for Selected Pathway Categoriesa at Weeks 1 and 12

Pathway categories Number of pathways Median BMDs (mg As/l)
 
  Week 1 Week 12 
Apoptosis and survival 31 13.0–45.1 7.4–45.3 
    p53 dependent apoptosis 28.6 24.4 
    Caspase cascade 39.7 12.0 
Cell adhesion 17 8.5–36.8 7.2–10.5 
Cell cycle 16 11.3–42.5 7.7–18.2 
    Regulation of G1/S transition 26.1–27.4 12.0–19.2 
Chemotaxis 14.4–26.8 7.4–9.5 
Cytoskeleton remodeling 19 11.1–31.3 6.5–28.1 
Development 109 12.5–46.9 6.4–24.6 
    Tgfb induction of EMT 13.5–30.5 8.1–9.7 
    Activation of Erk 14.3–31.9 6.5–17.5 
    Egfr signaling 14.4–25.4 8.3–9.2 
    Vegf signaling 16.3–27.2 9.0–10.4 
    Wnt signaling 16.0–28.3 8.1–12.2 
    Esr1 15.1–28.9 9.1–9.7 
    Notch signaling 16.7–24.5 8.6–10.3 
    Igf1r signaling 22.8 8.1 
DNA damage response 10 21.2–38.9 7.2–31.4 
G-protein signaling 28/26 10.1–34.1 8.1–36.1 
Immune response 83/81 8.7–43.1 6.7–41.8 
Oxidative stress 11.1–12.4 10.7–12.2 
Signal transduction 8/10 14.9–28.4 8.1–12.6 
Pathway categories Number of pathways Median BMDs (mg As/l)
 
  Week 1 Week 12 
Apoptosis and survival 31 13.0–45.1 7.4–45.3 
    p53 dependent apoptosis 28.6 24.4 
    Caspase cascade 39.7 12.0 
Cell adhesion 17 8.5–36.8 7.2–10.5 
Cell cycle 16 11.3–42.5 7.7–18.2 
    Regulation of G1/S transition 26.1–27.4 12.0–19.2 
Chemotaxis 14.4–26.8 7.4–9.5 
Cytoskeleton remodeling 19 11.1–31.3 6.5–28.1 
Development 109 12.5–46.9 6.4–24.6 
    Tgfb induction of EMT 13.5–30.5 8.1–9.7 
    Activation of Erk 14.3–31.9 6.5–17.5 
    Egfr signaling 14.4–25.4 8.3–9.2 
    Vegf signaling 16.3–27.2 9.0–10.4 
    Wnt signaling 16.0–28.3 8.1–12.2 
    Esr1 15.1–28.9 9.1–9.7 
    Notch signaling 16.7–24.5 8.6–10.3 
    Igf1r signaling 22.8 8.1 
DNA damage response 10 21.2–38.9 7.2–31.4 
G-protein signaling 28/26 10.1–34.1 8.1–36.1 
Immune response 83/81 8.7–43.1 6.7–41.8 
Oxidative stress 11.1–12.4 10.7–12.2 
Signal transduction 8/10 14.9–28.4 8.1–12.6 
a

Pathway categories not included: metabolism, biosynthesis, transcription, translation, transport, blood coagulation, cardiac hypertrophy, muscle contraction, and neurophysiological processes.

Global Expression Changes

The expression changes at the four concentrations (0.5, 2, 10, and 50 mg As/l) and two time points (1 and 12 weeks) are displayed chromatically in Figure 1, where blue indicates downregulation and red indicates upregulation. A number of general features are evident:

  • Expression at 1 week was primarily downregulated (blue), whereas at week 12, it was primarily upregulated (red)

  • Downregulation was greatest at the highest concentration at week 1, and upregulation was greatest at the highest concentration at week 12

  • There appears to be a small subset of genes with a reverse trend toward greater downregulation at week 12 (grouped at top of Fig. 1)

  • At both time points, a U-shaped concentration-response curve was observed for many genes, with a nadir at 2 mg As/l, as evidenced by the relative lack of coloration in the second and 6th columns of Figure 1.

FIG. 1.

Gene expression changes at four doses (0.5, 2, 10, and 50 mg As/l) and two time points (1 and 12 weeks). The figure contains the union of genes showing significant changes at any dose or time point (q value < 0.05 and ±1.5 fold change). Blue bars represent decreased expression, and red bars represent increased expression.

FIG. 1.

Gene expression changes at four doses (0.5, 2, 10, and 50 mg As/l) and two time points (1 and 12 weeks). The figure contains the union of genes showing significant changes at any dose or time point (q value < 0.05 and ±1.5 fold change). Blue bars represent decreased expression, and red bars represent increased expression.

The contrast between weeks 1 and 12 is even more striking when restricting the comparison to number of genes significantly upregulated or downregulated (q value < 0.05, 1.5-fold or greater) at each concentration and time points (Fig. 2). The lack of expression changes at the 2 mg As/l concentration is also apparent. There was little overlap in the genes affected at the two time points; the number of genes in common between 1 and 12 weeks were 1, 0, 47, and 34 at 0.5, 2, 10, and 50 mg As/l, respectively. Similarly, there was little overlap in the genes affected at the low and high concentrations (Fig. 3). A complete listing of the significant expression changes at all concentrations and time points is included in the Supplementary materials.

FIG. 2.

Number of genes significantly downregulated (blue) or upregulated (red) as a function of drinking water concentration at weeks 1 and 12. Significance was defined as ±1.5 fold and q value < 0.05.

FIG. 2.

Number of genes significantly downregulated (blue) or upregulated (red) as a function of drinking water concentration at weeks 1 and 12. Significance was defined as ±1.5 fold and q value < 0.05.

FIG. 3.

Comparison of significant (q value < 0.05 and ±1.5 fold change) gene expression changes at different concentrations and times. Data at 2 mg As/l not included due to the small number of expression changes at that concentration.

FIG. 3.

Comparison of significant (q value < 0.05 and ±1.5 fold change) gene expression changes at different concentrations and times. Data at 2 mg As/l not included due to the small number of expression changes at that concentration.

BMD Analysis

The distributions of GeneGo pathway median BMD values at weeks 1 and 12 are shown in Figure 4. The distribution of median BMD values for GeneGo pathways was bimodal at week 1 with peaks at about 14 and 26 mg As/l, whereas at week 12, they were clustered in the vicinity of 8 mg As/l. Pathways showing a significant concentration-response included those related to morphogenesis, inflammation, cell cycle control, DNA damage response, and apoptosis/survival (Table 1). The complete GeneGo pathway benchmark results are included in the Supplementary materials.

FIG. 4.

Number of GeneGo pathways with median BMD values at a given concentration (mg As/l). Blue bars represent week 1, and red bars represent week 12.

FIG. 4.

Number of GeneGo pathways with median BMD values at a given concentration (mg As/l). Blue bars represent week 1, and red bars represent week 12.

Concentration- and Time-Dependent Gene Expression

Gene enrichment analysis was conducted at each concentration and time points. Highlights of the analysis are provided here, and a partial listing of the significantly enriched pathways is provided in Table 2. The full listing of the 10 most enriched pathways and process networks at each concentration and time points is included in the Supplementary materials.

TABLE 2

Significantly Enriched GeneGo Pathways (false discovery rate < 0.05)

GeneGo pathway maps, week 1 -LOG (p value) Number of genes affected Total genes in network 
    0.5 ppm N/A N/A N/A 
    2 ppm N/A N/A N/A 
    10 ppm N/A N/A N/A 
    50 ppm    
        Regulation of G1/S transition (part 1) 4.694 38 
        Cytoskeleton remodeling 4.482 102 
        Tgf-beta-dependent induction of EMT via Smads 3.596 35 
        Regulation of Eif2 activity 3.412 39 
        Tgf-beta-dependent induction of EMT via Rhoa, P13k, and Ilk. 3.135 46 
Week 12    
GeneGo pathway maps, week 12 -LOG (p value) Number of genes affected Total genes in network 
    0.5 ppm    
        Integrin-mediated cell adhesion and migration 10.259 11 48 
        Cytoskeleton remodeling 8.676 13 102 
        Tgf, Wnt, and cytoskeletal remodeling 8.217 13 111 
        Regulation of EMT 7.648 10 64 
        Tgf-beta-dependent induction of EMT via Rhoa, P13k, and Ilk. 6.588 46 
    2 ppm    
        Activation of Erk by Acm1, Acm3, and Acm5. 4.969 44 
        Leptin signaling via Jak/Stat and Mapk cascades 3.527 25 
        Il-3 activation and signaling pathway 3.338 31 
        Oncostatin M signaling via Mapk 3.232 35 
        Hedgehog and Pth signaling pathways in bone and cartilage development 3.184 37 
    10 ppm    
        Tgf-beta-dependent induction of EMT via Rhoa, P13k and Ilk. 7.174 46 
        Fibronectin-binding integrins in cell motility 6.139 31 
        Thrombopoietin-regulated cell processes 6.093 45 
        Role of Cdk5 in neuronal development 5.847 34 
        Gm-csf signaling 5.729 50 
    50 ppm    
        Tgf-beta-dependent induction of EMT via Rhoa, P13k, and Ilk. 9.12 14 46 
        Tgf, Wnt, and cytoskeletal remodeling 8.319 20 111 
        Cytoskeleton remodeling 8.18 19 102 
        Regulation of Enos activity in endothelial cells 7.993 15 64 
        Regulation of EMT 7.993 15 64 
GeneGo pathway maps, week 1 -LOG (p value) Number of genes affected Total genes in network 
    0.5 ppm N/A N/A N/A 
    2 ppm N/A N/A N/A 
    10 ppm N/A N/A N/A 
    50 ppm    
        Regulation of G1/S transition (part 1) 4.694 38 
        Cytoskeleton remodeling 4.482 102 
        Tgf-beta-dependent induction of EMT via Smads 3.596 35 
        Regulation of Eif2 activity 3.412 39 
        Tgf-beta-dependent induction of EMT via Rhoa, P13k, and Ilk. 3.135 46 
Week 12    
GeneGo pathway maps, week 12 -LOG (p value) Number of genes affected Total genes in network 
    0.5 ppm    
        Integrin-mediated cell adhesion and migration 10.259 11 48 
        Cytoskeleton remodeling 8.676 13 102 
        Tgf, Wnt, and cytoskeletal remodeling 8.217 13 111 
        Regulation of EMT 7.648 10 64 
        Tgf-beta-dependent induction of EMT via Rhoa, P13k, and Ilk. 6.588 46 
    2 ppm    
        Activation of Erk by Acm1, Acm3, and Acm5. 4.969 44 
        Leptin signaling via Jak/Stat and Mapk cascades 3.527 25 
        Il-3 activation and signaling pathway 3.338 31 
        Oncostatin M signaling via Mapk 3.232 35 
        Hedgehog and Pth signaling pathways in bone and cartilage development 3.184 37 
    10 ppm    
        Tgf-beta-dependent induction of EMT via Rhoa, P13k and Ilk. 7.174 46 
        Fibronectin-binding integrins in cell motility 6.139 31 
        Thrombopoietin-regulated cell processes 6.093 45 
        Role of Cdk5 in neuronal development 5.847 34 
        Gm-csf signaling 5.729 50 
    50 ppm    
        Tgf-beta-dependent induction of EMT via Rhoa, P13k, and Ilk. 9.12 14 46 
        Tgf, Wnt, and cytoskeletal remodeling 8.319 20 111 
        Cytoskeleton remodeling 8.18 19 102 
        Regulation of Enos activity in endothelial cells 7.993 15 64 
        Regulation of EMT 7.993 15 64 

Week 1

0.5 mg As/l.

No pathways were enriched at this concentration and time points; however, significant enrichment was observed in the process network for Notch signaling. Of the seven downregulated genes in this process, only one has a known function: Neurl1, a ubiquitin ligase that targets the Notch receptor ligand Jagged1 (Koutelou et al., 2008). Downregulation of Neurl1 releases the inhibition of Notch signaling, leading to induction of epithelial-mesenchymal transitions (EMT). EMT represents a cellular stress response associated with decreased cell adhesion, increased mobility, and resistance to apoptosis (Lee et al., 2006). Neurl1 was downregulated at all concentrations at week 1 but not at week 12.

2 mg As/l.

No genes met the criteria for both significance and fold change.

10 mg As/l.

No significant enrichment was observed in gene pathways; however, several process networks were enriched that relate to cytoskeleton rearrangement. All of the gene expression changes in these networks were downregulation. Significantly, upregulated genes included Hnrnpu, which promotes cell survival by stabilizing Myc mRNA (Weidensdorfer et al., 2009), and Eif5, a translation initiation factor essential for cell proliferation (Balabanov et al., 2007).

50 mg As/l.

Significant enrichment was observed in pathways for cytoskeleton remodeling, regulation of the G1/S transition, and inhibition of EMT (associated with downregulation of Tgfb2). In addition, there was significant enrichment of the process networks for Wnt-related signaling (associated with downregulation of Cyclin D/D2 and upregulation of antiproliferative Smad3) and translation initiation (associated with upregulation of the translation initiation factor, Eif4g1/3).

Week 12

0.5 mg As/l.

Significant enrichment was observed in the pathways for cell adhesion, cytoskeleton remodeling, and Tfgb induction of EMT (associated with upregulation of Tgfb2). Concordant process networks were also enriched. All of the gene changes in these pathways and networks were upregulation, with the exception of the Ap-1 precursor, Fos, which was downregulated.

2 mg As/l.

Significant enrichment was observed in the pathways for Erk and Il-3 activation, as well as for oncostatin M signaling. Significantly, enriched process networks included regulation of EMT, Il-4 inflammatory signaling, Bcr immune pathway, antiapoptosis mediated by external signals via Mapk and Jak/Stat, Wnt signaling, and regulation of cell proliferation. Many of these responses were associated with upregulation of Bcl6, which inhibits Jun, and downregulation of Fos. Decreases in Jun and Fos have a complementary effect in decreasing Ap-1 activity.

10 mg As/l.

Significant enrichment was observed in the pathways for cytoskeleton remodeling, cell adhesion, and Tgfb induction of EMT, while significantly enriched process networks included cell adhesion, Il-6 signaling, phagocytosis, estrogen surface receptor pathway signaling, and inflammatory signaling. Significant upregulated genes included the Igf-1 receptor, which plays a critical role in cell transformation, Braf, a proto-oncogene that regulates mitogenic signaling through the Mapk/Erk pathway, and Pten, which acts as a tumor suppressor by downregulating the Akt/Pkb signaling pathway. Fos, on the other hand, was downregulated.

50 mg As/l.

Significant enrichment was observed in the pathways for Tgfb induction of EMT, cytoskeleton remodeling, and cell adhesion, as well as the process networks for regulation of EMT, cell adhesion, estrogen surface receptor pathway signaling, and Akt/Pkb signaling. Significantly, upregulated genes included Ets1 (involved in stem cell development), Bcl2 (antiapoptosis), Hif1a (hypoxia signaling), Akt1 (proliferation), Igf1, Igf1r, Egfr (epidermal growth factor receptor), Braf, Tgfb1, Tgfb2, and, Tgfbr1. Fos was significantly downregulated.

Concentration- and Time-Related Changes

Tgfb2 was significantly downregulated at week 1 but significantly upregulated at week 12; a similar behavior was observed for Gsk3b, which inhibits Jun. Although the trend for most genes was from downregulation at week 1 to upregulation at week 12 (Fig. 5), there were also subsets of genes demonstrating other patterns. Genes showing concentration-related downregulation at 12 weeks but not at 1 week included Fos, Egr1, Egr2, and Cyr61 (Fig. 6a). The Eif5 translation initiation gene was significantly upregulated at 10 mg As/l at both 1 and 12 weeks, whereas the Eif4ebp2 (aka, 4e-bp2) translation repressor gene was significantly downregulated at 50 mg As/l at both time points. Figures 5 and 6 illustrate the variety of concentration- and time-dependent responses observed for the genes displaying the largest expression changes in this study.

FIG. 5.

Dose-response for expression (ratio to controls) of selected genes showing downregulation at week 1 and upregulation at week 12.

FIG. 5.

Dose-response for expression (ratio to controls) of selected genes showing downregulation at week 1 and upregulation at week 12.

FIG. 6.

Dose-response for expression (ratio to controls) of selected genes showing downregulation at both time points (a and b), upregulation at both time points (c and d), and increasing expression change from week 1–12 (e and f).

FIG. 6.

Dose-response for expression (ratio to controls) of selected genes showing downregulation at both time points (a and b), upregulation at both time points (c and d), and increasing expression change from week 1–12 (e and f).

DISCUSSION

In this study, female C57BL6 mice were exposed to arsenate in drinking water for up to 12 weeks at concentrations ranging from 0.5 to 50 mg As/l, and urinary bladders were analyzed for changes in gene expression after 1 and 12 weeks of exposure. BMD-response analysis was performed to identify the gene signaling pathways affected as a function of concentration and duration of exposure. This study represents the first time genomic concentration-response analysis has been performed on bladder tissue after subchronic in vivo exposures to Asi in drinking water.

It was not possible to perform histopathological examination of the bladders in this study because all of the available bladder tissue was needed for the genomic and dosimetric analyses. However, based on previous studies with arsenate and arsenite in the mouse (Suzuki et al. 2008), only the highest drinking water concentration used in this study (50 mg/l) could have been associated with even mild toxicity. Suzuki et al. (2008) treated C57BL6 mice with 100 mg As/l for 2 or 10 weeks. For both treatment periods, they reported mild hyperplasia in the urothelium of one out of five mice. The urothelia of the remaining mice were normal. Because our highest concentration (50 mg As/l) was less than the Suzuki et al. (2008) concentration, we would expect minimal toxicity in the urothelium of the treated mice in this study.

The drinking water concentrations used in this study are considered relevant to human exposures, despite the fact that the drinking water concentrations (0.5–50 mg As/l) are higher than most human exposures. The arsenic concentrations in blood and tissues observed at the highest doses in this study, on the order of 0.1–1 μg As/g (Kenyon et al. 2008), are in the range of those reported in human populations chronically exposed to carcinogenic levels of arsenic in drinking water (Mazumder, 2005; Pi et al. 2002). Moreover, the drinking water concentrations in this study are comparable to those (6–24 mg As/l) that have recently been shown to produce tumors in mice following whole-life exposure (Tokar et al., 2011).

At both 1 and 12 weeks of exposure, gene expression changes in the urinary bladders of the mice were observed to occur primarily at the lowest concentration (0.5 mg As/l) and the two highest concentrations (10 and 50 mg As/l), with a much more limited response at the intermediate concentration of 2 mg As/l (Fig. 2). This bimodal concentration-response likely reflects a concentration-dependent transition in the effects of Asi on the mouse urinary bladder. Further support for a transition is provided by the minimal overlap in the genes affected at the low and high drinking water concentrations at either time point (Fig. 3) as well as the striking differences in the pathways affected at the low and high concentrations. The existence of a concentration-dependent transition in the interaction of Asi with cells is also supported by in vitro studies reporting marked changes in gene expression with increasing arsenite concentration (Andrew et al., 2003; Hu et al., 2002).

In this study, arsenite concentrations in urine ranged from ∼0.05 μg/l at the 0.5 mg As/l concentration to 16 μg/l at the 50 mg As/l concentration (Kenyon et al., 2008). These concentrations are comparable to the lower end of the nominal arsenite concentrations used in published in vitro genomic studies, which ranged from 0.05 to 100μM (Gentry et al. 2010). Of course, in this in vivo study, the cells were also exposed to arsenate and the methylated metabolites, which would be expected to contribute to cellular responses, making direct comparison to the in vitro arsenite exposure results difficult. Although arsenite was not directly measured in the bladder tissue, the concentrations of total Asi in the bladder, when they were measurable, were on the order of one-third of the concentrations in the urine.

Gene expression changes at the two time points in this study provide a striking contrast, with general downregulation of genes after 1 week of exposure as opposed to general upregulation at 12 weeks. There was also little overlap in the specific genes altered at 1 and 12 weeks. A recently reported study of the genomic response in the lungs of C3H mice exposed to arsenite in drinking water for 30 days (Chilakapati et al., 2009) found surprisingly few gene alterations: 57, 9, 3, 22, and 17 genes differentially expressed at concentrations of 0.05, 0.25, 1, 10, and 85 mg As/l, respectively. It is possible that this limited response was due to an unfortunate choice of exposure duration, which was intermediate between the two time points examined in the present study. That is, after 30 days of exposure to arsenite, an initial adaptive response may have been substantially suppressed, and the long-term response may not yet have developed sufficiently to be detected. A small subset of genes showed a reverse trend toward greater downregulation at week 12. These included Fos, Egr1,Egr2, Cyr61, Nr4a1, all of which are associated with early growth response, and Bat1a, which is associated with the Nfkb inflammatory response (Figs. 6 a, b, e, and f).

Only a few in vitro studies have been reported that compare the effects of short- and long-term arsenite exposure. Hu et al. (2002) compared acute (24 h) and chronic (10–20 week) exposures of human GM847 fibroblasts to arsenite at low concentrations (0.1 and 5μM acutely versus 0.1 and 0.5μM chronically). The DNA binding activities of Ap-1 and Nf-kb, which are involved in the oxidative stress response, were increased after acute exposure but were decreased after chronic exposure. Similarly, Fos and Jun protein levels were increased acutely but were decreased after chronic treatment. Although Fos and Jun mRNA levels were unaffected acutely, they were significantly decreased after chronic exposure. In the present study, Fos expression was unaffected at week 1 in vivo but was downregulated at week 12, in agreement with the in vitro mRNA results of Hu et al. (2002). In addition, Bcl2, which inhibits Jun, was unaffected at week 1 but upregulated at week 12, consistent with the observed longer term downregulation of Jun reported in the in vitro study.

Additional evidence for this longer term suppression of an initial adaptive response to Asi is provided by a study of short- and long-term exposures of NIH3T3 cells to arsenite (Hu et al., 2003), which reported a large increase in glutathione concentrations after 24 h exposures ranging from 0.5 to 10μM arsenite, in contrast to decreased glutathione concentrations after 56–133 days of exposure at 0.1 and 0.5μM. The results of the present in vivo study are consistent with these in vitro results: the cellular responses to short-term and long-term Asi exposure are quite different, with an initial response that is largely reversed on longer exposure. This time-dependence of the effects of Asi exposure on cellular responses may be an important aspect of the mode of action for Asi carcinogenicity. Recently, Li et al. (2010) exposed human keratinocytes (HaCaT) to 1.0μM arsenite for up to 15 weeks. They observed initial increases in phospho-TP53, Cdkn1a (p21), and Mdm2 that decreased at longer exposure times. After 15 weeks of exposure, cells demonstrated increased proliferation, DNA double-strand breaks, and anchorage-independent growth. The authors found that this transformation resulted from a repressive effect of Nf-kb on Tp53 function, leading to genomic instability.

BMD analysis determined that a large number of key signaling pathway BMD values clustered in the vicinity of the 10 mg As/l exposure concentration (Table 1). Affected pathways included cellular responses related to morphogenesis, inflammation (immune response), cell cycle control, DNA damage response, and apoptosis/survival. The effects on cell cycle control and DNA damage response are consistent with evidence that arsenite exposure is associated with inhibition of a number of DNA repair processes (Hu et al., 1998; Li and Rossman, 1989; Lynn et al., 1997; Rossman, 1999; Sykora and Snow, 2008; Yager and Wiencke, 1997). Several potentially oncogenic pathways are activated at these concentrations, including the Wnt, Igf1, Egfr, and estrogen surface receptor pathways.

Interestingly, a number of animal studies using arsenite at concentrations on the order of 50 mg As/l (summarized in Gentry et al., 2005) have failed to demonstrate an increase in tumor incidence. The BMDs for p53- and caspace-mediated apoptosis around 10 mg As/l in this study are consistent with evidence from other studies that high doses of arsenite can preferentially induce apoptosis (Berenson and Yeh, 2006; Gentry et al., 2010; Zheng et al., 2005). Arsenite is more toxic than arsenate to the mouse bladder, as demonstrated by the observation that arsenite, but not arsenate, produced cytotoxicity and exfoliation in the female mouse urinary bladder epithelium after 2-week exposures to 100 mg As/l in drinking water (Suzuki et al., 2008). It is possible that studies at higher doses have failed to induce tumors because induction of apoptosis becomes dominant. The concentration-response for genomic effects in this study indicates that the carcinogenicity of arsenic in mice may peak at drinking water concentrations on the order of 10 mg As/l. This conclusion is consistent with the results of a recently published whole-life bioassay of inorganic carcinogenicity in the CD1 mouse (Tokar et al., 2011), which demonstrated similar tumorigenicity following exposures at 6, 12, and 24 mg As/l.

The lowest median BMD values for GeneGo pathways were on the order of 5 mg As/l; that is, above the lowest two concentrations used in the study. The fact that a number of pathways were enriched at the lowest drinking water concentration, well below the BMD values, might reflect the impact of the nonmonotonic concentration-response (Fig. 1) on the benchmark modeling. Pathways affected at these lower concentrations included several related to EMT. EMT represents a cellular stress response associated with decreased cell adhesion, increased mobility, and resistance to apoptosis. The in vivo genomic evidence of EMT at relatively low arsenic exposures in this study is supported by in vitro data from long-term (> 100 day) exposures of partially immortalized NIH3T3 cells to arsenite (Hu et al., 2003). Cells exposed to 0.1μM arsenite in this study exhibited anchorage-independent growth. The arsenite-exposed cells also demonstrated more aggressive cell growth, a transformed phenotype, and their partial immortalization (30–40 passages) was extended to more than 55 passages. This in vitro transformation was observed at exposures on the order of 0.1μM (7.5 μg As/l), similar to the arsenite concentrations in urine at the lowest two exposures in this study.

In conclusion, our study of genomic responses in the mouse urinary bladder after short- and long-term exposures to arsenate in drinking water is consistent with previously published results of in vitro studies on the cellular effects of arsenite. In particular, there is clear evidence of an initial adaptive response that is suppressed on longer exposure. This suppression is marked by a reversal in the direction of gene changes, primarily from downregulation to upregulation over time. While the specific genes affected at each time point differed, pathways affected after either short- or long-term exposure were substantially similar (Table 1). A bimodal concentration-response for number of altered genes was observed at both 1 and 12 weeks of exposure, suggesting a change in the nature of Asi effects on cells at drinking water exposures between 1 and 10 mg As/l. Although a number of gene responses, particularly those associated with EMT, were observed at the lowest exposure concentration in this study (0.5 mg As/l), benchmark analysis indicates that arsenic drinking water concentrations on the order of 2 mg As/l and above are required to significantly perturb cellular pathways/networks in the mouse bladder. Comparison of the genomic concentration-responses observed at the 1- and 12-week time points indicates a trend toward decreases in the higher BMDs over time; therefore, effects of arsenic might be observed at somewhat lower concentrations following chronic exposure. However, the evidence of a concentration-dependent transition in the mode of action for inorganic arsenic in the vicinity of 2 mg As/l was consistent across the shorter term and longer term exposure periods; suggesting that this threshold might also be relevant to chronic exposures.

FUNDING

Electric Power Research Institute (EPRI) Contract PID 059811, Agreement EP-P15532/C7711.

SUPPLEMENTARY DATA

Supplementary data are available online at http://toxsci.oxfordjournals.org.

The authors wish to thank Mel Andersen, for his insightful comments on a draft of this manuscript, and Alina Efremenko, for her invaluable assistance in the analysis of the genomic data. The opinions expressed in this paper are those of the authors and do not necessarily represent the position of the U. S. Environmental Protection Administration or EPRI.

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Author notes

Disclaimer: This manuscript has been reviewed in accordance with the policy of the National Health and Environmental Effects Research Laboratory, U.S. Environmental Protection Agency, and approved for publication. Approval does not signify that the contents necessarily reflect the views and policies of the Agency nor does mention of trade names or commercial products constitute endorsement or recommendation for use.