A Systems Biology Approach Reveals Converging Molecular Mechanisms that Link Different POPs to Common Metabolic Diseases.

BACKGROUND: A number of epidemiological studies have identified statistical associations between persistent organic pollutants (POPs) and metabolic diseases, but testable hypotheses regarding underlying molecular mechanisms to explain these linkages have not been published. OBJECTIVES: We assessed the underlying mechanisms of POPs that have been associated with metabolic diseases; three well-known POPs [2,3,7,8-tetrachlorodibenzodioxin (TCDD), 2,2´,4,4´,5,5´-hexachlorobiphenyl (PCB 153), and 4,4´-dichlorodiphenyldichloroethylene (p,p´-DDE)] were studied. We used advanced database search tools to delineate testable hypotheses and to guide laboratory-based research studies into underlying mechanisms by which this POP mixture could produce or exacerbate metabolic diseases. METHODS: For our searches, we used proprietary systems biology software (MetaCore™/MetaDrug™) to conduct advanced search queries for the underlying interactions database, followed by directional network construction to identify common mechanisms for these POPs within two or fewer interaction steps downstream of their primary targets. These common downstream pathways belong to various cytokine and chemokine families with experimentally well-documented causal associations with type 2 diabetes. CONCLUSIONS: Our systems biology approach allowed identification of converging pathways leading to activation of common downstream targets. To our knowledge, this is the first study to propose an integrated global set of step-by-step molecular mechanisms for a combination of three common POPs using a systems biology approach, which may link POP exposure to diseases. Experimental evaluation of the proposed pathways may lead to development of predictive biomarkers of the effects of POPs, which could translate into disease prevention and effective clinical treatment strategies. CITATION: Ruiz P, Perlina A, Mumtaz M, Fowler BA. 2016. A systems biology approach reveals converging molecular mechanisms that link different POPs to common metabolic diseases. Environ Health Perspect 124:1034-1041; http://dx.doi.org/10.1289/ehp.1510308.

Low-Dose Cadmium Causes Metabolic and Genetic Dysregulation Associated With Fatty Liver Disease in Mice.

Cadmium (Cd) is present in food at low levels and accumulates in humans throughout life because it is not effectively excreted. Cd from smoking or occupational exposure shows adverse effects on health, but the mechanistic effect of Cd at low dietary intake levels is poorly studied. Epidemiology studies found that nonalcoholic fatty liver disease (NAFLD), common in U.S. adults, is associated with Cd burden. In cell studies, we found that environmental low-dose Cd oxidized proteins and stimulated inflammatory signaling. However, little is known about low-dose Cd effects on liver function and associated metabolic pathways in vivo. We investigated effects of low-level Cd exposure on liver gene transcripts, metabolites, and associated metabolic pathways and function after challenging mice with Cd (10 mg/l) by drinking water. Results showed liver Cd in treated mice was similar to adult humans without occupational or smoking exposures and 10-fold higher than control mouse values. Pathway analysis of significantly altered liver genes and metabolites mapped to functional pathways of lipid metabolism, cell death and mitochondrial oxidative phosphorylation. These are well-recognized pathways associated with NAFLD. Cd-treated mice had higher liver enzymes in plasma and a trend toward fat accumulation in liver. To verify low-dose Cd-induced stimulation of cell death pathways, phosphorylation of c-Jun N-terminal kinase (JNK) was examined in cultured hepatic cells. Consistent with mouse liver data, low-dose Cd stimulated JNK activation. Together, the results show that low-dose Cd exposure causes liver function changes consistent with a role in NAFLD and possibly also nonalcoholic steatohepatitis.

Biomarkers in toxicology and risk assessment.

Over the last 30 years, the field of biomarkers has greatly expanded as early and specific endpoints for monitoring cellular responses to various disease states and exposures to drugs and chemical agents. They have enjoyed some success as predictors of health outcomes for a number of clinical diseases, but the application to chemical exposure risk assessments has been more limited. Biomarkers may be classified into categories of markers of exposure, effect, and susceptibility. Currently, "omics" biomarkers (i.e., genomic, proteomic, and metabolomic/metabonomic) are the major classes of biomarkers under development. These markers represent a continuum of cellular responses to drug or chemical exposures and provide linkages to mechanisms of cell injury/cell death or carcinogenic transformation. On the other hand, translation and application of these biomarkers for risk assessment has been limited due to validation and interpretation issues that need to be addressed in order for these potentially extremely valuable endpoints to reach their full potential as predictive tools for public health. This short chapter will briefly review these three "omics" biomarker classes and examine some validation/translation aspects needed in order for them to reach their full potential and acceptance as valuable tools for application to risk assessment.

Modeling chemical interaction profiles: I. Spectral data-activity relationship and structure-activity relationship models for inhibitors and non-inhibitors of cytochrome P450 CYP3A4 and CYP2D6 isozymes.

An interagency collaboration was established to model chemical interactions that may cause adverse health effects when an exposure to a mixture of chemicals occurs. Many of these chemicals--drugs, pesticides, and environmental pollutants--interact at the level of metabolic biotransformations mediated by cytochrome P450 (CYP) enzymes. In the present work, spectral data-activity relationship (SDAR) and structure-activity relationship (SAR) approaches were used to develop machine-learning classifiers of inhibitors and non-inhibitors of the CYP3A4 and CYP2D6 isozymes. The models were built upon 602 reference pharmaceutical compounds whose interactions have been deduced from clinical data, and 100 additional chemicals that were used to evaluate model performance in an external validation (EV) test. SDAR is an innovative modeling approach that relies on discriminant analysis applied to binned nuclear magnetic resonance (NMR) spectral descriptors. In the present work, both 1D ¹³C and 1D ¹5N-NMR spectra were used together in a novel implementation of the SDAR technique. It was found that increasing the binning size of 1D ¹³C-NMR and ¹5N-NMR spectra caused an increase in the tenfold cross-validation (CV) performance in terms of both the rate of correct classification and sensitivity. The results of SDAR modeling were verified using SAR. For SAR modeling, a decision forest approach involving from 6 to 17 Mold2 descriptors in a tree was used. Average rates of correct classification of SDAR and SAR models in a hundred CV tests were 60% and 61% for CYP3A4, and 62% and 70% for CYP2D6, respectively. The rates of correct classification of SDAR and SAR models in the EV test were 73% and 86% for CYP3A4, and 76% and 90% for CYP2D6, respectively. Thus, both SDAR and SAR methods demonstrated a comparable performance in modeling a large set of structurally diverse data. Based on unique NMR structural descriptors, the new SDAR modeling method complements the existing SAR techniques, providing an independent estimator that can increase confidence in a structure-activity assessment. When modeling was applied to hazardous environmental chemicals, it was found that up to 20% of them may be substrates and up to 10% of them may be inhibitors of the CYP3A4 and CYP2D6 isoforms. The developed models provide a rare opportunity for the environmental health branch of the public health service to extrapolate to hazardous chemicals directly from human clinical data. Therefore, the pharmacological and environmental health branches are both expected to benefit from these reported models.

Modeling chemical interaction profiles: II. Molecular docking, spectral data-activity relationship, and structure-activity relationship models for potent and weak inhibitors of cytochrome P450 CYP3A4 isozyme.

Polypharmacy increasingly has become a topic of public health concern, particularly as the U.S. population ages. Drug labels often contain insufficient information to enable the clinician to safely use multiple drugs. Because many of the drugs are bio-transformed by cytochrome P450 (CYP) enzymes, inhibition of CYP activity has long been associated with potentially adverse health effects. In an attempt to reduce the uncertainty pertaining to CYP-mediated drug-drug/chemical interactions, an interagency collaborative group developed a consensus approach to prioritizing information concerning CYP inhibition. The consensus involved computational molecular docking, spectral data-activity relationship (SDAR), and structure-activity relationship (SAR) models that addressed the clinical potency of CYP inhibition. The models were built upon chemicals that were categorized as either potent or weak inhibitors of the CYP3A4 isozyme. The categorization was carried out using information from clinical trials because currently available in vitro high-throughput screening data were not fully representative of the in vivo potency of inhibition. During categorization it was found that compounds, which break the Lipinski rule of five by molecular weight, were about twice more likely to be inhibitors of CYP3A4 compared to those, which obey the rule. Similarly, among inhibitors that break the rule, potent inhibitors were 2-3 times more frequent. The molecular docking classification relied on logistic regression, by which the docking scores from different docking algorithms, CYP3A4 three-dimensional structures, and binding sites on them were combined in a unified probabilistic model. The SDAR models employed a multiple linear regression approach applied to binned 1D ¹³C-NMR and 1D ¹5N-NMR spectral descriptors. Structure-based and physical-chemical descriptors were used as the basis for developing SAR models by the decision forest method. Thirty-three potent inhibitors and 88 weak inhibitors of CYP3A4 were used to train the models. Using these models, a synthetic majority rules consensus classifier was implemented, while the confidence of estimation was assigned following the percent agreement strategy. The classifier was applied to a testing set of 120 inhibitors not included in the development of the models. Five compounds of the test set, including known strong inhibitors dalfopristin and tioconazole, were classified as probable potent inhibitors of CYP3A4. Other known strong inhibitors, such as lopinavir, oltipraz, quercetin, raloxifene, and troglitazone, were among 18 compounds classified as plausible potent inhibitors of CYP3A4. The consensus estimation of inhibition potency is expected to aid in the nomination of pharmaceuticals, dietary supplements, environmental pollutants, and occupational and other chemicals for in-depth evaluation of the CYP3A4 inhibitory activity. It may serve also as an estimate of chemical interactions via CYP3A4 metabolic pharmacokinetic pathways occurring through polypharmacy and nutritional and environmental exposures to chemical mixtures.

Metal ions affecting the kidney.

This chapter provides a succinct summary of the nephrotoxic effects of a number of metals/metalloids on an individual or mixture basis. There is a discussion of routes of exposure, mechanisms of uptake by renal cells and the potential impact of nanomaterials on these processes. An emphasis is placed on the toxicity of these metals/ metalloids to individual cell types in the kidney and the application of biomarkers for the early detection of kidney cell injury prior to the onset of an overt clinical state such as end-stage renal disease. The issue of interactions between nephrotoxic metals in mixture exposures is discussed in relation to the application of molecular biomarkers for early detection of renal cell injury.

Exposure to Pb, Cd, and As mixtures potentiates the production of oxidative stress precursors: 30-day, 90-day, and 180-day drinking water studies in rats.

Exposure to chemical mixtures is a common and important determinant of toxicity and is of particular concern due to their appearance in sources of drinking water. Despite this, few in vivo mixture studies have been conducted to date to understand the health impact of chemical mixtures compared to single chemicals. Interactive effects of lead (Pb), cadmium (Cd) and arsenic (As) were evaluated in 30-, 90-, and 180-day factorial design drinking water studies in rats designed to test the hypothesis that ingestion of such mixtures at individual component Lowest-Observed-Effect-Levels (LOELs) results in increased levels of the pro-oxidant delta aminolevulinic acid (ALA), iron, and copper. LOEL levels of Pb, Cd, and As mixtures resulted in the increased presence of mediators of oxidative stress such as ALA, copper, and iron. ALA increases were followed by statistically significant increases in kidney copper in the 90- and 180-day studies. Statistical evidence of interaction was identified for six biologically relevant variables: blood delta aminolevulinic acid dehydratase (ALAD), kidney ALAD, urinary ALA, urinary iron, kidney iron, and kidney copper. The current investigations underscore the importance of considering interactive effects that common toxic agents such as Pb, Cd, and As may have upon one another at low-dose levels. The interactions between known toxic trace elements at biologically relevant concentrations shown here demonstrate a clear need to rigorously review methods by which national/international agencies assess health risks of chemicals, since exposures may commonly occur as complex mixtures.

SAR/QSAR methods in public health practice.

Methods of (Quantitative) Structure-Activity Relationship ((Q)SAR) modeling play an important and active role in ATSDR programs in support of the Agency mission to protect human populations from exposure to environmental contaminants. They are used for cross-chemical extrapolation to complement the traditional toxicological approach when chemical-specific information is unavailable. SAR and QSAR methods are used to investigate adverse health effects and exposure levels, bioavailability, and pharmacokinetic properties of hazardous chemical compounds. They are applied as a part of an integrated systematic approach in the development of Health Guidance Values (HGVs), such as ATSDR Minimal Risk Levels, which are used to protect populations exposed to toxic chemicals at hazardous waste sites. (Q)SAR analyses are incorporated into ATSDR documents (such as the toxicological profiles and chemical-specific health consultations) to support environmental health assessments, prioritization of environmental chemical hazards, and to improve study design, when filling the priority data needs (PDNs) as mandated by Congress, in instances when experimental information is insufficient. These cases are illustrated by several examples, which explain how ATSDR applies (Q)SAR methods in public health practice.

Research recommendations for selected IARC-classified agents.

OBJECTIVES: There are some common occupational agents and exposure circumstances for which evidence of carcinogenicity is substantial but not yet conclusive for humans. Our objectives were to identify research gaps and needs for 20 agents prioritized for review based on evidence of widespread human exposures and potential carcinogenicity in animals or humans. DATA SOURCES: For each chemical agent (or category of agents), a systematic review was conducted of new data published since the most recent pertinent International Agency for Research on Cancer (IARC) Monograph meeting on that agent. DATA EXTRACTION: Reviewers were charged with identifying data gaps and general and specific approaches to address them, focusing on research that would be important in resolving classification uncertainties. An expert meeting brought reviewers together to discuss each agent and the identified data gaps and approaches. DATA SYNTHESIS: Several overarching issues were identified that pertained to multiple agents; these included the importance of recognizing that carcinogenic agents can act through multiple toxicity pathways and mechanisms, including epigenetic mechanisms, oxidative stress, and immuno- and hormonal modulation. CONCLUSIONS: Studies in occupational populations provide important opportunities to understand the mechanisms through which exogenous agents cause cancer and intervene to prevent human exposure and/or prevent or detect cancer among those already exposed. Scientific developments are likely to increase the challenges and complexities of carcinogen testing and evaluation in the future, and epidemiologic studies will be particularly critical to inform carcinogen classification and risk assessment processes.

Interpreting NHANES biomonitoring data, cadmium.

Cadmium (Cd) occurs naturally in the environment and the general population's exposure to it is predominantly through diet. Chronic Cd exposure is a public health concern because Cd is a known carcinogen; it accumulates in the body and causes kidney damage. The National Health and Nutritional Examination Survey (NHANES) has measured urinary Cd; the 2003-2004 NHANES survey cycle reported estimates for 2257 persons aged 6 years and older in the Fourth National Report on Human Exposure to Environmental Chemicals. As part of translational research to make computerized models accessible to health risk assessors we re-coded a cadmium model in Berkeley Madonna simulation language. This model was used in our computational toxicology laboratory to predict the urinary excretion of cadmium. The model simulated the NHANES-measured data very well from ages 6 to 60+ years. An unusual increase in Cd urinary excretion was observed among 6-11-year-olds, followed by a continuous monotonic rise into the seventh decade of life. This observation was also made in earlier studies that could be life stage-related and a function of anatomical and phsysiological changes occurring during this period of life. Urinary excretion of Cd was approximately twofold higher among females than males in all age groups. The model describes Cd's cumulative nature in humans and accommodates the observed variation in exposure/uptake over the course of a lifetime. Such models may be useful for interpreting biomonitoring data and risk assessment.

Modification by ALAD of the association between blood lead and blood pressure in the U.S. population: results from the Third National Health and Nutrition Examination Survey.

BACKGROUND: Environmental lead exposure has been found to be associated with an increased risk of hypertension. Individuals vary greatly in susceptibility to lead toxicity, and genetic susceptibility has often been cited as the probable cause for such variation. OBJECTIVE: The main objective is to determine the role of the aminolevulinic acid dehydratase (ALAD) gene, which encodes the main carrier protein of lead in blood, in the association between lead exposure and blood pressure (BP) and hypertension in the U.S. population. METHODS: We analyzed data from individuals >or= 17 years of age who participated in the Third National Health and Nutrition Examination Survey for whom DNA was available (n = 6,016). Multivariable logistic and linear regressions stratified by race/ethnicity were used to examine whether hypertension and BP were associated with ALAD and blood lead levels (BLL). RESULTS: BLL was associated with systolic BP in non-Hispanic whites and with hypertension and systolic and diastolic BP in non-Hispanic blacks. BLL was not associated with BP outcomes in Mexican Americans. Non-Hispanic white ALAD2 carriers in the highest BLL quartile (3.852.9 microg/dL) had a significantly higher adjusted prevalence odds ratio for hypertension compared with ALAD1 homozygous individuals. We also found a significant interaction between lead concentration and the ALAD2 allele in non-Hispanic whites and non-Hispanic blacks in relation to systolic BP. CONCLUSIONS: BLL may be an important risk factor for hypertension and increased systolic and diastolic BP. These associations may be modified by ALAD genotype.

Monitoring of human populations for early markers of cadmium toxicity: a review.

Exposure of human populations to cadmium (Cd) from air, food and water may produce effects in organs such as the kidneys, liver, lungs, cardiovascular, immune and reproductive systems. Since Cd has been identified as a human carcinogen, biomarkers for early detection of susceptibility to cancer are of an importance to public health. The ability to document Cd exposure and uptake of this element through biological monitoring is a first step towards understanding its health effects. Interpretation and application of biological monitoring data for predicting human health outcomes require correlation with biological measures of organ system responses to the documented exposure. Essential to this understanding is the detection and linkage of early biological responses toxic effects in target cell populations. Fortunately, advances in cell biology have resulted in the development of pre-clinical biological markers (biomarkers) that demonstrate measurable and characteristic molecular changes in organ systems following chemical exposures that occur prior to the onset of overt clinical disease or development of cancer. Technical advances have rendered a number of these biomarkers practical for monitoring Cd-exposed human populations. Biomarkers will be increasingly important in relation to monitoring effects from the exposure to new Cd-based high technology materials. For example, cadmium-selenium (CdSe), nano-materials made from combinations of these elements have greatly altered cellular uptake characteristics due to particle size. These differences may greatly alter effects at the target cell level and hence risks for organ toxicities from such exposures. The value of validated biomarkers for early detection of systemic Cd-induced effects in humans cannot be underestimated due to the rapid expansion of nano-material technologies. This review will attempt to briefly summarize the applications, to date, of biomarker endpoints for assessing target organ system effects in humans and experimental systems from Cd exposure. Further, it will attempt to provide a prospective look at the possible future of biomarkers. The emphasis will be on the detection of early toxic effects from exposure to Cd in new products such as nano-materials and identification of populations at special risk for Cd toxicity.

Proteomic and metabolomic biomarkers for III-V semiconductors: and prospects for application to nano-materials.

There has been an increased appreciation over the last 20 years that chemical agents at very low dose levels can produce biological responses in protein expression patterns (proteomic responses) or alterations in sensitive metabolic pathways (metabolomic responses). Marked improvements in analytical methodologies, such as 2-D gel electrophoresis, matrix-assisted laser desorption-time of flight (MALDI-TOF) and surface enhanced laser desorption-time of flight (SELDI-TOF) technologies are capable of identifying specific protein patterns related to exposure to chemicals either alone or as mixtures. The detection and interpretation of early cellular responses to chemical agents have also made great advances through correlative ultrastructural morphometric and biochemical studies. Similarly, advances in analytical technologies such as HPLC, proton NMR, MALDI-TOF, and SELDI-TOF have permitted early detection of changes in a number of essential metabolic pathways following chemical exposures by measurement of alterations in metabolic products from those pathways. Data from these approaches are increasingly regarded as potentially useful biomarkers of chemical exposure and early cellular responses. Validation and establishment of linkages to biological outcomes are needed in order for biomarkers of effect to be established. This short review will cover a number of the above techniques and report data from chemical exposures to two binary III-V semiconductor compounds to illustrate gender differences in proteomic responses. In addition, the use of these methodologies in relation to rapid safety evaluations of nanotechnology products will be discussed.

Roles of biomarkers in evaluating interactions among mixtures of lead, cadmium and arsenic.

Human exposure to environmental chemicals is most correctly characterized as exposure to mixtures of these agents. The metals/metalloids, lead (Pb), cadmium (Cd), and arsenic (As), are among the leading toxic agents detected in the environment. Exposure to these elements, particularly at chronic low dose levels, is still a major public health concern. Concurrent exposure to Pb, Cd, or As may produce additive or synergistic interactions or even new effects that are not seen in single component exposures. Evaluating these interactions on a mechanistic basis is essential for risk assessment and management of metal/metalloid mixtures. This paper will review a number of individual studies that addressed interactions of these metals/metalloids in both experimental and human exposure studies with particular emphasis on biomarkers. In general, co-exposure to metal/metalloid mixtures produced more severe effects at both relatively high dose and low dose levels in a biomarker-specific manner. These effects were found to be mediated by dose, duration of exposure and genetic factors. While traditional endpoints, such as morphological changes and biochemical parameters for target organ toxicity, were effective measures for evaluating the toxicity of high dose metal/metalloid mixtures, biomarkers for oxidative stress, altered heme biosynthesis parameters, and stress proteins showed clear responses in evaluating toxicity of low dose metal/metalloid mixtures. Metallothionein, heat shock proteins, and glutathione are involved in regulating interactive effects of metal/metalloid mixtures at low dose levels. These findings suggest that further studies on interactions of these metal/metalloid mixtures utilizing biomarker endpoints are highly warranted.

Lead and delta-aminolevulinic acid dehydratase polymorphism: where does it lead? A meta-analysis.

BACKGROUND: Lead poisoning affects many organs in the body. Lead inhibits delta-aminolevulinic acid dehydratase (ALAD), an enzyme with two co-dominantly expressed alleles, ALAD1 and ALAD2. OBJECTIVE: Our meta-analysis studied the effects of the ALAD polymorphism on a) blood and bone lead levels and b) indicators of target organ toxicity. DATA SOURCE: We included studies reporting one or more of the following by individuals with genotypes ALAD1-1 and ALAD1-2/2-2: blood lead level (BLL), tibia or trabecular lead level, zinc protoporphyrin (ZPP), hemoglobin, serum creatinine, blood urea nitrogen (BUN), dimercaptosuccinic acid-chelatable lead, or blood pressure. DATA EXTRACTION: Sample sizes, means, and standard deviations were extracted for the genotype groups. DATA SYNTHESIS: There was a statistically significant association between ALAD2 carriers and higher BLL in lead-exposed workers (weighted mean differences of 1.93 microg/dL). There was no association with ALAD carrier status among environmentally exposed adults with BLLs < 10 microg/dL. ALAD2 carriers were potentially protected against adverse hemapoietic effects (ZPP and hemoglobin levels), perhaps because of decreased lead bioavailability to heme pathway enzymes. CONCLUSION: Carriers of the ALAD2 allele had higher BLLs than those who were ALAD1 homozygous and higher hemoglobin and lower ZPP, and the latter seems to be inversely related to BLL. Effects on other organs were not well delineated, partly because of the small number of subjects studied and potential modifications caused by other proteins in target tissues or by other polymorphic genes.

Genetic factors that might lead to different responses in individuals exposed to perchlorate.

Perchlorate has been detected in groundwater in many parts of the United States, and recent detection in vegetable and dairy food products indicates that contamination by perchlorate is more widespread than previously thought. Perchlorate is a competitive inhibitor of the sodium iodide symporter, the thyroid cell-surface protein responsible for transporting iodide from the plasma into the thyroid. An estimated 4.3% of the U.S. population is subclinically hypothyroid, and 6.9% of pregnant women may have low iodine intake. Congenital hypothyroidism affects 1 in 3,000 to 1 in 4,000 infants, and 15% of these cases have been attributed to genetic defects. Our objective in this review is to identify genetic biomarkers that would help define subpopulations sensitive to environmental perchlorate exposure. We review the literature to identify genetic defects involved in the iodination process of the thyroid hormone synthesis, particularly defects in iodide transport from circulation into the thyroid cell, defects in iodide transport from the thyroid cell to the follicular lumen (Pendred syndrome), and defects of iodide organification. Furthermore, we summarize relevant studies of perchlorate in humans. Because of perchlorate inhibition of iodide uptake, it is biologically plausible that chronic ingestion of perchlorate through contaminated sources may cause some degree of iodine discharge in populations that are genetically susceptible to defects in the iodination process of the thyroid hormone synthesis, thus deteriorating their conditions. We conclude that future studies linking human disease and environmental perchlorate exposure should consider the genetic makeup of the participants, actual perchlorate exposure levels, and individual iodine intake/excretion levels.

Metallothionein expression in invasive and in situ breast carcinomas.

BACKGROUND/METHODS: The primary aims of this study were to examine the expression of metallothionein (MT) in 123 primary invasive breast carcinomas and the in situ components of these carcinomas and to assess the association between MT expression and certain socio-demographic and clinico-pathologic characteristics. MT expression was assessed using immunohistochemical procedures and semi-quantified using an immunoreactivity score. RESULTS: Results showed that 57.7% of the invasive tumors and 43.3% of the in situ carcinomas in the study were MT-positive. Chi-squared analyses showed that MT expression was significantly higher in the tumors of women categorized as being of 'other' race and of women with tumors of high histological grade. CONCLUSIONS: The results of this study suggest that MT is a biomarker of tumor differentiation and aggressiveness and that MT expression may differ by race.

Metabolomic and proteomic biomarkers for III-V semiconductors: chemical-specific porphyrinurias and proteinurias.

A pressing need exists to develop and validate molecular biomarkers to assess the early effects of chemical agents, both individually and in mixtures. This is particularly true for new and chemically intensive industries such as the semiconductor industry. Previous studies from this laboratory and others have demonstrated element-specific alterations of the heme biosynthetic pathway for the III-V semiconductors gallium arsenide (GaAs) and indium arsenide (InAs) with attendant increased urinary excretion of specific heme precursors. These data represent an example of a metabolomic biomarker to assess chemical effects early, before clinical disease develops. Previous studies have demonstrated that the intratracheal or subcutaneous administration of GaAs and InAs particles to hamsters produces the induction of the major stress protein gene families in renal proximal tubule cells. This was monitored by 35-S methionine labeling of gene products followed by two-dimensional gel electrophoresis after exposure to InAs particles. The present studies examined whether these effects were associated with the development of compound-specific proteinuria after 10 or 30 days following subcutaneous injection of GaAs or InAs particles in hamsters. The results of these studies demonstrated the development of GaAs- and InAs-specific alterations in renal tubule cell protein expression patterns that varied at 10 and 30 days. At the 30-day point, cells in hamsters that received InAs particles showed marked attenuation of protein expression, suggesting inhibition of the stress protein response. These changes were associated with GaAs and InAs proteinuria patterns as monitored by two-dimensional gel electrophoresis and silver staining. The intensity of the protein excretion patterns increased between the 10- and 30-day points and was most pronounced for animals in the 30-day InAs treatment group. No overt morphologic signs of cell death were seen in renal tubule cells of these animals. Western blot analyses of the urines with antibodies to the 32-, 70-, and 90-kDa stress protein families did not show the presence of these molecules, indicating that these proteins were not excreted in the urine samples. These data suggest that the observed proteinuria patterns were not a result of cell death and that the observed chemical-specific proteinurias were produced before marked cellular toxicity. These findings suggest a hypothesis involving GaAs and InAs interference with stress protein chaperoning of reabsorbed proteins for proteosomic degradation and the probable chaperoning of damaged intracellular proteins from renal proximal tubule cells into the urinary filtrate. Overall, the results of these studies provide further information on the nephrotoxicity of these semiconductor compounds. They also suggest the use of two-dimensional gel electrophoresis with silver staining of urinary protein patterns as a potentially useful proteomic approach to renal damage early in relation to intracellular proteotoxicity in kidney tubule cells.