AroER tri-screen is a biologically relevant assay for endocrine disrupting chemicals modulating the activity of aromatase and/or the estrogen receptor

Use of Tox21 screening data to profile PFAS bioactivities on nuclear receptors, cellular stress pathways, and cytochrome p450 enzymes

Per- and poly-fluoroalkyl substances (PFAS) are synthetic chemicals widely used in commercial products. PFAS are a global concern due to their persistence in the environment and extensive associations with adverse health outcomes. While legacy PFAS have been extensively studied, many non-legacy PFAS lack sufficient toxicity information. In this study, we first analyzed the bioactivity of PFAS using Tox21 screening data surveying more than 75 assay endpoints (e.g., nuclear receptors, stress response, and metabolism) to understand the toxicity of non-legacy PFAS and investigate potential new targets of PFAS. From the Tox21 screening data analysis, we confirmed several known PFAS targets/pathways and identified several potential novel targets/pathways of PFAS. To confirm the effect of PFAS on these novel targets/pathways, we conducted several cell- and enzyme-based assays in the follow-up studies. We found PFAS inhibited cytochromes P450s (CYPs), especially CYP2C9 with IC50 values of < 1 µM. Considering PFAS affected other targets/pathways at > 10 µM, PFAS have a higher affinity to CYP2C9. This PFAS-CYP2C9 interaction was further investigated using molecular docking analysis. The result suggested that PFAS directly bind to the active sites of CYP2C9. These findings have important implications to understand the mechanism of PFAS action and toxicity.

Systematic computational toxicity analysis of the ozonolytic degraded compounds of azo dyes: Quantitative structure-activity relationship (QSAR) and adverse outcome pathway (AOP) based approach

The present study identifies and analyses the degraded products of three azo dyes (Reactive Orange 16, Reactive Red 120, and Direct Red 80) and proffers their in silico toxicity predictions. In our previously published work, the synthetic dye effluents were degraded using an ozonolysis-based Advanced Oxidation Process. In the present study, the degraded products of the three dyes were analysed using GC-MS at endpoint strategy and further subjected to in silico toxicity analysis using Toxicity Estimation Software Tool (TEST), Prediction Of TOXicity of chemicals (ProTox-II), and Estimation Programs Interface Suite (EPI Suite). Several physiological toxicity endpoints, such as hepatotoxicity, carcinogenicity, mutagenicity, cellular and molecular interactions, were considered to assess the Quantitative Structure-Activity Relationships (QSAR) and adverse outcome pathways. The environmental fate of the by-products in terms of their biodegradability and possible bioaccumulation was also assessed. Results of ProTox-II suggested that the azo dye degradation products are carcinogenic, immunotoxic, and cytotoxic and displayed toxicity towards Androgen Receptor and Mitochondrial Membrane Potential. TEST results predicted LC50 and IGC50 values for three organisms Tetrahymena pyriformis, Daphnia magna, and Pimephales promelas. EPISUITE software via the BCFBAF module surmises that the degradation products' bioaccumulation (BAF) and bioconcentration factors (BCF) are high. The cumulative inference of the results suggests that most degradation by-products are toxic and need further remediation strategies. The study aims to complement existing tests to predict toxicity and prioritise the elimination/reduction of harmful degradation products of primary treatment procedures. The novelty of this study is that it streamlines in silico approaches to predict the nature of toxicity of degradation by-products of toxic industrial affluents like azo dyes. These approaches can assist the first phase of toxicology assessments for any pollutant for regulatory decision-making bodies to chalk out appropriate action plans for their remediation.

New Evidence on BPA's Role in Adipose Tissue Development of Proinflammatory Processes and Its Relationship with Obesity

Bisphenol A (BPA) is a xenobiotic with endocrine disruptor properties which interacts with various receptors, eliciting a cellular response. In the plastic industry, BPA is widely used in the production of polycarbonate and epoxy-phenolic resins to provide elastic properties. It can be found in the lining of canned foods, certain plastic containers, thermal printing papers, composite dental fillings, and medical devices, among other things. Therefore, it is a compound that, directly or indirectly, is in daily contact with the human organism. BPA is postulated to be a factor responsible for the global epidemic of obesity and non-communicable chronic diseases, belonging to the obesogenic and diabetogenic group of compounds. Hence, this endocrine disruptor may be responsible for the development of metabolic disorders, promoting in fat cells an increase in proinflammatory pathways and upregulating the expression and release of certain cytokines, such as IL6, IL1β, and TNFα. These, in turn, at a systemic and local level, are associated with a chronic low-grade inflammatory state, which allows the perpetuation of the typical physiological complications of obesity.

Mechanism-Driven and Clinically Focused Development of Botanical Foods as Multitarget Anticancer Medicine: Collective Perspectives and Insights from Preclinical Studies, IND Applications and Early-Phase Clinical Trials

Cancer progression and mortality remain challenging because of current obstacles and limitations in cancer treatment. Continuous efforts are being made to explore complementary and alternative approaches to alleviate the suffering of cancer patients. Epidemiological and nutritional studies have indicated that consuming botanical foods is linked to a lower risk of cancer incidence and/or improved cancer prognosis after diagnosis. From these observations, a variety of preclinical and clinical studies have been carried out to evaluate the potential of botanical food products as anticancer medicines. Unfortunately, many investigations have been poorly designed, and encouraging preclinical results have not been translated into clinical success. Botanical products contain a wide variety of chemicals, making them more difficult to study than traditional drugs. In this review, with the consideration of the regulatory framework of the USFDA, we share our collective experiences and lessons learned from 20 years of defining anticancer foods, focusing on the critical aspects of preclinical studies that are required for an IND application, as well as the checkpoints needed for early-phase clinical trials. We recommend a developmental pipeline that is based on mechanisms and clinical considerations.

Effects of central nervous system drugs on androgen, estrogen α, glucocorticoid, and thyroid receptors

Some drugs that act on the central nervous system (CNS) are known to affect the endocrine system, although the mechanisms of endocrine toxicity are not well characterized to date. Such CNS drugs include antipsychotics, anticonvulsants, and antidepressants. In the present study, in-vitro firefly luciferase reporter-gene assays using the AR-EcoScreen assay using Chinese hamster ovary (CHO) cell line, hERα-HeLa9903, MDA-kb2, and GH3.TRE-Luc cell lines were used to determine the effects of nine CNS drugs on the androgen receptor, estrogen receptor α, glucocorticoid receptor, and thyroid hormone receptor, respectively. In the AR-EcoScreen assay using CHO cells, anti-androgenic activities were shown for carbamazepine (IC₅₀, 167 μM), clonazepam (IC₅₀, 26.7 μM), eslicarbazepine acetate (IC₅₀, 375 μM), fluoxetine (at 25 μM), lorazepam (IC₅₀, 16.4 μM), and sertraline (IC₅₀, 8.7 μM). In the hERα-HeLa-9903 cells, estrogen receptor α agonistic activities were shown for fluoxetine, paroxetine, and sertraline (at 10 μM and 25 μM), and in the GH3.TRE-Luc cells, the same three CNS drugs showed antithyroid activities (IC₅₀s, 11.6, 11.9, 2.7 μM, respectively). In the hERα-HeLa-9903 cells, estrogen receptor α antagonistic activities were shown for carbamazepine (IC₅₀, 114.3 μM), clonazepam (IC₅₀, 52.9 μM), and eslicarbazepine acetate (IC₅₀, 376.6 μM). When the CNS drugs were tested in the MDA-kb2 cells, none of them showed any activities toward glucocorticoid receptors. Little to no effects were seen toward any of these nuclear receptors for paliperidone and risperidone. The increased signal in the estrogen receptor α agonism assay seen for fluoxetine and paroxetine was confirmed to be mediated through estrogen receptor α. Additionally, we examined the interference of these CNS drugs with the firefly luciferase enzyme. These data elucidate the potential for adverse endocrine effects for some of these CNS drugs, which should therefore contribute to informed choice when prescribing them. However, long-term exposure to therapeutic concentrations of CNS drugs that have activities on the endocrine system should be explored further also in vivo.

A Fluorometric CYP19A1 (Aromatase) Activity Assay in Live Cells

Inhibition of estrogen synthesis is an integral component of the frontline pharmacologic therapy for the treatment of estrogen receptor positive cancers. However, there is currently no direct, high-throughput-ready assay for aromatase (also known as CYP19A1) that can be performed in live cells. Herein we present a cell-based assay that allows for multiplexed assessment of enzyme activity, protein half-life, cell viability, and identification of inhibitors with slow off-rates.

A Gene Expression Biomarker Identifies Chemical Modulators of Estrogen Receptor α in an MCF-7 Microarray Compendium

Identification of chemicals that affect hormone-regulated systems will help to predict endocrine disruption. In our previous study, a 46 gene biomarker was found to be an accurate predictor of estrogen receptor (ER) α modulation in chemically treated MCF-7 cells. Here, potential ERα modulators were identified using the biomarker by screening a microarray compendium consisting of ∼1600 gene expression comparisons representing exposure to ∼1200 chemicals. A total of ∼170 chemicals were identified as potential ERα modulators. In the Connectivity Map 2.0 collection, 75 and 39 chemicals were predicted to activate or suppress ERα, and they included 12 and six known ERα agonists and antagonists/selective ERα modulators, respectively. Nineteen and eight of the total number were also identified as active in an ERα transactivation assay carried out in an MCF-7-derived cell line used to screen the Tox21 10K chemical library in agonist or antagonist modes, respectively. Chemicals predicted to modulate ERα in MCF-7 cells were examined further using global and targeted gene expression in wild-type and ERα-null cells, transactivation assays, and cell-free ERα coregulator interaction assays. Environmental chemicals classified as weak and very weak agonists were confirmed to activate ERα including apigenin, kaempferol, and oxybenzone. Novel activators included digoxin, nabumetone, ivermectin, and six progestins. Novel suppressors included emetine, mifepristone, niclosamide, and proscillaridin. Our strategy will be useful to identify environmentally relevant ERα modulators in future high-throughput transcriptomic screens.

Paroxetine-Overview of the Molecular Mechanisms of Action

In the 21st century and especially during a pandemic, the diagnosis and treatment of depression is an essential part of the daily practice of many family doctors. It mainly affects patients in the age category 15–44 years, regardless of gender. Anxiety disorders are often diagnosed in children and adolescents. Social phobias can account for up to 13% of these diagnoses. Social anxiety manifests itself in fear of negative social assessment and humiliation, which disrupts the quality of social functioning. Treatment of the above-mentioned disorders is based on psychotherapy and pharmacotherapy. Serious side effects or mortality from antidepressant drug overdose are currently rare. Recent studies indicate that paroxetine (ATC code: N06AB), belonging to the selective serotonin reuptake inhibitors, has promising therapeutic effects and is used off-label in children and adolescents. The purpose of this review is to describe the interaction of paroxetine with several molecular targets in various points of view including the basic chemical and pharmaceutical properties. The central point of the review is focused on the pharmacodynamic analysis based on the molecular mechanism of binding paroxetine to various therapeutic targets.

Comparing Machine Learning Models for Aromatase (P450 19A1)

Aromatase, or cytochrome P450 19A1, catalyzes the aromatization of androgens to estrogens within the body. Changes in the activity of this enzyme can produce hormonal imbalances that can be detrimental to sexual and skeletal development. Inhibition of this enzyme can occur with drugs and natural products as well as environmental chemicals. Therefore, predicting potential endocrine disruption via exogenous chemicals requires that aromatase inhibition be considered in addition to androgen and estrogen pathway interference. Bayesian machine learning methods can be used for prospective prediction from the molecular structure without the need for experimental data. Herein, the generation and evaluation of multiple machine learning models utilizing different sources of aromatase inhibition data are described. These models are applied to two test sets for external validation with molecules relevant to drug discovery from the public domain. In addition, the performance of multiple machine learning algorithms was evaluated by comparing internal five-fold cross-validation statistics of the training data. These methods to predict aromatase inhibition from molecular structure, when used in concert with estrogen and androgen machine learning models, allow for a more holistic assessment of endocrine-disrupting potential of chemicals with limited empirical data and enable the reduction of the use of hazardous substances.

Comparison of Machine Learning Models for the Androgen Receptor

The androgen receptor (AR) is a target of interest for endocrine disruption research, as altered signaling can affect normal reproductive and neurological development for generations. In an effort to prioritize compounds with alternative methodologies, the U.S. Environmental Protection Agency (EPA) used in vitro data from 11 assays to construct models of AR agonist and antagonist signaling pathways. While these EPA ToxCast AR models require in vitro data to assign a bioactivity score, Bayesian machine learning methods can be used for prospective prediction from molecule structure alone. This approach was applied to multiple types of data corresponding to the EPA's AR signaling pathway with proprietary software, Assay Central. The training performance of all machine learning models, including six other algorithms, was evaluated by internal 5-fold cross-validation statistics. Bayesian machine learning models were also evaluated with external predictions of reference chemicals to compare prediction accuracies to published results from the EPA. The machine learning model group selected for further studies of endocrine disruption consisted of continuous AC50 data from the February 2019 release of ToxCast/Tox21. These efforts demonstrate how machine learning can be used to predict AR-mediated bioactivity and can also be applied to other targets of endocrine disruption.

Molecular Mechanisms of Polybrominated Diphenyl Ethers (BDE-47, BDE-100, and BDE-153) in Human Breast Cancer Cells and Patient-Derived Xenografts

Polybrominated diphenyl ethers (PBDEs) have been used as flame retardants in household materials. Their environmental persistence has led to continuous human exposure and significant tissue levels. Three PBDE congeners (BDE-47, BDE-100, and BDE-153) have been frequently detected in human serum. Although these compounds appear to possess endocrine disrupting activity, studies are largely missing to determine the biological mechanisms of PBDEs in breast cancer cells. Here, we assessed PBDE bioactivities with three complementary strategies: receptor binding/activity assays; nonbiased RNA-sequencing analysis using an estrogen-dependent breast cancer cell line MCF-7aroERE; and in vivo assessments using patient-derived xenograft (PDX) models of human breast cancer. According to the results from in vitro experiments, the PBDE congeners regulate distinct nuclear receptor signaling pathways. BDE-47 acts as a weak agonist of both estrogen receptor α (ERα) and estrogen-related receptor α (ERRα); it could stimulate proliferation of MCF-7aroERE and induced expression of ER-regulated genes (including cell cycle genes). BDE-153 was found to act as a weak antagonist of ERα. BDE-100 could act as (1) an agonist of aryl hydrocarbon receptor (AhR), inducing expression of CYP1A1 and CYP1B1 and (2) as a very weak agonist/antagonist of ERα. In vivo, a mixture of the three congeners with ratios detected in human serum was tested in an ER+ PDX model. The mixture exhibited estrogenic activity through apoptosis/cell cycle regulation and increased the expression of a proliferation marker, Ki-67. These results advance our understanding of the mechanisms of PBDE exposure in breast cancer cells.

Computational Study of Drugs Targeting Nuclear Receptors

Endocrine-disrupting chemicals have been shown to interfere with the endocrine system function at the level of hormone synthesis, transport, metabolism, binding, action, and elimination. They are associated with several health problems in humans: obesity, diabetes mellitus, infertility, impaired thyroid and neuroendocrine functions, neurodevelopmental problems, and cancer are among them. As drugs are chemicals humans can be frequently exposed to for longer periods of time, special emphasis should be put on their endocrine-disrupting potential. In this study, we conducted a screen of 1046 US-approved and marketed small-molecule drugs (molecular weight between 60 and 600) for estimating their endocrine-disrupting properties. Binding affinity to 12 nuclear receptors was assessed with a molecular-docking program, Endocrine Disruptome. We identified 130 drugs with a high binding affinity to a nuclear receptor that is not their pharmacological target. In a subset of drugs with predicted high binding affinities to a nuclear receptor with Endocrine Disruptome, the positive predictive value was 0.66 when evaluated with in silico results obtained with another molecular docking program, VirtualToxLab, and 0.32 when evaluated with in vitro results from the Tox21 database. Computational screening was proven useful in prioritizing drugs for in vitro testing. We suggest that the novel interactions of drugs with nuclear receptors predicted here are further investigated.

Towards a Treatment for Gulf War Illness: A Consensus Docking Approach

Introduction

Gulf War Illness (GWI) currently has no known cure and affects soldiers deployed during the Persian Gulf War. It is thought to originate from exposure to neurotoxicants combined with battlefield stress, and previous research indicates that treatment first involves inhibition of interleukin-2 and tumor necrosis factor alpha, followed by the glucocorticoid receptor. However, the off-target effects of pharmaceuticals hinder development of a drug treatment therapy.

Materials and Methods

AutoDock 4.2, AutoDock Vina, and Schrodinger’s Glide were used to perform consensus docking, a computational technique where pharmaceuticals are screened against targets using multiple scoring algorithms to obtain consistent binding affinities. FDA approved pharmaceuticals were docked against the above-mentioned immune and stress targets to determine a drug therapy for GWI. Additionally, the androgen and estrogen targets were screened to avoid pharmaceuticals with off-target interactions.

Results

While suramin bound to both immune targets with high affinity, top binders of the hormonal and glucocorticoid targets were non-specific towards their respective proteins, possibly due to high structure similarity between these proteins.

Conclusions

Development of a drug treatment therapy for GWI is threatened by the tight interplay between the immune and hormonal systems, often leading to drug interactions. Increasing knowledge of these interactions can lead to break-through therapies.

Development of a prioritization method for chemical-mediated effects on steroidogenesis using an integrated statistical analysis of high-throughput H295R data

Synthesis of 11 steroid hormones in human adrenocortical carcinoma cells (H295R) was measured in a high-throughput steroidogenesis assay (HT-H295R) for 656 chemicals in concentration-response as part of the US Environmental Protection Agency's ToxCast program. This work extends previous analysis of the HT-H295R dataset and model by examining the utility of a novel prioritization metric based on the Mahalanobis distance that reduced these 11-dimensional data to 1-dimension via calculation of a mean Mahalanobis distance (mMd) at each chemical concentration screened for all hormone measures available. Herein, we evaluated the robustness of mMd values, and demonstrate that covariance and variance of the hormones measured appear independent of the chemicals screened and are inherent to the assay; the Type I error rate of the mMd method is less than 1%; and, absolute fold changes (up or down) of 1.5 to 2-fold have sufficient power for statistical significance. As a case study, we examined hormone responses for aromatase inhibitors in the HT-H295R assay and found high concordance with other ToxCast assays for known aromatase inhibitors. Finally, we used mMd and other ToxCast cytotoxicity data to demonstrate prioritization of the most selective and active chemicals as candidates for further in vitro or in silico screening.

Environmental exposures during windows of susceptibility for breast cancer: a framework for prevention research

Background

The long time from exposure to potentially harmful chemicals until breast cancer occurrence poses challenges for designing etiologic studies and for implementing successful prevention programs. Growing evidence from animal and human studies indicates that distinct time periods of heightened susceptibility to endocrine disruptors exist throughout the life course. The influence of environmental chemicals on breast cancer risk may be greater during several windows of susceptibility (WOS) in a woman’s life, including prenatal development, puberty, pregnancy, and the menopausal transition. These time windows are considered as specific periods of susceptibility for breast cancer because significant structural and functional changes occur in the mammary gland, as well as alterations in the mammary micro-environment and hormone signaling that may influence risk. Breast cancer research focused on these breast cancer WOS will accelerate understanding of disease etiology and prevention.

Main text

Despite the plausible heightened mechanistic influences of environmental chemicals on breast cancer risk during time periods of change in the mammary gland’s structure and function, most human studies of environmental chemicals are not focused on specific WOS. This article reviews studies conducted over the past few decades that have specifically addressed the effect of environmental chemicals and metals on breast cancer risk during at least one of these WOS. In addition to summarizing the broader evidence-base specific to WOS, we include discussion of the NIH-funded Breast Cancer and the Environment Research Program (BCERP) which included population-based and basic science research focused on specific WOS to evaluate associations between breast cancer risk and particular classes of endocrine-disrupting chemicals—including polycyclic aromatic hydrocarbons, perfluorinated compounds, polybrominated diphenyl ethers, and phenols—and metals. We outline ways in which ongoing transdisciplinary BCERP projects incorporate animal research and human epidemiologic studies in close partnership with community organizations and communication scientists to identify research priorities and effectively translate evidence-based findings to the public and policy makers.

Conclusions

An integrative model of breast cancer research is needed to determine the impact and mechanisms of action of endocrine disruptors at different WOS. By focusing on environmental chemical exposure during specific WOS, scientists and their community partners may identify when prevention efforts are likely to be most effective.

A plurality of molecular targets: The receptor ecosystem for bisphenol-A (BPA)

Bisphenol-A (BPA) is a well-known endocrine disrupting compound (EDC), capable of affecting the normal function and development of the reproductive system, brain, adipose tissue, and more. In spite of these diverse and well characterized effects, there is often comparatively little known about the molecular mechanisms which bring them about. BPA has traditionally been regarded as a primarily estrogenic EDC, and this perspective is often what guides research into the effects of BPA. However, emerging data from in-vitro and in-silico models show that BPA binds with a significant number of hormone receptors, including a number of nuclear and membrane-bound estrogen receptors, androgen receptors, as well as the thyroid hormone receptor, glucocorticoid receptor, and PPARγ. With this increased diversity of receptor targets, it may be possible to explain some of the more puzzling aspects of BPA pharmacology, including its non-monotonic dose-response curve, as well as experimental results which disagree with estrogenic positive controls. This paper reviews the receptors for which BPA has a known interaction, and discusses the implications of taking these receptors into account when studying the disruptive effects of BPA on growth and development.

Carcinogenic risk and Bisphenol A exposure: A focus on molecular aspects in endoderm derived glands

Epidemiological and experimental evidence associates the exposure to Bisphenol A with the increase of cancer risk in several organs, including prostate. BPA targets different pathways involved in carcinogenicity including the Nuclear Receptors (i.e. estrogen and androgen receptors), stress regulated proteins and, finally, epigenetic changes. Here, we analyse BPA-dependent carcinogenesis in endoderm-derived glands, thyroid, liver, pancreas and prostate focusing on cell signalling, DNA damage repair pathways and epigenetic modifications. Mainly, we gather molecular data evidencing harmful effects at doses relevant for human risk (low-doses). Since few molecular data are available, above all for the pancreas, we analysed transcriptomic data generated in our laboratory to suggest possible mechanisms of BPA carcinogenicity in endoderm-derived glands, discussing the role of nuclear receptors and stress/NF-kB pathways. We evidence that an in vitro toxicogenomic approach might suggest mechanisms of toxicity applicable to cells having the same developmental origin. Although we cannot draw firm conclusions, published data summarized in this review suggest that exposure to BPA, primarily during the developmental stages, represents a risk for carcinogenesis of endoderm-derived glands.

Serum Testosterone Concentrations and Urinary Bisphenol A, Benzophenone-3, Triclosan, and Paraben Levels in Male and Female Children and Adolescents: NHANES 2011-2012

BACKGROUND

Exposure to environmental phenols (e.g., bisphenol A, benzophenone-3, and triclosan) and parabens is widespread in the population. Many of these chemicals have been shown to have anti-androgenic effects both in vitro and in vivo.

OBJECTIVE

We examined the association of bisphenol A (BPA), benzophenone-3 (BP-3), triclosan (TCS), and parabens with serum total testosterone (TT) levels in child and adolescent participants (ages 6-19 years) in the National Health and Nutrition Examination Survey (NHANES) 2011-2012.

METHODS

We performed multivariable linear regression to estimate associations between natural log-transformed serum TT and quartiles of urinary BPA, BP-3, TCS, and parabens in male and female children (ages 6-11 years) and adolescents (ages 12-19 years).

RESULTS

BP-3 and BPA were associated with significantly lower TT in male adolescents, and BPA was associated with significantly higher TT in female adolescents. TT was not consistently associated with TCS or total parabens in children or adolescents of either sex.

CONCLUSIONS

To our knowledge, this is the first study to report an association of both BP-3 and BPA with serum TT in adolescents. Associations between BPA and TT differed according to sex in adolescents, with inverse associations in boys and positive associations in girls. BP-3 was associated with significantly lower TT in adolescent boys only. However, because of the limitations inherent to the cross-sectional study design, further studies are needed to confirm and elucidate on our findings. Citation: Scinicariello F, Buser MC. 2016. Serum testosterone concentrations and urinary bisphenol A, benzophenone-3, triclosan, and paraben levels in male and female children and adolescents: NHANES 2011-2012. Environ Health Perspect 124:1898-1904; http://dx.doi.org/10.1289/EHP150.

Paroxetine-The Antidepressant from Hell? Probably Not, But Caution Required

Paroxetine, also known by the trade names Aropax, Paxil, Pexeva, Seroxat, Sereupin and Brisdelle, was first marketed in the U.S. in 1992. Effective for major depression and various anxiety disorders, it quickly gained a sizable share of the antidepressant prescription market. By the late 1990s, paroxetine frequently was being associated with serious drug interactions and medication side effects. Most significantly, in a major Canadian epidemiological study examining the relationship between antidepressants and diseases, paroxetine was associated with a 620 percent increase in the rate of breast cancer in women who had taken it over a four-year period. Though re-analyses of this investigation discounted the magnitude of these findings, other studies have associated paroxetine with numerous side effects and adverse events not reported in clinical trials. Among these are effects on male fertility, birth defects, gestational hypertension, prolonged QT interval in infants, hyperprolactinemia, cognitive impairment in the elderly, autism, sexual side effects, weight gain, and suicidality, aggression, and akathisia in children and adolescents. Paroxetine has the highest inhibitory constant for the P450 2D6 isoenzyme of all antidepressants (Ki = 0.065-4.65 micromoles). This high affinity explains its high inhibitory interaction profile with substrates for 2D6. Paroxetine's potent 2D6 inhibition also implies that significant inhibition of the metabolism of 2D6 carcinogen substrates occurs which implies an increased probability of oncogenesis. Through 2D6 inhibition, tamoxifen metabolism is inhibited, which has been found to increase the risk of dying from breast cancer over a five-year period in women on both medications. Paroxetine also is a potent inhibitor of 3A4 with multiple 3A4 substrate interactions. Paroxetine has the highest known affinity for the serotonin transporter (0.13 nanomoles) of any currently used antidepressant. These characteristics and their potential negative consequences along with other adverse effects are considered and weighed against paroxetine's efficacious antidepressant and anxiolytic effects.

Moving Toward Integrating Gene Expression Profiling Into High-Throughput Testing: A Gene Expression Biomarker Accurately Predicts Estrogen Receptor α Modulation in a Microarray Compendium

Microarray profiling of chemical-induced effects is being increasingly used in medium- and high-throughput formats. Computational methods are described here to identify molecular targets from whole-genome microarray data using as an example the estrogen receptor α (ERα), often modulated by potential endocrine disrupting chemicals. ERα biomarker genes were identified by their consistent expression after exposure to 7 structurally diverse ERα agonists and 3 ERα antagonists in ERα-positive MCF-7 cells. Most of the biomarker genes were shown to be directly regulated by ERα as determined by ESR1 gene knockdown using siRNA as well as through chromatin immunoprecipitation coupled with DNA sequencing analysis of ERα-DNA interactions. The biomarker was evaluated as a predictive tool using the fold-change rank-based Running Fisher algorithm by comparison to annotated gene expression datasets from experiments using MCF-7 cells, including those evaluating the transcriptional effects of hormones and chemicals. Using 141 comparisons from chemical- and hormone-treated cells, the biomarker gave a balanced accuracy for prediction of ERα activation or suppression of 94% and 93%, respectively. The biomarker was able to correctly classify 18 out of 21 (86%) ER reference chemicals including "very weak" agonists. Importantly, the biomarker predictions accurately replicated predictions based on 18 in vitro high-throughput screening assays that queried different steps in ERα signaling. For 114 chemicals, the balanced accuracies were 95% and 98% for activation or suppression, respectively. These results demonstrate that the ERα gene expression biomarker can accurately identify ERα modulators in large collections of microarray data derived from MCF-7 cells.

Cell-Based High-Throughput Screening for Aromatase Inhibitors in the Tox21 10K Library

Multiple mechanisms exist for endocrine disruption; one nonreceptor-mediated mechanism is via effects on aromatase, an enzyme critical for maintaining the normal in vivo balance of androgens and estrogens. We adapted the AroER tri-screen 96-well assay to 1536-well format to identify potential aromatase inhibitors (AIs) in the U.S. Tox21 10K compound library. In this assay, screening with compound alone identifies estrogen receptor alpha (ERα) agonists, screening in the presence of testosterone (T) identifies AIs and/or ERα antagonists, and screening in the presence of 17β-estradiol (E2) identifies ERα antagonists. Screening the Tox-21 library in the presence of T resulted in finding 302 potential AIs. These compounds, along with 31 known AI actives and inactives, were rescreened using all 3 assay formats. Of the 333 compounds tested, 113 (34%; 63 actives, 50 marginal actives) were considered to be potential AIs independent of cytotoxicity and ER antagonism activity. Structure-activity analysis suggested the presence of both conventional (eg, 1, 2, 4, - triazole class) and novel AI structures. Due to their novel structures, 14 of the 63 potential AI actives, including both drugs and fungicides, were selected for confirmation in the biochemical tritiated water-release aromatase assay. Ten compounds were active in the assay; the remaining 4 were only active in high-throughput screen assay, but with low efficacy. To further characterize these 10 novel AIs, we investigated their binding characteristics. The AroER tri-screen, in high-throughput format, accurately and efficiently identified chemicals in a large and diverse chemical library that selectively interact with aromatase.

AroER tri-screen™ is a novel functional assay to estimate both estrogenic and estrogen precursor activity of chemicals or biological specimens

The purpose of the study is to define AroER tri-screen's utility for identifying endocrine-disrupting chemicals (EDCs) that target aromatase and/or estrogen receptor (ER), and to measure the total estrogenic activity in biological specimens. ER-positive, aromatase-expressing MCF-7 breast cancer cells were stably transfected with an estrogen responsive element (ERE)-driven luciferase reporter plasmid to yield a new high-throughput screening platform-the AroER tri-screen. AroER tri-screen was capable of identifying estrogen precursors, such as cortodoxone, which function as estrogens through a two-step conversion process in aromatase-expressing tissue. Furthermore, the system proved useful for assessing EDC activity in biologically relevant samples. Estimating these activities is critical because natural estrogens and estrogenic EDCs are important factors in ER-positive breast cancer risk. As our research demonstrates, incorporating functionally active aromatase into the AroER tri-screen produces a powerful and unique tool to (1) identify new EDCs targeting aromatase and/or ER; (2) discover novel EDCs activated by aromatase; and (3) estimate overall estrogenic activities in biological samples as a potential intermediate risk factor for breast cancer.