This study, designed and conducted as part of the International Life Sciences Institute working group on the Application of Genomics and Proteomics, examined the changes in the expression profile of genes associated with the administration of three different nephrotoxicants--cisplatin, gentamicin, and puromycin--to assess the usefulness of microarrays in the understanding of mechanism(s) of nephrotoxicity. Male Sprague-Dawley rats were treated with daily doses of puromycin (5-20 mg/kg/day for 21 days), gentamicin (2-240 mg/kg/day for 7 days), or a single dose of cisplatin (0.1-5 mg/kg). Groups of rats were sacrificed at various times after administration of these compounds for standard clinical chemistry, urine analysis, and histological evaluation of the kidney. RNA was extracted from the kidney for microarray analysis. Principal component analysis and gene expression-based clustering of compound effects confirmed sample separation based on dose, time, and degree of renal toxicity. In addition, analysis of the profile components revealed some novel changes in the expression of genes that appeared to be associated with injury in specific portions of the nephron and reflected the mechanism of action of these various nephrotoxicants. For example, although puromycin is thought to specifically promote injury of the podocytes in the glomerulus, the changes in gene expression after chronic exposure of this compound suggested a pattern similar to the known proximal tubular nephrotoxicants cisplatin and gentamicin; this prediction was confirmed histologically. We conclude that renal gene expression profiling coupled with analysis of classical end points affords promising opportunities to reveal potential new mechanistic markers of renal toxicity.

Exposure to some compounds with estrogenic activity, during fetal development, has been shown to alter development of reproductive organs, leading to abnormal function and disease either after birth or during adulthood. In order to understand the molecular events associated with the estrogenicity of different chemicals and to determine whether common sets of gene expression changes can be predictive of estrogenic activity, we have used microarray technology to determine the transcriptional program influenced by exposure to this class of compounds during organogenesis and development. Changes in patterns of gene expression were determined in the developing uterus and ovaries of Sprague-Dawley rats on GD 20, exposed to graded dosages (sc) of 17alpha-ethynyl estradiol (EE), genistein, or bisphenol A (BPA) from GD 11 to GD 20. Dose levels were roughly equipotent in estrogenic activity. We compared the transcript profiles between treatment groups and controls, using oligonucleotide arrays to determine the expression level of approximately 7000 rat genes and over 1000 expressed squence tags (ESTs). At the highest tested doses of EE, BPA, or genistein, we determined that less than 2% of the mRNA detected by the array showed a 2-fold or greater change in their expression level (increase or decrease). A dose-dependent analysis of the transcript profile revealed a common set of genes whose expression is significantly and reproducibly modified in the same way by each of the 3 chemicals tested. Additionally, each compound induces changes in the expression of other transcripts that are not in common with the others, which indicated not all compounds with estrogenic activity act alike. The results of this study demonstrate that transplacental exposure to chemicals with estrogenic activity changes the gene expression profile of estrogen-sensitive tissues, and that the analysis of the transcript profile of these tissues could be a valuable approach to determining the estrogenicity of different compounds.

Developmental and reproductive toxicity (DART) end points are important hazard end points that need to be addressed in the risk assessment of chemicals to determine whether or not they are the critical effects in the overall risk assessment. These hazard end points are difficult to predict using current in silico tools because of the diversity of mechanisms of action that elicit DART effects and the potential for narrow windows of vulnerability. DART end points have been projected to consume the majority of animals used for compliance with REACH; thus, additional nonanimal predictive tools are urgently needed. This article presents an empirically based decision tree for determining whether or not a chemical has receptor-binding properties and structural features that are consistent with chemical structures known to have toxicity for DART end points. The decision tree is based on a detailed review of 716 chemicals (664 positive, 16 negative, and 36 with insufficient data) that have DART end-point data and are grouped into defined receptor binding and chemical domains. When tested against a group of chemicals not included in the training set, the decision tree is shown to identify a high percentage of chemicals with known DART effects. It is proposed that this decision tree could be used both as a component of a screening system to identify chemicals of potential concern and as a component of weight-of-evidence decisions based on structure-activity relationships (SAR) to fill data gaps without generating additional test data. In addition, the chemical groupings generated could be used as a starting point for the development of hypotheses for in vitro testing to elucidate mode of action and ultimately in the development of refined SAR principles for DART that incorporate mode of action (adverse outcome pathways).

SummaryGrouping of substances and utilizing read-across of data within those groups represents an important data gap filling technique for chemical safety assessments. Categories/analogue groups are typically developed based on structural similarity and, increasingly often, also on mechanistic (biological) similarity. While read-across can play a key role in complying with legislation such as the European REACH regulation, the lack of consensus regarding the extent and type of evidence necessary to support it often hampers its successful application and acceptance by regulatory authorities. Despite a potentially broad user community, expertise is still concentrated across a handful of organizations and individuals. In order to facilitate the effective use of read-across, this document presents the state of the art, summarizes insights learned from reviewing ECHA published decisions regarding the relative successes/pitfalls surrounding read-across under REACH, and compiles the relevant activities and guidance documents. Special emphasis is given to the available existing tools and approaches, an analysis of ECHA's published final decisions associated with all levels of compliance checks and testing proposals, the consideration and expression of uncertainty, the use of biological support data, and the impact of the ECHA Read-Across Assessment Framework (RAAF) published in 2015.

The profound effects of 17beta-estradiol on cell growth, differentiation, and general homeostasis of the reproductive and other systems, are mediated mostly by regulation of temporal and cell type-specific expression of different genes. In order to understand better the molecular events associated with the activation of the estrogen receptor (ER), we have used microarray technology to determine the transcriptional program and dose-response characteristics of exposure to a potent synthetic estrogen, 17 alpha-ethynyl estradiol (EE), during prepubertal development. Changes in patterns of gene expression were determined in the immature uterus and ovaries of Sprague-Dawley rats on postnatal day (PND) 24, 24 h after exposure to EE, at 0.001, 0.01, 0.1, 1 and 10 micro g EE/kg/day (sc), for four days (dosing from PND 20 to 23). The transcript profiles were compared between treatment groups and controls using oligonucleotide arrays to determine the expression level of approximately 7000 annotated rat genes and over 1740 expressed sequence tags (ESTs). Quantification of the number of genes whose expression was modified by the treatment, for each of the various doses of EE tested, showed clear evidence of a dose-dependent treatment effect that follows a monotonic response, concordant with the dose-response pattern of uterine wet-weight gain and luminal epithelial cell height. The number of genes whose expression is affected by EE exposure increases according to dose. At the highest dose tested of EE, we determined that the expression level of over 300 genes was modified significantly (p < or = 0.0001). A dose-dependent analysis of the transcript profile revealed a set of 88 genes whose expression is significantly and reproducibly modified (increased or decreased) by EE exposure (p < or = 0.0001). The results of this study demonstrate that, exposure to a potent estrogenic chemical during prepubertal maturation changes the gene expression profile of estrogen-sensitive tissues. Furthermore, the products of the EE-regulated genes identified in these tissues have a physiological role in different intracellular pathways, information that will be valuable to determine the mechanism of action of estrogens. Moreover, those genes could be used as biomarkers to identify chemicals with estrogenic activity.

The purpose of this study was to determine (1) the transcriptional program elicited by exposure to three estrogen receptor (ER) agonists: 17 alpha-ethynyl estradiol (EE), genistein (Ges), and bisphenol A (BPA) during fetal development of the rat testis and epididymis; and (2) whether very low dosages of estrogens (evaluated over five orders of magnitude of dosage) produce unexpected changes in gene expression (i.e., a non-monotonic dose-response curve). In three independently conducted experiments, Sprague-Dawley rats were dosed (sc) with 0.001-10 microg EE/kg/day, 0.001-100 mg Ges/kg/day, or 0.002-400 mg BPA/kg/day. While morphological changes in the developing reproductive system were not observed, the gene expression profile of target tissues were modified in a dose-responsive manner. Independent dose-response analyses of the three studies identified 59 genes that are significantly modified by EE, 23 genes by Ges, and 15 genes by BPA (out of 8740), by at least 1.5 fold (up- or down-regulated). Even more genes were observed to be significantly changed when only the high dose is compared with all lower doses: 141, 46, and 67 genes, respectively. Global analyses aimed at detecting genes consistently modified by all of the chemicals identified 50 genes whose expression changed in the same direction across the three chemicals. The dose-response curve for gene expression changes was monotonic for each chemical, with both the number of genes significantly changed and the magnitude of change, for each gene, decreasing with decreasing dose. Using the available annotation of the gene expression changes induced by ER-agonist, our data suggest that a variety of cellular pathways are affected by estrogen exposure. These results indicate that gene expression data are diagnostic of mode of action and, if they are evaluated in the context of traditional toxicological end-points, can be used to elucidate dose-response characteristics.

Connectivity mapping is a method used in the pharmaceutical industry to find connections between small molecules, disease states, and genes. The concept can be applied to a predictive toxicology paradigm to find connections between chemicals, adverse events, and genes. In order to assess the applicability of the technique for predictive toxicology purposes, we performed gene array experiments on 34 different chemicals: bisphenol A, genistein, ethinyl-estradiol, tamoxifen, clofibrate, dehydorepiandrosterone, troglitazone, diethylhexyl phthalate, flutamide, trenbolone, phenobarbital, retinoic acid, thyroxine, 1α,25-dihydroxyvitamin D3, clobetasol, farnesol, chenodeoxycholic acid, progesterone, RU486, ketoconazole, valproic acid, desferrioxamine, amoxicillin, 6-aminonicotinamide, metformin, phenformin, methotrexate, vinblastine, ANIT (1-naphthyl isothiocyanate), griseofulvin, nicotine, imidacloprid, vorinostat, 2,3,7,8-tetrachloro-dibenzo-p-dioxin (TCDD) at the 6-, 24-, and 48-hour time points for 3 different concentrations in the 4 cell lines: MCF7, Ishikawa, HepaRG, and HepG2 GEO (super series accession no.: GSE69851). The 34 chemicals were grouped in to predefined mode of action (MOA)-based chemical classes based on current literature. Connectivity mapping was used to find linkages between each chemical and between chemical classes. Cell line-specific linkages were compared with each other and to test whether the method was platform and user independent, a similar analysis was performed against publicly available data. The study showed that the method can group chemicals based on MOAs and the inter-chemical class comparison alluded to connections between MOAs that were not predefined. Comparison to the publicly available data showed that the method is user and platform independent. The results provide an example of an alternate data analysis process for high-content data, beneficial for predictive toxicology, especially when grouping chemicals for read across purposes.

Within the International Life Sciences Institute Committee on Genomics, a working group was formed to focus on the application of microarray technology to preclinical assessments of druginduced nephrotoxicity. As part of this effort, Sprague-Dawley rats were treated with the nephrotoxicant cisplatin at doses of 0.3-5 mg/kg over a 4-to 144-hr time course. RNA prepared from these animals was run on a variety of microarray formats at multiple sites. A set of 93 differentially expressed genes associated with cisplatin-induced renal injury was identified on the National Institute of Environmental Health Sciences (NIEHS) custom cDNA microarray platform using quadruplicate measurements of pooled animal RNA. The reproducibility of this profile of statistically significant gene changes on other platforms, in pooled and individual animal replicate samples, and in an independent study was investigated. A good correlation in response between platforms was found among the 48 genes in the NIEHS data set that could be matched to probes on the Affymetrix RGU34A array by UniGene identifier or sequence alignment. Similar results were obtained with genes that could be linked between the NIEHS and Incyte or PHASE-1 arrays. The degree of renal damage induced by cisplatin in individual animals was commensurate with the number of differentially expressed genes in this data set. These results suggest that gene profiles linked to specific types of tissue injury or mechanisms of toxicity and identified in wellperformed replicated microarray experiments may be extrapolatable across platform technologies, laboratories, and in-life studies.