The objectives of this work were to: 1) develop an integrated analysis of chemical-mediated effects on steroidogenesis in the HT-H295R assay; and, 2) evaluate whether the HT-H295R assay predicts estrogen and androgen production specifically via comparison with the OECD-validated H295R assay. This dataset is associated with the following publication: Haggard, D., A. Karmaus, M. Martin, R. Judson, W. Setzer, and K. Paul-Friedman. (Toxicological Sciences) High-throughput H295R steroidogenesis assay: utility as an alternative and a statistical approach to characterize effects on steroidogenesis. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 162(2): 509-534, (2018).

HT-H295R data was downloaded using the ToxCast pipeline (tcpl) R package and is publicly available. Multi-concentration level 0 data from invitrodb (version 3.1) were downloaded and converted from g/ml into micromolar concentrations prior to calculation of mMds and data simulation (Supplemental Data 1). This dataset is associated with the following publication: Haggard, D., W. Setzer, R. Judson, and K. Friedman. Development of a prioritization method for chemical-mediated effects on steroidogenesis using an integrated statistical analysis of high-throughput H295R data. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 109: 104510, (2019).

Disruption of steroidogenesis by environmental chemicals can result in altered hormone levels causing adverse reproductive and developmental effects. A high-throughput assay using H295R human adrenocortical carcinoma cells was used to evaluate the effect of 2060 chemical samples on steroidogenesis via high-performance liquid chromatography followed by tandem mass spectrometry quantification of 10 steroid hormones, including progestagens, glucocorticoids, androgens, and estrogens. The study employed a 3 stage screening strategy. The first stage established the maximum tolerated concentration (MTC; ≥ 70% viability) per sample. The second stage quantified changes in hormone levels at the MTC whereas the third stage performed concentration-response (CR) on a subset of samples. At all stages, cells were prestimulated with 10 µM forskolin for 48 h to induce steroidogenesis followed by chemical treatment for 48 h. Of the 2060 chemical samples evaluated, 524 samples were selected for 6-point CR screening, based in part on significantly altering at least 4 hormones at the MTC. CR screening identified 232 chemical samples with concentration-dependent effects on 17β-estradiol and/or testosterone, with 411 chemical samples showing an effect on at least one hormone across the steroidogenesis pathway. Clustering of the concentration-dependent chemical-mediated steroid hormone effects grouped chemical samples into 5 distinct profiles generally representing putative mechanisms of action, including CYP17A1 and HSD3B inhibition. A distinct pattern was observed between imidazole and triazole fungicides suggesting potentially distinct mechanisms of action. From a chemical testing and prioritization perspective, this assay platform provides a robust model for high-throughput screening of chemicals for effects on steroidogenesis. This dataset is associated with the following publication: Karmaus , A., C. Toole, D. Filer , K. Lewis, and M. Martin. (Toxicological Sciences) High-throughput screening of chemical effects on steroidogenesis using H295R human adrenocortical carcinoma cells. TOXICOLOGICAL SCIENCES. Society of Toxicology, 150(2): 323-332, (2016).

Dataset for 'Evaluation of a high-throughput H295R homogenous time resolved fluorescence assay for androgen and estrogen steroidogenesis screening', Garnovskaya, et al., Toxicology in Vitro, Vol 92, 105659, Oct 2023, https://doi.org/10.1016/j.tiv.2023.105659. Contains the ToxCast Pipeline datasets and curve fits that can be pulled up from InvitroDB on the CompTox Chemicals Dashboard. This dataset is associated with the following publication: Garnovskaya, M., M. Feshuk, W. Stewart, K. Friedman, R. Thomas, and C. Deisenroth. Evaluation of a High-throughput H295R Homogenous Time Resolved Fluorescence Assay for Androgen and Estrogen Steroidogenesis Screening. TOXICOLOGY IN VITRO. Elsevier Science Ltd, New York, NY, USA, 92: 105659, (2023).

Dataset from Foster, M.J., et al., Evaluating structure-based activity in a high-throughput assay for steroid biosynthesis, Computational Toxicology, Vol 24, No. 100245, Nov 2022, DOI https://doi.org/10.1016/j.comtox.2022.100245 The work described herein was conducted in R software (version 4.0.2) and is available at GitHub (https://github.com/USEPA/CompTox-HTH295R-SAR) and the US EPA Clowder repository as well as in Supplemental File 1 as an html file including code and resultant output. This dataset is associated with the following publication: Foster, M., G. Patlewicz, I. Shah, D. Haggard, R. Judson, and K. Friedman. Evaluating structure-based activity in a high-throughput assay for steroid biosynthesis. Computational Toxicology. Elsevier B.V., Amsterdam, NETHERLANDS, 24: 100245, (2022).

The greater dynamic range of testosterone production in a highly purified rat Leydig cell assay permitted the detection of chemical induced inhibition that was not detected by the high throughput screening format of the H295R steroidogenesis assay. This dataset is associated with ORD-022468 entered in STICS. This dataset is associated with the following publication: Botteri Principato, N., J. Suarez, S. Laws, and G. Klinefelter. The Use of Purified Rat Leydig Cells Complements the H295R Screen to Detect Chemical Induced Alterations in Testosterone Production. BIOLOGY OF REPRODUCTION. Society for the Study of Reproduction, 98(2): 239-249, (2018).

The greater dynamic range of testosterone production in a highly purified rat Leydig cell assay permitted the detection of chemical induced inhibition that was not detected by the high throughput screening format of the H295R steroidogenesis assay. This dataset is associated with ORD-022468 entered in STICS. This dataset is associated with the following publication: Botteri Principato, N., J. Suarez, S. Laws, and G. Klinefelter. The Use of Purified Rat Leydig Cells Complements the H295R Screen to Detect Chemical Induced Alterations in Testosterone Production. BIOLOGY OF REPRODUCTION. Society for the Study of Reproduction, 98(2): 239-249, (2018).

Data on 1855 chemicals were generated during ToxCast Phases I and II and Tox21 screening using 11 AR-related in vitro assays to build a computational network model for AR pathway activity. This dataset is associated with the following publication: Kleinstreuer, N.C., P. Ceger, E. Watt, M. Martin, K. Houck, P. Browne, R. Thomas, W. Casey, D. Dix, D. Allen, S. Sakamuru, M. Xia, R. Huang, and R. Judson. (Chemical Research in Toxicology) Development and Validation of a Computational Model for Androgen Receptor Activity. CHEMICAL RESEARCH IN TOXICOLOGY. American Chemical Society, Washington, DC, USA, 30(4): 946-964, (2017).

Background Changes in breast density are highly correlated with steroid hormone exposure. Materials and methods In a cross-sectional study of 396 Caucasian and African-American women, we evaluated whether polymorphisms in genes involved in steroid hormone biosynthesis and metabolism, CYP17 (T27C), COMT (Val158Met), 17HSDB1 (Ser312Gly) and 3HSDB1 (Asn367Thr), predict mammographic density. We also evaluated whether associations vary by menopausal and hormone replacement therapy status. Results We found no strong consistent relationships between polymorphisms in these genes and breast density. African-American women homozygous for the Thr allele of 3HSDB1 had increased density (the absolute difference versus the Asn/Asn genotype was +19.7%; P trend = 0.02), while Caucasian homozygous women had decreased density (-5.1%; P trend = 0.04). Among premenopausal women, carriers of the Ser allele had (not significantly) greater density (versus Gly/Gly genotype: +7.1%; P trend = 0.07). In addition, among current users of hormone replacement therapy, we observed that women with the low-activity Met/Met genotype of COMT had greater breast density (versus the Val/Val genotype: +11.7%; P trend = 0.01). Conclusion Additional large studies evaluating these and other candidate breast cancer genes will be required to determine what proportion, if any, of the interindividual differences in breast density are due to underlying genetic variation in genes involved in steroid hormone biosynthesis or metabolism.

ToxCast bioactivity data and model predictions for the estrogen receptor (ER) and androgen receptor (AR) pathways were obtained from the inks provided. This dataset is associated with the following publication: Lizarraga, L., J. Dean, J. Kaiser, S. Wesselkamper, J. Lambert, and J. Zhao. A Case Study on the Application of An Expert-driven Read-Across Approach in Support of Quantitative Risk Assessment of p,p’-Dichlorodiphenyldichloroethane. REGULATORY TOXICOLOGY AND PHARMACOLOGY. Elsevier Science Ltd, New York, NY, USA, 103: 301-313, (2019).