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Interpretation of positive genotoxicity findings using the current in vitro testing battery is a major challenge to industry and regulatory agencies. These tests, especially mammalian cell assays, have high sensitivity but suffer from low specificity, leading to high rates of irrelevant positive findings (i.e., positive results in vitro that are not relevant to human cancer hazard). We developed an in vitro transcriptomic biomarker-based approach that provides biological relevance to positive genotoxicity assay data, particularly for in vitro chromosome damage assays and propose its application for assessing the relevance of the in vitro positive results to carcinogenic hazard. The transcriptomic biomarker TGx-DDI (previously known as TGx-28.65) readily distinguishes DNA damage-inducing (DDI) agents from non-DDI agents. In this study, we demonstrated the ability of the biomarker to classify 45 test agents across a broad set of chemical classes as DDI or non-DDI. Furthermore, we assessed the biomarker's utility in derisking known irrelevant positive agents and evaluated its performance across analytical platforms. We correctly classified 90% (9 of 10) of chemicals with irrelevant positive findings in in vitro chromosome damage assays as negative. We developed a standardized experimental and analytical protocol for our transcriptomics biomarker, as well as an enhanced application of TGx-DDI for high-throughput cell-based genotoxicity testing using nCounter technology. This biomarker can be integrated in genetic hazard assessment as a follow-up to positive chromosome damage findings. In addition, we propose how it might be used in chemical screening and assessment. This approach offers an opportunity to significantly improve risk assessment and reduce cost. [ABSTRACT FROM AUTHOR]

Estrogen plays an important role in the regulation of vascular tone and in the pathophysiology of cardiovascular disease. Physiological effects of estrogen are mediated through estrogen receptors alpha (ERalpha) and beta (ERbeta), which are both expressed in vascular smooth muscle and endothelial cells. However, the molecular pathways mediating estrogen effects in blood vessels are not well defined. We have performed gene expression profiling in the mouse aorta to identify comprehensive gene sets the expression of which is regulated by long-term (1 wk) estrogen treatment. The ER subtype dependence of the alterations in gene expression was characterized by parallel gene expression profiling experiments in ERalpha-deficient [ERalpha knockout (ERalphaKO)] and ERbeta-deficient (ERbetaKO) mice. Importantly, these data revealed that ERalpha- and ERbeta-dependent pathways regulate distinct and largely nonoverlapping sets of genes. Whereas ERalpha is essential for most of the estrogen-mediated increase in gene expression in wild-type aortas, ERbeta mediates the large majority (nearly 90%) of estrogen-mediated decreases in gene expression. Biological functions of the estrogen-regulated genes include extracellular matrix synthesis, in addition to electron transport in the mitochondrion and reactive oxygen species pathways. Of note, the estrogen/ERbeta pathway mediates down-regulation of mRNAs for nuclear-encoded subunits in each of the major complexes of the mitochondrial respiratory chain. Several estrogen-regulated genes also encode transcription factors. Computational analysis of promoters from coexpressed genes revealed overrepresentation of binding sites for such factors, lending support for an estrogen-regulatory transcriptional network in the vasculature. Overall, these findings provide a foundation for understanding the molecular basis for estrogen effects on vasculature gene expression.

Estrogen influences the physiology of many target tissues in both women and men. The long-term effects of estrogen are mediated predominantly by nuclear estrogen receptors (ERs) functioning as DNA-binding transcription factors. Tissue-specific responses to estrogen therefore result from regulation of different sets of genes. However, it remains perplexing as to what regulatory sequence contexts specify distinct genomic responses. First, this review classifies estrogen response sequences in mammalian target genes. Of note, around one third of known human target genes associate only indirectly with ER, through intermediary transcription factor(s). Then, computational approaches are presented both for refining direct ER-binding sites and for formulating hypotheses regarding the overall genomic expression pattern. Surprisingly, limited evolutionary conservation of specific estrogen-responsive sites is observed between human and mouse. Finally, consideration of the cellular functions of regulated human genes suggests links between particular biological roles and specific types of estrogen response elements, although with the important caveat that only a restricted set of target genes is available. These analyses support the view that specific, hormone-driven gene expression programs can result from the interplay of environmental and cellular cues with the distinct types of estrogen-response sequences.