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High-Throughput Transcriptomics (HTTr) Chemical Screening in U-2 OS cells

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NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP523356
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High-throughput transcriptomics (HTTr) uses gene expression profiling to characterize the biological activity of chemicals in in vitro cell-based test systems. In this study, the TempO-Seq human whole transcriptome assay was used to screen 1201 unique chemicals from the EPA's ToxCast collection. Chemicals were screened at eight concentrations in U-2 OS cells using an exposure duration of 24 hours. Transcriptome profiles were analyzed using a previously described signature concentration-response modeling approach. Clustering and gene signature similarity analyses were used to facilitate molecular target prediction. Test chemicals were identified that likely interact with specific molecular targets including: glucocorticoid receptor, retinoic acid receptor, and the progesterone receptor. Finally, HTTr data were compared to a high throughput phenotypical profiling data spanning the same test chemicals and concentration range revealing modest agreement between the two data streams with respect to chemical potency estimates and bioactivity calls. The study demonstrates that HTTr can be used to inform chemical risk assessment by determining in vitro points-of-departure, predicting likely mechanism of action, and complementing existing high throughput data streams.
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2025-08-01
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