Skip to main content
U.S. Department of Energy
Office of Scientific and Technical Information

Signature analysis of high-throughput transcriptomics screening data for mechanistic inference and chemical grouping (in EN)

Journal Article · · Toxicological Sciences
Abstract

High-throughput transcriptomics (HTTr) uses gene expression profiling to characterize the biological activity of chemicals in in vitro cell-based test systems. As an extension of a previous study testing 44 chemicals, HTTr was used to screen an additional 1,751 unique chemicals from the EPA’s ToxCast collection in MCF7 cells using 8 concentrations and an exposure duration of 6 h. We hypothesized that concentration-response modeling of signature scores could be used to identify putative molecular targets and cluster chemicals with similar bioactivity. Clustering and enrichment analyses were conducted based on signature catalog annotations and ToxPrint chemotypes to facilitate molecular target prediction and grouping of chemicals with similar bioactivity profiles. Enrichment analysis based on signature catalog annotation identified known mechanisms of action (MeOAs) associated with well-studied chemicals and generated putative MeOAs for other active chemicals. Chemicals with predicted MeOAs included those targeting estrogen receptor (ER), glucocorticoid receptor (GR), retinoic acid receptor (RAR), the NRF2/KEAP/ARE pathway, AP-1 activation, and others. Using reference chemicals for ER modulation, the study demonstrated that HTTr in MCF7 cells was able to stratify chemicals in terms of agonist potency, distinguish ER agonists from antagonists, and cluster chemicals with similar activities as predicted by the ToxCast ER Pathway model. Uniform manifold approximation and projection (UMAP) embedding of signature-level results identified novel ER modulators with no ToxCast ER Pathway model predictions. Finally, UMAP combined with ToxPrint chemotype enrichment was used to explore the biological activity of structurally related chemicals. The study demonstrates that HTTr can be used to inform chemical risk assessment by determining in vitro points of departure, predicting chemicals’ MeOA and grouping chemicals with similar bioactivity profiles.

Research Organization:
Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0014664
OSTI ID:
2582453
Journal Information:
Toxicological Sciences, Journal Name: Toxicological Sciences Journal Issue: 1 Vol. 202; ISSN 1096-6080
Publisher:
Oxford University Press
Country of Publication:
United States
Language:
EN

Similar Records

Towards replacement of animal tests with in vitro assays: a gene expression biomarker predicts in vitro and in vivo estrogen receptor activity
Journal Article · Fri Jun 10 20:00:00 EDT 2022 · Chemico-Biological Interactions · OSTI ID:1981556

High-throughput screening tools facilitate calculation of a combined exposure-bioactivity index for chemicals with endocrine activity
Journal Article · Sat Feb 08 19:00:00 EST 2020 · Environment International · OSTI ID:1904995

Application of Cell Painting for chemical hazard evaluation in support of screening-level chemical assessments
Journal Article · Mon Apr 10 20:00:00 EDT 2023 · Toxicology and Applied Pharmacology · OSTI ID:2425588

Related Subjects