2022 journal article

Grouping of UVCB Substances with Dose-Response Transcriptomics Data from Human Cell-Based Assays

ALTEX-ALTERNATIVES TO ANIMAL EXPERIMENTATION, 39(3), 388–404.

By: J. House n, F. Grimm*, W. Klaren*, A. Dalzell*, S. Kuchi*, S. Zhang*, K. Lenz*, P. Boogaard ...

co-author countries: Belgium 🇧🇪 Germany 🇩🇪 United Kingdom of Great Britain and Northern Ireland 🇬🇧 Netherlands 🇳🇱 United States of America 🇺🇸
MeSH headings : Biological Assay; Endothelial Cells; Humans; Induced Pluripotent Stem Cells; Petroleum; Transcriptome
Source: Web Of Science
Added: August 29, 2022

The application of in vitro biological assays as new approach methodologies (NAMs) to support grouping of UVCB (unknown or variable composition, complex reaction products, and biological materials) substances has recently been demonstrated. In addition to cell-based phenotyping as NAMs, in vitro transcriptomic profiling is used to gain deeper mechanistic understanding of biological responses to chemicals and to support grouping and read-across. However, the value of gene expression profiling for characterizing complex substances like UVCBs has not been explored. Using 141 petroleum substance extracts, we performed dose-response transcriptomic profiling in human induced pluripotent stem cell (iPSC)-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, as well as cell lines MCF7 and A375. The goal was to determine whether transcriptomic data can be used to group these UVCBs and to further characterize the molecular basis for in vitro biological responses. We found distinct transcriptional responses for petroleum substances by manufacturing class. Pathway enrichment informed interpretation of effects of substances and UVCB petroleum-class. Transcriptional activity was strongly correlated with concentration of polycyclic aromatic compounds (PAC), especially in iPSC-derived hepatocytes. Supervised analysis using transcriptomics, alone or in combination with bioactivity data collected on these same substances/cells, suggest that transcriptomics data provide useful mechanistic information, but only modest additional value for grouping. Overall, these results further demonstrate the value of NAMs for grouping of UVCBs, identify informative cell lines, and provide data that could be used for justifying selection of substances for further testing that may be required for registration.