A tiered testing strategy based on in vitro phenotypic and transcriptomic data for selecting representative petroleum UVCBs for toxicity evaluation in vivo

Abstract

Hazard evaluation of substances of “unknown or variable composition, complex reaction products and biological materials” (UVCBs) remains a major challenge in regulatory science because their chemical composition is difficult to ascertain. Petroleum substances are representative UVCBs and human cell-based data has been previously used to substantiate their groupings for regulatory submissions. We hypothesized that a combination of phenotypic and transcriptomic data could be integrated to make decisions as to selection of group-representative worst-case petroleum UVCBs for subsequent toxicity evaluation in vivo. We used data obtained from 141 substances from 16 manufacturing categories previously tested in six human cell types (induced pluripotent stem cell (iPSC)-derived hepatocytes, cardiomyocytes, neurons, and endothelial cells, and MCF7 and A375 cell lines). Benchmark doses for gene-substance combinations were calculated, and both transcriptomic and phenotype-derived points of departure (PODs) were obtained. Correlation analysis and machine learning were used to assess associations between phenotypic and transcriptional PODs and to determine the most informative cell types and assays, thus representing a cost-effective integrated testing strategy. We found that two cell types—iPSC-derived-hepatocytes and -cardiomyocytes—contributed the most informative and protective PODs and may be used to inform selection of representative petroleum UVCBs for further toxicity evaluation in vivo. Overall, while the use of new approach methodologies to prioritize UVCBs has not been widely adopted, our study proposes a tiered testing strategy based on iPSC-derived hepatocytes and cardiomyocytes to inform selection of representative worst-case petroleum UVCBs from each manufacturing category for further toxicity evaluation in vivo.

Integrative Chemical–Biological Grouping of Complex High Production Volume Substances from Lower Olefin Manufacturing Streams

“…These studies showed that the bioactivity and transcriptomic data correlate strongly with the PAC content of each substance and can be used to rank overall categories in a way similar to that using other hazard data (typically from animal and genotoxicity studies); however, they cannot be used to substantiate existing groupings. These data are still highly informative, as a combination of bioactivity and transcriptomic data could be integrated to make decisions as to the selection of class-representative worst-case petroleum UVCBs for subsequent evaluation in vivo [ 57 ].…”

Risk-based prioritization of PFAS using phenotypic and transcriptomic data from human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes

“…The Bioconductor's DESeq2 package (Love et al, 2014) was utilized to assemble the complete normalized count matrix as detailed above. The normalized counts data (counts + 1 to zero-protect the data for further analyses on the logarithmic scale) were processed using the BMDExpress (v.2.3) software (Phillips et al, 2019) for transcriptomic benchmark dose modelling as detailed in (Tsai et al, 2023). Data were first pre-filtered with Williams' trend test (p-value ≤0.05 within each transcript and substance) and an absolute fold change ≥1.5 (compared with vehicle controls); genes that did not pass these criteria at any dose were removed from further analysis.…”

“…In addition, while iPSC-derived cardiomyocytes are a useful model for cardiotoxicity screening, both in studies of cell function (Burnett et al, 2019(Burnett et al, , 2021aChen et al, 2021;House et al, 2021) and in gene expression studies (House et al, 2022;Tsai et al, 2023;Grimm et al, 2018), gene expression effects from PFAS exposure in cardiomyocytes have not been reported. In this respect, our study provides a unique dataset that showed that PFAS exposure can perturb gene expression in iPSC-CM with patterns that were distinct from those in iPSC-Hep.…”

“…exposure limits for environmental chemicalsthe US EPA has proposed to use transcriptomic reference values (TRV) as a novel EPA Transcriptomic Assessment Product (ETAP) (US EPA, 2023). Therefore, transcriptomic data are not only regarded as useful in mechanistic interpretation, but also for dose-response step in risk assessment (Nyffeler et al, 2022;Harrill et al, 2021;Tsai et al, 2023;Johnson et al, 2022). Interestingly, a study by (Reardon et al, 2021) examined PFAS-associated in vitro tPODs in primary human liver spheroids and demonstrated that they may be more "protective" in comparison to apical PODs derived from animal studies for most chemicals analyzed, which further demonstrated the value of the use of in vitro transcriptomic data in risk assessment.…”

Informing Hazard Identification and Risk Characterization of Environmental Chemicals by Combining Transcriptomic and Functional Data from Human-Induced Pluripotent Stem-Cell-Derived Cardiomyocytes

“…Transcriptomic data-derived points of departure (tPODs) from iPSC-derived cardiomyocytes have been shown to be equally or more protective than phenotypic data-derived PODs (pPODs) for poly-and per-fluorinated substances (PFAS) 36 and petroleum refining products. 37 Still, no study has probed the potential of in vitro transcriptomics as a largescale screening approach for testing diverse environmental chemicals in iPSC-derived cardiomyocytes. Therefore, this study tested the hypothesis that using high-throughput transcriptomic data in iPSC-derived cardiomyocytes, coupled with phenotypic data on cell beating and viability, can inform hazard identification and enable risk characterization for substances with potential cardiotoxicity.…”