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Applications for estimation of in vivo toxicity point of departure for discovery stage molecule predictive safety assessment

ABSTRACT: Utilization of in vitro (cellular) techniques, like Cell Painting and transcriptomics-based methods could provide powerful tools for risk assessment and regulatory decision-making. However, using these models generates challenges translating in vitro concentrations to corresponding in vivo internal exposures. We tested whether in vivo (rat liver) transcriptional and apical points of departure (PODs) could be accurately predicted from in vitro (rat hepatocyte or human HepaRG) transcriptional PODs or HepaRG Cell Painting PODs using PBPK modeling. We compared two PBPK models, ADMET predictor and the httk R package, and found httk to predict the rat hepatocyte no observed transcriptional effect level (NOTEL)-derived PODs more accurately. Our findings suggest that a rat liver apical and transcriptome POD can be estimated utilizing a combination of in vitro transcriptome-based PODs coupled with PBPK modeling for IVIVE.

ORGANISM(S): Rattus norvegicus Homo sapiens

PROVIDER: GSE269501 | GEO | 2025/06/28

REPOSITORIES: GEO

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Project description:Background: Modern testing paradigms seek to apply human-relevant cell culture models and integrate data from multiple test systems to accurately inform potential hazards and modes of action for chemical toxicology. In genetic toxicology, the use of metabolically competent human hepatocyte cell culture models provides clear advantages over other more commonly used cell lines that require the use of external metabolic activation systems, such as rat liver S9. HepaRG™ cells are metabolically competent cells that express Phase I and II metabolic enzymes and differentiate into mature hepatocyte-like cells, making them ideal for toxicity testing. We assessed the performance of the flow cytometry in vitro micronucleus (MN) test and the TGx-DDI transcriptomic biomarker to detect DNA damage-inducing (DDI) chemicals in human HepaRG™ cells after a 3-day repeat exposure. The biomarker, developed for use in human TK6 cells, is a panel of 64 genes that accurately classifies chemicals as DDI or non-DDI. Herein, the TGx-DDI biomarker was analyzed by Ion AmpliSeq whole transcriptome sequencing to assess its classification accuracy using this more modern gene expression technology as a secondary objective. Methods: HepaRG™ cells were exposed to increasing concentrations of 10 test chemicals (six genotoxic chemicals, including one aneugen, and four non-genotoxic chemicals). Cytotoxicity and genotoxicity were measured using the In Vitro MicroFlow® kit, which was run in parallel with the TGx-DDI biomarker. Results: A concentration-related decrease in relative survival and a concomitant increase in MN frequency were observed for genotoxic chemicals in HepaRG™ cells. All five DDI and five non-DDI agents were correctly classified (as genotoxic/non-genotoxic and DDI/non-DDI) by pairing the test methods. The aneugenic agent (colchicine) yielded the expected positive result in the MN test and negative (non-DDI) result by TGx-DDI. Conclusions: This next generation genotoxicity testing strategy is aligned with the paradigm shift occurring in the field of genetic toxicology. It provides mechanistic insight in a human-relevant cell-model, paired with measurement of a conventional endpoint, to inform the potential for adverse health effects. This work provides support for combining these assays in an integrated test strategy for accurate, higher throughput genetic toxicology testing in this metabolically competent human progenitor cell line.

Project description:For assessing the cancer-causing potential for humans of a chemical compound, the conventional approach is the use of the 2-year rodent carcinogenicity bioassay, thus alternatives such as in vitro toxicogenomics are highly desired. In the present study, the transcriptomics responses following exposure to genotoxic (GTX) and non-genotoxic (NGTX) hepatocarcinogens and non-carcinogens (NC) in five liver-based in vitro models, namely conventional and epigenetically-stabilized cultures of primary rat hepatocytes, the human hepatoma-derived HepaRG and HepG2 cell lines and the human embryonic stem cell-derived hepatocyte-like cells hES-Heps are examined and compared. The global gene expression profiles of five commonly used liver-based in vitro systems are investigated, namely conventional cultures of primary rat hepatocytes (HepsC), Trichostatin A (TSA)-stabilized cultures of primary rat hepatocytes (HepsT), human embryonic stem cell-derived hepatocyte-like cells (hES-Hep), HepG2 and HepaRG cells. These models are exposed to 15 prototypical compounds which have been carefully chosen and belong to 3 toxic classes i.e. (i) genotoxic (GTX) (aflatoxin B1, AFB1; 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone, NNK; 2-nitrofluorene, 2NF; benzo(a)pyrene, BaP; cyclophosphamide, CYCLO), (ii) non-genotoxic (NGTX) (methapyrilene hydrochloride, MPH; piperonylbutoxide , PIPB; Wy-14643, WYE; phenobarbital sodium, SPB; 12-O-tetradecanoylphorbol-13-acetate, TPA) carcinogens and (iii) non-carcinogens (NC) (nifedipine, NIF; clonidine, CND; D-mannitol, MAN; tolbutamide, TOL; diclofenac sodium, SDF). For the gene- and pathway- based analysis, the raw microarray data was re-annotated to Ensembl version 61 genome and Gene Chip Robust Multi-array Average (GC-RMA) normalized (Dai et al. 2005). This resulted in 11,187 and 18,919 probe sets for the rat and the human models, respectively. For the classification analysis, the raw microarray data was annotated using the chip description files from Affymetrix and then GC-RMA normalized. In order to eliminate batch effects, data from the different studies were half-z normalized. Half-z-normalization adjusts the logarithmic expression values of transcripts within a group such that each transcript has zero mean.

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Applications for estimation of in vivo toxicity point of departure for discovery stage molecule predictive safety assessment

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