Transcriptomic responses generated by hepatocarcinogens in a battery of liver-based in vitro models

Abstract

As the conventional approach to assess the potential of a chemical to cause cancer in humans still includes the 2-year rodent carcinogenicity bioassay, development of alternative methodologies is needed. 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 cell lines HepaRG and HepG2 and human embryonic stem cell-derived hepatocyte-like cells, are examined. For full characterization of the systems, several bioinformatics approaches are employed including gene-based, ConsensusPathDB-based and classification analysis. They provide convincingly similar outcomes, namely that upon exposure to carcinogens, the HepaRG generates a gene classifier (a gene classifier is defined as a selected set of characteristic gene signatures capable of distinguishing GTX, NGTX carcinogens and NC) able to discriminate the GTX carcinogens from the NGTX carcinogens and NC. The other in vitro models also yield cancer-relevant characteristic gene groups for the GTX exposure, but some genes are also deregulated by the NGTX carcinogens and NC. Irrespective of the tested in vitro model, the most uniformly expressed pathways following GTX exposure are the p53 and those that are subsequently induced. The NGTX carcinogens triggered no characteristic cancer-relevant gene profiles in all liver-based in vitro systems. In conclusion, liver-based in vitro models coupled with transcriptomics techniques, especially in the case when the HepaRG cell line is used, represent valuable tools for obtaining insight into the mechanism of action and identification of GTX carcinogens.

High-throughput data integration of RNA–miRNA–circRNA reveals novel insights into mechanisms of benzo[a]pyrene-induced carcinogenicity

“…Since the liver represents one of the major target organs in the rodent cancer bioassay, a human liver cell model thus is a preferred option. In toxicogenomics, HepG2 has previously been shown to provide a model for classifying carcinogenic chemicals with higher accuracy that the rodent cancer bioassay (19,20). While this has been the outcome of statistical approaches, it is now tempting to also subject the HepG2 cell system to mechanistic investigations, using high throughput sequencing.…”

Integration of metabolic activation with a predictive toxicogenomics signature to classify genotoxic versus nongenotoxic chemicals in human TK6 cells

“…In a study by Doktorova et al [2013], human hepatoma‐dervied HepaRG cells were exposed to 15 prototypical compounds belonging to three toxic classes: (i) genotoxic carcinogens [AFB1; 4‐(methylnitrosamino)‐1‐(3‐pyridyl)‐1‐butanone (NNK); 2‐nitrofluorene (2NF); BaP; cyclophosphamide (CYCLO)], (ii) nongenotoxic carcinogens [methapyrilene hydrochloride (MPH); piperonylbutoxide (PIPB), Wy‐14643 (WYE), phenobarbital sodium (SPB), 12‐ O ‐tetradecanoylphorbol‐13‐acetate (TPA)]; and (iii) noncarcinogens [nifedipine (NIF); clonidine (CND); d ‐mannitol (MAN); tolbutamide (TOL); diclofenac sodium (SDF)] for 72 hr to study the transcriptomic responses. Raw CEL files from this study generated using Affymetrix U133 Plus 2.0 GeneChips (GEO accession number GSE40117) were downloaded to test the TGx‐28.65 biomaker in a human cell line with inherent metabolic capabilities [Doktorova et al, ]. The human HepaRG microarray data were RMA normalized in R using the ReadAffy function in the Affy package.…”

Transcriptomic effect marker patterns of genotoxins – a comparative study with literature data

“…Especially the AB1 datasets with the identifiers x and y from Tryndyak et al () (cp. Table ) and the NNK data from Doktorova et al () were different from the other datasets in the PCA analysis. Results were similar when only the DEGs were considered for the PCA instead of the entire datasets (not shown).…”