Identifying multiscale translational safety biomarkers using a network-based systems approach

Callegaro, Giulia; Schimming, Johannes P.; González, Janet Piñero; Kunnen, Steven J.; Wijaya, Lukas S; Trairatphisan, Panuwat; Berk, Linda van den; Beetsma, Kim; Furlong, Laura I.; Sutherland, Jeffrey J.; Mollon, Jennifer; Stevens, James; Water, Bob van de

doi:10.1016/j.isci.2023.106094

Cited by 5 publications

(12 citation statements)

References 49 publications

(104 reference statements)

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“…We have used large toxicogenomics datasets from rat 28‐day repeat dose toxicity studies to establish a rat liver TXG‐MAPr and identified activation of gene co‐expression networks that are associated with, e.g., in vivo onset of liver single cell necrosis (=apoptosis). HepG2 BAC‐GFP reporters for TRIB3 and MTHFD2 that represent this gene network contribute to screening for liabilities that have direct in vivo toxicological relevance 26 . Other improvements are required to be able to directly relate in vitro reporter outcomes towards DILI risk in the clinic.…”

Section: Discussionmentioning

confidence: 99%

“…HepG2 BAC-GFP reporters for TRIB3 and MTHFD2 that represent this gene network contribute to screening for liabilities that have direct in vivo toxicological relevance. 26 Other improvements are required to be able to directly relate in vitro reporter outcomes towards DILI risk in the clinic. The current screening set-up had several limitations that need to be overcome in the future:…”

Section: Antimycotic and Cns Drugs That Induce Ddit3 Expression Impai...mentioning

confidence: 99%

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The integrated stress response‐related expression of CHOP due to mitochondrial toxicity is a warning sign for DILI liability

Vlasveld,

Callegaro,

Fisher

et al. 2024

Liver International

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Background and AimsDrug‐induced liver injury (DILI) is one of the most frequent reasons for failure of drugs in clinical trials or market withdrawal. Early assessment of DILI risk remains a major challenge during drug development. Here, we present a mechanism‐based weight‐of‐evidence approach able to identify certain candidate compounds with DILI liabilities due to mitochondrial toxicity.MethodsA total of 1587 FDA‐approved drugs and 378 kinase inhibitors were screened for cellular stress response activation associated with DILI using an imaging‐based HepG2 BAC‐GFP reporter platform including the integrated stress response (CHOP), DNA damage response (P21) and oxidative stress response (SRXN1).ResultsIn total 389, 219 and 104 drugs were able to induce CHOP‐GFP, P21‐GFP and SRXN1‐GFP expression at 50 μM respectively. Concentration response analysis identified 154 FDA‐approved drugs as critical CHOP‐GFP inducers. Based on predicted and observed (pre‐)clinical DILI liabilities of these drugs, nine antimycotic drugs (e.g. butoconazole, miconazole, tioconazole) and 13 central nervous system (CNS) agents (e.g. duloxetine, fluoxetine) were selected for transcriptomic evaluation using whole‐genome RNA‐sequencing of primary human hepatocytes. Gene network analysis uncovered mitochondrial processes, NRF2 signalling and xenobiotic metabolism as most affected by the antimycotic drugs and CNS agents. Both the selected antimycotics and CNS agents caused impairment of mitochondrial oxygen consumption in both HepG2 and primary human hepatocytes.ConclusionsTogether, the results suggest that early pre‐clinical screening for CHOP expression could indicate liability of mitochondrial toxicity in the context of DILI, and, therefore, could serve as an important warning signal to consider during decision‐making in drug development.

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Section: Discussionmentioning

confidence: 99%

Section: Antimycotic and Cns Drugs That Induce Ddit3 Expression Impai...mentioning

confidence: 99%

The integrated stress response‐related expression of CHOP due to mitochondrial toxicity is a warning sign for DILI liability

Vlasveld,

Callegaro,

Fisher

et al. 2024

Liver International

Self Cite

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“…Callegaro et al took a similar WGCNA approach to extract modules of co-expressed genes from both human hepatocytes and rat liver transcriptome data using the TG-GATES database. 9,10 They also created a public analysis tool, the TXG-MAPr, using an R Shiny framework that allows the user to mine modules for biological function and extract mechanistic information using transcriptomic data from new experiments with uncharacterized hepatotoxicants (https://txg-mapr.eu/). Using this analysis approach, they demonstrate the utility of using human primary hepatocytes networks across different analysis platforms, for example, microarray versus RNA-Seq, and by identifying disease associations across individual liver donors when only partial transcriptomic data are available from targeted expression platform, such as the S1500+.…”

Section: Gene Network Approaches To Define Mechanisms Of Pathogenesismentioning

confidence: 99%

Section: Gene Network Approaches To Define Mechanisms Of Pathogenesismentioning

confidence: 99%

“…32 Callegaro et al used this preservation approach to identify a preserved ATF4 gene network that is associated with occurrence of single cell necrosis (apoptosis) of hepatocytes in rat liver, and is preserved in human primary hepatocytes, to identify Tribbles homolog 3 (TRIB3) as a translational biomarker useful for screening compound with drug-induced liver injury liability in human primary hepatocytes. 10 Co-expression approaches have also been applied to derive gene signatures using a seed gene approach. Podtelezhnikov et al used a combination of clustering, correlation analysis, and linear modeling to show that genes identified in the literature as targets for xenobiotic responsive transcription factors are members of co-expressed gene signatures that can be used to characterize new compounds.…”

Section: Gene Network Approaches To Define Mechanisms Of Pathogenesismentioning

confidence: 99%

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Toxicogenomics Approaches to Address Toxicity and Carcinogenicity in the Liver

Pandiri,

Auerbach,

Stevens

et al. 2023

Toxicol Pathol

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Toxicogenomic technologies query the genome, transcriptome, proteome, and the epigenome in a variety of toxicological conditions. Due to practical considerations related to the dynamic range of the assays, sensitivity, cost, and technological limitations, transcriptomic approaches are predominantly used in toxicogenomics. Toxicogenomics is being used to understand the mechanisms of toxicity and carcinogenicity, evaluate the translational relevance of toxicological responses from in vivo and in vitro models, and identify predictive biomarkers of disease and exposure. In this session, a brief overview of various transcriptomic technologies and practical considerations related to experimental design was provided. The advantages of gene network analyses to define mechanisms were also discussed. An assessment of the utility of toxicogenomic technologies in the environmental and pharmaceutical space showed that these technologies are being increasingly used to gain mechanistic insights and determining the translational relevance of adverse findings. Within the environmental toxicology area, there is a broader regulatory consideration of benchmark doses derived from toxicogenomics data. In contrast, these approaches are mainly used for internal decision-making in pharmaceutical development. Finally, the development and application of toxicogenomic signatures for prediction of apical endpoints of regulatory concern continues to be area of intense research.

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A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury

Wijaya,

Gabor,

Pot

et al. 2023

Toxicological Sciences

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Drug-induced liver injury (DILI) remains the main reason for drug development attritions largely due to poor mechanistic understanding. Toxicogenomic to interrogate the mechanism of DILI has been broadly performed. Gene coregulation network-based transcriptome analysis is a bioinformatics approach that potentially contributes to improve mechanistic interpretation of toxicogenomic data. Here we performed an extensive concentration time course response-toxicogenomic study in the HepG2 cell line exposed to 20 DILI compounds, 7 reference compounds for stress response pathways, and 10 agonists for cytokines and growth factor receptors. We performed whole transcriptome targeted RNA sequencing to more than 500 conditions and applied weighted gene coregulated network analysis to the transcriptomics data followed by the identification of gene coregulated networks (modules) that were strongly modulated upon the exposure of DILI compounds. Preservation analysis on the module responses of HepG2 and PHH demonstrated highly preserved adaptive stress response gene coregulated networks. We correlated gene coregulated networks with cell death onset and causal relationships of 67 critical target genes of these modules with the onset of cell death was evaluated using RNA interference screening. We identified GTPBP2, HSPA1B, IRF1, SIRT1, and TSC22D3 as essential modulators of DILI compound-induced cell death. These genes were also induced by DILI compounds in PHH. Altogether, we demonstrate the application of large transcriptome datasets combined with network-based analysis and biological validation to uncover the candidate determinants of DILI.

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Identifying multiscale translational safety biomarkers using a network-based systems approach

Cited by 5 publications

References 49 publications

The integrated stress response‐related expression of CHOP due to mitochondrial toxicity is a warning sign for DILI liability

The integrated stress response‐related expression of CHOP due to mitochondrial toxicity is a warning sign for DILI liability

Toxicogenomics Approaches to Address Toxicity and Carcinogenicity in the Liver

A network-based transcriptomic landscape of HepG2 cells uncovering causal gene-cytotoxicity interactions underlying drug-induced liver injury

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