Next generation risk assessment of chemicals revolves around the use of mechanistic information without animal experimentation. In this regard, toxicogenomics has proven to be a useful tool to... Show moreNext generation risk assessment of chemicals revolves around the use of mechanistic information without animal experimentation. In this regard, toxicogenomics has proven to be a useful tool to elucidate the underlying mechanisms of adverse effects of xenobiotics. In the present study, two widely used human in vitro hepatocyte culture systems, namely primary human hepatocytes (PHH) and human hepatoma HepaRG cells, were exposed to liver toxicants known to induce liver cholestasis, steatosis or necrosis. Benchmark concentration-response modelling was applied to transcriptomics gene co-expression networks (modules) to derive benchmark concentrations (BMCs) and to gain mechanistic insight into the hepatotoxic effects. BMCs derived by concentration-response modelling of gene co-expression modules recapitulated concentration-response modelling of individual genes. Although PHH and HepaRG cells showed overlap in deregulated genes and modules by the liver toxicants, PHH demonstrated a higher responsiveness, based on the lower BMCs of co-regulated gene modules. Such BMCs can be used as transcriptomics point of departure (tPOD) for assessing module-associated cellular (stress) pathways/processes. This approach identified clear tPODs of around maximum systemic concentration (Cmax) levels for the tested drugs, while for cosmetics ingredients the BMCs were 10-100-fold higher than the estimated plasma concentrations. This approach could serve next generation risk assessment practice to identify early responsive modules at low BMCs, that could be linked to key events in liver adverse outcome pathways. In turn, this can assist in delineating potential hazards of new test chemicals using in vitro systems and used in a risk assessment when BMCs are paired with chemical exposure assessment. Show less
Callegaro, G.; Schimming, J.P.; Piñero González, J.; Kunnen, S.J.; Wijaya, L.S.; Trairatphisan, P.; ... ; Water, B. van de 2023
Animal testing is the current standard for drug and chemicals safety assessment, but hazards translation to human is uncertain. Human in vitro models can address the species translation but might... Show moreAnimal testing is the current standard for drug and chemicals safety assessment, but hazards translation to human is uncertain. Human in vitro models can address the species translation but might not replicate in vivo complexity. Herein, we propose a network-based method addressing these translational multiscale problems that derives in vivo liver injury biomarkers applicable to in vitro human early safety screening. We applied weighted correlation network analysis (WGCNA) to a large rat liver transcriptomic dataset to obtain co-regulated gene clusters (modules). We identified modules statistically associated with liver pathologies, including a module enriched for ATF4-regulated genes as associated with the occurrence of hepatocellular single-cell necrosis, and as preserved in human liver in vitro models. Within the module, we identified TRIB3 and MTHFD2 as a novel candidate stress biomarkers, and developed and used BAC-eGFPHepG2 reporters in a compound screening, identifying compounds showing ATF4-dependent stress response and potential early safety signals. Show less
Vrijenhoek, N.G.; Wehr, M.M.; Kunnen, S.J.; Wijaya, L.S.; Callegaro, G.; Moné, M.J.; ... ; Water, B. van de 2022
Chemical read-across is commonly evaluated without particular knowledge of the biological mechanisms leading to observed adverse outcomes in vivo. Integrating data that indicate shared modes of... Show moreChemical read-across is commonly evaluated without particular knowledge of the biological mechanisms leading to observed adverse outcomes in vivo. Integrating data that indicate shared modes of action in humans will strengthen read-across cases. Here we studied transcriptomic responses of primary human hepatocytes (PHH) to a large panel of carboxylic acids to include detailed mode-of-action data as a proof-of-concept for read-across in risk assessment. In rodents, some carboxylic acids, including valproic acid (VPA), are known to cause hepatic steatosis, whereas others do not. We investigated transcriptomics responses of PHHs stimulated for 24 h by 18 structurally different VPA analogues in a concentration range to determine biological similarity in relation to in vivo steatotic potential. Using a targeted high-throughput screening assay we assessed the differential expression of ~3,000 genes covering relevant biological pathways. Differentially expressed gene analysis revealed differences in potency of carboxylic acids and expression patterns were highly similar for structurally similar compounds. Strong clustering occurred for steatosis-positive versus steatosis-negative carboxylic acids. To quantitatively define biological read-across, we combined pathway analysis and weighted gene co-expression network analysis. Active carboxylic acids displayed high similarity in gene network modulation. Importantly, free fatty acid synthesis modulation and stress pathway responses are affected by active carboxylic acids, providing coherent mechanistic underpinning for our findings. Our work shows that transcriptomic analysis of cultured human hepatocytes can reinforce the prediction of liver injury outcome based on quantitative and mechanistic biological data and support the application in read-across. Show less
Callegaro, G.; Kunnen, S.J.; Trairatphisan, P.; Grosdidier, S.; Niemeijer, M.; Hollander, W. den; ... ; Water, B. van de 2021
Mechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising... Show moreMechanism-based risk assessment is urged to advance and fully permeate into current safety assessment practices, possibly at early phases of drug safety testing. Toxicogenomics is a promising source of mechanisms-revealing data, but interpretative analysis tools specific for the testing systems (e.g. hepatocytes) are lacking. In this study, we present the TXG-MAPr webtool (available at https://txg-mapr.eu/WGCNA_PHH/TGGATEs_PHH/ ), an R-Shiny-based implementation of weighted gene co-expression network analysis (WGCNA) obtained from the Primary Human Hepatocytes (PHH) TG-GATEs dataset. The 398 gene co-expression networks (modules) were annotated with functional information (pathway enrichment, transcription factor) to reveal their mechanistic interpretation. Several well-known stress response pathways were captured in the modules, were perturbed by specific stressors and showed preservation in rat systems (rat primary hepatocytes and rat in vivo liver), with the exception of DNA damage and oxidative stress responses. A subset of 87 well-annotated and preserved modules was used to evaluate mechanisms of toxicity of endoplasmic reticulum (ER) stress and oxidative stress inducers, including cyclosporine A, tunicamycin and acetaminophen. In addition, module responses can be calculated from external datasets obtained with different hepatocyte cells and platforms, including targeted RNA-seq data, therefore, imputing biological responses from a limited gene set. As another application, donors' sensitivity towards tunicamycin was investigated with the TXG-MAPr, identifying higher basal level of intrinsic immune response in donors with pre-existing liver pathology. In conclusion, we demonstrated that gene co-expression analysis coupled to an interactive visualization environment, the TXG-MAPr, is a promising approach to achieve mechanistic relevant, cross-species and cross-platform evaluation of toxicogenomic data. Show less
Several cellular processes and pathways were altered both by fluid shear stress and Pkd1 gene disruption in renal epithelial cells. Many of these signaling pathways are implicated in ADPKD as... Show moreSeveral cellular processes and pathways were altered both by fluid shear stress and Pkd1 gene disruption in renal epithelial cells. Many of these signaling pathways are implicated in ADPKD as well. However, more than 20 years after the discovery of PKD1 and PKD2 as genetic cause of ADPKD, the exact cellular function of the polycystins still remains unclear. Our data indicate that polycystin-1 is not a direct mechano-sensor, but it restrains shear stress induced gene expression via an unknown mechanism. Additional research is required to identify the cellular function of polycystins and the mechanism of mechanotransduction. This is needed to refine the mechanism of cyst formation in ADPKD and other ciliopathies, which could identify potential targets for therapy. Nevertheless, we showed that inhibition of activin signaling is a promising therapy to slow cyst progression in Pkd1del mice. Although other treatment strategies have been tested successfully to reduce PKD progression in pre-clinical studies, the efficacy in human patients is sometimes minimal or absent. Therefore, it has been suggested to target multiple signaling pathways affected in ADPKD. These combined therapies should reestablish the balance in cellular signaling of renal epithelial cells and maintain cellular homeostasis within physiological boundaries. Show less
Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most... Show morePolycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD. Show less
Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most... Show morePolycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD. Show less
Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most... Show morePolycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD. Show less
Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most... Show morePolycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD. Show less
Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most... Show morePolycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD. Show less
Polycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most... Show morePolycystic kidney disease (PKD) is a prevalent disorder characterized by renal cysts that lead to kidney failure. Various signaling pathways have been targeted to stop disease progression, but most interventions still focus on alleviating PKD-associated symptoms. The mechanistic complexity of the disease, as well as the lack of functional in vitro assays for compound testing, has made drug discovery for PKD challenging. To identify modulators of PKD, Pkd1–/– kidney tubule epithelial cells were applied to a scalable and automated 3D cyst culture model for compound screening, followed by phenotypic profiling to determine compound efficacy. We used this screening platform to screen a library of 273 kinase inhibitors to probe various signaling pathways involved in cyst growth. We show that inhibition of several targets, including aurora kinase, CDK, Chk, IGF-1R, Syk, and mTOR, but, surprisingly, not PI3K, prevented forskolin-induced cyst swelling. Additionally, we show that multiparametric phenotypic classification discriminated potentially undesirable (i.e., cytotoxic) compounds from molecules inducing the desired phenotypic change, greatly facilitating hit selection and validation. Our findings show that a pathophysiologically relevant 3D cyst culture model of PKD coupled to phenotypic profiling can be used to identify potentially therapeutic compounds and predict and validate molecular targets for PKD. Show less
Autosomal dominant polycystic kidney disease (ADPKD) caused by mutations in either the PKD1 or PKD2 gene is a major cause of end-stage renal failure. A number of compounds targeting specific... Show moreAutosomal dominant polycystic kidney disease (ADPKD) caused by mutations in either the PKD1 or PKD2 gene is a major cause of end-stage renal failure. A number of compounds targeting specific signaling pathways were able to inhibit cystogenesis in rodent models and are currently being tested in clinical trials. However, given the complex signaling in ADPKD, an ideal therapy would likely have to comprise several pathways at once. Therefore, multitarget compounds may provide promising therapeutic interventions for the treatment of ADPKD. To test this hypothesis, we treated Pkd1-deletion mice with diferuloylmethane (curcumin), a compound without appreciable side effects and known to modulate several pathways that are also altered in ADPKD, e.g., mammalian target of rapamycin (mTOR) and Wnt signaling. After conditional inactivation of Pkd1, mTOR signaling was indeed elevated in cystic kidneys. Interestingly, also activation of signal transducers and activator of transcription 3 (STAT3) strongly correlated with cyst progression. Both pathways were effectively inhibited in vitro by curcumin. Importantly, Pkd1-deletion mice that were treated with curcumin and killed at an early stage of PKD displayed improved renal histology and reduced STAT3 activation, proliferation index, cystic index, and kidney weight/body weight ratios. In addition, renal failure was significantly postponed in mice with severe PKD. These data suggest that multitarget compounds hold promising potential for safe and effective treatment of ADPKD. Show less
Leonhard, W.N.; Wal, A. van der; Novalic, Z.; Kunnen, S.J.; Gansevoort, R.T.; Breuning, M.H.; ... ; Peters, D.J.M. 2011
