Inhibition of the renal apical sodium dependent bile acid transporter prevents cholemic nephropathy in mice with obstructive cholestasis.

BACKGROUND & AIMS: Cholemic nephropathy (CN) is a severe complication of cholestatic liver diseases for which there is no specific treatment. We revisited its pathophysiology with the aim of identifying novel therapeutic strategies. METHODS: Cholestasis was induced by bile duct ligation (BDL) in mice. Bile flux in kidneys and livers was visualized by intravital imaging, supported by MALDI mass spectrometry imaging and liquid chromatography-tandem mass spectrometry. The effect of AS0369, a systemically bioavailable apical sodium-dependent bile acid transporter (ASBT) inhibitor, was evaluated by intravital imaging, RNA-sequencing, histological, blood, and urine analyses. Translational relevance was assessed in kidney biopsies from patients with CN, mice with a humanized bile acid (BA) spectrum, and via analysis of serum BAs and KIM-1 (kidney injury molecule 1) in patients with liver disease and hyperbilirubinemia. RESULTS: Proximal tubular epithelial cells (TECs) reabsorbed and enriched BAs, leading to oxidative stress and death of proximal TECs, casts in distal tubules and collecting ducts, peritubular capillary leakiness, and glomerular cysts. Renal ASBT inhibition by AS0369 blocked BA uptake into TECs and prevented kidney injury up to 6 weeks after BDL. Similar results were obtained in mice with humanized BA composition. In patients with advanced liver disease, serum BAs were the main determinant of KIM-1 levels. ASBT expression in TECs was preserved in biopsies from patients with CN, further highlighting the translational potential of targeting ASBT to treat CN. CONCLUSIONS: BA enrichment in proximal TECs followed by oxidative stress and cell death is a key early event in CN. Inhibiting renal ASBT and consequently BA enrichment in TECs prevents CN and systemically decreases BA concentrations. IMPACT AND IMPLICATIONS: Cholemic nephropathy (CN) is a severe complication of cholestasis and an unmet clinical need. We demonstrate that CN is triggered by the renal accumulation of bile acids (BAs) that are considerably increased in the systemic blood. Specifically, the proximal tubular epithelial cells of the kidney take up BAs via the apical sodium-dependent bile acid transporter (ASBT). We developed a therapeutic compound that blocks ASBT in the kidneys, prevents BA overload in tubular epithelial cells, and almost completely abolished all disease hallmarks in a CN mouse model. Renal ASBT inhibition represents a potential therapeutic strategy for patients with CN.

Identifying alert concentrations using a model-based bootstrap approach.

The determination of alert concentrations, where a pre-specified threshold of the response variable is exceeded, is an important goal of concentration-response studies. The traditional approach is based on investigating the measured concentrations and attaining statistical significance of the alert concentration by using a multiple t-test procedure. In this paper, we propose a new model-based method to identify alert concentrations, based on fitting a concentration-response curve and constructing a simultaneous confidence band for the difference of the response of a concentration compared to the control. In order to obtain these confidence bands, we use a bootstrap approach which can be applied to any functional form of the concentration-response curve. This particularly offers the possibility to investigate also those situations where the concentration-response relationship is not monotone and, moreover, to detect alerts at concentrations which were not measured during the study, providing a highly flexible framework for the problem at hand.

Guidance for statistical design and analysis of toxicological dose-response experiments, based on a comprehensive literature review.

The analysis of dose-response, concentration-response, and time-response relationships is a central component of toxicological research. A major decision with respect to the statistical analysis is whether to consider only the actually measured concentrations or to assume an underlying (parametric) model that allows extrapolation. Recent research suggests the application of modelling approaches for various types of toxicological assays. However, there is a discrepancy between the state of the art in statistical methodological research and published analyses in the toxicological literature. The extent of this gap is quantified in this work using an extensive literature review that considered all dose-response analyses published in three major toxicological journals in 2021. The aspects of the review include biological considerations (type of assay and of exposure), statistical design considerations (number of measured conditions, design, and sample sizes), and statistical analysis considerations (display, analysis goal, statistical testing or modelling method, and alert concentration). Based on the results of this review and the critical assessment of three selected issues in the context of statistical research, concrete guidance for planning, execution, and analysis of dose-response studies from a statistical viewpoint is proposed.

Interruption of bile acid uptake by hepatocytes after acetaminophen overdose ameliorates hepatotoxicity.

BACKGROUND & AIMS: Acetaminophen (APAP) overdose remains a frequent cause of acute liver failure, which is generally accompanied by increased levels of serum bile acids (BAs). However, the pathophysiological role of BAs remains elusive. Herein, we investigated the role of BAs in APAP-induced hepatotoxicity. METHODS: We performed intravital imaging to investigate BA transport in mice, quantified endogenous BA concentrations in the serum of mice and patients with APAP overdose, analyzed liver tissue and bile by mass spectrometry and MALDI-mass spectrometry imaging, assessed the integrity of the blood-bile barrier and the role of oxidative stress by immunostaining of tight junction proteins and intravital imaging of fluorescent markers, identified the intracellular cytotoxic concentrations of BAs, and performed interventions to block BA uptake from blood into hepatocytes. RESULTS: Prior to the onset of cell death, APAP overdose causes massive oxidative stress in the pericentral lobular zone, which coincided with a breach of the blood-bile barrier. Consequently, BAs leak from the bile canaliculi into the sinusoidal blood, which is then followed by their uptake into hepatocytes via the basolateral membrane, their secretion into canaliculi and repeated cycling. This, what we termed 'futile cycling' of BAs, led to increased intracellular BA concentrations that were high enough to cause hepatocyte death. Importantly, however, the interruption of BA re-uptake by pharmacological NTCP blockage using Myrcludex B and Oatp knockout strongly reduced APAP-induced hepatotoxicity. CONCLUSIONS: APAP overdose induces a breach of the blood-bile barrier which leads to futile BA cycling that causes hepatocyte death. Prevention of BA cycling may represent a therapeutic option after APAP intoxication. LAY SUMMARY: Only one drug, N-acetylcysteine, is approved for the treatment of acetaminophen overdose and it is only effective when given within ∼8 hours after ingestion. We identified a mechanism by which acetaminophen overdose causes an increase in bile acid concentrations (to above toxic thresholds) in hepatocytes. Blocking this mechanism prevented acetaminophen-induced hepatotoxicity in mice and evidence from patients suggests that this therapy may be effective for longer periods after ingestion compared to N-acetylcysteine.

Comparison Of Observation-Based And Model-Based Identification Of Alert Concentrations From Concentration-Expression Data.

MOTIVATION: An important goal of concentration-response studies in toxicology is to determine an 'alert' concentration where a critical level of the response variable is exceeded. In a classical observation-based approach, only measured concentrations are considered as potential alert concentrations. Alternatively, a parametric curve is fitted to the data that describes the relationship between concentration and response. For a prespecified effect level, both an absolute estimate of the alert concentration and an estimate of the lowest concentration where the effect level is exceeded significantly are of interest. RESULTS: In a simulation study for gene expression data, we compared the observation-based and the model-based approach for both absolute and significant exceedance of the prespecified effect level. Results show that, compared to the observation-based approach, the model-based approach overestimates the true alert concentration less often and more frequently leads to a valid estimate, especially for genes with large variance. AVAILABILITY AND IMPLEMENTATION: The code used for the simulation studies is available via the GitHub repository: https://github.com/FKappenberg/Paper-IdentificationAlertConcentrations. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Classification of Developmental Toxicants in a Human iPSC Transcriptomics-Based Test.

Despite the progress made in developmental toxicology, there is a great need for in vitro tests that identify developmental toxicants in relation to human oral doses and blood concentrations. In the present study, we established the hiPSC-based UKK2 in vitro test and analyzed genome-wide expression profiles of 23 known teratogens and 16 non-teratogens. Compounds were analyzed at the maximal plasma concentration (Cmax) and at 20-fold Cmax for a 24 h incubation period in three independent experiments. Based on the 1000 probe sets with the highest variance and including information on cytotoxicity, penalized logistic regression with leave-one-out cross-validation was used to classify the compounds as test-positive or test-negative, reaching an area under the curve (AUC), accuracy, sensitivity, and specificity of 0.96, 0.92, 0.96, and 0.88, respectively. Omitting the cytotoxicity information reduced the test performance to an AUC of 0.94, an accuracy of 0.79, and a sensitivity of 0.74. A second method, which used the number of significantly deregulated probe sets to classify the compounds, resulted in a specificity of 1; however, the AUC (0.90), accuracy (0.90), and sensitivity (0.83) were inferior compared to those of the logistic regression-based procedure. Finally, no increased performance was achieved when the high test concentrations (20-fold Cmax) were used, in comparison to testing within the realistic clinical range (1-fold Cmax). In conclusion, although further optimization is required, for example, by including additional readouts and cell systems that model different developmental processes, the UKK2-test in its present form can support the early discovery-phase detection of human developmental toxicants.

Model selection characteristics when using MCP-Mod for dose-response gene expression data.

We extend the scope of application for MCP-Mod (Multiple Comparison Procedure and Modeling) to in vitro gene expression data and assess its characteristics regarding model selection for concentration gene expression curves. Precisely, we apply MCP-Mod on single genes of a high-dimensional gene expression data set, where human embryonic stem cells were exposed to eight concentration levels of the compound valproic acid (VPA). As candidate models we consider the sigmoid Emax$E_{\max }$ (four-parameter log-logistic), linear, quadratic, Emax$E_{\max }$ , exponential, and beta model. Through simulations we investigate the impact of omitting one or more models from the candidate model set to uncover possibly superfluous models and to evaluate the precision and recall rates of selected models. Each model is selected according to Akaike information criterion (AIC) for a considerable number of genes. For less noisy cases the popular sigmoid Emax$E_{\max }$ model is frequently selected. For more noisy data, often simpler models like the linear model are selected, but mostly without relevant performance advantage compared to the second best model. Also, the commonly used standard Emax$E_{\max }$ model has an unexpected low performance.

Handling deviating control values in concentration-response curves.

In cell biology, pharmacology and toxicology dose-response and concentration-response curves are frequently fitted to data with statistical methods. Such fits are used to derive quantitative measures (e.g. EC[Formula: see text] values) describing the relationship between the concentration of a compound or the strength of an intervention applied to cells and its effect on viability or function of these cells. Often, a reference, called negative control (or solvent control), is used to normalize the data. The negative control data sometimes deviate from the values measured for low (ineffective) test compound concentrations. In such cases, normalization of the data with respect to control values leads to biased estimates of the parameters of the concentration-response curve. Low quality estimates of effective concentrations can be the consequence. In a literature study, we found that this problem occurs in a large percentage of toxicological publications. We propose different strategies to tackle the problem, including complete omission of the controls. Data from a controlled simulation study indicate the best-suited problem solution for different data structure scenarios. This was further exemplified by a real concentration-response study. We provide the following recommendations how to handle deviating controls: (1) The log-logistic 4pLL model is a good default option. (2) When there are at least two concentrations in the no-effect range, low variances of the replicate measurements, and deviating controls, control values should be omitted before fitting the model. (3) When data are missing in the no-effect range, the Brain-Cousens model sometimes leads to better results than the default model.

Prediction of human drug-induced liver injury (DILI) in relation to oral doses and blood concentrations.

Drug-induced liver injury (DILI) cannot be accurately predicted by animal models. In addition, currently available in vitro methods do not allow for the estimation of hepatotoxic doses or the determination of an acceptable daily intake (ADI). To overcome this limitation, an in vitro/in silico method was established that predicts the risk of human DILI in relation to oral doses and blood concentrations. This method can be used to estimate DILI risk if the maximal blood concentration (Cmax) of the test compound is known. Moreover, an ADI can be estimated even for compounds without information on blood concentrations. To systematically optimize the in vitro system, two novel test performance metrics were introduced, the toxicity separation index (TSI) which quantifies how well a test differentiates between hepatotoxic and non-hepatotoxic compounds, and the toxicity estimation index (TEI) which measures how well hepatotoxic blood concentrations in vivo can be estimated. In vitro test performance was optimized for a training set of 28 compounds, based on TSI and TEI, demonstrating that (1) concentrations where cytotoxicity first becomes evident in vitro (EC10) yielded better metrics than higher toxicity thresholds (EC50); (2) compound incubation for 48 h was better than 24 h, with no further improvement of TSI after 7 days incubation; (3) metrics were moderately improved by adding gene expression to the test battery; (4) evaluation of pharmacokinetic parameters demonstrated that total blood compound concentrations and the 95%-population-based percentile of Cmax were best suited to estimate human toxicity. With a support vector machine-based classifier, using EC10 and Cmax as variables, the cross-validated sensitivity, specificity and accuracy for hepatotoxicity prediction were 100, 88 and 93%, respectively. Concentrations in the culture medium allowed extrapolation to blood concentrations in vivo that are associated with a specific probability of hepatotoxicity and the corresponding oral doses were obtained by reverse modeling. Application of this in vitro/in silico method to the rat hepatotoxicant pulegone resulted in an ADI that was similar to values previously established based on animal experiments. In conclusion, the proposed method links oral doses and blood concentrations of test compounds to the probability of hepatotoxicity.

Relevance of the incubation period in cytotoxicity testing with primary human hepatocytes.

Primary human hepatocytes (PHHs) remain the gold standard for in vitro testing in the field of pharmacology and toxicology. One crucial parameter influencing the results of in vitro tests is the incubation period with test compounds. It has been suggested that longer incubation periods may be critical for the prediction of repeated dose toxicity. However, a study that systematically analyzes the relationship between incubation period and cytotoxicity in PHHs is not available. To close this gap, 30 compounds were tested in a concentration-dependent manner for cytotoxicity in cultivated cryopreserved PHHs (three donors per compound) for 1, 2 and 7 days. The median of the EC50 values of all compounds decreased 1.78-fold on day 2 compared to day 1, and 1.89-fold on day 7 compared to day 1. Median values of EC50 ratios of all compounds at day 2 and day 7 were close to one but for individual compounds the ratio increased up to almost six. Strong correlations were obtained for EC50 on day 1 and day 7 (R = 0.985; 95% CI 0.960-0.994), day 1 and day 2 (R = 0.964; 95% CI 0.910-0.986), as well as day 2 and day 7 (R = 0.981; 95% CI 0.955-0.992). However, compound specific differences also occurred. Whereas, for example, busulfan showed a relatively strong increase on day 7 compared to day 1, cytotoxicity of acetaminophen did not increase during longer incubation periods. To validate the observed correlations, a publicly available data set, containing data on the cytotoxicity of human hepatocytes cultivated as spheroids for incubation periods of 5 and 14 days, was analyzed. A high correlation coefficient of EC50 values at day 5 and day 14 was obtained (R = 0.894; 95% CI 0.798-0.945). In conclusion, the median cytotoxicity of the test compounds increased between 1 and 2 days of incubation, with no or only a minimal further increase until day 7. It remains to be studied whether the different results obtained for some individual compounds after longer exposure periods would correspond better to human-repeated dose toxicity.

Information sharing in high-dimensional gene expression data for improved parameter estimation in concentration-response modelling.

In toxicological concentration-response studies, a frequent goal is the determination of an 'alert concentration', i.e. the lowest concentration where a notable change in the response in comparison to the control is observed. In high-throughput gene expression experiments, e.g. based on microarray or RNA-seq technology, concentration-response profiles can be measured for thousands of genes simultaneously. One approach for determining the alert concentration is given by fitting a parametric model to the data which allows interpolation between the tested concentrations. It is well known that the quality of a model fit improves with the number of measured data points. However, adding new replicates for existing concentrations or even several replicates for new concentrations is time-consuming and expensive. Here, we propose an empirical Bayes approach to information sharing across genes, where in essence a weighted mean of the individual estimate for one specific parameter of a fitted model and the mean of all estimates of the entire set of genes is calculated as a result. Results of a controlled plasmode simulation study show that for many genes a notable improvement in terms of the mean squared error (MSE) between estimate and true underlying value of the parameter can be observed. However, for some genes, the MSE increases, and this cannot be prevented by using a more sophisticated prior distribution in the Bayesian approach.

Benefit of using interaction effects for the analysis of high-dimensional time-response or dose-response data for two-group comparisons.

High throughput RNA sequencing experiments are widely conducted and analyzed to identify differentially expressed genes (DEGs). The statistical models calculated for this task are often not clear to practitioners, and analyses may not be optimally tailored to the research hypothesis. Often, interaction effects (IEs) are the mathematical equivalent of the biological research question but are not considered for different reasons. We fill this gap by explaining and presenting the potential benefit of IEs in the search for DEGs using RNA-Seq data of mice that receive different diets for different time periods. Using an IE model leads to a smaller, but likely more biologically informative set of DEGs compared to a common approach that avoids the calculation of IEs.

Transcriptome-based prediction of drugs, inhibiting cardiomyogenesis in human induced pluripotent stem cells.

Animal studies for embryotoxicity evaluation of potential therapeutics and environmental factors are complex, costly, and time-consuming. Often, studies are not of human relevance because of species differences. In the present study, we recapitulated the process of cardiomyogenesis in human induced pluripotent stem cells (hiPSCs) by modulation of the Wnt signaling pathway to identify a key cardiomyogenesis gene signature that can be applied to identify compounds and/or stress factors compromising the cardiomyogenesis process. Among the 23 tested teratogens and 16 non-teratogens, we identified three retinoids including 13-cis-retinoic acid that completely block the process of cardiomyogenesis in hiPSCs. Moreover, we have identified an early gene signature consisting of 31 genes and associated biological processes that are severely affected by the retinoids. To predict the inhibitory potential of teratogens and non-teratogens in the process of cardiomyogenesis we established the "Developmental Cardiotoxicity Index" (CDI31g) that accurately differentiates teratogens and non-teratogens to do or do not affect the differentiation of hiPSCs to functional cardiomyocytes.

Risk assessment of parabens in a transcriptomics-based in vitro test.

Parabens have been used for decades as preservatives in food, drugs and cosmetics. The majority however, were banned in 2009 and 2014 leaving only methyl-, ethyl-, propyl-, and butyl-derivates available for subsequent use. Methyl- and propylparaben have been extensively tested in vivo, with no resulting evidence for developmental and reproductive toxicity (DART). In contrast, ethylparaben has not yet been tested for DART in animal experiments, and it is currently debated if additional animal studies are warranted. In order to perform a comparison of the four currently approved parabens, we used a previously established in vitro test based on human induced pluripotent stem cells (iPSC) that are exposed to test substances during their differentiation to neuroectodermal cells. EC50 values for cytotoxicity were 906 µM, 698 µM, 216 µM and 63 µM for methyl-, ethyl-, propyl- and butylparaben, respectively, demonstrating that cytotoxicity increases with increasing alkyl chain length. Genome-wide analysis demonstrated that FDR-adjusted significant gene expression changes occurred only at cytotoxic or close to cytotoxic concentrations, for example 1720 differentially expressed genes (DEG) at 1000 µM ethylparaben, 1 DEG at 316 µM, and no DEG at 100 µM or lower concentrations. The highest concentration of ethylparaben that did not induce any cytotoxicity nor DEG was 1670-fold above the highest concentration reported in biomonitoring studies (60 nM ethylparaben in cord blood). In conclusion, cytotoxicity and gene expression alterations of ethylparaben occurred at concentrations of approximately three orders of magnitude above human blood concentrations; moreover, the substance fitted well into a scenario where toxicity increases with the alkyl chain length, and gene expression changes only occur at cytotoxic or close to cytotoxic concentrations. Therefore, no evidence was obtained suggesting that in vivo DART with ethylparaben would lead to different results as the methyl- or propyl derivates.

Discordance of HER2-Low between Primary Tumors and Matched Distant Metastases in Breast Cancer.

We examined differences in HER2 expression between primary tumors and distant metastases, particularly within the HER2-negative primary breast cancer cohort (HER2-low and HER2-zero). The retrospective study included 191 consecutive paired samples of primary breast cancer and distant metastases diagnosed between 1995 and 2019. HER2-negative samples were divided into HER2-zero (immunohistochemistry [IHC] score 0) and HER2-low (IHC score 1+ or 2+/in situ hybridization [ISH]-negative). The main objective was to analyze the discordance rate between matched primary and metastatic samples, focusing on the site of distant metastasis, molecular subtype, and de novo metastatic breast cancer. The relationship was determined by cross-tabulation and calculation of Cohen's Kappa coefficient. The final study cohort included 148 paired samples. The largest proportion in the HER2-negative cohort was HER2-low [primary tumor 61.4% (n = 78), metastatic samples 73.5% (n = 86)]. The discordance rate between the HER2 status of primary tumors and corresponding distant metastases was 49.6% (n = 63) (Kappa -0.003, 95%CI -0.15-0.15). Development of a HER2-low phenotype occurred most frequently (n = 52, 40.9%), mostly with a switch from HER2-zero to HER2-low (n = 34, 26.8%). Relevant HER2 discordance rates were observed between different metastatic sites and molecular subtypes. Primary metastatic breast cancer had a significantly lower HER2 discordance rate than secondary metastatic breast cancer [30.2% (Kappa 0.48, 95%CI 0.27-0.69) versus 50.5% (Kappa 0.14, 95% CI -0.03-0.32)]. This highlights the importance of evaluating potentially therapy-relevant discordance rates between a primary tumor and corresponding distant metastases.

Influence of bile acids on the cytotoxicity of chemicals in cultivated human hepatocytes.

Bile acids (BA) are known to influence the susceptibility of hepatocytes to chemicals. We investigated the cytotoxicity of 18 compounds with known hepatotoxicity status and pharmacokinetics in cultivated primary human hepatocytes with and without the addition of a BA mix to the cell culture medium. This BA mix consisted of physiological ratios of the most abundant human BA at a cholestatic sum concentration of 0.5 mM, which corresponds to 50% of the EC10 (cytotoxicity) of the mix. The BA mix decreased the EC10 of 7 compounds by a factor greater than 1.5, but also increased the EC10 of 5 compounds. The compounds with increased susceptibility include the known hepatotoxicants and BSEP/MRP2 inhibitors rifampicin, ketoconazole, atorvastatin, and cyclosporin A. However, the cytotoxicity of some non-hepatotoxic compounds was also enhanced, among them glucose, which is not known to be an inhibitor of canalicular bile acid export. A recently established technique to quantify how well hepatotoxic and non-hepatotoxic compounds are separated by an in vitro test indicated that the addition of the BA mix did not improve separation. In conclusion, the addition of BA to cultivated hepatocytes leads to a complex situation with increased and decreased susceptibilities depending on the specific compound.

Long-term prognostic significance of HER2-low and HER2-zero in node-negative breast cancer.

BACKGROUND: Recently, novel antibody--drug conjugates (ADCs) showed clinical activity in a subset of advanced human epidermal growth factor receptor 2 (HER2)-negative patients. We investigated the prognostic significance of HER2-low and HER2-zero tumours. PATIENTS AND METHODS: The retrospective cohort study included 410 consecutive node-negative breast cancer patients without adjuvant systemic therapy treated between 1985 and 2000 (median follow-up: 16.73 [IQR 8.58-23.45] years). 351 (85.6%) were HER-2 negative and subdivided into HER2-zero (immunohistochemistry [IHC] score 0) and HER2-low (IHC score 1+ or 2+/in situ hybridisation [ISH]-negative). HER2 gene expression was available in 170 (48.4%) patients. Differences in HER2 status for immunohistochemistry, gene expression and clinico-pathologic parameters were assessed using Fisher's exact test, Pearson's correlation and Mann-Whitney test. Prognosis was investigated using the Kaplan-Meier method and Cox regression analyses. RESULTS: Of the 351 HER2-negative patients, 198 (56.4%) had HER2-low tumours and 153 (43.6%) were HER2-zero. Significant differences between HER2-zero and HER2-low tumours were found in histologic grading (P = 0.001), Ki-67 (P = 0.013) and HER2 gene expression (P = 0.002). HER2-low patients had significantly longer disease-free survival (DFS) (15-year rate: 67.5% [95% CI 61.0-74.7] vs. 47.3% [95% CI 39.9-56.1], P < 0.001) and overall survival (OS) (15-year rate: 75.4% [95% CI 69.4-81.9] vs. 66.8% [95% CI 59.5-74.9], P = 0.009). The OS difference was observed in hormone receptor (HR)-positive (P = 0.039) but not HR-negative (P = 0.086) tumours. The results of multivariable analyses confirmed the independent prognostic significance of HER2 status (DFS: HR, 0.546; 95% CI, 0.402-0.743; P < 0.001; OS: HR, 0.653; 95% CI, 0.458-0.932; P = 0.019). CONCLUSION: HER2-low patients had a better survival than HER2-zero patients.

High Accuracy Classification of Developmental Toxicants by In Vitro Tests of Human Neuroepithelial and Cardiomyoblast Differentiation.

Human-relevant tests to predict developmental toxicity are urgently needed. A currently intensively studied approach makes use of differentiating human stem cells to measure chemically-induced deviations of the normal developmental program, as in a recent study based on cardiac differentiation (UKK2). Here, we (i) tested the performance of an assay modeling neuroepithelial differentiation (UKN1), and (ii) explored the benefit of combining assays (UKN1 and UKK2) that model different germ layers. Substance-induced cytotoxicity and genome-wide expression profiles of 23 teratogens and 16 non-teratogens at human-relevant concentrations were generated and used for statistical classification, resulting in accuracies of the UKN1 assay of 87-90%. A comparison to the UKK2 assay (accuracies of 90-92%) showed, in general, a high congruence in compound classification that may be explained by the fact that there was a high overlap of signaling pathways. Finally, the combination of both assays improved the prediction compared to each test alone, and reached accuracies of 92-95%. Although some compounds were misclassified by the individual tests, we conclude that UKN1 and UKK2 can be used for a reliable detection of teratogens in vitro, and that a combined analysis of tests that differentiate hiPSCs into different germ layers and cell types can even further improve the prediction of developmental toxicants.

The hepatocyte export carrier inhibition assay improves the separation of hepatotoxic from non-hepatotoxic compounds.

An in vitro/in silico method that determines the risk of human drug induced liver injury in relation to oral doses and blood concentrations of drugs was recently introduced. This method utilizes information on the maximal blood concentration (Cmax) for a specific dose of a test compound, which can be estimated using physiologically-based pharmacokinetic modelling, and a cytotoxicity test in cultured human hepatocytes. In the present study, we analyzed if the addition of an assay that measures the inhibition of bile acid export carriers, like BSEP and/or MRP2, to the existing method improves the differentiation of hepatotoxic and non-hepatotoxic compounds. Therefore, an export assay for 5-chloromethylfluorescein diacetate (CMFDA) was established. We tested 36 compounds in a concentration-dependent manner for which the risk of hepatotoxicity for specific oral doses and the capacity to inhibit hepatocyte export carriers are known. Compared to the CTB cytotoxicity test, substantially lower EC10 values were obtained using the CMFDA assay for several known BSEP and/or MRP2 inhibitors. To quantify if the addition of the CMFDA assay to our test system improves the overall separation of hepatotoxic from non-hepatotoxic compounds, the toxicity separation index (TSI) was calculated. We obtained a better TSI using the lower alert concentration from either the CMFDA or the CTB test (TSI: 0.886) compared to considering the CTB test alone (TSI: 0.775). In conclusion, the data show that integration of the CMFDA assay with an in vitro test battery improves the differentiation of hepatotoxic and non-hepatotoxic compounds in a set of compounds that includes bile acid export carrier inhibitors.

In vitro/in silico prediction of drug induced steatosis in relation to oral doses and blood concentrations by the Nile Red assay.

The accumulation of lipid droplets in hepatocytes is a key feature of drug-induced liver injury (DILI) and can be induced by a subset of hepatotoxic compounds. In the present study, we optimized and evaluated an in vitro technique based on the fluorescent dye Nile Red, further named Nile Red assay to quantify lipid droplets induced by the exposure to chemicals. The Nile Red assay and a cytotoxicity test (CTB assay) were then performed on cells exposed concentration-dependently to 60 different compounds. Of these, 31 were known to induce hepatotoxicity in humans, and 13 were reported to also cause steatosis. In order to compare in vivo relevant blood concentrations, pharmacokinetic models were established for all compounds to simulate the maximal blood concentrations (Cmax) at therapeutic doses. The results showed that several hepatotoxic compounds induced an increase in lipid droplets at sub-cytotoxic concentrations. To compare how well (1) the cytotoxicity test alone, (2) the Nile Red assay alone, and (3) the combination of the cytotoxicity test and the Nile Red assay (based on the lower EC10 of both assays) allow the differentiation between hepatotoxic and non-hepatotoxic compounds, a previously established performance metric, the Toxicity Separation Index (TSI) was calculated. In addition, the Toxicity Estimation Index (TEI) was calculated to determine how well blood concentrations that cause an increased DILI risk can be estimated for hepatotoxic compounds. Our findings indicate that the combination of both assays improved the TSI and TEI compared to each assay alone. In conclusion, the study demonstrates that inclusion of the Nile Red assay into in vitro test batteries may improve the prediction of DILI compounds.