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Assessment of Drug-Induced Liver Injury through Cell Morphology and Gene Expression Analysis

Feb 7, 2024 | 2023, Chemical Research in Toxicology, Journal publications

Abstract

Drug-induced liver injury (DILI) is a significant concern in drug development, often leading to drug withdrawal. Although many studies aim to identify biomarkers and gene/pathway signatures related to liver toxicity and aim to predict DILI compounds, this remains a challenge in drug discovery. With a strong development of high-content screening/imaging (HCS/HCI) for phenotypic screening, we explored the morphological cell perturbations induced by DILI compounds. In the first step, cell morphological signatures were associated with two datasets of DILI chemicals (DILIRank and eTox). The mechanisms of action were then analyzed for chemicals having transcriptomics data and sharing similar morphological perturbations. Signaling pathways associated with liver toxicity (cell cycle, cell growth, apoptosis, …) were then captured, and a hypothetical relation between cell morphological perturbations and gene deregulation was illustrated within our analysis. Finally, using the cell morphological signatures, machine learning approaches were developed to predict chemicals with a potential risk of DILI. Some models showed relevant performance with validation set balanced accuracies between 0.645 and 0.739. Overall, our findings demonstrate the utility of combining HCI with transcriptomics data to identify the morphological and gene expression signatures related to DILI chemicals. Moreover, our protocol could be extended to other toxicity end points, offering a promising avenue for comprehensive toxicity assessment in drug discovery.

An Adverse Outcome Pathway Network for Chemically Induced Oxidative Stress Leading to (Non)genotoxic Carcinogenesis

May 22, 2023 | 2023, Chemical Research in Toxicology, Journal publications

Abstract

Nongenotoxic (NGTX) carcinogens induce cancer via other mechanisms than direct DNA damage. A recognized mode of action for NGTX carcinogens is induction of oxidative stress, a state in which the amount of oxidants in a cell exceeds its antioxidant capacity, leading to regenerative proliferation. Currently, carcinogenicity assessment of environmental chemicals primarily relies on genetic toxicity end points. Since NGTX carcinogens lack genotoxic potential, these chemicals may remain undetected in such evaluations. To enhance the predictivity of test strategies for carcinogenicity assessment, a shift toward mechanism-based approaches is required. Here, we present an adverse outcome pathway (AOP) network for chemically induced oxidative stress leading to (NGTX) carcinogenesis. To develop this AOP network, we first investigated the role of oxidative stress in the various cancer hallmarks. Next, possible mechanisms for chemical induction of oxidative stress and the biological effects of oxidative damage to macromolecules were considered. This resulted in an AOP network, of which associated uncertainties were explored. Ultimately, development of AOP networks relevant for carcinogenesis in humans will aid the transition to a mechanism-based, human relevant carcinogenicity assessment that involves a substantially lower number of laboratory animals.

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

Mar 2, 2023 | 2022, Chemical Research in Toxicology, Journal publications

Abstract

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.