Omics technologies to understand drug toxicity mechanisms

Advances in drug-induced liver injury research: in vitro models, mechanisms, omics and gene modulation techniques

Drug-induced liver injury (DILI) refers to drug-mediated damage to the structure and function of the liver, ranging from mild elevation of liver enzymes to severe hepatic insufficiency, and in some cases, progressing to liver failure. The mechanisms and clinical symptoms of DILI are diverse due to the varying combination of drugs, making clinical treatment and prevention complex. DILI has significant public health implications and is the primary reason for post-marketing drug withdrawals. The search for reliable preclinical models and validated biomarkers to predict and investigate DILI can contribute to a more comprehensive understanding of adverse effects and drug safety. In this review, we examine the progress of research on DILI, enumerate in vitro models with potential benefits, and highlight cellular molecular perturbations that may serve as biomarkers. Additionally, we discuss omics approaches frequently used to gather comprehensive datasets on molecular events in response to drug exposure. Finally, three commonly used gene modulation techniques are described, highlighting their application in identifying causal relationships in DILI. Altogether, this review provides a thorough overview of ongoing work and approaches in the field of DILI.

Time-course cross-species transcriptomics reveals conserved hepatotoxicity pathways induced by repeated administration of cyclosporine A

Cyclosporine A (CsA) has shown efficacy against immunity-related diseases despite its toxicity in various organs, including the liver, emphasizing the need to elucidate its underlying hepatotoxicity mechanism. This study aimed to capture the alterations in genome-wide expression over time and the subsequent perturbations of corresponding pathways across species. Six data from humans, mice, and rats, including animal liver tissue, human liver microtissues, and two liver cell lines exposed to CsA toxic dose, were used. The microtissue exposed to CsA for 10 d was analyzed to obtain dynamically differentially expressed genes (DEGs). Single-time points data at 1, 3, 5, 7, and 28 d of different species were used to provide additional evidence. Using liver microtissue-based longitudinal design, DEGs that were consistently up- or down-regulated over time were captured, and the well-known mechanism involved in CsA toxicity was elucidated. Thirty DEGs that consistently changed in longitudinal data were also altered in 28-d rat in-house data with concordant expression. Some genes (e.g. TUBB2A, PLIN2, APOB) showed good concordance with identified DEGs in 1-d and 7-d mouse data. Pathway analysis revealed up-regulations of protein processing, asparagine N-linked glycosylation, and cargo concentration in the endoplasmic reticulum. Furthermore, the down-regulations of pathways related to biological oxidations and metabolite and lipid metabolism were elucidated. These pathways were also enriched in single-time-point data and conserved across species, implying their biological significance and generalizability. Overall, the human organoids-based longitudinal design coupled with cross-species validation provides temporal molecular change tracking, aiding mechanistic elucidation and biologically relevant biomarker discovery.

Cytotoxicity and toxicoproteomics analysis of thiazolidinedione exposure in human-derived cardiomyocytes

Thiazolidinediones (TZDs) (e.g. pioglitazone and rosiglitazone), known insulin sensitiser agents for type II diabetes mellitus, exhibit controversial effects on cardiac tissue. Despite consensus on their association with increased heart failure risk, limiting TZD use in diabetes management, the underlying mechanisms remain uncharacterised. Herein, we report a comprehensive in vitro investigation utilising a novel toxicoproteomics pipeline coupled with cytotoxicity assays in human adult cardiomyocytes to elucidate mechanistic insights into TZD cardiotoxicity. The cytotoxicity assay findings showed a significant loss of mitochondrial adenosine triphosphate production upon exposure to either TZD agents, which may underpin TZD cardiotoxicity. Our toxicoproteomics analysis revealed that mitochondrial dysfunction primarily stems from oxidative phosphorylation impairment, with distinct signalling mechanisms observed for both agents. The type of cell death differed strikingly between the two agents, with rosiglitazone exhibiting features of caspase-dependent apoptosis and pioglitazone implicating mitochondrial-mediated necroptosis, as evidenced by the protein upregulation in the phosphoglycerate mutase family 5-dynamin-related protein 1 axis. Furthermore, our analysis revealed additional mechanistic aspects of cardiotoxicity, showcasing drug specificity. The downregulation of various proteins involved in protein machinery and protein processing in the endoplasmic reticulum was observed in rosiglitazone-treated cells, implicating proteostasis in the rosiglitazone cardiotoxicity. Regarding pioglitazone, the findings suggested the potential activation of the interplay between the complement and coagulation systems and the disruption of the cytoskeletal architecture, which was primarily mediated through the integrin-signalling pathways responsible for pioglitazone-induced myocardial contractile failure. Collectively, this study unlocks substantial mechanistic insight into TZD cardiotoxicity, providing the rationale for future optimisation of antidiabetic therapies.

Toxic effects of fragmented polyethylene terephthalate particles on the marine rotifer Brachionus koreanus: Based on ingestion and egestion assay, in vivo toxicity test, and multi-omics analysis

Microplastics (MPs) are a major concern in marine ecosystem because MPs are persistent and ubiquitous in oceans and are easily consumed by marine biota. Although many studies have reported the toxicity of MPs to marine biota, the toxicity of environmentally relevant types of MPs is little understood. We investigated the toxic effects of fragmented polyethylene terephthalate (PET) MP, one of the most abundant MPs in the ocean, on the marine rotifer Brachionus koreanus at the individual and molecular level. No significant rotifer mortality was observed after exposure to PET MPs for 24 and 48 h. The ingestion and egestion assays showed that rotifers readily ingested PET MPs in the absence of food but not when food was supplied; thus, there were also no chronic effects of PET MPs. In contrast, intracellular reactive oxygen species levels and glutathione S-transferase activity in rotifers were significantly increased by PET MPs. Transcriptomic and metabolomic analyses revealed that genes and metabolites related to energy metabolism and immune processes were significantly affected by PET MPs in a concentration-dependent manner. Although acute toxicity of PET MPs was not observed, PET MPs are potentially toxic to the antioxidant system, immune system, and energy metabolism in rotifers.

Tackling neurodegeneration in vitro with omics: a path towards new targets and drugs

Drug discovery is a generally inefficient and capital-intensive process. For neurodegenerative diseases (NDDs), the development of novel therapeutics is particularly urgent considering the long list of late-stage drug candidate failures. Although our knowledge on the pathogenic mechanisms driving neurodegeneration is growing, additional efforts are required to achieve a better and ultimately complete understanding of the pathophysiological underpinnings of NDDs. Beyond the etiology of NDDs being heterogeneous and multifactorial, this process is further complicated by the fact that current experimental models only partially recapitulate the major phenotypes observed in humans. In such a scenario, multi-omic approaches have the potential to accelerate the identification of new or repurposed drugs against a multitude of the underlying mechanisms driving NDDs. One major advantage for the implementation of multi-omic approaches in the drug discovery process is that these overarching tools are able to disentangle disease states and model perturbations through the comprehensive characterization of distinct molecular layers (i.e., genome, transcriptome, proteome) up to a single-cell resolution. Because of recent advances increasing their affordability and scalability, the use of omics technologies to drive drug discovery is nascent, but rapidly expanding in the neuroscience field. Combined with increasingly advanced in vitro models, which particularly benefited from the introduction of human iPSCs, multi-omics are shaping a new paradigm in drug discovery for NDDs, from disease characterization to therapeutics prediction and experimental screening. In this review, we discuss examples, main advantages and open challenges in the use of multi-omic approaches for the in vitro discovery of targets and therapies against NDDs.

Toxicometabolomics-based cardiotoxicity evaluation of Thiazolidinedione exposure in human-derived cardiomyocytes

INTRODUCTION

Thiazolidinediones (TZDs), represented by pioglitazone and rosiglitazone, are a class of cost-effective oral antidiabetic agents posing a marginal hypoglycaemia risk. Nevertheless, observations of heart failure have hindered the clinical use of both therapies.

OBJECTIVE

Since the mechanism of TZD-induced heart failure remains largely uncharacterised, this study aimed to explore the as-yet-unidentified mechanisms underpinning TZD cardiotoxicity using a toxicometabolomics approach.

METHODS

The present investigation included an untargeted liquid chromatography-mass spectrometry-based toxicometabolomics pipeline, followed by multivariate statistics and pathway analyses to elucidate the mechanism(s)of TZD-induced cardiotoxicity using AC16 human cardiomyocytes as a model, and to identify the prognostic features associated with such effects.

RESULTS

Acute administration of either TZD agent resulted in a significant modulation in carnitine content, reflecting potential disruption of the mitochondrial carnitine shuttle. Furthermore, perturbations were noted in purine metabolism and amino acid fingerprints, strongly conveying aberrations in cardiac energetics associated with TZD usage. Analysis of our findings also highlighted alterations in polyamine (spermine and spermidine) and amino acid (L-tyrosine and valine) metabolism, known modulators of cardiac hypertrophy, suggesting a potential link to TZD cardiotoxicity that necessitates further research. In addition, this comprehensive study identified two groupings - (i) valine and creatine, and (ii) L-tryptophan and L-methionine - that were significantly enriched in the above-mentioned mechanisms, emerging as potential fingerprint biomarkers for pioglitazone and rosiglitazone cardiotoxicity, respectively.

CONCLUSION

These findings demonstrate the utility of toxicometabolomics in elaborating on mechanisms of drug toxicity and identifying potential biomarkers, thus encouraging its application in the toxicological sciences. (245 words).

Evolution and impact of high content imaging

The field of high content imaging has steadily evolved and expanded substantially across many industry and academic research institutions since it was first described in the early 1990's. High content imaging refers to the automated acquisition and analysis of microscopic images from a variety of biological sample types. Integration of high content imaging microscopes with multiwell plate handling robotics enables high content imaging to be performed at scale and support medium- to high-throughput screening of pharmacological, genetic and diverse environmental perturbations upon complex biological systems ranging from 2D cell cultures to 3D tissue organoids to small model organisms. In this perspective article the authors provide a collective view on the following key discussion points relevant to the evolution of high content imaging: • Evolution and impact of high content imaging: An academic perspective • Evolution and impact of high content imaging: An industry perspective • Evolution of high content image analysis • Evolution of high content data analysis pipelines towards multiparametric and phenotypic profiling applications • The role of data integration and multiomics • The role and evolution of image data repositories and sharing standards • Future perspective of high content imaging hardware and software.

The prediction of drug sensitivity by multi-omics fusion reveals the heterogeneity of drug response in pan-cancer

Cancer drug response prediction based on genomic information plays a crucial role in modern pharmacogenomics, enabling individualized therapy. Given the expensive and complexity of biological experiments, computational methods serve as effective tools in predicting cancer drug sensitivity. In this study, we proposed a novel method called Multi-Omics Integrated Collective Variational Autoencoders (MOICVAE), which leverages integrated omics knowledge, including genomic and transcriptomic data, to fill in missing cancer-drug associations and enhance drug sensitivity prediction. Our method employs an encoder-decoder network to learn latent feature representations from cell lines. These learned feature vectors are then fed into a collective variational autoencoder network to train an association matrix. We evaluated MOICVAE on the GDSC and CCLE benchmark datasets using 10-fold cross-validation and achieved impressive AUCs of 0.856 and 0.808, respectively, outperforming state-of-the-art methods. Furthermore, on the TCGA dataset, consisting of 25 drugs across 7 cancer types, MOICVAE exhibited an average AUC of 0.91 in predicting drug sensitivity. Additionally, significant differences were observed in survival, tumor inflammatory assessment, and tumor microenvironment between the predicted drug-sensitive and drug-resistant groups. These results are consistent with predictions made on the METABRIC dataset. Moreover, we discovered that fusing omics data based on mRNA and CNV (copy number variations) yielded superior results in drug sensitivity prediction. MOICVAE not only achieved higher accuracy in drug sensitivity prediction but also provided additional value for combining immunotherapy with chemotherapy, offering patients with more precise treatment options. The code and dataset for MOICVAE are freely available at https://github.com/wanggnoc/MOICVAE.