In vitro transcriptomic prediction of hepatotoxicity for early drug discovery

KDR polymorphism (1192G/A, 1719A/T) and modulation of ARV drug-induced hepatotoxicity

Kinase insert Domain containing Receptor (KDR)/Vascular Endothelial Growth Factor Receptor (VEGFR-2) participate in endothelial dysfunction, which can lead to chronic liver disease. KDR reflects naturally against the toxicants from the damaged liver cells. Association of KDR polymorphism has been reported with many diseases including liver disease, but its role has not been described in ARV induced hepatotoxicity. Hence, we examined the exonic regions KDR (1192G/A, 1719A/T) polymorphism from 165 HIV-infected individuals (34/165 had ARV induced hepatotoxicity, 131/165 were with no hepatotoxicity) and 160 normal uninfected individuals by PCR-RFLP. In univariate analysis, KDR 1719 TT genotype presented at greater frequency from all HIV positive individuals in contrast with normal uninfected individuals (7.87% vs. 4.4%, OR = 1.72, P = 0.38). Individuals with KDR 1719 TT genotype had a risk for increasing hepatotoxicity and its severity (OR = 1.91, P = 0.38). Individuals with haplotype AT had risk for increasing hepatotoxicity and its severity (OR = 1.60, P = 0.50; OR = 2.35, P = 0.27). Whereas haplotype AA was associated with reduced risk of developing hepatotoxicity (OR = 0.40, P = 0.04). Individuals with KDR 1719 TT genotype were at greater risk of advancement of HIV disease (OR = 2.31, P = 0.23). Individuals with KDR 1719 TT genotype had more vulnerability for developing hepatotoxicity among alcohol users (OR = 2.57, P = 0.23). Individuals with KDR 1719 TT genotype were at higher risk of developing hepatotoxicity and its severity among nevirapine and alcohol consumers (OR = 2.47, P = 0.24; OR = 5.42, P = 0.42). In multivariate analysis, hepatotoxicity patients taking ART inclusive of nevirapine was associated with the severity of hepatotoxicity (OR = 4.82, P = 0.002). In conclusion, KDR 1719 TT genotype and haplotype AT may have a risk for development of hepatotoxicity and its severity. Haplotype AA may have influence to reduce the risk of developing hepatotoxicity.

Signaling Pathways Regulated by Silica Nanoparticles

Silica nanoparticles are a class of molecules commonly used in drug or gene delivery systems that either facilitate the delivery of therapeutics to specific drug targets or enable the efficient delivery of constructed gene products into biological systems. Some in vivo or in vitro studies have demonstrated the toxic effects of silica nanoparticles. Despite the availability of risk management tools in response to the growing use of synthetic silica in commercial products, the molecular mechanism of toxicity induced by silica nanoparticles is not well characterized. The purpose of this study was to elucidate the effects of silica nanoparticle exposure in three types of cells including human aortic endothelial cells, mouse-derived macrophages, and A549 non-small cell lung cancer cells using toxicogenomic analysis. The results indicated that among all three cell types, the TNF and MAPK signaling pathways were the common pathways upregulated by silica nanoparticles. These findings may provide insight into the effects of silica nanoparticle exposure in the human body and the possible mechanism of toxicity.

The Association between the Usage of Non-Steroidal Anti-Inflammatory Drugs and Cognitive Status: Analysis of Longitudinal and Cross-Sectional Studies from the Global Alzheimer's Association Interactive Network and Transcriptomic Data

The degenerative cognitive and physical decline of Alzheimer patients, coupled with the extensive psychological and economic tolls imposed on family members that serve as caretakers, necessitate the discovery of effective cures and preventative measures for age-related cognitive depreciation. In the journey of Alzheimer’s disease treatment discovery, several cross-sectional and longitudinal studies have delineated a noticeable association between the use of nonsteroidal anti-inflammatory drugs (NSAIDs), a class of low-cost drugs with minimal side effects, and the alleviation of age-related memory impairment. In this study, four datasets (two cross-sectional and two longitudinal studies) derived from the Global Alzheimer’s Association Interactive Network (GAAIN) were analyzed. The significant association between the usage of NSAIDs and better cognitive status was observed. The results agree with the findings of previous studies that the use of NSAIDs may be beneficial in the early stages of Alzheimer’s disease. Transcriptomic data show that ibuprofen treatment results in upregulation of several genes involved in arachidonic acid metabolism including PPARγ, Cyp4a12b, Cyp2c66, and Cyp2c37 in the hippocampus. The increase in conversion of arachidonic acid into anti-inflammatory 16C and 18C dicarboxylic acids as well as epoxyeicosatrienoic acids may play a role in reducing the risk of Alzheimer’s disease development.

Integration of metabolomics and transcriptomics in nanotoxicity studies

Biomedical research involving nanoparticles has produced useful products with medical applications. However, the potential toxicity of nanoparticles in biofluids, cells, tissues, and organisms is a major challenge. The '-omics' analyses provide molecular profiles of multifactorial biological systems instead of focusing on a single molecule. The 'omics' approaches are necessary to evaluate nanotoxicity because classical methods for the detection of nanotoxicity have limited ability in detecting miniscule variations within a cell and do not accurately reflect the actual levels of nanotoxicity. In addition, the 'omics' approaches allow analyses of in-depth changes and compensate for the differences associated with high-throughput technologies between actual nanotoxicity and results from traditional cytotoxic evaluations. However, compared with a single omics approach, integrated omics provides precise and sensitive information by integrating complex biological conditions. Thus, these technologies contribute to extended safety evaluations of nanotoxicity and allow the accurate diagnoses of diseases far earlier than was once possible in the nanotechnology era. Here, we review a novel approach for evaluating nanotoxicity by integrating metabolomics with metabolomic profiling and transcriptomics, which is termed "metabotranscriptomics". [BMB Reports 2018; 51(1): 14-20].

Transcriptomics in toxicology

Xenobiotics, of which many are toxic, may enter the human body through multiple routes. Excessive human exposure to xenobiotics may exceed the body's capacity to defend against the xenobiotic-induced toxicity and result in potentially fatal adverse health effects. Prevention of the adverse health effects, potentially associated with human exposure to the xenobiotics, may be achieved by detecting the toxic effects at an early, reversible and, therefore, preventable stage. Additionally, an understanding of the molecular mechanisms underlying the toxicity may be helpful in preventing and/or managing the ensuing adverse health effects. Human exposures to a large number of xenobiotics are associated with hepatotoxicity or pulmonary toxicity. Global gene expression changes taking place in biological systems, in response to exposure to xenobiotics, may represent the early and mechanistically relevant cellular events contributing to the onset and progression of xenobiotic-induced adverse health outcomes. Hepatotoxicity and pulmonary toxicity resulting from exposure to xenobiotics are discussed as specific examples to demonstrate the potential application of transcriptomics or global gene expression analysis in the prevention of adverse health effects associated with exposure to xenobiotics.

Idiosyncratic Drug-Induced Liver Injury (IDILI): Potential Mechanisms and Predictive Assays

Idiosyncratic drug-induced liver injury (IDILI) is a significant source of drug recall and acute liver failure (ALF) in the United States. While current drug development processes emphasize general toxicity and drug metabolizing enzyme- (DME-) mediated toxicity, it has been challenging to develop comprehensive models for assessing complete idiosyncratic potential. In this review, we describe the enzymes and proteins that contain polymorphisms believed to contribute to IDILI, including ones that affect phase I and phase II metabolism, antioxidant enzymes, drug transporters, inflammation, and human leukocyte antigen (HLA). We then describe the various assays that have been developed to detect individual reactions focusing on each of the mechanisms described in the background. Finally, we examine current trends in developing comprehensive models for examining these mechanisms. There is an urgent need to develop a panel of multiparametric assays for diagnosing individual toxicity potential.

Using Chemical-Induced Gene Expression in Cultured Human Cells to Predict Chemical Toxicity

Chemical toxicity is conventionally evaluated in animal models. However, animal models are resource intensive; moreover, they face ethical and scientific challenges because the outcomes obtained by animal testing may not correlate with human responses. To develop an alternative method for assessing chemical toxicity, we investigated the feasibility of using chemical-induced genome-wide expression changes in cultured human cells to predict the potential of a chemical to cause specific organ injuries in humans. We first created signatures of chemical-induced gene expression in a vertebral-cancer of the prostate cell line for ∼15,000 chemicals tested in the US National Institutes of Health Library of Integrated Network-Based Cellular Signatures program. We then used the signatures to create naı̈ve Bayesian prediction models for chemical-induced human liver cholestasis, interstitial nephritis, and long QT syndrome. Detailed cross-validation analyses indicated that the models were robust with respect to false positives and false negatives in the samples we used to train the models and could predict the likelihood that chemicals would cause specific organ injuries. In addition, we performed a literature search for drugs and dietary supplements, not formally categorized as causing organ injuries in humans but predicted by our models to be most likely to do so. We found a high percentage of these compounds associated with case reports of relevant organ injuries, lending support to the idea that in vitro cell-based experiments can be used to predict the toxic potential of chemicals. We believe that this approach, combined with a robust technique to model human exposure to chemicals, may serve as a promising alternative to animal-based chemical toxicity assessment.

The Art and Science of Diagnosing and Managing Drug-induced Liver Injury in 2015 and Beyond

Drug-induced liver injury (DILI) remains a leading reason why new compounds are dropped from further study or are the subject of product warnings and regulatory actions. Hy's Law of drug-induced hepatocellular jaundice causing a case-fatality rate or need for transplant of 10% or higher has been validated in several large national registries, including the ongoing, prospective U.S. Drug-Induced Liver Injury Network. It serves as the basis for stopping rules in clinical trials and in clinical practice. Because DILI can mimic all known causes of acute and chronic liver disease, establishing causality can be difficult. Histopathologic findings are often nonspecific and rarely, if ever, considered pathognomonic. A daily drug dose >50-100 mg is more likely to be hepatotoxic than does <10 mg, especially if the compound is highly lipophilic or undergoes extensive hepatic metabolism. The quest for a predictive biomarker to replace alanine aminotransferase is ongoing. Markers of necrosis and apoptosis such as microRNA-122 and keratin 18 may prove useful in identifying patients at risk for severe injury when they initially present with a suspected acetaminophen overdose. Although a number of drugs causing idiosyncratic DILI have HLA associations that may allow for pre-prescription testing to prevent hepatotoxicity, the cost and relatively low frequency of injury among affected patients limit the current usefulness of such genome-wide association studies. Alanine aminotransferase monitoring is often recommended but has rarely been shown to be an effective method to prevent serious DILI. Guidelines on the diagnosis and management of DILI have recently been published, although specific therapies remain limited. The LiverTox Web site has been introduced as an interactive online virtual textbook that makes the latest information on more than 650 agents available to clinicians, regulators, and drug developers alike.

In silico assessment of adverse drug reactions and associated mechanisms

During recent years, various in silico approaches have been developed to estimate chemical and biological drug features, for example chemical fragments, protein targets, pathways, among others, that correlate with adverse drug reactions (ADRs) and explain the associated mechanisms. These features have also been used for the creation of predictive models that enable estimation of ADRs during the early stages of drug development. In this review, we discuss various in silico approaches to predict these features for a certain drug, estimate correlations with ADRs, establish causal relationships between selected features and ADR mechanisms and create corresponding predictive models.

LC-MS untargeted metabolomic analysis of drug-induced hepatotoxicity in HepG2 cells

Hepatotoxicity is the number one cause for agencies not approving and withdrawing drugs for the market. Drug-induced human hepatotoxicity frequently goes undetected in preclinical safety evaluations using animal models. Human-derived in vitro models represent a common alternative to in vivo tests to detect toxic effects during preclinical testing. Most current in vitro toxicity assays rely on the measurement of nonspecific or low sensitive endpoints, which result in poor concordance with human liver toxicity. Therefore, making more accurate predictions of the potential hepatotoxicity of new drugs remains a challenge. Metabolomics, whose aim is to globally assess all the metabolites present in a biological sample, may represent an alternative in the search for sensitive sublethal markers of drug-induced hepatotoxicity. To this end, a comprehensive LC-MS-based untargeted metabolite profiling analysis of HepG2 cells, exposed to a set of well-described model hepatotoxins and innocuous compounds, was performed. It allowed to determine meaningful metabolic changes triggered by a toxic insult and gave a first estimation of the main toxicity-related pathways. Based on these metabolic patterns, a partial least squares-discriminant analysis model, able to discriminate between nontoxic and hepatotoxic compounds, was constructed. The approach described herein may provide an alternative for animal testing in preclinical stages of drug development and a controlled experimental approach to gain a better understanding of the underlying causes of hepatotoxicity.

Transcriptomic studies on liver toxicity of acetaminophen

Acetaminophen is widely used as a pain reliever and to reduce fever. At high doses, it can cause severe hepatotoxicity. Acetaminophen overdose has become the leading cause of acute liver failure in the US. The mechanisms for acetaminophen-induced liver injury are unclear. Transcriptomic studies can identify the changes in expression of thousands of genes when exposed to supratherapeutic doses of acetaminophen. These studies elucidated the mechanism of acetaminophen-induced hepatotoxicity and also provide insight into future development of diagnosis and treatment options for acetaminophen-induced acute liver failure. The following is a brief overview of some recent transcriptomic studies and gene-expression-based prediction models on liver toxicity induced by acetaminophen.

Integrating multiple omics to unravel mechanisms of Cyclosporin A induced hepatotoxicity in vitro

In order to improve attrition rates of candidate-drugs there is a need for a better understanding of the mechanisms underlying drug-induced hepatotoxicity. We aim to further unravel the toxicological response of hepatocytes to a prototypical cholestatic compound by integrating transcriptomic and metabonomic profiling of HepG2 cells exposed to Cyclosporin A. Cyclosporin A exposure induced intracellular cholesterol accumulation and diminished intracellular bile acid levels. Performing pathway analyses of significant mRNAs and metabolites separately and integrated, resulted in more relevant pathways for the latter. Integrated analyses showed pathways involved in cell cycle and cellular metabolism to be significantly changed. Moreover, pathways involved in protein processing of the endoplasmic reticulum, bile acid biosynthesis and cholesterol metabolism were significantly affected. Our findings indicate that an integrated approach combining metabonomics and transcriptomics data derived from representative in vitro models, with bioinformatics can improve our understanding of the mechanisms of action underlying drug-induced hepatotoxicity. Furthermore, we showed that integrating multiple omics and thereby analyzing genes, microRNAs and metabolites of the opposed model for drug-induced cholestasis can give valuable information about mechanisms of drug-induced cholestasis in vitro and therefore could be used in toxicity screening of new drug candidates at an early stage of drug discovery.

Do breast cancer cell lines provide a relevant model of the patient tumor methylome?

It is well documented that tumor cells undergo dramatic genetic and epigenetic changes during initial establishment as cell lines and in subsequent serial passaging, and that the resultant cell lines may have evolved significantly from the primary tumors from which they were derived. This has potential implications due to their widespread use in drug response experiments and studies of genomic function. One approach to optimizing the design of such cell line studies is to identify and use the cell lines that faithfully recapitulate critical features of primary tumors. To evaluate the epigenetic fidelity of breast cancer cell lines in the context of primary tumors, we performed methylation profiling of 55 well-characterized breast cancer cell lines on the Illumina HumanMethylation27 BeadChip platform, and compared them to publicly available methylation profiles of primary breast tumors. We found that the DNA methylation profiles of breast cancer cell lines largely retain the features that characterize primary tumors, although there are crucial differences as well. We describe these similarities and differences between primary tumors and breast cancer cell lines in detail, and develop a quantitative measure of similarity that is used to score each cell line with respect to how faithfully its methylation profile mirrors that of primary tumors.

Human skin-derived stem cells as a novel cell source for in vitro hepatotoxicity screening of pharmaceuticals

Human skin-derived precursors (hSKP) are postnatal stem cells with neural crest properties that reside in the dermis of human skin. These cells can be easily isolated from small (fore) skin segments and have the capacity to differentiate into multiple cell types. In this study, we show that upon exposure to hepatogenic growth factors and cytokines, hSKP acquire sufficient hepatic features that could make these cells suitable in vitro tools for hepatotoxicity screening of new chemical entities and already existing pharmaceutical compounds. Indeed, hepatic differentiated hSKP [hSKP-derived hepatic progenitor cells (hSKP-HPC)] express hepatic progenitor cell markers (EPCAM, NCAM2, PROM1) and adult hepatocyte markers (ALB), as well as key biotransformation enzymes (CYP1B1, FMO1, GSTA4, GSTM3) and influx and efflux drug transporters (ABCC4, ABCA1, SLC2A5). Using a toxicogenomics approach, we could demonstrate that hSKP-HPC respond to acetaminophen exposure in a comparable way to primary human hepatocytes in culture. The toxicological responses "liver damage", "liver proliferation", "liver necrosis" and "liver steatosis" were found to be significantly enriched in both in vitro models. Also genes associated with either cytotoxic responses or induction of apoptosis (BCL2L11, FOS, HMOX1, TIMP3, and AHR) were commonly upregulated and might represent future molecular biomarkers for hepatotoxicity. In conclusion, our data gives a first indication that hSKP-HPC might represent a suitable preclinical model for in vitro screening of hepatotoxicity. To the best of our knowledge, this is the first report in which human postnatal stem cells derived from skin are described as a potentially relevant cell source for in vitro hepatotoxicity testing of pharmaceutical compounds.

Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME

This review encompasses the most important advances in liver functions and hepatotoxicity and analyzes which mechanisms can be studied in vitro. In a complex architecture of nested, zonated lobules, the liver consists of approximately 80 % hepatocytes and 20 % non-parenchymal cells, the latter being involved in a secondary phase that may dramatically aggravate the initial damage. Hepatotoxicity, as well as hepatic metabolism, is controlled by a set of nuclear receptors (including PXR, CAR, HNF-4α, FXR, LXR, SHP, VDR and PPAR) and signaling pathways. When isolating liver cells, some pathways are activated, e.g., the RAS/MEK/ERK pathway, whereas others are silenced (e.g. HNF-4α), resulting in up- and downregulation of hundreds of genes. An understanding of these changes is crucial for a correct interpretation of in vitro data. The possibilities and limitations of the most useful liver in vitro systems are summarized, including three-dimensional culture techniques, co-cultures with non-parenchymal cells, hepatospheres, precision cut liver slices and the isolated perfused liver. Also discussed is how closely hepatoma, stem cell and iPS cell-derived hepatocyte-like-cells resemble real hepatocytes. Finally, a summary is given of the state of the art of liver in vitro and mathematical modeling systems that are currently used in the pharmaceutical industry with an emphasis on drug metabolism, prediction of clearance, drug interaction, transporter studies and hepatotoxicity. One key message is that despite our enthusiasm for in vitro systems, we must never lose sight of the in vivo situation. Although hepatocytes have been isolated for decades, the hunt for relevant alternative systems has only just begun.

Latest advances in predicting DILI in human subjects: focus on biomarkers

INTRODUCTION

The quest for a biomarker that would reliably identify patients at risk of developing acute drug-induced liver injury (DILI) to a specific agent or class of agents before it occurs, has been underway for years. Historical host factors for DILI, such as older age and female gender, are not considered sufficient to truly predict an individual's inherent risk of DILI. In vitro and animal-based biomarker discoveries, in many instances, have not been considered accurate enough for drug development in human subjects nor for use in clinical practice.

AREAS COVERED

In order to assess the current state of biomarkers to predict idiosyncratic human DILI, the authors utilized the PubMed literature search tool to identify research reports dealing with clinical DILI biomarkers covering the period of 2010 through to June 2012. Studies involving pharmacogenetic, proteomic and toxicogenomic analyses are preferentially reviewed.

EXPERT OPINION

Although acute DILI has been linked to specific genetic associations (e.g., flucloxacillin and HLA-B*5701; and certain polymorphisms seen with anti-TB agent DILI), such predictors have been able to identify only some patients at risk for only a limited number of drugs. Proteomic-based biomarkers from stored sera in the US DILI Network, such as apolipoprotein E, have been identified as potential candidates, but require further study. As it currently stands, the quest for a widely applicable, validated DILI biomarker remains an ongoing clinical challenge.

An ex vivo perfusion system emulating in vivo conditions in noncirrhotic and cirrhotic human liver

Various models are used for investigating human liver diseases and testing new drugs. However, data generated in such models have only limited relevance for in vivo conditions in humans. We present here an ex vivo perfusion system using human liver samples that enables the characterization of parameters in a functionally intact tissue context. Resected samples of noncirrhotic liver (NC; n = 10) and cirrhotic liver (CL; n = 12) were perfused for 6-h periods. General and liver-specific parameters (glucose, lactate, oxygen, albumin, urea, and bile acids), liver enzymes (aspartate aminotransferase, alanine aminotransferase, lactate dehydrogenase, glutamate dehydrogenase, and γ-glutamyl transferase), overall (M65) and apoptotic (M30) cell-death markers, and indicators of phase-I/phase-II biotransformations were analyzed. The measurement readings closely resembled (patho)physiological characteristics in patients with NC and CL. Mean courses of glucose levels reflected the CLs' reduced glycogen storage capability. Furthermore, CL samples exhibited significantly stronger increases in lactate, bile acids, and the M30/M65 ratio than NC specimens. Likewise, NC samples exhibited more rapid phase-I transformations of phenacetin, midazolam, and diclofenac and phase-I to phase-II turnover rates of the respective intermediates than CL tissue. Collectively, these findings reveal the better hepatic functionality in NC. Perfusion of human liver tissue with this system emulates in vivo conditions and clearly discriminates between noncirrhotic and cirrhotic tissue. This highly reliable device for investigating basic hepatic functionality and testing safety/toxicity, pharmacokinetics/pharmacodynamics and efficacies of novel therapeutic modalities promises to generate superior data compared with those obtained via existing economic perfusion systems.

New perspectives for in vitro risk assessment of multiwalled carbon nanotubes: application of coculture and bioinformatics

Nanotechnology is a rapidly expanding field with wide application for industrial and medical use; therefore, understanding the toxicity of engineered nanomaterials is critical for their commercialization. While short-term in vivo studies have been performed to understand the toxicity profile of various nanomaterials, there is a current effort to shift toxicological testing from in vivo observational models to predictive and high-throughput in vitro models. However, conventional monoculture results of nanoparticle exposure are often disparate and not predictive of in vivo toxic effects. A coculture system of multiple cell types allows for cross-talk between cells and better mimics the in vivo environment. This review proposes that advanced coculture models, combined with integrated analysis of genome-wide in vivo and in vitro toxicogenomic data, may lead to development of predictive multigene expression-based models to better determine toxicity profiles of nanomaterials and consequent potential human health risk due to exposure to these compounds.