Blood gene expression signatures predict exposure levels

The antiviral activity of tripartite motif protein 38 in hepatitis B virus replication and gene expression and its association with treatment responses during PEG-IFN-α antiviral therapy

Hepatitis B virus (HBV) infection represents one of the most critical health problems worldwide. Tripartite motif protein 38 (TRIM38) is an interferon-stimulated gene (ISG) that inhibits various DNA and RNA viruses.In this study, we found a mechanistic correlation between TRIM38 expression levels and the efficacy of HBV infection and IFN-α therapy in patients with CHB. TRIM38 was highly induced by IFN-alpha (IFN-α) in vivo and in vitro. TRIM38 overexpression inhibited HBV replication and gene expression in HepG2 and HepG2.2.15 cells, whereas knockdown of TRIM38 increased these processes. Further experiments indicated that TRIM38 protein enhanced the antiviral effect of IFN-α by enhancing the expression of antiviral proteins. A prospective study revealed high TRIM38 levels in peripheral blood PBMCs were from early responders, and increased TRIM38 expression correlated with a better response to PEG-IFN-α therapy. Taken together, our study suggests that TRIM38 plays a vital role in HBV replication and gene expression.

SIRT2 Promotes HBV Transcription and Replication by Targeting Transcription Factor p53 to Increase the Activities of HBV Enhancers and Promoters

Chronic hepatitis B (CHB) virus infection is one of the leading causes of cirrhosis and liver cancer. Although the major drugs against CHB including nucleos(t)ide analogs and PEG-interferon can effectively control human hepatitis B virus (HBV) infection, complete cure of HBV infection is quite rare. Targeting host factors involved in the viral life cycle contributes to developing innovative therapeutic strategies to improve HBV clearance. In this study, we found that the mRNA and protein levels of SIRT2, a class III histone deacetylase, were significantly upregulated in CHB patients, and that SIRT2 protein level was positively correlated with HBV viral load, HBsAg/HBeAg levels, HBcrAg, and ALT/AST levels. Functional analysis confirmed that ectopic SIRT2 overexpression markedly increased total HBV RNAs, 3.5-kb RNA and HBV core DNA in HBV-infected HepG2-Na⁺/taurocholate cotransporting polypeptide cells and primary human hepatocytes. In contrast, SIRT2 silencing inhibited HBV transcription and replication. In addition, we found a positive correlation between SIRT2 expression and HBV RNAs synthesis as well as HBV covalently closed circular DNA transcriptional activity. A mechanistic study suggested that SIRT2 enhances the activities of HBV enhancer I/HBx promoter (EnI/Xp) and enhancer II/HBc promoter (EnII/Cp) by targeting the transcription factor p53. The levels of HBV EnI/Xp and EnII/Cp-bound p53 were modulated by SIRT2. Both the mutation of p53 binding sites in EnI/Xp and EnII/Cp as well as overexpression of p53 abolished the effect of SIRT2 on HBV transcription and replication. In conclusion, our study reveals that, in terms of host factors, a SIRT2-targeted program might be a more effective therapeutic strategy for HBV infection.

Ccrn4l as a pre-dose marker for prediction of cisplatin-induced hepatotoxicity susceptibility

Clinical cisplatin use is often limited by its drug-induced liver injury (DILI). Particularly, individual differences in susceptibility to DILI can cause life-threatening medical conditions. This study aimed to uncover the inherent genetic factors determining individual variations in hepatotoxicity susceptibility. Rats were subjected to liver biopsy and a 3-week postoperative recovery period before cisplatin administration. At 2 days post-treatment with cisplatin, the rats exhibited histopathological and serum biochemical alterations in the liver, and changes in hydrogen peroxide and cytochrome P450-2E1 levels. Based on these results of liver-related biochemical markers, 32 rats were grouped into the susceptible (top five) and resistant (bottom five) groups. Using RNA-sequencing, we compared gene expressions in the liver pre-biopsied from these two groups before cisplatin treatment and found 161 differently expressed genes between the Susceptible and Resistant groups. Among them, the clock-controlled Ccrn4l responsible for 'rhythmic process' was identified as a common gene downregulated inherently prior to drug exposure in both cisplatin- and acetaminophen-sensitive animals. Additionally, low Ccrn4l levels before cisplatin treatment in the Susceptible group were maintained even after treatment, with decreased antioxidants, increased nitration, and apoptosis. The relationship of Ccrn4l with catalase and mitochondrial RNAs in the liver was confirmed by correlation of their hepatic levels among individuals and similar patterns of circadian variation in their mRNA expression. Remarkably, Ccrn4l knockdown promoted cisplatin-induced mitochondrial dysfunction in WB-F344 cells with antioxidant catalase and apoptosis-related Bax changes. Inherent individual hepatic Ccrn4l level might be a novel factor affecting cisplatin-induced hepatotoxicity susceptibility, possibly through regulation of mitochondrial and antioxidant functions.

Investigating gene expression profiles of whole blood and peripheral blood mononuclear cells using multiple collection and processing methods

Gene expression profiling using blood samples is a valuable tool for biomarker discovery in clinical studies. Different whole blood RNA collection and processing methods are highly variable and might confound comparisons of results across studies. The main aim of the current study is to compare how blood storage, extraction methodologies, and the blood components themselves may influence gene expression profiling. Whole blood and peripheral blood mononuclear cell (PBMC) samples were collected in triplicate from five healthy donors. Whole blood was collected in RNAgard® and PAXgene® Blood RNA Tubes, as well as in collection tubes with anticoagulants such as dipotassium ethylenediaminetetraacetic acid (K2EDTA) and Acid Citrate Dextrose Solution A (ACD-A). PBMCs were separated using sodium citrate Cell Preparation Tubes (CPT™), FICOLL™, magnetic separation, and the LeukoLOCK™ methods. After blood collection, the LeukoLOCK™, K2EDTA and ACD-A blood tubes were shipped overnight using cold conditions and samples from the rest of the collection were immediately frozen with or without pre-processing. The RNA was isolated from whole blood and PBMCs using a total of 10 different experimental conditions employing several widely utilized RNA isolation methods. The RNA quality was assessed by RNA Integrity Number (RIN), which showed that all PBMC procedures had the highest RIN values when blood was stabilized in TRIzol® Reagent before RNA extraction. Initial data analysis showed that human blood stored and shipped at 4°C overnight performed equally well when checked for quality using RNA integrity number when compared to frozen stabilized blood. Comparisons within and across donor/method replicates showed signal-to-noise patterns which were not captured by RIN value alone. Pathway analysis using the top 1000 false discovery rate (FDR) corrected differentially expressed genes (DEGs) showed frozen vs. cold shipping conditions greatly impacted gene expression patterns in whole blood. However, the top 1000 FDR corrected DEGs from PBMCs preserved after frozen vs. cold shipping conditions (LeukoLOCK™ preserved in RNAlater®) revealed no significantly affected pathways. Our results provide novel insight into how RNA isolation, various storage, handling, and processing methodologies can influence RNA quality and apparent gene expression using blood samples. Careful consideration is necessary to avoid bias resulting from downstream processing. Better characterization of the effects of collection method idiosyncrasies will facilitate further research in understanding the effect of gene expression variability in human sample types.

Multi-Walled Carbon Nanotube-Induced Gene Expression Biomarkers for Medical and Occupational Surveillance

As the demand for multi-walled carbon nanotube (MWCNT) incorporation into industrial and biomedical applications increases, so does the potential for unintentional pulmonary MWCNT exposure, particularly among workers during manufacturing. Pulmonary exposure to MWCNTs raises the potential for development of lung inflammation, fibrosis, and cancer among those exposed; however, there are currently no effective biomarkers for detecting lung fibrosis or predicting the risk of lung cancer resulting from MWCNT exposure. To uncover potential mRNAs and miRNAs that could be used as markers of exposure, this study compared in vivo mRNA and miRNA expression in lung tissue and blood of mice exposed to MWCNTs with in vitro mRNA and miRNA expression from a co-culture model of human lung epithelial and microvascular cells, a system previously shown to have a higher overall genome-scale correlation with mRNA expression in mouse lungs than either cell type grown separately. Concordant mRNAs and miRNAs identified by this study could be used to drive future studies confirming human biomarkers of MWCNT exposure. These potential biomarkers could be used to assess overall worker health and predict the occurrence of MWCNT-induced diseases.

A cross-talk between blood-cell neuroplasticity-related genes and environmental enrichment in working dogs

This study aims to identify a panel of blood-cell neuroplasticity-related genes expressed following environmental enrichment stimulation (EE). The Drug detection (DD) training course was an excellent model for the study of EE in the working dog. This research is divided into two experimental trials. In the First Trial, we identified a panel of blood-cell neuroplasticity related-genes associated with DD ability acquired during the training course. In the Second Trial, we assessed the EE additional factor complementary feeding effect on blood-cell neuroplasticity gene expressions. In the First and Second Trials, at different time points of the DD test, blood samples were collected, and NGF, BDNF, VEGFA, IGF1, EGR1, NGFR, and ICE2 blood-cell neuroplasticity related-genes were analyzed. As noted in the First Trial, the DD test in working dogs induced the transient up-regulation of VEGFA, NGF, NGFR, BDNF, and IGF, immediately after the DD test, suggesting the existence of gene regulations. On the contrary, the Second Trial, with feeding implementation, showed an absence of mRNA up-regulation after the DD test. We suppose that complementary feeding alters the systemic metabolism, which, in turn, changes neuroplasticity-related gene blood-cell mRNA. These findings suggested that, in working dogs, there is a cross-talk between blood-cell neuroplasticity-related genes and environmental enrichment. These outcomes could be used to improve future treatments in sensory implementation.

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.

Pulmonary toxicity and global gene expression changes in response to sub-chronic inhalation exposure to crystalline silica in rats

Exposure to crystalline silica results in serious adverse health effects, most notably, silicosis. An understanding of the mechanism(s) underlying silica-induced pulmonary toxicity is critical for the intervention and/or prevention of its adverse health effects. Rats were exposed by inhalation to crystalline silica at a concentration of 15 mg/m³, 6 hr/day, 5 days/week for 3, 6 or 12 weeks. Pulmonary toxicity and global gene expression profiles were determined in lungs at the end of each exposure period. Crystalline silica was visible in lungs of rats especially in the 12-week group. Pulmonary toxicity, as evidenced by an increase in lactate dehydrogenase (LDH) activity and albumin content and accumulation of macrophages and neutrophils in the bronchoalveolar lavage (BAL), was seen in animals depending upon silica exposure duration. The most severe histological changes, noted in the 12-week exposure group, consisted of chronic active inflammation, type II pneumocyte hyperplasia, and fibrosis. Microarray analysis of lung gene expression profiles detected significant differential expression of 38, 77, and 99 genes in rats exposed to silica for 3-, 6-, or 12-weeks, respectively, compared to time-matched controls. Among the significantly differentially expressed genes (SDEG), 32 genes were common in all exposure groups. Bioinformatics analysis of the SDEG identified enrichment of functions, networks and canonical pathways related to inflammation, cancer, oxidative stress, fibrosis, and tissue remodeling in response to silica exposure. Collectively, these results provided insights into the molecular mechanisms underlying pulmonary toxicity following sub-chronic inhalation exposure to crystalline silica in rats.

Sex-specific variation in signaling pathways and gene expression patterns in human leukocytes in response to endotoxin and exercise

Background

While exercise effects on the immune system have received increasing attention in recent years, it remains unclear to what extent gender and fluctuations in sex hormones during menstrual cycle influence immunological responses to exercise.

Methods

We investigated mRNA changes induced through exhaustive exercise (half-marathon; pre-exercise and post-exercise [30 min, 3 h, 24 h] on whole blood cultures ± lipopolysaccharide [LPS] [1 h]) with a specific focus on sex differences (men vs women in luteal phase) as an extension of our previous study.

Results

Inflammation related signaling pathways, TLRs, cytosolic DNA sensing and RIG-I like receptors were differentially activated between sexes in LPS-stimulated cultures. Genes differentially regulated between sexes included TNIP-1, TNIP-3, IL-6, HIVEP1, CXCL3, CCR3, IL-8, and CD69, revealing a bias towards less anti-inflammatory gene regulation in women compared to men. In addition, several genes relevant to brain function (KMO, DDIT4, VEGFA, IGF1R, IGF2R, and FGD4) showed differential activation between sexes. Some of these genes (e.g., KMO in women, DDIT4 in both sexes) potentially constitute neuroprotective mechanisms.

Conclusions

These data reveal that the exercise-induced change in gene expression might be gender and menstrual cycle phase dependent.

Electronic supplementary material

The online version of this article (doi:10.1186/s12974-016-0758-5) contains supplementary material, which is available to authorized users.

Identification of gene expression signature for cigarette smoke exposure response--from man to mouse

Gene expression profiling data can be used in toxicology to assess both the level and impact of toxicant exposure, aligned with a vision of 21st century toxicology. Here, we present a whole blood-derived gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Such a signature that can be measured in a surrogate tissue (whole blood) may help in monitoring smoking exposure as well as discontinuation of exposure when the primarily impacted tissue (e.g., lung) is not readily accessible. The signature consisted of LRRN3, SASH1, PALLD, RGL1, TNFRSF17, CDKN1C, IGJ, RRM2, ID3, SERPING1, and FUCA1. Several members of this signature have been previously described in the context of smoking. The signature translated well across species and could distinguish mice that were exposed to cigarette smoke from ones exposed to air only or had been withdrawn from cigarette smoke exposure. Finally, the small signature of only 11 genes could be converted into a polymerase chain reaction-based assay that could serve as a marker to monitor compliance with a smoking abstinence protocol.

Blood transcript immune signatures distinguish a subset of people with elevated serum ALT from others given acetaminophen

The diagnosis of drug-induced liver injury is hindered by the limited utility of clinical chemistries. We have shown that hepatotoxicants can produce peripheral blood transcriptome "signatures" (PBTS) in rodents and humans. In this study, 42 adults were treated with acetaminophen (APAP; 1 g every 6 hours) for seven days, followed by three days of placebo. Eleven subjects received only placebo. After five days, 12 subjects (30%) had increases in serum alanine aminotransferase (ALT) levels ("responders"). PBTS of 707 and 760 genes, respectively, could distinguish responders and nonresponders from placebos. Functional analysis of the responder PBTS revealed increased expression of genes involved in TH2-mediated and innate immune responses, whereas the nonresponders demonstrated increased gene expression consistent with a tolerogenic immune response. Taken together, these observations suggest that the clinical subjects with transient increases in serum ALT failed to maintain or intensify a hepatic tolerogenic immune response.

Adaptation to acetaminophen exposure elicits major changes in expression and distribution of the hepatic proteome

Acetaminophen overdose is the leading cause of acute liver failure. One dose of 10–15 g causes severe liver damage in humans, whereas repeated exposure to acetaminophen in humans and animal models results in autoprotection. Insight of this process is limited to select proteins implicated in acetaminophen toxicity and cellular defence. Here we investigate hepatic adaptation to acetaminophen toxicity from a whole proteome perspective, using quantitative mass spectrometry. In a rat model, we show the response to acetaminophen involves the expression of 30% of all proteins detected in the liver. Genetic ablation of a master regulator of cellular defence, NFE2L2, has little effect, suggesting redundancy in the regulation of adaptation. We show that adaptation to acetaminophen has a spatial component, involving a shift in regionalisation of CYP2E1, which may prevent toxicity thresholds being reached. These data reveal unexpected complexity and dynamic behaviour in the biological response to drug-induced liver injury.

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.

Technical guide for applications of gene expression profiling in human health risk assessment of environmental chemicals

Toxicogenomics promises to be an important part of future human health risk assessment of environmental chemicals. The application of gene expression profiles (e.g., for hazard identification, chemical prioritization, chemical grouping, mode of action discovery, and quantitative analysis of response) is growing in the literature, but their use in formal risk assessment by regulatory agencies is relatively infrequent. Although additional validations for specific applications are required, gene expression data can be of immediate use for increasing confidence in chemical evaluations. We believe that a primary reason for the current lack of integration is the limited practical guidance available for risk assessment specialists with limited experience in genomics. The present manuscript provides basic information on gene expression profiling, along with guidance on evaluating the quality of genomic experiments and data, and interpretation of results presented in the form of heat maps, pathway analyses and other common approaches. Moreover, potential ways to integrate information from gene expression experiments into current risk assessment are presented using published studies as examples. The primary objective of this work is to facilitate integration of gene expression data into human health risk assessments of environmental chemicals.

Identification of drug-induced toxicity biomarkers for treatment determination

Drug-induced organ toxicity (DIOT) that leads to the removal of marketed drugs or termination of candidate drugs has been a leading concern for regulatory agencies and pharmaceutical companies. In safety studies, the genomic assays are conducted after the treatment so that drug-induced adverse effects can occur. Two types of biomarkers are observed: biomarkers of susceptibility and biomarkers of response. This paper presents a statistical model to distinguish two types of biomarkers and procedures to identify susceptible subpopulations. The biomarkers identified are used to develop classification model to identify susceptible subpopulation. Two methods to identify susceptibility biomarkers were evaluated in terms of predictive performance in subpopulation identification, including sensitivity, specificity, and accuracy. Method 1 considered the traditional linear model with a variable-by-treatment interaction term, and Method 2 considered fitting a single predictor variable model using only treatment data. Monte Carlo simulation studies were conducted to evaluate the performance of the two methods and impact of the subpopulation prevalence, probability of DIOT, and sample size on the predictive performance. Method 2 appeared to outperform Method 1, which was due to the lack of power for testing the interaction effect. Important statistical issues and challenges regarding identification of preclinical DIOT biomarkers were discussed. In summary, identification of predictive biomarkers for treatment determination highly depends on the subpopulation prevalence. When the proportion of susceptible subpopulation is 1% or less, a very large sample size is needed to ensure observing sufficient number of DIOT responses for biomarker and/or subpopulation identifications.

Toxicogenomics profiling of bone marrow from rats treated with topotecan in combination with oxaliplatin: a mechanistic strategy to inform combination toxicity

Combinations of anticancer agents may have synergistic anti-tumor effects, but enhanced hematological toxicity often limit their clinical use. We examined whether "microarray profiles" could be used to compare early molecular responses following a single dose of agents administered individually with that of the agents administered in a combination. We compared the mRNA responses within bone marrow of Sprague-Dawley rats after a single 30 min treatment with topotecan at 4.7 mg/kg or oxaliplatin at 15 mg/kg alone to that of sequentially administered combination therapy or vehicle control for 1, 6, and 24 h. We also examined the histopathology of the bone marrow following all treatments. Drug-related histopathological lesions were limited to bone marrow hypocellularity for animals dosed with either agent alone or in combination. Lesions had an earlier onset and higher incidence for animals given topotecan alone or in combination with oxaliplatin. Severity increased from mild to moderate when topotecan was administered prior to oxaliplatin compared with administering oxaliplatin first. Notably, six patterns of co-expressed genes were detected at the 1 h time point that indicate regulatory expression of genes that are dependent on the order of the administration. These results suggest alterations in histone biology, chromatin remodeling, DNA repair, bone regeneration, and respiratory and oxidative phosphorylation are among the prominent pathways modulated in bone marrow from animals treated with an oxaliplatin/topotecan combination. These data also demonstrate the potential for early mRNA patterns derived from target organs of toxicity to inform toxicological risk and molecular mechanisms for agents given in combination.

Multi-walled carbon nanotube-induced gene expression in vitro: concordance with in vivo studies

There is a current interest in reducing the in vivo toxicity testing of nanomaterials in animals by increasing toxicity testing using in vitro cellular assays; however, toxicological results are seldom concordant between in vivo and in vitro models. This study compared global multi-walled carbon nanotube (MWCNT)-induced gene expression from human lung epithelial and microvascular endothelial cells in monoculture and coculture with gene expression from mouse lungs exposed to MWCNT. Using a cutoff of 10% false discovery rate and 1.5 fold change, we determined that there were more concordant genes (gene expression both up- or downregulated in vivo and in vitro) expressed in both cell types in coculture than in monoculture. When reduced to only those genes involved in inflammation and fibrosis, known outcomes of in vivo MWCNT exposure, there were more disease-related concordant genes expressed in coculture than monoculture. Additionally, different cellular signaling pathways are activated in response to MWCNT dependent upon culturing conditions. As coculture gene expression better correlated with in vivo gene expression, we suggest that cellular cocultures may offer enhanced in vitro models for nanoparticle risk assessment and the reduction of in vivo toxicological testing.

Complement receptor 1 expression in peripheral blood mononuclear cells and the association with clinicopathological features and prognosis of nasopharyngeal carcinoma

PURPOSE

Complement receptor 1 (CR1) is induced by Epstein-Barr virus (EBV) and may be a potential biomarker of nasopharyngeal carcinoma (NPC). We conducted the present study to evaluate the association of CR1 expression with clinicopathological features and prognosis of NPC.

METHODS

We enrolled 145 NPC patients and 110 controls. Expression levels of CR1 in peripheral blood mononuclear cells (PBMCs) were detected using quantitative real-time PCR and associations with clinicopathological features and prognosis were examined.

RESULTS

CR1 levels in the NPC group [3.54 (3.34, 3.79)] were slightly higher than those in the controls [3.33 (3.20, 3.47)] (P<0.001). Increased CR1 expression was associated with histology classification (type III vs. type II, P=0.002), advanced clinical stage (P=0.003), high T stage (P=0.017), and poor overall survival (HR, 4.89; 95% CI, 1.23-19.42; P=0.024). However, there were no statistically significant differences in CR1 expression among N or M stages.

CONCLUSION

These findings indicate that CR1 expression in PBMCs may be a new biomarker for prognosis of NPC and a potential therapeutic target.

Pathogenesis of idiosyncratic drug-induced liver injury and clinical perspectives

Idiosyncratic drug-induced liver injury (DILI) is a rare disease that develops independently of drug dose, route, or duration of administration. Furthermore, idiosyncratic DILI is not a single disease entity but rather a spectrum of rare diseases with varying clinical, histological, and laboratory features. The pathogenesis of DILI is not fully understood. Standardization of the DILI nomenclature and methods to assess causality, along with the information provided by the LiverTox Web site, will harmonize and accelerate research on DILI. Studies of new serum biomarkers such as glutamate dehydrogenase, high mobility group box protein 1, and microRNA-122 could provide information for use in diagnosis and prognosis and provide important insights into the mechanisms of the pathogenesis of DILI. Single nucleotide polymorphisms in the HLA region have been associated with idiosyncratic hepatotoxicity attributed to flucloxacillin, ximelagatran, lapatinib, and amoxicillin-clavulanate. However, genome-wide association studies of pooled cases have not associated any genetic factors with idiosyncratic DILI. Whole genome and whole exome sequencing analyses are under way to study cases of DILI attributed to a single medication. Serum proteomic, transcriptome, and metabolome as well as intestinal microbiome analyses will increase our understanding of the mechanisms of this disorder. Further improvements to in vitro and in vivo test systems should advance our understanding of the causes, risk factors, and mechanisms of idiosyncratic DILI.

Contributions of pharmacogenetics and transcriptomics to the understanding of the hypersensitivity drug reactions

Hypersensitivity drug reactions (HDRs) represent a large and important health problem, affecting many patients and leading to a variety of clinical entities, some of which can be life-threatening. The culprit drugs include commonly used medications including antibiotics and NSAIDs. Nontherapeutical agents, such as contrast media, are also involved. Because the pathophysiological mechanisms are not well known and the current diagnostic procedures are somewhat insufficient, new approaches are needed for understanding the complexity of HDRs. Histochemical and molecular biology studies have enabled us to classify these reactions more precisely. Pharmacogenetics has led to the identification of several genes, involved mainly in T-cell-dependent responses, with a number of markers being replicated in different studies. These markers are now being considered as potential targets for reducing the number of HDRs. Transcriptomic approaches have also been used to investigate HDRs by identifying genes that show different patterns of expression in a number of clinical entities. This information can be of value for further elucidation of the mechanisms involved. Although first studies were performed using RT-PCR analysis to monitor the acute phase of the reaction, nowadays high-density expression platforms represent a more integrative way for providing a complete view of gene expression. By combining a detailed and precise clinical description with information obtained by these approaches, we will obtain a better understanding and management of patients with HDRs.

Quantitative liver-specific protein fingerprint in blood: a signature for hepatotoxicity

We discuss here a new approach to detecting hepatotoxicity by employing concentration changes of liver-specific blood proteins during disease progression. These proteins are capable of assessing the behaviors of their cognate liver biological networks for toxicity or disease perturbations. Blood biomarkers are highly desirable diagnostics as blood is easily accessible and baths virtually all organs. Fifteen liver-specific blood proteins were identified as markers of acetaminophen (APAP)-induced hepatotoxicity using three proteomic technologies: label-free antibody microarrays, quantitative immunoblotting, and targeted iTRAQ mass spectrometry. Liver-specific blood proteins produced a toxicity signature of eleven elevated and four attenuated blood protein levels. These blood protein perturbations begin to provide a systems view of key mechanistic features of APAP-induced liver injury relating to glutathione and S-adenosyl-L-methionine (SAMe) depletion, mitochondrial dysfunction, and liver responses to the stress. Two markers, elevated membrane-bound catechol-O-methyltransferase (MB-COMT) and attenuated retinol binding protein 4 (RBP4), report hepatic injury significantly earlier than the current gold standard liver biomarker, alanine transaminase (ALT). These biomarkers were perturbed prior to onset of irreversible liver injury. Ideal markers should be applicable for both rodent model studies and human clinical trials. Five of these mouse liver-specific blood markers had human orthologs that were also found to be responsive to human hepatotoxicity. This panel of liver-specific proteins has the potential to effectively identify the early toxicity onset, the nature and extent of liver injury and report on some of the APAP-perturbed liver networks.

Hopes and challenges in using miRNAs as translational biomarkers for drug-induced liver injury

There is a need for better biomarkers of drug-induced liver injury (DILI) to guide risk assessment and patient management. Over the past 3 years, both animal and clinical studies have provided proof-of-concept data showing that a subset of miRNAs appear to offer unique advantages over the conventional DILI biomarkers, such as enhanced sensitivity and specificity, reduced inter-individual variations, the potential to differentiate lethal and nonlethal liver injury, and the ability to reflect the patterns and even the etiology of liver injury. Notably, many studies have demonstrated that level of miR-122, a liver-enriched miRNA accounting for approximately 70% of total hepatic miRNAs, was increased many fold in the blood when DILI occurred. However, currently available data are predominantly based on animal models and not human samples. Due to the lack of a standard quantification method for miRNAs and confirmatory studies using a comprehensive list of drugs and patients, the true value of all reported miRNA biomarkers remains to be carefully assessed. An outstanding challenge is to examine if miRNAs are also useful for idiosyncratic DILI, which constitutes the major part of clinical DILI cases but generally cannot be recapitulated in traditional animal models or in clinical trials (the latter due to its relative rarity).

Blood transcriptomics: applications in toxicology

The number of new chemicals that are being synthesized each year has been steadily increasing. While chemicals are of immense benefit to mankind, many of them have a significant negative impact, primarily owing to their inherent chemistry and toxicity, on the environment as well as human health. In addition to chemical exposures, human exposures to numerous non-chemical toxic agents take place in the environment and workplace. Given that human exposure to toxic agents is often unavoidable and many of these agents are found to have detrimental human health effects, it is important to develop strategies to prevent the adverse health effects associated with toxic exposures. Early detection of adverse health effects as well as a clear understanding of the mechanisms, especially at the molecular level, underlying these effects are key elements in preventing the adverse health effects associated with human exposure to toxic agents. Recent developments in genomics, especially transcriptomics, have prompted investigations into this important area of toxicology. Previous studies conducted in our laboratory and elsewhere have demonstrated the potential application of blood gene expression profiling as a sensitive, mechanistically relevant and practical surrogate approach for the early detection of adverse health effects associated with exposure to toxic agents. The advantages of blood gene expression profiling as a surrogate approach to detect early target organ toxicity and the molecular mechanisms underlying the toxicity are illustrated and discussed using recent studies on hepatotoxicity and pulmonary toxicity. Furthermore, the important challenges this emerging field in toxicology faces are presented in this review article.

Gene expression profiles in peripheral blood mononuclear cells of Chinese nickel refinery workers with high exposures to nickel and control subjects

BACKGROUND

Occupational exposure to nickel (Ni) is associated with an increased risk of lung and nasal cancers. Ni compounds exhibit weak mutagenic activity, alter the cell's epigenetic homeostasis, and activate signaling pathways. However, changes in gene expression associated with Ni exposure have only been investigated in vitro. This study was conducted in a Chinese population to determine whether occupational exposure to Ni was associated with differential gene expression profiles in the peripheral blood mononuclear cells (PBMC) of Ni-refinery workers when compared with referents.

METHODS

Eight Ni-refinery workers and ten referents were selected. PBMC RNA was extracted and gene expression profiling was conducted using Affymetrix exon arrays. Differentially expressed genes (DEG) between both groups were identified in a global analysis.

RESULTS

There were a total of 2,756 DEGs in the Ni-refinery workers relative to the referents [false discovery rate (FDR) adjusted P < 0.05] with 770 upregulated genes and 1,986 downregulated genes. DNA repair and epigenetic genes were significantly overrepresented (P < 0.0002) among the DEGs. Of 31 DNA repair genes, 29 were repressed in the Ni-refinery workers and 2 were overexpressed. Of the 16 epigenetic genes, 12 were repressed in the Ni-refinery workers and 4 were overexpressed.

CONCLUSIONS

The results of this study indicate that occupational exposure to Ni is associated with alterations in gene expression profiles in PBMCs of subjects.

IMPACT

Gene expression may be useful in identifying patterns of deregulation that precede clinical identification of Ni-induced cancers.

Transcriptomics analysis of lungs and peripheral blood of crystalline silica-exposed rats

Minimally invasive approaches to detect/predict target organ toxicity have significant practical applications in occupational toxicology. The potential application of peripheral blood transcriptomics as a practical approach to study the mechanisms of silica-induced pulmonary toxicity was investigated. Rats were exposed by inhalation to crystalline silica (15 mg/m(3), 6 h/day, 5 days) and pulmonary toxicity and global gene expression profiles of lungs and peripheral blood were determined at 32 weeks following termination of exposure. A significant elevation in bronchoalveolar lavage fluid lactate dehydrogenase activity and moderate histological changes in the lungs, including type II pneumocyte hyperplasia and fibrosis, indicated pulmonary toxicity in the rats. Similarly, significant infiltration of neutrophils and elevated monocyte chemotactic protein-1 levels in the lungs showed pulmonary inflammation in the rats. Microarray analysis of global gene expression profiles identified significant differential expression [>1.5-fold change and false discovery rate (FDR) p < 0.01] of 520 and 537 genes, respectively, in the lungs and blood of the exposed rats. Bioinformatics analysis of the differentially expressed genes demonstrated significant similarity in the biological processes, molecular networks, and canonical pathways enriched by silica exposure in the lungs and blood of the rats. Several genes involved in functions relevant to silica-induced pulmonary toxicity such as inflammation, respiratory diseases, cancer, cellular movement, fibrosis, etc, were found significantly differentially expressed in the lungs and blood of the silica-exposed rats. The results of this study suggested the potential application of peripheral blood gene expression profiling as a toxicologically relevant and minimally invasive surrogate approach to study the mechanisms underlying silica-induced pulmonary toxicity.

Identification of Identical Transcript Changes in Liver and Whole Blood during Acetaminophen Toxicity

The ability to identify mechanisms underlying drug-induced liver injury (DILI) in man has been hampered by the difficulty in obtaining liver tissue from patients. It has recently been proposed that whole blood toxicogenomics may provide a non-invasive means for mechanistic studies of human DILI. However, it remains unclear to what extent changes in whole blood transcriptome mirror those in liver mechanistically linked to hepatotoxicity. To address this question, we applied the program Extracting Patterns and Identifying co-expressed Genes (EPIG) to publically available toxicogenomic data obtained from rats treated with both toxic and subtoxic doses of acetaminophen (APAP). In a training set of animals, we identified genes (760 at 6 h and 185 at 24 h post dose) with similar patterns of expression in blood and liver during APAP-induced hepatotoxicity. The pathways represented in the coordinately regulated genes largely involved mitochondrial and immune functions. The identified expression signatures were then evaluated in a separate set of animals for discernment of APAP exposure level or APAP-induced hepatotoxicity. At 6 h, the gene sets from liver and blood had equally sufficient classification of APAP exposure levels. At 24 h when toxicity was evident, the gene sets did not perform well in evaluating APAP exposure doses, but provided accurate classification of dose-independent liver injury that was evaluated by serum ALT elevation in the blood. Only 38 genes were common to both the 6 and 24-h gene sets, but these genes had the same capability as the parent gene sets to discern the exposure level and degree of liver injury. Some of the parallel transcript changes reflect pathways that are relevant to APAP hepatotoxicity, including mitochondria and immune functions. However, the extent to which these changes reflect similar mechanisms of action in both tissues remains to be determined.

The impact of classification of interest on predictive toxicogenomics

The era of toxicogenomics has introduced a new way of monitoring the effect of environmental stressors and toxicants on biological systems via quantification of changes in gene expression. Because the liver is one of the major organs for synthesis and secretion of substances which metabolize endogenous and exogenous materials, there has been a great deal of interest in elucidating predictive and mechanistic genomic markers of hepatotoxicity. This mini-review will bring context to a limited number of toxicogenomics studies which used genomics to evaluate the transcriptional changes in blood and liver in response to acetaminophen (APAP) or other liver toxicants, but differed according to the classification of interest (COI), i.e., the partitioning of the samples a priori according to a common toxicological characteristic. The toxicogenomics studies highlighted are characterized by a classification of either no/low vs. high APAP dose exposure, none vs. observed necrosis, and severity of necrosis. The overlap or lack thereof between the gene classifiers and the modulated biological processes that are elucidated will be discussed to enhance the understanding of the effect of the particular COI model and experimental design used for prediction.

'Omics analysis of low dose acetaminophen intake demonstrates novel response pathways in humans

Acetaminophen is the primary cause of acute liver toxicity in Europe/USA, which led the FDA to reconsider recommendations concerning safe acetaminophen dosage/use. Unfortunately, the current tests for liver toxicity are no ideal predictive markers for liver injury, i.e. they only measure acetaminophen exposure after profound liver toxicity has already occurred. Furthermore, these tests do not provide mechanistic information. Here, 'omics techniques (global analysis of metabolomic/gene-expression responses) may provide additional insight. To better understand acetaminophen-induced responses at low doses, we evaluated the effects of (sub-)therapeutic acetaminophen doses on metabolite formation and global gene-expression changes (including, for the first time, full-genome human miRNA expression changes) in blood/urine samples from healthy human volunteers. Many known and several new acetaminophen-metabolites were detected, in particular in relation to hepatotoxicity-linked, oxidative metabolism of acetaminophen. Transcriptomic changes indicated immune-modulating effects (2g dose) and oxidative stress responses (4g dose). For the first time, effects of acetaminophen on full-genome human miRNA expression have been considered and confirmed the findings on mRNA level. 'Omics techniques outperformed clinical chemistry tests and revealed novel response pathways to acetaminophen in humans. Although no definitive conclusion about potential immunotoxic effects of acetaminophen can be drawn from this study, there are clear indications that the immune system is triggered even after intake of low doses of acetaminophen. Also, oxidative stress-related gene responses, similar to those seen after high dose acetaminophen exposure, suggest the occurrence of possible pre-toxic effects of therapeutic acetaminophen doses. Possibly, these effects are related to dose-dependent increases in levels of hepatotoxicity-related metabolites.

Identification and characterization of adverse effects in 21st century toxicology

The practice of toxicology is changing rapidly, as demonstrated by the response to the 2007 NRC report on "Toxicity Testing in the 21(st) Century." New assays are being developed to replace animal testing; yet the use of data from these assays in decision making is not clear. A Health and Environmental Sciences Institute committee held a May 2011 workshop to discuss approaches to identifying adverse effects in the context of the NRC report. Scientists from industry, government, academia, and NGOs discussed two case studies and explored how information from new, high data content assays developed for screening can be used to differentiate adverse effects from adaptive responses. The terms "adverse effect" and "adaptive response" were defined, as well as two new terms, the relevant pathways of toxicological concern (RPTCs) and relevant responses for regulation (RRRs). RPTCs are biochemical pathways associated with adverse events and need to be elucidated before they are used in regulatory decision making. RRRs are endpoints that are the basis for risk assessment and may or may not be at the level of pathways. Workshop participants discussed the criteria for determining whether, at the RPTC level, an effect is potentially adverse or potentially indicative of adaptability, and how the use of prototypical, data-rich compounds could lead to a greater understanding of RPTCs and their use as RRRs. Also discussed was the use of RPTCs in a weight-of-evidence approach to risk assessment. Inclusion of data at this level could decrease uncertainty in risk assessments but will require the use of detailed dosimetry and consideration of exposure context and the time and dose continuum to yield scientifically based decisions. The results of this project point to the need for an extensive effort to characterize RPTCs and their use in risk assessment to make the vision of the 2007 NRC report a reality.

In silico models for drug-induced liver injury--current status

INTRODUCTION

Drug-induced liver injury (DILI) is one of the most important reasons for drug attrition at both pre-approval and post-approval stages. Therefore, it is crucial to develop methods that will detect potential hepatotoxicity among drug candidates as early and quickly as possible. However, the complexity of hepatotoxicity endpoint makes it very difficult to predict. In addition, there is still a lack of sensitive and specific biomarkers for DILI that consequently leads to a scarcity of reliable hepatotoxic data, which are the key to any modelling approach.

AREAS COVERED

This review explores the current status of existing in silico models predicting hepatotoxicity. Over the past decade, attempts have been made to compile hepatotoxicity data and develop in silico models, which can be used as a first-line screening of drug candidates for further testing.

EXPERT OPINION

Most of the predictive methods discussed in this review are based on the structural properties of chemicals and do not take into account genetic and environmental factors; therefore, their predictions are still uncertain. To improve the predictability of in silico models for DILI, it is essential to better understand its mechanisms as well as to develop sensitive toxicogenomics biomarkers, which show relatively good differentiation between hepatotoxins and non-hepatotoxins.

Systems biology approach for new target and biomarker identification

The pharmaceutical industry is spending increasingly large amounts of money on the discovery and development of novel medicines, but this investment is not adequately paying off in an increased rate of newly approved drugs by the FDA. The post-genomic era has provided a wealth of novel approaches for generating large, high-dimensional genetic and transcriptomic data sets from large cohorts of preclinical species as well as normal and diseased individuals. This systems biology approach to understanding disease-related biology is revolutionizing our understanding of the cellular pathways and gene networks underlying the onset of disease, and the mechanisms of pharmacological treatments that ameliorate disease phenotypes. In this article, we review a number of approaches being used by pharmaceutical and biotechnology companies, e.g., high-throughput DNA genotyping, sequencing, and genome-wide gene expression profiling, to enable drug discovery and development through the identification of new drug targets and biomarkers of disease progression, drug pharmacodynamics, and predictive markers for selecting the patients most likely to respond to therapy.

Multiwalled carbon nanotube-induced gene signatures in the mouse lung: potential predictive value for human lung cancer risk and prognosis

Concerns over the potential for multiwalled carbon nanotubes (MWCNT) to induce lung carcinogenesis have emerged. This study sought to (1) identify gene expression signatures in the mouse lungs following pharyngeal aspiration of well-dispersed MWCNT and (2) determine if these genes were associated with human lung cancer risk and progression. Genome-wide mRNA expression profiles were analyzed in mouse lungs (n = 160) exposed to 0, 10, 20, 40, or 80 μg of MWCNT by pharyngeal aspiration at 1, 7, 28, and 56 d postexposure. By using pairwise statistical analysis of microarray (SAM) and linear modeling, 24 genes were selected, which have significant changes in at least two time points, have a more than 1.5-fold change at all doses, and are significant in the linear model for the dose or the interaction of time and dose. Additionally, a 38-gene set was identified as related to cancer from 330 genes differentially expressed at d 56 postexposure in functional pathway analysis. Using the expression profiles of the cancer-related gene set in 8 mice at d 56 postexposure to 10 μg of MWCNT, a nearest centroid classification accurately predicts human lung cancer survival with a significant hazard ratio in training set (n = 256) and test set (n = 186). Furthermore, both gene signatures were associated with human lung cancer risk (n = 164) with significant odds ratios. These results may lead to development of a surveillance approach for early detection of lung cancer and prognosis associated with MWCNT in the workplace.

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.

Biomarker classifiers for identifying susceptible subpopulations for treatment decisions

AIM

A main goal of pharmacogenomics is to develop genomic signatures to predict patients' responses to a drug or therapy for treatment decisions. Identification of patients who would have no beneficial effect or have the risk of developing adverse effects from an unnecessary treatment could save enormous cost in the healthcare system and clinical trials. This article presents an approach for developing a biomarker classifier for identifying a fraction of susceptible patients, who should be spared unnecessary treatment prior to treatment.

MATERIALS & METHODS

The identification of susceptible patients involves two steps. The first step is to identify biomarkers of susceptibility from a mixture of biomarkers of susceptibility and biomarkers of response; the second step is to develop a classifier using an ensemble classification algorithm, as the number of susceptible patients is generally much smaller than the number of nonsusceptible patients.

RESULTS

Selection of the biomarkers of susceptibility is essential to achieve good prediction accuracy. The ensemble algorithm significantly improves the prediction accuracy compared with the standard classifiers.

CONCLUSION

The study shows that classifiers developed based on the biomarkers obtained by comparing the genomic profiles of responders to those of nonresponders may lead to a high misclassification error rate. Classifiers to identify a small fraction of the subpopulation should take imbalanced class sizes into consideration. A large sample size may be needed in order to ensure detection of a sufficient number of biomarkers and a sufficient number of susceptible subjects for classifier development and validation.

Identification of urinary microRNA profiles in rats that may diagnose hepatotoxicity

Circulating microRNAs (miRNAs) have emerged as novel noninvasive biomarkers for several diseases and other types of tissue injury. This study tested the hypothesis that changes in the levels of urinary miRNAs correlate with liver injury induced by hepatotoxicants. Sprague-Dawley rats were administered acetaminophen (APAP) or carbon tetrachloride (CCl(4)) and one nonhepatotoxicant (penicillin/PCN). Urine samples were collected over a 24 h period after a single oral dose of APAP (1250 mg/kg), CCl(4) (2000 mg/kg), or PCN (2400 mg/kg). APAP and CCl(4) induced liver injury based upon increased serum alanine and aspartate aminotransferase levels and histopathological findings, including liver necrosis. APAP and CCl(4) both significantly increased the urinary levels of 44 and 28 miRNAs, respectively. In addition, 10 of the increased miRNAs were in common between APAP and CCl(4). In contrast, PCN caused a slight decrease of a different nonoverlapping set of urinary miRNAs. Cluster analysis revealed a distinct urinary miRNA pattern from the hepatotoxicant-treated groups when compared with vehicle controls and PCN. Analysis of hepatic miRNA levels suggested that the liver was the source of the increased urinary miRNAs after APAP exposure; however, the results from CCl(4) were equivocal. Computational analysis was used to predict target genes of the 10 shared hepatotoxicant-induced miRNAs. Liver gene expression profiling using whole genome microarrays identified eight putative miRNA target genes that were significantly altered in the liver of APAP- and CCl(4)-treated animals. In conclusion, the patterns of urinary miRNA may hold promise as biomarkers of hepatotoxicant-induced liver injury.

Predictive Power Estimation Algorithm (PPEA)--a new algorithm to reduce overfitting for genomic biomarker discovery

Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA), which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1) PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2) the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3) using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4) more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

Pentraxin 3 as a potential biomarker of acetaminophen-induced liver injury

OBJECTIVE

Overdose of acetaminophen (APAP) can lead to severe liver injury in humans and experimental animals. Pentraxin-3 (PTX-3) is produced and released by several cell types. In this study, we aimed to evaluate whether PTX-3 is a potential biomarker in the identification of APAP-induced liver injury.

MATERIALS AND METHODS

Thirty adult male Wistar rats were randomly divided into three groups: control, APAP-1 and APAP-2 groups. APAP-1 (1 g/kg) and APAP-2 (2 g/kg) group rats were given APAP by gastric tube. Liver tissues and blood samples were obtained for biochemical and histopathological analysis. Biochemical parameters, plasma and liver PTX-3 levels and degree of liver necrosis were measured in all groups.

RESULTS

APAP treatments caused necrosis in liver and accompanied by elevated liver PTX-3 levels after 48 h. In APAP-1 and APAP-2 groups when compared with control group (7.5±3.3 ng/mg protein), mean liver PTX-3 concentrations were 14.1±3.0 (p=0.032) and 28.5±8.2 (p<0.001) ng/mg protein, respectively. All rats (100%) in the APAP-2 group had the degree 3 liver necrosis. However 10%, 40% and 50% of rats had the degree 1, the degree 2 and the degree 3 liver necrosis in the APAP-1 group, respectively. The degrees of liver necrosis of the APAP-1 and APAP-2 groups were higher than the group of control (p<0.001 and p<0.001, respectively).

CONCLUSIONS

PTX-3 may have a role in the APAP-induced liver injury in the rats. The elevated liver PTX-3 in the APAP-induced hepatic necrosis might be a marker of acute histological liver damage. Further prospective studies are necessary to clarify the prognostic value of liver PTX-3 for prediction of histological hepatic necrosis in the APAP-induced liver injury.

In vitro transcriptomic prediction of hepatotoxicity for early drug discovery

Liver toxicity (hepatotoxicity) is a critical issue in drug discovery and development. Standard preclinical evaluation of drug hepatotoxicity is generally performed using in vivo animal systems. However, only a small number of preselected compounds can be examined in vivo due to high experimental costs. A more efficient yet accurate screening technique that can identify potentially hepatotoxic compounds in the early stages of drug development would thus be valuable. Here, we develop and apply a novel genomic prediction technique for screening hepatotoxic compounds based on in vitro human liver cell tests. Using a training set of in vivo rodent experiments for drug hepatotoxicity evaluation, we discovered common biomarkers of drug-induced liver toxicity among six heterogeneous compounds. This gene set was further triaged to a subset of 32 genes that can be used as a multi-gene expression signature to predict hepatotoxicity. This multi-gene predictor was independently validated and showed consistently high prediction performance on five test sets of in vitro human liver cell and in vivo animal toxicity experiments. The predictor also demonstrated utility in evaluating different degrees of toxicity in response to drug concentrations, which may be useful not only for discerning a compound's general hepatotoxicity but also for determining its toxic concentration.

Benzene, the exposome and future investigations of leukemia etiology

Benzene exposure is associated with acute myeloid leukemia (AML), myelodysplastic syndromes (MDS), and probably lymphoma and childhood leukemia. Biological plausibility for a causal role of benzene in these diseases comes from its toxicity to hematopoietic stem cells (HSC) or progenitor cells, from which all leukemias and related disorders arise. The effect of this toxicity is manifest as lowered blood counts (hematotoxicity), even in individuals occupationally exposed to low levels of benzene. Benzene can induce AML/MDS via several well-characterized pathways associated with these diseases. Through its metabolites, benzene induces multiple alterations that likely contribute to the leukemogenic process, and appears to operate via multiple modes of action. To improve mechanistic understanding and for risk assessment purposes, it may be possible to measure several of the key events in these modes of action in an in vitro model of the bone marrow stem cell niche. Even though benzene is leukemogenic at relatively low occupational levels of exposure, it seems unlikely that it is a major cause of leukemia in the general population exposed to benzene in the ppb range. Other established non-genetic causes of AML, e.g. smoking, ionizing radiation and cancer chemotherapy, also only explain about 20% of AML incidence, leaving ∼80% unexplained. The question arises as to how to find the causes of the majority of de novo AMLs that remain unexplained. We propose that we should attempt to characterize the 'exposome' of human leukemia by using unbiased laboratory-based methods to find the unknown 'environmental' factors that contribute to leukemia etiology.

Transcriptional profiling to identify biomarkers of disease and drug response

The discovery, biological qualification and analytical validation of genomic biomarkers requires extensive collaborations between individuals with expertise in biology, statistics, bioinformatics, chemistry, clinical medicine, regulatory science and so on. For clinical utility, blood-borne biomarkers (e.g., mRNA and miRNA) of organ damage, drug toxicity and/or response would be preferred to those that are tissue based. Currently used biomarkers such as serum creatinine (indicating renal dysfunction) denote organ damage whether caused by disease, physical injury or drugs. Therefore, it is anticipated that studies of disease will discover biomarkers that can also be used to identify drug-induced injury and vice versa. This article describes transcriptomic blood-borne biomarkers that have been reported to be connected with disease and drug toxicity. Much more qualification and validation needs to be carried out before many of these biomarkers can prove useful. Discussed here are some of the lessons learned and roadblocks to success.

Multi-walled carbon nanotube-induced gene expression in the mouse lung: association with lung pathology

Due to the fibrous shape and durability of multi-walled carbon nanotubes (MWCNT), concerns regarding their potential for producing environmental and human health risks, including carcinogenesis, have been raised. This study sought to investigate how previously identified lung cancer prognostic biomarkers and the related cancer signaling pathways are affected in the mouse lung following pharyngeal aspiration of well-dispersed MWCNT. A total of 63 identified lung cancer prognostic biomarker genes and major signaling biomarker genes were analyzed in mouse lungs (n=80) exposed to 0, 10, 20, 40, or 80μg of MWCNT by pharyngeal aspiration at 7 and 56days post-exposure using quantitative PCR assays. At 7 and 56days post-exposure, a set of 7 genes and a set of 11 genes, respectively, showed differential expression in the lungs of mice exposed to MWCNT vs. the control group. Additionally, these significant genes could separate the control group from the treated group over the time series in a hierarchical gene clustering analysis. Furthermore, 4 genes from these two sets of significant genes, coiled-coil domain containing-99 (Ccdc99), muscle segment homeobox gene-2 (Msx2), nitric oxide synthase-2 (Nos2), and wingless-type inhibitory factor-1 (Wif1), showed significant mRNA expression perturbations at both time points. It was also found that the expression changes of these 4 overlapping genes at 7days post-exposure were attenuated at 56days post-exposure. Ingenuity Pathway Analysis (IPA) found that several carcinogenic-related signaling pathways and carcinogenesis itself were associated with both the 7 and 11 gene signatures. Taken together, this study identifies that MWCNT exposure affects a subset of lung cancer biomarkers in mouse lungs.