Decreased translation of Dio3 mRNA is associated with drug-induced hepatotoxicity.

Recent work has demonstrated the importance of post-transcriptional gene regulation in toxic responses. In the present study, we used two rat models to investigate mRNA translation in the liver following xenobiotic-induced toxicity. By combining polysome profiling with genomic methodologies, we were able to assess global changes in hepatic mRNA translation. Dio3 (iodothyronine deiodinase type III) was identified as a gene that exhibited specific translational repression and had a functional role in a number of relevant canonical pathways. Western blot analysis indicated that this repression led to reduced D3 (the protein expressed by Dio3) levels, enhanced over time and with increased dose. Using Northern blotting techniques and qRT-PCR (quantitative reverse transcription-PCR), we confirmed further that there was no reduction in Dio3 mRNA, suggesting that translational repression of Dio3 is an important determinant of the reduced D3 protein expression following liver damage. Finally, we show that drug-induced hepatotoxicity appears to cause localized disruptions in thyroid hormone levels in the liver and plasma. We suggest that this leads to reduced translation of Dio3 mRNA, which results in decreased D3 production. It may therefore be possible that this is an important mechanism by which the liver can, upon early signs of damage, act rapidly to maintain its own energy equilibrium, thereby avoiding global disruption of the hypothalamic-pituitary-thyroid axis.

A long-term three dimensional liver co-culture system for improved prediction of clinically relevant drug-induced hepatotoxicity.

Drug-induced liver injury (DILI) is the major cause for liver failure and post-marketing drug withdrawals. Due to species-specific differences in hepatocellular function, animal experiments to assess potential liabilities of drug candidates can predict hepatotoxicity in humans only to a certain extent. In addition to animal experimentation, primary hepatocytes from rat or human are widely used for pre-clinical safety assessment. However, as many toxic responses in vivo are mediated by a complex interplay among different cell types and often require chronic drug exposures, the predictive performance of hepatocytes is very limited. Here, we established and characterized human and rat in vitro three-dimensional (3D) liver co-culture systems containing primary parenchymal and non-parenchymal hepatic cells. Our data demonstrate that cells cultured on a 3D scaffold have a preserved composition of hepatocytes, stellate, Kupffer and endothelial cells and maintain liver function for up to 3months, as measured by the production of albumin, fibrinogen, transferrin and urea. Additionally, 3D liver co-cultures maintain cytochrome P450 inducibility, form bile canaliculi-like structures and respond to inflammatory stimuli. Upon incubation with selected hepatotoxicants including drugs which have been shown to induce idiosyncratic toxicity, we demonstrated that this model better detected in vivo drug-induced toxicity, including species-specific drug effects, when compared to monolayer hepatocyte cultures. In conclusion, our results underline the importance of more complex and long lasting in vitro cell culture models that contain all liver cell types and allow repeated drug-treatments for detection of in vivo-relevant adverse drug effects.

EU framework 6 project: predictive toxicology (PredTox)--overview and outcome.

In this publication, we report the outcome of the integrated EU Framework 6 PROJECT: Predictive Toxicology (PredTox), including methodological aspects and overall conclusions. Specific details including data analysis and interpretation are reported in separate articles in this issue. The project, partly funded by the EU, was carried out by a consortium of 15 pharmaceutical companies, 2 SMEs, and 3 universities. The effects of 16 test compounds were characterized using conventional toxicological parameters and "omics" technologies. The three major observed toxicities, liver hypertrophy, bile duct necrosis and/or cholestasis, and kidney proximal tubular damage were analyzed in detail. The combined approach of "omics" and conventional toxicology proved a useful tool for mechanistic investigations and the identification of putative biomarkers. In our hands and in combination with histopathological assessment, target organ transcriptomics was the most prolific approach for the generation of mechanistic hypotheses. Proteomics approaches were relatively time-consuming and required careful standardization. NMR-based metabolomics detected metabolite changes accompanying histopathological findings, providing limited additional mechanistic information. Conversely, targeted metabolite profiling with LC/GC-MS was very useful for the investigation of bile duct necrosis/cholestasis. In general, both proteomics and metabolomics were supportive of other findings. Thus, the outcome of this program indicates that "omics" technologies can help toxicologists to make better informed decisions during exploratory toxicological studies. The data support that hypothesis on mode of action and discovery of putative biomarkers are tangible outcomes of integrated "omics" analysis. Qualification of biomarkers remains challenging, in particular in terms of identification, mechanistic anchoring, appropriate specificity, and sensitivity.

A comparative integrated transcript analysis and functional characterization of differential mechanisms for induction of liver hypertrophy in the rat.

The main goal of the present work was to better understand the molecular mechanisms underlying liver hypertrophy (LH), a recurrent finding observed following acute or repeated drug administration to animals, using transcriptomic technologies together with the results from conventional toxicology methods. Administration of 5 terminated proprietary drug candidates from participating companies involved in the EU Innomed PredTox Project or the reference hepatotoxicant troglitazone to rats for up to a 14-day duration induced LH as the main liver phenotypic toxicity outcome. The integrated analysis of transcriptomic liver expression data across studies turned out to be the most informative approach for the generation of mechanistic models of LH. In response to a xenobiotic stimulus, a marked increase in the expression of xenobiotic metabolizing enzymes (XME) was observed in a subset of 4 studies. Accumulation of these newly-synthesized proteins within the smooth endoplasmic reticulum (SER) would suggest proliferation of this organelle, which most likely is the main molecular process underlying the LH observed in XME studies. In another subset of 2 studies (including troglitazone), a marked up-regulation of genes involved in peroxisomal fatty acid ß-oxidation was noted, associated with induction of genes involved in peroxisome proliferation. Therefore, an increase in peroxisome abundance would be the main mechanism underlying LH noted in this second study subset. Together, the use of transcript profiling provides a means to generate putative mechanistic models underlying the pathogenesis of liver hypertrophy, to distinguish between subtle variations in subcellular organelle proliferation and creates opportunities for improved mechanism-based risk assessment.

Cross-study and cross-omics comparisons of three nephrotoxic compounds reveal mechanistic insights and new candidate biomarkers.

The European InnoMed-PredTox project was a collaborative effort between 15 pharmaceutical companies, 2 small and mid-sized enterprises, and 3 universities with the goal of delivering deeper insights into the molecular mechanisms of kidney and liver toxicity and to identify mechanism-linked diagnostic or prognostic safety biomarker candidates by combining conventional toxicological parameters with "omics" data. Mechanistic toxicity studies with 16 different compounds, 2 dose levels, and 3 time points were performed in male Crl: WI(Han) rats. Three of the 16 investigated compounds, BI-3 (FP007SE), Gentamicin (FP009SF), and IMM125 (FP013NO), induced kidney proximal tubule damage (PTD). In addition to histopathology and clinical chemistry, transcriptomics microarray and proteomics 2D-DIGE analysis were performed. Data from the three PTD studies were combined for a cross-study and cross-omics meta-analysis of the target organ. The mechanistic interpretation of kidney PTD-associated deregulated transcripts revealed, in addition to previously described kidney damage transcript biomarkers such as KIM-1, CLU and TIMP-1, a number of additional deregulated pathways congruent with histopathology observations on a single animal basis, including a specific effect on the complement system. The identification of new, more specific biomarker candidates for PTD was most successful when transcriptomics data were used. Combining transcriptomics data with proteomics data added extra value.

The enhanced value of combining conventional and "omics" analyses in early assessment of drug-induced hepatobiliary injury.

The InnoMed PredTox consortium was formed to evaluate whether conventional preclinical safety assessment can be significantly enhanced by incorporation of molecular profiling ("omics") technologies. In short-term toxicological studies in rats, transcriptomics, proteomics and metabolomics data were collected and analyzed in relation to routine clinical chemistry and histopathology. Four of the sixteen hepato- and/or nephrotoxicants given to rats for 1, 3, or 14days at two dose levels induced similar histopathological effects. These were characterized by bile duct necrosis and hyperplasia and/or increased bilirubin and cholestasis, in addition to hepatocyte necrosis and regeneration, hepatocyte hypertrophy, and hepatic inflammation. Combined analysis of liver transcriptomics data from these studies revealed common gene expression changes which allowed the development of a potential sequence of events on a mechanistic level in accordance with classical endpoint observations. This included genes implicated in early stress responses, regenerative processes, inflammation with inflammatory cell immigration, fibrotic processes, and cholestasis encompassing deregulation of certain membrane transporters. Furthermore, a preliminary classification analysis using transcriptomics data suggested that prediction of cholestasis may be possible based on gene expression changes seen at earlier time-points. Targeted bile acid analysis, based on LC-MS metabonomics data demonstrating increased levels of conjugated or unconjugated bile acids in response to individual compounds, did not provide earlier detection of toxicity as compared to conventional parameters, but may allow distinction of different types of hepatobiliary toxicity. Overall, liver transcriptomics data delivered mechanistic and molecular details in addition to the classical endpoint observations which were further enhanced by targeted bile acid analysis using LC/MS metabonomics.

Gene expression-based in vivo and in vitro prediction of liver toxicity allows compound selection at an early stage of drug development.

We have analyzed gene expression and histopathology of rat liver treated with a histamine-3 receptor inverse agonist under development for the treatment of obesity 24 h after a single acute administration. While histopathology did not identify a clear liver toxicity, analysis of gene changes strongly suggested the development of toxicity. This prediction was confirmed in a 2-week repeat-dose rat study where prominent liver pathology occurred, while gene changes that lead to the prediction persisted. A subset of these genes was analyzed in vitro in both rat and human hepatocytes to reveal the potential relevancy of the findings for the situation in humans. This comprehensive analysis of the development compound at the gene expression level allowed interpretation of findings of the follow-up compound in a frontloaded 24-h single-dose acute study that was initiated before regular 2-week repeat-dose studies started. The high similarity of the follow-up compound to the lead compound based on gene expression lead to the immediate termination of the development program for this compound series. Our data demonstrate the value of genomics-based early toxicity prediction in short-term in vivo studies for the characterization of compounds to allow prioritization and selection of suited candidates before compound-, animal-, and cost-intensive longer term studies are undertaken.

Preclinical evidence for nitrogen-containing bisphosphonate inhibition of farnesyl diphosphate (FPP) synthase in the kidney: implications for renal safety.

Bisphosphonates are potent inhibitors of osteoclast-mediated bone resorption and play an important role in the treatment of osteoporosis, metastatic bone disease, and Paget disease. However, nephrotoxicity has been reported with some bisphosphonates. Nitrogen-containing bisphosphonates directly inhibit farnesyl diphosphate (FPP) synthase activity (mevalonate pathway) and reduce protein prenylation leading to osteoclast cell death. The aim here was to elucidate if this inhibition also occurs in kidney cells and may directly account for nephrotoxicity. In an exploratory study in rats receiving zoledronate or ibandronate an approximate 2-fold increase in FPP synthase mRNA levels was observed in the kidney. The involvement of the mevalonate pathway was confirmed in subsequent in vitro studies with zoledronate, ibandronate, and pamidronate, using the non-nitrogen containing bisphosphonate clodronate as a comparator. In vitro changes in FPP synthase mRNA expression, enzyme activity, and levels of prenylated proteins were assessed. Using two cell lines (a rat normal kidney cell line, NRK-52E, and a human kidney proximal tubule cell line, HK-2), ibandronate and zoledronate were identified as most cytotoxic (EC50: 23/>1000 microM and 16/82 microM, respectively) and as the most potent inhibitors of FPP synthase (IC50; 1.6/7.4 microM and 0.5/0.7 microM, respectively). In both cell lines, inhibition of FPP synthase activity occurred prior to a decrease in levels of prenylated proteins followed by cytotoxicity. This further supports that the mechanism responsible for osteoclast inhibition (therapeutic effect) might also underlie the mechanism of nephrotoxicity.

Gene expression analysis of the hepatotoxicant methapyrilene in primary rat hepatocytes: an interlaboratory study.

Genomics technologies are used in several disciplines, including toxicology. However, these technologies are relatively new, and their applications require further investigations. When investigators apply these technologies to in vitro experiments, two major issues need to be clarified: a) can in vitro toxicity studies, in combination with genomics analyses, be used to predict the toxicity of a compound; and b) are the generated toxicogenomics data reproducible between laboratories? These questions were addressed by an interlaboratory study with laboratories of four pharmaceutical companies. We evaluated gene expression patterns from cultured rat primary hepatocytes after a 24-hr incubation with methapyrilene (MP). Extensive data analysis showed that comparison of genomics data from different sources is complex because both experimental and statistical variability are important confounding factors. However, appropriate statistical tools allowed us to use gene expression profiles to distinguish high-dose-treated cells from vehicle-treated cells. Moreover, we correctly identified MP in an independently generated in vitro database, underlining that in vitro toxicogenomics could be a predictive tool for toxicity. From a mechanistic point of view, despite the observed site-to-site variability, there was good concordance regarding the affected biologic processes. Several subsets of regulated genes were obtained by analyzing the data sets with one method or using different statistical analysis methods. The identified genes are involved in cellular processes that are associated to the exposure of primary hepatocytes to MP. Whether they are specific for MP and are cause or consequence of the toxicity requires further investigations.

Assessment of hepatotoxic liabilities by transcript profiling.

Male Wistar rats were treated with various model compounds or the appropriate vehicle controls in order to create a reference database for toxicogenomics assessment of novel compounds. Hepatotoxic compounds in the database were either known hepatotoxicants or showed hepatotoxicity during preclinical testing. Histopathology and clinical chemistry data were used to anchor the transcript profiles to an established endpoint (steatosis, cholestasis, direct acting, peroxisomal proliferation or nontoxic/control). These reference data were analyzed using a supervised learning method (support vector machines, SVM) to generate classification rules. This predictive model was subsequently used to assess compounds with regard to a potential hepatotoxic liability. A steatotic and a non-hepatotoxic 5HT(6) receptor antagonist compound from the same series were successfully discriminated by this toxicogenomics model. Additionally, an example is shown where a hepatotoxic liability was correctly recognized in the absence of pathological findings. In vitro experiments and a dog study confirmed the correctness of the toxicogenomics alert. Another interesting observation was that transcript profiles indicate toxicologically relevant changes at an earlier timepoint than routinely used methods. Together, these results support the useful application of toxicogenomics in raising alerts for adverse effects and generating mechanistic hypotheses that can be followed up by confirmatory experiments.

Toxicogenomics in predictive toxicology in drug development.

The goal of toxicology is the assessment of possible risk to man. An emerging technology with the potential to have a major impact on risk assessment is toxicogenomics. In this review, we provide an overview of the many possibilities for toxicogenomics including technology platforms, data interpretation, and regulatory perspective and we give examples of toxicogenomics investigations. Toxicogenomics is a powerful tool for compound classification, for mechanistic studies, and for the detection of toxicity markers. Thus, toxicogenomics helps in the extrapolation of findings across species and increases predictability. Biomarkers are valuable in the evaluation of compounds at earlier development phases, improving clinical candidate selection. Caution regarding the interpretation of the results is still necessary. Nevertheless, toxicogenomics will accelerate preclinical safety assessments and improve the prediction of toxic liabilities, as well as of potential risk accumulation for drug-drug or drug-disease interactions.

Toxicogenomics in the pharmaceutical industry: hollow promises or real benefit?

Almost 10 years ago, microarray technology was established as a new powerful tool for large-scale analysis of gene expression. Soon thereafter the new technology was discovered by toxicologists for the purpose of deciphering the molecular events underlying toxicity, and the term "Toxicogenomics" appeared in scientific literature. Ever since, the toxicology community was fascinated by the multiplicity of sophisticated possibilities toxicogenomics seems to offer: genome-wide analysis of toxicant-induced expression profiles may provide a means for prediction of toxicity prior to classical toxicological endpoints such as histopathology or clinical chemistry. Some researchers even speculated of the classical methods being superfluous before long. It was assumed that by using toxicogenomics it would be possible to classify compounds early in drug development and consequently save animals, time, and money in pre-clinical toxicity studies. Moreover, it seemed within reach to unravel the molecular mechanisms underlying toxicity. The feasibility of bridging data derived from in vitro and in vivo systems, identifying new biomarkers, and comparing toxicological responses "across-species" was also excessively praised. After several years of intensive application of microarray technology in the field of toxicology, not only by the pharmaceutical industry, it is now time to survey its achievements and to question how many of these wishes and promises have really come true.

Discriminating different classes of toxicants by transcript profiling.

Male rats were treated with various model compounds or the appropriate vehicle controls. Most substances were either well-known hepatotoxicants or showed hepatotoxicity during preclinical testing. The aim of the present study was to determine if biological samples from rats treated with various compounds can be classified based on gene expression profiles. In addition to gene expression analysis using microarrays, a complete serum chemistry profile and liver and kidney histopathology were performed. We analyzed hepatic gene expression profiles using a supervised learning method (support vector machines; SVMs) to generate classification rules and combined this with recursive feature elimination to improve classification performance and to identify a compact subset of probe sets with potential use as biomarkers. Two different SVM algorithms were tested, and the models obtained were validated with a compound-based external cross-validation approach. Our predictive models were able to discriminate between hepatotoxic and nonhepatotoxic compounds. Furthermore, they predicted the correct class of hepatotoxicant in most cases. We provide an example showing that a predictive model built on transcript profiles from one rat strain can successfully classify profiles from another rat strain. In addition, we demonstrate that the predictive models identify nonresponders and are able to discriminate between gene changes related to pharmacology and toxicity. This work confirms the hypothesis that compound classification based on gene expression data is feasible.

Interlaboratory evaluation of rat hepatic gene expression changes induced by methapyrilene.

Several studies using microarrays have shown that changes in gene expression provide information about the mechanism of toxicity induced by xenobiotic agents. Nevertheless, the issue of whether gene expression profiles are reproducible across different laboratories remains to be determined. To address this question, several members of the Hepatotoxicity Working Group of the International Life Sciences Institute Health and Environmental Sciences Institute evaluated the liver gene expression profiles of rats treated with methapyrilene (MP). Animals were treated at one facility, and RNA was distributed to five different sites for gene expression analysis. A preliminary evaluation of the number of modulated genes uncovered striking differences between the five different sites. However, additional data analysis demonstrated that these differences had an effect on the absolute gene expression results but not on the outcome of the study. For all users, unsupervised algorithms showed that gene expression allows the distinction of the high dose of MP from controls and low dose. In addition, the use of a supervised analysis method (support vector machines) made it possible to correctly classify samples. In conclusion, the results show that, despite some variability, robust gene expression changes were consistent between sites. In addition, key expression changes related to the mechanism of MP-induced hepatotoxicity were identified. These results provide critical information regarding the consistency of microarray results across different laboratories and shed light on the strengths and limitations of expression profiling in drug safety analysis.

Gene expression in two hepatic cell lines, cultured primary hepatocytes, and liver slices compared to the in vivo liver gene expression in rats: possible implications for toxicogenomics use of in vitro systems.

Microarray technology allows the simultaneous analysis of mRNA expression levels of thousands of genes. In the field of toxicogenomics, this technology could help to identify potentially unsafe compounds based on the changes in mRNA expression patterns they induce. Rodent in vivo and in vitro systems are currently the experimental models of choice for predictive toxicology, especially in early phases of development. This study characterizes several hepatic in vitro systems based on mRNA expression profiles, comparing them to gene expression in liver tissue. The in vitro systems investigated comprise two rat liver cell lines (BRL3A and NRL clone 9), primary hepatocytes in conventional monolayer or in sandwich culture, and liver slices. The results demonstrate that liver slices exhibit the strongest similarity to liver tissue regarding mRNA expression, whereas the two cell lines are quite different from the whole liver. We were able to identify genes with strong changes in expression levels in all or at least one of the in vitro systems relative to whole liver. In particular, for some cytochrome P450s the differences observed on the mRNA expression level were paralleled by protein expression and enzymatic activity. In addition, the effect of time in culture was assessed. We were able to show a profound effect of the duration of culture. Expression patterns change most rapidly soon after cell isolation and culture initiation and stabilize with time in culture. The findings are discussed with respect to the usefulness of the various hepatic in vitro systems for microarray-based toxicological testing of compounds.

Proteomic analysis of the rat liver.

Rat is a useful, widely used animal model for biological and toxicity studies. We analyzed total and cytosolic rat liver proteins by applying proteomics technologies. The proteins were separated by two-dimensional electrophoresis employing broad and narrow range immobilized pH gradient strips, followed by MALDI-MS analysis of the tryptic digests. Two hundred and seventy-three different gene products were identified, of which approximately 60% were enzymes with a broad spectrum of catalytic activities. Most of the identified proteins were detected in other rat protein samples as well, which were analyzed in our laboratory. Fifteen gene products were detected for the first time. These were represented by one spot each, whereas most of the frequently detected proteins were represented by multiple spots. In average, approximately five to 10 spots corresponded to one gene product. The database includes a large number of proteins known to be involved in toxicology-relevant pathways and may be useful in toxicity prediction studies.

Identification of metabolites, clinical chemistry markers and transcripts associated with hepatotoxicity.

Early and accurate pre-clinical and clinical biomarkers of hepatotoxicity facilitate the drug development process and the safety monitoring in clinical studies. We selected eight known model compounds to be administered to male Wistar rats to identify biomarkers of drug induced liver injury (DILI) using transcriptomics, metabolite profiling (metabolomics) and conventional endpoints. We specifically explored early biomarkers in serum and liver tissue associated with histopathologically evident acute hepatotoxicity. A tailored data analysis strategy was implemented to better differentiate animals with no treatment-related findings in the liver from animals showing evident hepatotoxicity as assessed by histopathological analysis. From the large number of assessed parameters, our data analysis strategy allowed us to identify five metabolites in serum and five in liver tissue, 58 transcripts in liver tissue and seven clinical chemistry markers in serum that were significantly associated with acute hepatotoxicity. The identified markers comprised metabolites such as taurocholic acid and putrescine (measured as sum parameter together with agmatine), classical clinical chemistry markers like AST (aspartate aminotransferase), ALT (alanine aminotransferase), and bilirubin, as well as gene transcripts like Igfbp1 (insulin-like growth factor-binding protein 1) and Egr1 (early growth response protein 1). The response pattern of the identified biomarkers was concordant across all types of parameters and sample matrices. Our results suggest that a combination of several of these biomarkers could significantly improve the robustness and accuracy of an early diagnosis of hepatotoxicity.

A real-time impedance-based screening assay for drug-induced vascular leakage.

Vascular leakage is a serious side effect of therapies based on monoclonal antibodies or cytokines which may lead to life-threatening situations. With the steady increase of new drug development programs for large molecules, there is an urgent need for reliable tools to assess this potential liability of new medicines in a rapid and cost-effective manner. Using human umbilical vein endothelial cells (HUVECs) as a model for endothelium, we established an impedance-based assay measuring the integrity of the endothelial cell monolayer in real time. We could demonstrate that the HUVEC monolayer in our system was a relevant model as cells expressed major junctional proteins known to be responsible for maintaining tightness as well as receptors targeted by molecules known to induce vascular leakage in vivo. We assessed the time-dependent loss of barrier function using impedance and confirmed that signals obtained corresponded well to those from standard transwell assays. We assayed a series of reference molecules which led to the expected change of barrier integrity. A nonspecific cytotoxic effect could be excluded by using human fibroblasts as a nonresponder cell line. Finally, we could show reversibility of vascular permeability induced by histamine, IL-1ß, or TNF-α by coincubation with established antagonists, further demonstrating relevance of this new model. Taken together, our results suggest that impedance in combination with HUVECs as a specific model can be applied to assess clinically relevant vascular leakage on an in vitro level.

Bioengineered 3D human kidney tissue, a platform for the determination of nephrotoxicity.

The staggering cost of bringing a drug to market coupled with the extremely high failure rate of prospective compounds in early phase clinical trials due to unexpected human toxicity makes it imperative that more relevant human models be developed to better predict drug toxicity. Drug-induced nephrotoxicity remains especially difficult to predict in both pre-clinical and clinical settings and is often undetected until patient hospitalization. Current pre-clinical methods of determining renal toxicity include 2D cell cultures and animal models, both of which are incapable of fully recapitulating the in vivo human response to drugs, contributing to the high failure rate upon clinical trials. We have bioengineered a 3D kidney tissue model using immortalized human renal cortical epithelial cells with kidney functions similar to that found in vivo. These 3D tissues were compared to 2D cells in terms of both acute (3 days) and chronic (2 weeks) toxicity induced by Cisplatin, Gentamicin, and Doxorubicin using both traditional LDH secretion and the pre-clinical biomarkers Kim-1 and NGAL as assessments of toxicity. The 3D tissues were more sensitive to drug-induced toxicity and, unlike the 2D cells, were capable of being used to monitor chronic toxicity due to repeat dosing. The inclusion of this tissue model in drug testing prior to the initiation of phase I clinical trials would allow for better prediction of the nephrotoxic effects of new drugs.

A simple whole blood bioassay detects cytokine responses to anti-CD28SA and anti-CD52 antibodies.

INTRODUCTION: In 2006 the anti-CD28 superagonistic IgG4 TGN1412, having passed pre-clinical safety screens, caused a severe 'cytokine storm' in 6 healthy volunteers. Others have shown that for TGN1412 to induce an inflammatory signal in human peripheral blood mononuclear cells (PBMCs) or in human diluted blood, endothelial cells or bound monoclonal antibody (mAb) is required as part of a bioassay complex. These types of protocols rely on different donor cells and therefore have limitations as bioassays for pre-clinical testing. METHODS: We performed studies using human PBMC/endothelial cell co-cultures, whole blood/endothelial cell co-cultures and human whole blood alone. We bracketed responses of a CD28 superagonist antibody with mAbs against CD52 (alemtuzumab, MabCampath-1H) or epidermal growth factor receptor (cetuximab, Erbitux) and with the immunostimulant lipopolysaccharide. We detected cytokine responses at the level of protein release (using ELISAs and Luminex assays) and gene induction (using real-time PCR arrays). RESULTS: Here we confirm that IL-8 release was induced in a mixed endothelial cell-PBMC system by the anti-CD28 mAb. We go on to show that an alemtuzumab and an anti-CD28 mAb, but not cetuximab induced the release of a range of cytokines including IL-8, IL-6, IFNγ, IL-2 and IL10 after 24h and induced cytokine gene induction after 1h. Co-cultures of whole blood and HUVECS showed larger variability but no superiority over whole blood alone at a range of time points (0.5-48h). DISCUSSION: We suggest that, whilst limitations exist, human blood-based in vitro assays may prove useful in assessing the potential of mAbs and other biotherapeutics to cause release of cytokines in humans.