Toxicity and efficacy of green tea catechin derivative-based micellar nanocomplexes for anticancer protein delivery.

Toxicity towards non-tumor cells during anticancer therapy can be reduced by using nanoscale systems for anticancer drug delivery. Usually only the loaded drug has anticancer activity. Recently, micellar nanocomplexes (MNCs) comprising green tea catechin derivatives for the delivery of the anticancer proteins, such as Herceptin, have been developed. Herceptin as well as the MNCs without the drug were effective against HER2/neu-overexpressing human tumor cells and had synergistic anticancer effects in vitro and in vivo. It remained unclear which kinds of negative effects the MNCs had on tumor cells exactly, and which of their components mediated them. Also, it was unclear if MNC has any toxicity effects on the normal cells of vital human organ systems. Herein we examined the effects of Herceptin-MNCs and their individual components on human breast cancer cells and on normal primary human endothelial and kidney proximal tubular cells. We applied a novel in vitro model that predicts nephrotoxicity in humans with high accuracy, as well as high-content screening and microfluidic mono- and co-culture models to thoroughly address effects on various cell types. The results showed that MNCs alone were profoundly toxic for breast cancer cells, and induced apoptosis regardless of HER2/neu expression levels. Apoptosis was induced by both green tea catechin derivatives contained within MNCs. In contrast, MNCs were not toxic for normal human cells, and the probability was low that MNCs would be nephrotoxic in humans. Together, the results supported the hypothesis that green tea catechin derivative-based MNCs could improve efficacy and safety of therapies with anticancer proteins.

Predicting direct hepatocyte toxicity in humans by combining high-throughput imaging of HepaRG cells and machine learning-based phenotypic profiling.

Accurate prediction of drug- and chemical-induced hepatotoxicity remains to be a problem for pharmaceutical companies as well as other industries and regulators. The goal of the current study was to develop an in vitro/in silico method for the rapid and accurate prediction of drug- and chemical-induced hepatocyte injury in humans. HepaRG cells were employed for high-throughput imaging in combination with phenotypic profiling. A reference set of 69 drugs and chemicals was screened at a range of 7 concentrations, and the cellular response values were used for training a supervised classifier and for determining assay performance by using tenfold cross-validation. The results showed that the best performing phenotypic features were related to nuclear translocation of RELA (RELA proto-oncogene, NF-kB subunit; also known as NF-kappa B p65), DNA organization, and the F-actin cytoskeleton. Using a subset of 30 phenotypic features, direct hepatocyte toxicity in humans could be predicted with a test sensitivity, specificity and balanced accuracy of 73%, 92%, and 83%, respectively. The method was applied to another set of 26 drugs and chemicals with unclear annotation and their hepatocyte toxicity in humans was predicted. The results also revealed that the identified discriminative phenotypic changes were related to cell death and cellular senescence. Whereas cell death-related endpoints are widely applied in in vitro toxicology, cellular senescence-related endpoints are not, although cellular senescence can be induced by various drugs and other small molecule compounds and plays an important role in liver injury and disease. These findings show how phenotypic profiling can reveal unexpected chemical-induced mechanisms in toxicology.

Assessing Toxicity with Human Cell-Based In Vitro Methods.

In toxicology, there is a strong push towards replacing animal experiments with alternative methods, which include cell-based in vitro methods for the assessment of adverse health effects in humans. High-throughput methods are of central interest due to the large and steadily growing numbers of compounds that require assessment. Tremendous progress has been made during the last decade in developing and applying such methods. Innovative technologies for addressing complex biological interactions include induced pluripotent stem cell- and organoid-based approaches, organotypic coculture systems, and microfluidic 'multiorgan' chips. Combining in vitro methods with bioinformatics and in silico modeling generates new powerful tools for toxicity assessment, and the rapid progress in the field is expected to continue.

A Case Study with Triazole Fungicides to Explore Practical Application of Next-Generation Hazard Assessment Methods for Human Health.

The ongoing developments in chemical risk assessment have led to new concepts building on integration of sophisticated nonanimal models for hazard characterization. Here we explore a pragmatic approach for implementing such concepts, using a case study of three triazole fungicides, namely, flusilazole, propiconazole, and cyproconazole. The strategy applied starts with evaluating the overall level of concern by comparing exposure estimates to toxicological potential, followed by a combination of in silico tools and literature-derived high-throughput screening assays and computational elaborations to obtain insight into potential toxicological mechanisms and targets in the organism. Additionally, some targeted in vitro tests were evaluated for their utility to confirm suspected mechanisms of toxicity and to generate points of departure. Toxicological mechanisms instead of the current "end point-by-end point" approach should guide the selection of methods and assays that constitute a toolbox for next-generation risk assessment. Comparison of the obtained in silico and in vitro results with data from traditional in vivo testing revealed that, overall, nonanimal methods for hazard identification can produce adequate qualitative hazard information for risk assessment. Follow-up studies are needed to further refine the proposed approach, including the composition of the toolbox, toxicokinetics models, and models for exposure assessment.

Correction to: Particle toxicology and health - where are we?

After the publication of this article [1] it was hihglighted that the number of deaths related to natural disasters was incorrectly reported in the second paragraph of the Hazards from Natural particulates and the evolution of the biosphere section. This correction article shows the correct and incorrect statement. This correction does not change the idea presented in the article that from an evolutionary view point, natural disasters account only for a small fraction of the people on the planet. The original article has been updated.

Particle toxicology and health - where are we?

BACKGROUND: Particles and fibres affect human health as a function of their properties such as chemical composition, size and shape but also depending on complex interactions in an organism that occur at various levels between particle uptake and target organ responses. While particulate pollution is one of the leading contributors to the global burden of disease, particles are also increasingly used for medical purposes. Over the past decades we have gained considerable experience in how particle properties and particle-bio interactions are linked to human health. This insight is useful for improved risk management in the case of unwanted health effects but also for developing novel medical therapies. The concepts that help us better understand particles' and fibres' risks include the fate of particles in the body; exposure, dosimetry and dose-metrics and the 5 Bs: bioavailability, biopersistence, bioprocessing, biomodification and bioclearance of (nano)particles. This includes the role of the biomolecule corona, immunity and systemic responses, non-specific effects in the lungs and other body parts, particle effects and the developing body, and the link from the natural environment to human health. The importance of these different concepts for the human health risk depends not only on the properties of the particles and fibres, but is also strongly influenced by production, use and disposal scenarios. CONCLUSIONS: Lessons learned from the past can prove helpful for the future of the field, notably for understanding novel particles and fibres and for defining appropriate risk management and governance approaches.

Comment on Sjögren et al. (2018) A novel multi-parametric high-content screening assay in ciPTEC-OAT1 to predict drug-induced nephrotoxicity in drug discovery. Arch Toxicol 92(10):3175-3190.

Rapid progress is made in the development of high-content screening assays for the prediction of nephrotoxicity. The findings from different laboratories are consistent with respect to endpoints and concentration ranges screened. Discrepancies regarding compound annotation and the predictive performance analysis are discussed.

High-throughput prediction of nephrotoxicity in humans.

The Lush Science Prize 2016 was awarded to Daniele Zink and Lit-Hsin Loo for the interdisciplinary and collaborative work between their research groups in developing alternative methods for the prediction of nephrotoxicity in humans. The collaboration has led to the establishment of a series of pioneering alternative methods for nephrotoxicity prediction, which includes: predictive gene expression markers based on pro-inflammatory responses; predictive in vitro cellular models based on pluripotent stem cell-derived proximal tubular-like cells; and predictive cellular phenotypic markers based on chromatin and cytoskeletal changes. A high-throughput method was established for chemical testing, which is currently being used to predict the potential human nephrotoxicity of ToxCast compounds in collaboration with the US Environmental Protection Agency. Similar high-throughput imaging-based methodologies are currently being developed and adapted by the Zink and Loo groups, to include other human organs and cell types. The ultimate goal is to develop a portfolio of methods accepted for the accurate prediction of human organ-specific toxicity and the consequent replacement of animal experiments.

Stem cell-derived kidney cells and organoids: Recent breakthroughs and emerging applications.

The global rise in the numbers of kidney patients and the shortage in transplantable organs have led to an increasing interest in kidney-specific regenerative therapies, renal disease modelling and bioartificial kidneys. Sources for large quantities of high-quality renal cells and tissues would be required, also for applications in in vitro platforms for compound safety and efficacy screening. Stem cell-based approaches for the generation of renal-like cells and tissues would be most attractive, but such methods were not available until recently. This situation has drastically changed since 2013, and various protocols for the generation of renal-like cells and precursors from pluripotent stem cells (PSC) have been established. The most recent breakthroughs were related to the establishment of various protocols for the generation of PSC-derived kidney organoids. In combination with recent advances in genome editing, bioprinting and the establishment of predictive renal screening platforms this results in exciting new possibilities. This review will give a comprehensive overview over current PSC-based protocols for the generation of renal-like cells, precursors and organoids, and their current and potential applications in regenerative medicine, compound screening, disease modelling and bioartificial organs.

High-throughput imaging-based nephrotoxicity prediction for xenobiotics with diverse chemical structures.

The kidney is a major target for xenobiotics, which include drugs, industrial chemicals, environmental toxicants and other compounds. Accurate methods for screening large numbers of potentially nephrotoxic xenobiotics with diverse chemical structures are currently not available. Here, we describe an approach for nephrotoxicity prediction that combines high-throughput imaging of cultured human renal proximal tubular cells (PTCs), quantitative phenotypic profiling, and machine learning methods. We automatically quantified 129 image-based phenotypic features, and identified chromatin and cytoskeletal features that can predict the human in vivo PTC toxicity of 44 reference compounds with ~82 % (primary PTCs) or 89 % (immortalized PTCs) test balanced accuracies. Surprisingly, our results also revealed that a DNA damage response is commonly induced by different PTC toxicants that have diverse chemical structures and injury mechanisms. Together, our results show that human nephrotoxicity can be predicted with high efficiency and accuracy by combining cell-based and computational methods that are suitable for automation.

Prediction of drug-induced nephrotoxicity and injury mechanisms with human induced pluripotent stem cell-derived cells and machine learning methods.

The renal proximal tubule is a main target for drug-induced toxicity. The prediction of proximal tubular toxicity during drug development remains difficult. Any in vitro methods based on induced pluripotent stem cell-derived renal cells had not been developed, so far. Here, we developed a rapid 1-step protocol for the differentiation of human induced pluripotent stem cells (hiPSC) into proximal tubular-like cells. These proximal tubular-like cells had a purity of >90% after 8 days of differentiation and could be directly applied for compound screening. The nephrotoxicity prediction performance of the cells was determined by evaluating their responses to 30 compounds. The results were automatically determined using a machine learning algorithm called random forest. In this way, proximal tubular toxicity in humans could be predicted with 99.8% training accuracy and 87.0% test accuracy. Further, we studied the underlying mechanisms of injury and drug-induced cellular pathways in these hiPSC-derived renal cells, and the results were in agreement with human and animal data. Our methods will enable the development of personalized or disease-specific hiPSC-based renal in vitro models for compound screening and nephrotoxicity prediction.

The multi-facets of sustainable nanotechnology - Lessons from a nanosafety symposium.

An international symposium for nanosafety was held recently at the Nanyang Technological University in Singapore. Topics relating to understanding nanomaterial properties, tools, and infrastructure required for predicting hazardous outcomes, measuring nanomaterial exposure levels, systems approach for risk assessment and public's perception of nanotechnology were covered. The need for a multidisciplinary approach, across both natural and social sciences, for developing sustainable nanotechnology solutions was heavily emphasized. This commentary highlights the major issues discussed and the commitment of the nanosafety research community in Singapore to contribute collectively to realise the vision of sustainable nanotechnology.

Supervised prediction of drug-induced nephrotoxicity based on interleukin-6 and -8 expression levels.

BACKGROUND: Drug-induced nephrotoxicity causes acute kidney injury and chronic kidney diseases, and is a major reason for late-stage failures in the clinical trials of new drugs. Therefore, early, pre-clinical prediction of nephrotoxicity could help to prioritize drug candidates for further evaluations, and increase the success rates of clinical trials. Recently, an in vitro model for predicting renal-proximal-tubular-cell (PTC) toxicity based on the expression levels of two inflammatory markers, interleukin (IL)-6 and -8, has been described. However, this and other existing models usually use linear and manually determined thresholds to predict nephrotoxicity. Automated machine learning algorithms may improve these models, and produce more accurate and unbiased predictions. RESULTS: Here, we report a systematic comparison of the performances of four supervised classifiers, namely random forest, support vector machine, k-nearest-neighbor and naive Bayes classifiers, in predicting PTC toxicity based on IL-6 and -8 expression levels. Using a dataset of human primary PTCs treated with 41 well-characterized compounds that are toxic or not toxic to PTC, we found that random forest classifiers have the highest cross-validated classification performance (mean balanced accuracy = 87.8%, sensitivity = 89.4%, and specificity = 85.9%). Furthermore, we also found that IL-8 is more predictive than IL-6, but a combination of both markers gives higher classification accuracy. Finally, we also show that random forest classifiers trained automatically on the whole dataset have higher mean balanced accuracy than a previous threshold-based classifier constructed for the same dataset (99.3% vs. 80.7%). CONCLUSIONS: Our results suggest that a random forest classifier can be used to automatically predict drug-induced PTC toxicity based on the expression levels of IL-6 and -8.

Polysulfone membranes coated with polymerized 3,4-dihydroxy-l-phenylalanine are a versatile and cost-effective synthetic substrate for defined long-term cultures of human pluripotent stem cells.

Clinical and industrial applications of human pluripotent stem cells (hPSC) require large amounts of cells that have been expanded under defined conditions. Labor-intensive techniques and ill-defined or expensive compounds and substrates are not applicable. Here we describe a chemically defined synthetic substrate consisting of polysulfone (PSF) membranes coated with polymerized 3,4-dihydroxy-l-phenylalanine (DOPA). DOPA/PSF is inexpensive and can be easily produced at various shapes and sizes. DOPA/PSF supports long-term self-renewal of undifferentiated human embryonic (hESC) and human induced pluripotent stem cells (hiPSC) under defined conditions. Pluripotency is maintained for at least 10 passages. Adhesion of hPSC to DOPA/PSF is mainly mediated by a specific integrin heterodimer. Proliferation and gene expression patterns on DOPA/PSF and control substrates are comparable. Labor-intensive cultivation methods and use of serum or coating with proteins are not required. Together, these features make DOPA/PSF attractive for applications where large-scale expansion of human pluripotent stem cells under defined conditions is essential.

DNA compaction induced by a cationic polymer or surfactant impact gene expression and DNA degradation.

There is an increasing interest in achieving gene regulation in biotechnological and biomedical applications by using synthetic DNA-binding agents. Most studies have so far focused on synthetic sequence-specific DNA-binding agents. Such approaches are relatively complicated and cost intensive and their level of sophistication is not always required, in particular for biotechnological application. Our study is inspired by in vivo data that suggest that DNA compaction might contribute to gene regulation. This study exploits the potential of using synthetic DNA compacting agents that are not sequence-specific to achieve gene regulation for in vitro systems. The semi-synthetic in vitro system we use include common cationic DNA-compacting agents, poly(amido amine) (PAMAM) dendrimers and the surfactant hexadecyltrimethylammonium bromide (CTAB), which we apply to linearized plasmid DNA encoding for the luciferase reporter gene. We show that complexing the DNA with either of the cationic agents leads to gene expression inhibition in a manner that depends on the extent of compaction. This is demonstrated by using a coupled in vitro transcription-translation system. We show that compaction can also protect DNA against degradation in a dose-dependent manner. Furthermore, our study shows that these effects are reversible and DNA can be released from the complexes. Release of DNA leads to restoration of gene expression and makes the DNA susceptible to degradation by Dnase. A highly charged polyelectrolyte, heparin, is needed to release DNA from dendrimers, while DNA complexed with CTAB dissociates with the non-ionic surfactant C12E5. Our results demonstrate the relation between DNA compaction by non-specific DNA-binding agents and gene expression and gene regulation can be achieved in vitro systems in a reliable dose-dependent and reversible manner.

Drug-induced nephrotoxicity: clinical impact and preclinical in vitro models.

The kidney is a major target for drug-induced toxicity. Drug-induced nephrotoxicity remains a major problem in the clinical setting, where the use of nephrotoxic drugs is often unavoidable. This leads frequently to acute kidney injury, and current problems are discussed. One strategy to avoid such problems would be the development of drugs with decreased nephrotoxic potential. However, the prediction of nephrotoxicity during preclinical drug development is difficult and nephrotoxicity is typically detected only late. Also, the nephrotoxic potential of newly approved drugs is often underestimated. Regulatory approved or validated in vitro models for the prediction of nephrotoxicity are currently not available. Here, we will review current approaches on the development of such models. This includes a discussion of three-dimensional and microfluidic models and recently developed stem cell based approaches. Most in vitro models have been tested with a limited number of compounds and are of unclear predictivity. However, some studies have tested larger numbers of compounds and the predictivity of the respective in vitro model had been determined. The results showed that high predictivity can be obtained by using primary or stem cell derived human renal cells in combination with appropriate end points.

Identification of nephrotoxic compounds with embryonic stem-cell-derived human renal proximal tubular-like cells.

The kidney is a major target for drug-induced toxicity, and the renal proximal tubule is frequently affected. Nephrotoxicity is typically detected only late during drug development, and the nephrotoxic potential of newly approved drugs is often underestimated. A central problem is the lack of preclinical models with high predictivity. Validated in vitro models for the prediction of nephrotoxicity are not available. Major problems are related to the identification of appropriate cell models and end points. As drug-induced kidney injury is associated with inflammatory reactions, we explored the expression of inflammatory markers as end point for renal in vitro models. In parallel, we developed a new cell model. Here, we combined these approaches and developed an in vitro model with embryonic stem-cell-derived human renal proximal tubular-like cells that uses the expression of interleukin (IL)-6 and IL-8 as end points. The predictivity of the model was evaluated with 41 well-characterized compounds. The results revealed that the model predicts proximal tubular toxicity in humans with high accuracy. In contrast, the predictivity was low when well-established standard in vitro assays were used. Together, the results show that high predictivity can be obtained with in vitro models employing pluripotent stem cell-derived human renal proximal tubular-like cells.

A novel design of bioartificial kidneys with improved cell performance and haemocompatibility.

Treatment with bioartificial kidneys had beneficial effects in animal experiments and improved survival of critically ill patients with acute kidney injury in a Phase II clinical trial. However, a Phase II b clinical trial failed. This and other results suggested various problems with the current design of bioartificial kidneys. We propose a novel design to improve various properties of device, including haemocompatibility and cell performance. An important feature of the novel design is confinement of the blood to the lumina of the hollow fibre membranes. This avoids exposure of the blood to the non-haemocompatible outer surfaces of hollow fibre membranes, which usually occurs in bioartificial kidneys. We use these outer surfaces as substrate for cell growth. Our results show that commercial hollow fibre membranes can be directly applied in the bioreactor when human primary renal proximal tubular cells are grown in this configuration, and no coatings are required for the formation of robust and functional renal epithelia. Furthermore, we demonstrate that the bioreactor unit produces significant amounts of interleukins. This result helps to understand the immunomodulatory effects of bioartificial kidneys, which have been observed previously. The novel bioartificial kidney design outlined here and the results obtained would be expected to improve the safety and performance of bioartificial kidneys and to contribute to a better understanding of their effects.