Nano-risk Science: application of toxicogenomics in an adverse outcome pathway framework for risk assessment of multi-walled carbon nanotubes

Bioinformatics and machine learning to support nanomaterial grouping

Nanomaterials (NMs) offer plenty of novel functionalities. Moreover, their physicochemical properties can be fine-tuned to meet the needs of specific applications, leading to virtually unlimited numbers of NM variants. Hence, efficient hazard and risk assessment strategies building on New Approach Methodologies (NAMs) become indispensable. Indeed, the design, the development and implementation of NAMs has been a major topic in a substantial number of research projects. One of the promising strategies that can help to deal with the high number of NMs variants is grouping and read-across. Based on demonstrated structural and physicochemical similarity, NMs can be grouped and assessed together. Within an established NM group, read-across may be performed to fill in data gaps for data-poor variants using existing data for NMs within the group. Establishing a group requires a sound justification, usually based on a grouping hypothesis that links specific physicochemical properties to well-defined hazard endpoints. However, for NMs these interrelationships are only beginning to be understood. The aim of this review is to demonstrate the power of bioinformatics with a specific focus on Machine Learning (ML) approaches to unravel the NM Modes-of-Action (MoA) and identify the properties that are relevant to specific hazards, in support of grouping strategies. This review emphasizes the following messages: 1) ML supports identification of the most relevant properties contributing to specific hazards; 2) ML supports analysis of large omics datasets and identification of MoA patterns in support of hypothesis formulation in grouping approaches; 3) omics approaches are useful for shifting away from consideration of single endpoints towards a more mechanistic understanding across multiple endpoints gained from one experiment; and 4) approaches from other fields of Artificial Intelligence (AI) like Natural Language Processing or image analysis may support automated extraction and interlinkage of information related to NM toxicity. Here, existing ML models for predicting NM toxicity and for analyzing omics data in support of NM grouping are reviewed. Various challenges related to building robust models in the field of nanotoxicology exist and are also discussed.

Physicochemical properties of 26 carbon nanotubes as predictors for pulmonary inflammation and acute phase response in mice following intratracheal lung exposure

Carbon nanotubes (CNTs) vary in physicochemical properties which makes risk assessment challenging. Mice were pulmonary exposed to 26 well-characterized CNTs using the same experimental design and followed for one day, 28 days or 3 months. This resulted in a unique dataset, which was used to identify physicochemical predictors of pulmonary inflammation and systemic acute phase response. MWCNT diameter and SWCNT specific surface area were predictive of lower and higher neutrophil influx, respectively. Manganese and iron were shown to be predictive of higher neutrophil influx at day 1 post-exposure, whereas nickel content interestingly was predictive of lower neutrophil influx at all three time points and of lowered acute phase response at day 1 and 3 months post-exposure. It was not possible to separate effects of properties such as specific surface area and length in the multiple regression analyses due to co-variation.

Advancing chemical safety assessment through an omics-based characterization of the test system-chemical interaction

Assessing chemical safety is essential to evaluate the potential risks of chemical exposure to human health and the environment. Traditional methods relying on animal testing are being replaced by 3R (reduction, refinement, and replacement) principle-based alternatives, mainly depending on in vitro test methods and the Adverse Outcome Pathway framework. However, these approaches often focus on the properties of the compound, missing the broader chemical-biological interaction perspective. Currently, the lack of comprehensive molecular characterization of the in vitro test system results in limited real-world representation and contextualization of the toxicological effect under study. Leveraging omics data strengthens the understanding of the responses of different biological systems, emphasizing holistic chemical-biological interactions when developing in vitro methods. Here, we discuss the relevance of meticulous test system characterization on two safety assessment relevant scenarios and how omics-based, data-driven approaches can improve the future generation of alternative methods.

Are New Phthalate Ester Substitutes Safer than Traditional DBP and DiBP? Comparative Endocrine-Disrupting Analyses on Zebrafish Using In Vivo, Transcriptome, and In Silico Approaches

Although previous studies have confirmed the association between phthalate esters (PAEs) exposure and endocrine disorders in humans, few studies to date have systematically assessed the threats of new PAE alternatives to endocrine disruptions. Herein, zebrafish embryos were continuously exposed to two PAEs [di-n-butyl phthalate (DBP) and diisobutyl phthalate (DiBP)], two structurally related alternatives [diiononyl phthalate (DINP) and diisononyl hexahydrophthalate (DINCH)], and two non-PAE substitutes [dipropylene glycol dibenzoate (DGD) and glyceryl triacetate (GTA)], and the endocrine-disrupting effects were investigated during the early stages (8-48 hpf). For five endogenous hormones, including progesterone, testosterone, 17β-estradiol, triiodothyronine (T3), and cortisol, the tested chemicals disturbed the contents of at least one hormone at environmentally relevant concentrations (≤3.9 μM), except DINCH and GTA. Then, the concentration-dependent reduced zebrafish transcriptome analysis was performed. Thyroid hormone (TH)- and androgen/estrogen-regulated adverse outcome pathways (AOPs) were the two types of biological pathways most sensitive to PAE exposure. Notably, six compounds disrupted four TH-mediated AOPs, from the inhibition of deiodinases (molecular initiating event, MIE), a decrease in T3 levels (key event, KE), to mortality (adverse outcome, AO) with the quantitatively linear relationships between MIE-KE (|r| = 0.96, p = 0.002), KE-AO (|r| = 0.88, p = 0.02), and MIE-AO (|r| = 0.89, p = 0.02). Multiple structural analyses showed that benzoic acid is the critical toxicogenic fragment. Our data will facilitate the screening and development of green alternatives.

A curated gene and biological system annotation of adverse outcome pathways related to human health

Adverse outcome pathways (AOPs) are emerging as a central framework in modern toxicology and other fields in biomedicine. They serve as an extension of pathway-based concepts by depicting biological mechanisms as causally linked sequences of key events (KEs) from a molecular initiating event (MIE) to an adverse outcome. AOPs guide the use and development of new approach methodologies (NAMs) aimed at reducing animal experimentation. While AOPs model the systemic mechanisms at various levels of biological organisation, toxicogenomics provides the means to study the molecular mechanisms of chemical exposures. Systematic integration of these two concepts would improve the application of AOP-based knowledge while also supporting the interpretation of complex omics data. Hence, we established this link through rigorous curation of molecular annotations for the KEs of human relevant AOPs. We further expanded and consolidated the annotations of the biological context of KEs. These curated annotations pave the way to embed AOPs in molecular data interpretation, facilitating the emergence of new knowledge in biomedicine.

Transcriptomic profiling reveals differential cellular response to copper oxide nanoparticles and polystyrene nanoplastics in perfused human placenta

The growing nanoparticulate pollution (e.g. engineered nanoparticles (NPs) or nanoplastics) has been shown to pose potential threats to human health. In particular, sensitive populations such as pregnant women and their unborn children need to be protected from harmful environmental exposures. However, developmental toxicity from prenatal exposure to pollution particles is not yet well studied despite evidence of particle accumulation in human placenta. Our study aimed to investigate how copper oxide NPs (CuO NPs; 10-20 nm) and polystyrene nanoplastics (PS NPs; 70 nm) impact on gene expression in ex vivo perfused human placental tissue. Whole genome microarray analysis revealed changes in global gene expression profile after 6 h of perfusion with sub-cytotoxic concentrations of CuO (10 µg/mL) and PS NPs (25 µg/mL). Pathway and gene ontology enrichment analysis of the differentially expressed genes suggested that CuO and PS NPs trigger distinct cellular response in placental tissue. While CuO NPs induced pathways related to angiogenesis, protein misfolding and heat shock responses, PS NPs affected the expression of genes related to inflammation and iron homeostasis. The observed effects on protein misfolding, cytokine signaling, and hormones were corroborated by western blot (accumulation of polyubiquitinated proteins) or qPCR analysis. Overall, the results of the present study revealed extensive and material-specific interference of CuO and PS NPs with placental gene expression from a single short-term exposure which deserves increasing attention. In addition, the placenta, which is often neglected in developmental toxicity studies, should be a key focus in the future safety assessment of NPs in pregnancy.

Converting Nanotoxicity Data to Information Using Artificial Intelligence and Simulation

Decades of nanotoxicology research have generated extensive and diverse data sets. However, data is not equal to information. The question is how to extract critical information buried in vast data streams. Here we show that artificial intelligence (AI) and molecular simulation play key roles in transforming nanotoxicity data into critical information, i.e., constructing the quantitative nanostructure (physicochemical properties)-toxicity relationships, and elucidating the toxicity-related molecular mechanisms. For AI and molecular simulation to realize their full impacts in this mission, several obstacles must be overcome. These include the paucity of high-quality nanomaterials (NMs) and standardized nanotoxicity data, the lack of model-friendly databases, the scarcity of specific and universal nanodescriptors, and the inability to simulate NMs at realistic spatial and temporal scales. This review provides a comprehensive and representative, but not exhaustive, summary of the current capability gaps and tools required to fill these formidable gaps. Specifically, we discuss the applications of AI and molecular simulation, which can address the large-scale data challenge for nanotoxicology research. The need for model-friendly nanotoxicity databases, powerful nanodescriptors, new modeling approaches, molecular mechanism analysis, and design of the next-generation NMs are also critically discussed. Finally, we provide a perspective on future trends and challenges.

Prediction of zebrafish embryonic developmental toxicity by integrating omics with adverse outcome pathway

New approach methodologies (NAMs), especially omics-based high-throughput bioassays have been developed rapidly, providing rich mechanistic information such as molecular initiation events (MIEs) and (sub)cellular key events (KEs) in adverse outcome pathways (AOPs). However, how to apply the knowledge of MIEs/KEs to predict adverse outcomes (AOs) induced by chemicals represents a new challenge for computational toxicology. Here, an integrated method named ScoreAOP was developed and evaluated to predict chemicals' developmental toxicity for zebrafish embryos by integrating four related AOPs and dose-dependent reduced zebrafish transcriptome (RZT). The rules of ScoreAOP included 1) sensitivity of responsive KEs demonstrated by point of departure of KEs (POD_KE), 2) evidence reliability and 3) distance between KEs and AOs. Moreover, eleven chemicals with different modes of action (MoAs) were tested to evaluate ScoreAOP. Results showed that eight of the eleven chemicals caused developmental toxicity at tested concentration in apical tests. All the tested chemicals' developmental defects were predicted using ScoreAOP, whereas eight out of the eleven chemicals predicted by ScoreMIE which was developed to score MIEs disturbed by chemicals based on in vitro bioassays data. Finally, in terms of mechanism explanation, ScoreAOP clustered chemicals with different MoAs while ScoreMIE failed, and ScoreAOP revealed the activation of aryl hydrocarbon receptor (AhR) plays a significant role in dysfunction of cardiovascular system, resulting in zebrafish developmental defects and mortality. In conclusion, ScoreAOP represents a promising approach to apply mechanism information obtained from omics to predict AOs induced by chemicals.

Comparing species-different responses in pulmonary fibrosis research: Current understanding of in vitro lung cell models and nanomaterials

Pulmonary fibrosis (PF) is a chronic, irreversible lung disease that is typically fatal and characterized by an abnormal fibrotic response. As a result, vast areas of the lungs are gradually affected, and gas exchange is impaired, making it one of the world's leading causes of death. This can be attributed to a lack of understanding of the onset and progression of the disease, as well as a poor understanding of the mechanism of adverse responses to various factors, such as exposure to allergens, nanomaterials, environmental pollutants, etc. So far, the most frequently used preclinical evaluation paradigm for PF is still animal testing. Nonetheless, there is an urgent need to understand the factors that induce PF and find novel therapeutic targets for PF in humans. In this regard, robust and realistic in vitro fibrosis models are required to understand the mechanism of adverse responses. Over the years, several in vitro and ex vivo models have been developed with the goal of mimicking the biological barriers of the lung as closely as possible. This review summarizes recent progress towards the development of experimental models suitable for predicting fibrotic responses, with an emphasis on cell culture methods, nanomaterials, and a comparison of results from studies using cells from various species.

PROTEOMAS: a workflow enabling harmonized proteomic meta-analysis and proteomic signature mapping

Toxicological evaluation of substances in regulation still often relies on animal experiments. Understanding the substances' mode-of-action is crucial to develop alternative test strategies. Omics methods are promising tools to achieve this goal. Until now, most attention was focused on transcriptomics, while proteomics is not yet routinely applied in toxicology despite the large number of datasets available in public repositories. Exploiting the full potential of these datasets is hampered by differences in measurement procedures and follow-up data processing. Here we present the tool PROTEOMAS, which allows meta-analysis of proteomic data from public origin. The workflow was designed for analyzing proteomic studies in a harmonized way and to ensure transparency in the analysis of proteomic data for regulatory purposes. It agrees with the Omics Reporting Framework guidelines of the OECD with the intention to integrate proteomics to other omic methods in regulatory toxicology. The overarching aim is to contribute to the development of AOPs and to understand the mode of action of substances. To demonstrate the robustness and reliability of our workflow we compared our results to those of the original studies. As a case study, we performed a meta-analysis of 25 proteomic datasets to investigate the toxicological effects of nanomaterials at the lung level. PROTEOMAS is an important contribution to the development of alternative test strategies enabling robust meta-analysis of proteomic data. This workflow commits to the FAIR principles (Findable, Accessible, Interoperable and Reusable) of computational protocols.

Single-Walled vs. Multi-Walled Carbon Nanotubes: Influence of Physico-Chemical Properties on Toxicogenomics Responses in Mouse Lungs

Single-walled carbon nanotubes (SWCNTs) and multi-walled carbon nanotubes (MWCNTs) are nanomaterials with one or multiple layers of carbon sheets. While it is suggested that various properties influence their toxicity, the specific mechanisms are not completely known. This study was aimed to determine if single or multi-walled structures and surface functionalization influence pulmonary toxicity and to identify the underlying mechanisms of toxicity. Female C57BL/6J BomTac mice were exposed to a single dose of 6, 18, or 54 μg/mouse of twelve SWCNTs or MWCNTs of different properties. Neutrophil influx and DNA damage were assessed on days 1 and 28 post-exposure. Genome microarrays and various bioinformatics and statistical methods were used to identify the biological processes, pathways and functions altered post-exposure to CNTs. All CNTs were ranked for their potency to induce transcriptional perturbation using benchmark dose modelling. All CNTs induced tissue inflammation. MWCNTs were more genotoxic than SWCNTs. Transcriptomics analysis showed similar responses across CNTs at the pathway level at the high dose, which included the perturbation of inflammatory, cellular stress, metabolism, and DNA damage responses. Of all CNTs, one pristine SWCNT was found to be the most potent and potentially fibrogenic, so it should be prioritized for further toxicity testing.

Health risk assessment of cadmium exposure by integration of an in silico physiologically based toxicokinetic model and in vitro tests

Cadmium (Cd) is a common environmental pollutant that can damage multiple organs, including the kidney. To prevent renal effects, international authorities have set health-based guidance values of Cd from epidemiological studies. To explore the health risk of Cd exposure and whether human equivalent doses (HEDs) derived from in vitro tests match the current guidance values, we integrated renal tubular epithelial cell-based assays with a physiologically based toxicokinetic model combined with the Monte Carlo method. For females, the HEDs (μg/kg/week) derived from KE2 (DNA damage), KE3 (cell cycle arrest), and KE4 (apoptosis) were 0.20 (2.5th-97.5th percentiles: 0.09-0.48), 0.52 (0.24-1.26), and 2.73 (1.27-6.57), respectively; for males the respective HEDs were 0.23 (0.10-0.49), 0.60 (0.27-1.30), and 3.11 (1.39-6.78). Among them, HED_KE4 (female) was close to the tolerable weekly intake (2.5 μg/kg/week) set by the European Food Safety Authority. The margin of exposure (MOE) derived from HED_KE4 (female) indicated that risks of renal toxicity for populations living in cadmium-contaminated regions should be of concern. This study provided a new approach methodology (NAM) for environmental chemical risk assessment using in silico and in vitro methods.

Application of transcriptome profiling to inquire into the mechanism of nanoplastics toxicity during Ciona robusta embryogenesis

The growing concern on nanoplastics (<1 μm) impact on marine life has stimulated a significant amount of studies aiming to address ecotoxicity and disclose their mechanisms of action. Here, we applied an integrative approach to develop an Adverse Outcome Pathway (AOP) upon acute exposure to amino-modified polystyrene nanoparticles (PS-NH₂ NPs, 50 nm), as proxy for nanoplastics, during the embryogenesis of the chordate Ciona robusta. Genes related to glutathione metabolism, immune defense, nervous system, transport by aquaporins and energy metabolism were affected by either concentration tested of 10 or 15 μg mL^-1 of PS-NH₂. Transcriptomic data and in vivo experiments were assembled into two putative AOPs, identifying as key events the adhesion of PS-NH₂ as (molecular) initiating event, followed by oxidative stress, changes in transcription of specific genes, morphological defects, increase in reactive oxygen species level, impaired swimming behavior. As final adverse outcomes, altered larval development, reduced metamorphosis and inhibition of hatching were identified. Our study attempts to define AOPs for PS-NH₂ without excluding that chemicals leaching from them might also have a potential role in the observed outcome. Overall data provide new insights into the mechanism of action of PS-NH₂ NPs during chordate embryogenesis and offer further keys for a better knowledge of nanoplastics impact on early stages of marine life.

High aspect ratio nanomaterial-induced macrophage polarization is mediated by changes in miRNA levels

Introduction

Inhalation of nanomaterials may induce inflammation in the lung which if left unresolved can manifest in pulmonary fibrosis. In these processes, alveolar macrophages have an essential role and timely modulation of the macrophage phenotype is imperative in the onset and resolution of inflammatory responses. This study aimed to investigate, the immunomodulating properties of two industrially relevant high aspect ratio nanomaterials, namely nanocellulose and multiwalled carbon nanotubes (MWCNT), in an alveolar macrophage model.

Methods

MH-S alveolar macrophages were exposed at air-liquid interface to cellulose nanocrystals (CNC), cellulose nanofibers (CNF) and two MWCNT (NM-400 and NM-401). Following exposure, changes in macrophage polarization markers and secretion of inflammatory cytokines were analyzed. Furthermore, the potential contribution of epigenetic regulation in nanomaterial-induced macrophage polarization was investigated by assessing changes in epigenetic regulatory enzymes, miRNAs, and rRNA modifications.

Results

Our data illustrate that the investigated nanomaterials trigger phenotypic changes in alveolar macrophages, where CNF exposure leads to enhanced M1 phenotype and MWCNT promotes M2 phenotype. Furthermore, MWCNT exposure induced more prominent epigenetic regulatory events with changes in the expression of histone modification and DNA methylation enzymes as well as in miRNA transcript levels. MWCNT-enhanced changes in the macrophage phenotype were correlated with prominent downregulation of the histone methyltransferases Kmt2a and Smyd5 and histone deacetylases Hdac4, Hdac9 and Sirt1 indicating that both histone methylation and acetylation events may be critical in the Th2 responses to MWCNT. Furthermore, MWCNT as well as CNF exposure led to altered miRNA levels, where miR-155-5p, miR-16-1-3p, miR-25-3p, and miR-27a-5p were significantly regulated by both materials. PANTHER pathway analysis of the identified miRNA targets showed that both materials affected growth factor (PDGF, EGF and FGF), Ras/MAPKs, CCKR, GnRH-R, integrin, and endothelin signaling pathways. These pathways are important in inflammation or in the activation, polarization, migration, and regulation of phagocytic capacity of macrophages. In addition, pathways involved in interleukin, WNT and TGFB signaling were highly enriched following MWCNT exposure.

Conclusion

Together, these data support the importance of macrophage phenotypic changes in the onset and resolution of inflammation and identify epigenetic patterns in macrophages which may be critical in nanomaterial-induced inflammation and fibrosis.

Toxicogenomics Data for Chemical Safety Assessment and Development of New Approach Methodologies: An Adverse Outcome Pathway-Based Approach

Mechanistic toxicology provides a powerful approach to inform on the safety of chemicals and the development of safe-by-design compounds. Although toxicogenomics supports mechanistic evaluation of chemical exposures, its implementation into the regulatory framework is hindered by uncertainties in the analysis and interpretation of such data. The use of mechanistic evidence through the adverse outcome pathway (AOP) concept is promoted for the development of new approach methodologies (NAMs) that can reduce animal experimentation. However, to unleash the full potential of AOPs and build confidence into toxicogenomics, robust associations between AOPs and patterns of molecular alteration need to be established. Systematic curation of molecular events to AOPs will create the much-needed link between toxicogenomics and systemic mechanisms depicted by the AOPs. This, in turn, will introduce novel ways of benefitting from the AOPs, including predictive models and targeted assays, while also reducing the need for multiple testing strategies. Hence, a multi-step strategy to annotate AOPs is developed, and the resulting associations are applied to successfully highlight relevant adverse outcomes for chemical exposures with strong in vitro and in vivo convergence, supporting chemical grouping and other data-driven approaches. Finally, a panel of AOP-derived in vitro biomarkers for pulmonary fibrosis (PF) is identified and experimentally validated.

A Nanomedicine Structure-Activity Framework for Research, Development, and Regulation of Future Cancer Therapies

Despite their clinical success in drug delivery applications, the potential of theranostic nanomedicines is hampered by mechanistic uncertainty and a lack of science-informed regulatory guidance. Both the therapeutic efficacy and the toxicity of nanoformulations are tightly controlled by the complex interplay of the nanoparticle's physicochemical properties and the individual patient/tumor biology; however, it can be difficult to correlate such information with observed outcomes. Additionally, as nanomedicine research attempts to gradually move away from large-scale animal testing, the need for computer-assisted solutions for evaluation will increase. Such models will depend on a clear understanding of structure-activity relationships. This review provides a comprehensive overview of the field of cancer nanomedicine and provides a knowledge framework and foundational interaction maps that can facilitate future research, assessments, and regulation. By forming three complementary maps profiling nanobio interactions and pathways at different levels of biological complexity, a clear picture of a nanoparticle's journey through the body and the therapeutic and adverse consequences of each potential interaction are presented.

Toxicokinetics, dose-response, and risk assessment of nanomaterials: Methodology, challenges, and future perspectives

The rapid growth of nanomaterial applications has raised safety concerns for human health. A number of studies have been conducted to assess the toxicokinetics, toxicology, dose-response, and risk assessment of different nanomaterials using in vitro and in vivo animal and human models. However, current studies cannot meet the demand for efficient assessment of toxicokinetics, dose-response relationships, or the toxicological risk arising from the rapidly increasing number of newly synthesized nanomaterials. In this article, we review the methods for conducting toxicokinetics, hazard identification, dose-response, exposure, and risk assessment studies of nanomaterials, identify the knowledge gaps, and discuss the challenges remaining. We provide the rationale behind the appropriate design of nanomaterial plasma toxicokinetic and tissue distribution studies, including caveats on the interpretation and correlation of in vitro and in vivo toxicology studies. The potential of using physiologically based pharmacokinetic (PBPK) models to extrapolate toxicokinetic and toxicity findings from in vitro to in vivo and from animals to humans is discussed, and the knowledge gaps of PBPK modeling for nanomaterials are identified. While challenges still exist, there has been progress in the toxicokinetics, hazard identification, and risk assessment of nanomaterials in the past two decades. Recent advancements in the field are highlighted with relevant examples. We also share latest guidelines as well as our perspectives on future studies needed to characterize the toxicokinetics, toxicity, and dose-response relationship in support of nanomaterial risk assessment. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

Evaluating the Influences of Confounding Variables on Benchmark Dose using a Case Study in the Field of Ionizing Radiation

Purpose A vast amount of data regarding the effects of radiation stressors on transcriptional changes has been produced over the past few decades. These data have shown remarkable consistency across platforms and experimental design, enabling increased understanding of early molecular effects of radiation exposure. However, the value of transcriptomic data in the context of risk assessment is not clear and represents a gap that is worthy of further consideration. Recently, benchmark dose (BMD) modeling has shown promise in correlating a transcriptional point of departure (POD) to that derived using phenotypic outcomes relevant to human health risk assessment. Although frequently applied in chemical toxicity evaluation, our group has recently demonstrated application within the field of radiation research. This approach allows the possibility to quantitatively compare radiation-induced gene and pathway alterations across various datasets using BMD values and derive meaningful biological effects. However, before BMD modeling can confidently be used, an understanding of the impact of confounding variables on BMD outputs is needed. Methods: To this end, BMD modeling was applied to a publicly available microarray dataset (Gene Expression Omnibus #GSE23515) that used peripheral blood ex-vivo gamma-irradiated at 0.82 Gy/min, at doses of 0, 0.1, 0.5 or 2 Gy, and assessed 6 hours post-exposure. The dataset comprised six female smokers (F-S), six female non-smokers (F-NS), six male smokers (M-S), and six male non-smokers (M-NS). Results: A combined total of 412 genes were fit to models and the BMD distribution was noted to be bi-modal across the four groups. A total of 74, 41, 62 and 62 genes were unique to the F-NS, M-NS, F-S and M-S groups. Sixty-two BMD modeled genes and nine pathways were common across all four groups. There were no differential sensitivity of responses in the robust common genes and pathways. Conclusion: For radiation-responsive genes and pathways common across the study groups, the BMD distribution of transcriptional activity was unaltered by sex and smoking status. Although further validation of the data is needed, these initial findings suggest BMD values for radiation relevant genes and pathways are robust and could be explored further in future studies.

Developing Integrated Approaches for Testing and Assessment (IATAs) in order to support nanomaterial safety

Due to the unique characteristics of nanomaterials (NM) there has been an increase in their use in nanomedicines and innovative medical devices (MD). Although large numbers of NMs have now been developed, comprehensive safety investigations are still lacking. Current gaps in understanding the potential mechanisms of NM-induced toxicity can make it challenging to determine the safety testing necessary to support inclusion of NMs in MD applications. This article provides guidance for implementation of pre-clinical tailored safety assessment strategies with the aim to increase the translation of NMs from bench development to clinical use. Integrated Approaches to Testing and Assessment (IATAs) are a key tool in developing these strategies. IATAs follow an iterative approach to answer a defined question in a specific regulatory context to guide the gathering of relevant information for safety assessment, including existing experimental data, integrated with in silico model predictions where available and appropriate, and/or experimental procedures and protocols for generating new data to fill gaps. This allows NM developers to work toward current guidelines and regulations, while taking NM specific considerations into account. Here, an example IATA for NMs with potential for direct blood contact was developed for the assessment of haemocompatibility. This example IATA brings together the current guidelines for NM safety assessment within a framework that can be used to guide information and data gathering for the safety assessment of intravenously injected NMs. Additionally, the decision framework underpinning this IATA has the potential to be adapted to other testing needs and regulatory contexts.

Factors Modulating COVID-19: A Mechanistic Understanding Based on the Adverse Outcome Pathway Framework

Addressing factors modulating COVID-19 is crucial since abundant clinical evidence shows that outcomes are markedly heterogeneous between patients. This requires identifying the factors and understanding how they mechanistically influence COVID-19. Here, we describe how eleven selected factors (age, sex, genetic factors, lipid disorders, heart failure, gut dysbiosis, diet, vitamin D deficiency, air pollution and exposure to chemicals) influence COVID-19 by applying the Adverse Outcome Pathway (AOP), which is well-established in regulatory toxicology. This framework aims to model the sequence of events leading to an adverse health outcome. Several linear AOPs depicting pathways from the binding of the virus to ACE2 up to clinical outcomes observed in COVID-19 have been developed and integrated into a network offering a unique overview of the mechanisms underlying the disease. As SARS-CoV-2 infectibility and ACE2 activity are the major starting points and inflammatory response is central in the development of COVID-19, we evaluated how those eleven intrinsic and extrinsic factors modulate those processes impacting clinical outcomes. Applying this AOP-aligned approach enables the identification of current knowledge gaps orientating for further research and allows to propose biomarkers to identify of high-risk patients. This approach also facilitates expertise synergy from different disciplines to address public health issues.

AOP173 key event associated pathway predictor - online application for the prediction of benchmark dose lower bound (BMDLs) of a transcriptomic pathway involved in MWCNTs-induced lung fibrosis

Nano-QSAR model allows for prediction of the toxicity of materials that have not been experimentally tested before by linking the nano-related structural properties with the biological responses induced by nanomaterials. Prediction of adverse effects caused by substances without having to perform time- and cost-consuming experiments makes QSAR models promising tools for supporting risk assessment. However, very often, newly developed nano-QSAR models are not used in practice due to the complexity of their algorithms, the necessity to have experience in chemoinformatics, and their poor accessibility. In this perspective, the aim of this paper is to encourage developers of the QSAR models to take the effort to prepare user-friendly applications based on predictive models. This would make the developed models accessible to a wider community, and, in effect, promote their further application by regulators and decision-makers. Here, we describe a web-based application that enables to predict the transcriptomic pathway-level response perturbated in the lungs of mice exposed to multiwalled carbon nanotubes. The developed application is freely available at http://aop173-event1.nanoqsar-aop.com/apps/aop_app. It requires only two types of input information related to analyzed nanotubes (their length and diameter) to assess the doses that initiate the inflammation process that may lead to lung fibrosis.

Pulmonary toxicity and gene expression changes in response to whole-body inhalation exposure to multi-walled carbon nanotubes in rats

Purpose: To investigate the molecular mechanisms underlying the pulmonary toxicity induced by exposure to one form of multi-walled carbon nanotubes (MWCNT-7).Materials and methods: Rats were exposed, by whole-body inhalation, to air or an aerosol containing MWCNT-7 particles at target cumulative doses (concentration x time) ranging from 22.5 to 180 (mg/m³)h over a three-day (6 hours/day) period and toxicity and global gene expression profiles were determined in the lungs.Results: MWCNT-7 particles, associated with alveolar macrophages (AMs), were detected in rat lungs following the exposure. Mild to moderate lung pathological changes consisting of increased cellularity, thickening of the alveolar wall, alveolitis, fibrosis, and granuloma formation were detected. Bronchoalveolar lavage (BAL) toxicity parameters such as lactate dehydrogenase activity, number of AMs and polymorphonuclear leukocytes (PMNs), intracellular oxidant generation by phagocytes, and levels of cytokines were significantly (p < 0.05) increased in response to exposure to MWCNT-7. Global gene expression profiling identified several significantly differentially expressed genes (fold change >1.5 and FDR p value <0.05) in all the MWCNT-7 exposed rats. Bioinformatic analysis of the gene expression data identified significant enrichment of several diseases/biological function categories (for example, cancer, leukocyte migration, inflammatory response, mitosis, and movement of phagocytes) and canonical pathways (for example, kinetochore metaphase signaling pathway, granulocyte and agranulocyte adhesion and diapedesis, acute phase response, and LXR/RXR activation). The alterations in the lung toxicity parameters and gene expression changes exhibited a dose-response to the MWCNT exposure.Conclusions: Taken together, the data provided insights into the molecular mechanisms underlying the pulmonary toxicity induced by inhalation exposure of rats to MWCNT-7.

Novel Methods and Approaches for Safety Evaluation of Nanoparticle Formulations: A Focus Towards In Vitro Models and Adverse Outcome Pathways

Nanotoxicology is an emerging field employed in the assessment of unintentional hazardous effects produced by nanoparticles (NPs) impacting human health and the environment. The nanotoxicity affects the range between induction of cellular stress and cytotoxicity. The reasons so far reported for these toxicological effects are due to their variable sizes with high surface areas, shape, charge, and physicochemical properties, which upon interaction with the biological components may influence their functioning and result in adverse outcomes (AO). Thus, understanding the risk produced by these materials now is an important safety concern for the development of nanotechnology and nanomedicine. Since the time nanotoxicology has evolved, the methods employed have been majorly relied on in vitro cell-based evaluations, while these simple methods may not predict the complexity involved in preclinical and clinical conditions concerning pharmacokinetics, organ toxicity, and toxicities evidenced through multiple cellular levels. The safety profiles of nanoscale nanomaterials and nanoformulations in the delivery of drugs and therapeutic applications are of considerable concern. In addition, the safety assessment for new nanomedicine formulas lacks regulatory standards. Though the in vivo studies are greatly needed, the end parameters used for risk assessment are not predicting the possible toxic effects produced by various nanoformulations. On the other side, due to increased restrictions on animal usage and demand for the need for high-throughput assays, there is a need for developing and exploring novel methods to evaluate NPs safety concerns. The progress made in molecular biology and the availability of several modern techniques may offer novel and innovative methods to evaluate the toxicological behavior of different NPs by using single cells, cell population, and whole organisms. This review highlights the recent novel methods developed for the evaluation of the safety impacts of NPs and attempts to solve the problems that come with risk assessment. The relevance of investigating adverse outcome pathways (AOPs) in nanotoxicology has been stressed in particular.

The effects of gene × environment interactions on silver nanoparticle toxicity in the respiratory system: An adverse outcome pathway

The Adverse Outcome Pathway (AOP) framework is serving as a basis to integrate new data streams in order to enhance the power of predictive toxicology. AOP development for engineered nanomaterials (ENM), including silver nanoparticles (AgNP), is currently lagging behind other chemicals of regulatory interest due to our limited understanding of the mechanism by which underlying genetics or diseases directly modify host response to AgNP exposures. This also highlights the importance of considering the Aggregate Exposure Pathway (AEP) framework, which precedes the AOP framework and outlines source to target site exposure. The AEP and AOP frameworks interface at the target site, where a molecular initiating event (MIE) occurs and is followed by key events (KE) for adverse cellular and organ responses along a biological pathway and ends with the adverse organism response. The primary goal of this study is to use AgNP to interrogate the AEP-AOP framework by organizing and integrating in vitro dose-response data and in vivo exposure-response data from previous studies to evaluate the effects of interactions between host genetic and acquired factors, or gene × environment interactions (G × E), on AgNP toxicity in the respiratory system. Using this framework will help us to identify plausible key event relationships (KER) between MIE and adverse organism responses when KE are not measured using the same assay in order to derive future predictive models, guide research, and support development of tools for making risk-based, regulatory decisions on ENM. This article is categorized under: Toxicology and Regulatory Issues in Nanomedicine > Toxicology of Nanomaterials Toxicology and Regulatory Issues in Nanomedicine > Regulatory and Policy Issues in Nanomedicine.

Paving the way for application of next generation risk assessment to safety decision-making for cosmetic ingredients

Next generation risk assessment (NGRA) is an exposure-led, hypothesis-driven approach that has the potential to support animal-free safety decision-making. However, significant effort is needed to develop and test the in vitro and in silico (computational) approaches that underpin NGRA to enable confident application in a regulatory context. A workshop was held in Montreal in 2019 to discuss where effort needs to be focussed and to agree on the steps needed to ensure safety decisions made on cosmetic ingredients are robust and protective. Workshop participants explored whether NGRA for cosmetic ingredients can be protective of human health, and reviewed examples of NGRA for cosmetic ingredients. From the limited examples available, it is clear that NGRA is still in its infancy, and further case studies are needed to determine whether safety decisions are sufficiently protective and not overly conservative. Seven areas were identified to help progress application of NGRA, including further investments in case studies that elaborate on scenarios frequently encountered by industry and regulators, including those where a ‘high risk’ conclusion would be expected. These will provide confidence that the tools and approaches can reliably discern differing levels of risk. Furthermore, frameworks to guide performance and reporting should be developed.

Construction of Mode of Action for Cadmium-Induced Renal Tubular Dysfunction Based on a Toxicity Pathway-Oriented Approach

Although it is recognized that cadmium (Cd) causes renal tubular dysfunction, the mechanism of Cd-induced nephrotoxicity is not yet fully understood. Mode of action (MOA) is a developing tool for chemical risk assessment. To establish the mechanistic MOA of Cd-induced renal tubular dysfunction, the Comparative Toxicogenomics Database (CTD) was used to obtain genomics data of Cd-induced nephrotoxicity, and Ingenuity^® Pathway Analysis (IPA) software was applied for bioinformatics analysis. Based on the perturbed toxicity pathways during the process of Cd-induced nephrotoxicity, we established the MOA of Cd-induced renal tubular dysfunction and assessed its confidence with the tailored Bradford Hill criteria. Bioinformatics analysis showed that oxidative stress, DNA damage, cell cycle arrest, and cell death were the probable key events (KEs). Assessment of the overall MOA of Cd-induced renal tubular dysfunction indicated a moderate confidence, and there are still some evidence gaps to be filled by rational experimental designs.

Cross-Model Comparison of Transcriptomic Dose-Response of Short-Chain Chlorinated Paraffins

Short-chain chlorinated paraffins (SCCPs) have attracted attention because of their toxicological potential in humans and wildlife at environmentally relevant doses. However, limited information is available regarding mechanistic differences across species in terms of the biological pathways that are impacted by SCCP exposure. Here, a concentration-dependent reduced human transcriptome (RHT) approach was conducted to evaluate 15 SCCPs in HepG2 cells and compared with our previous results using a reduced zebrafish transcriptome (RZT) approach in zebrafish embryos (ZFEs). Generally, SCCPs induced a broader suite of biological pathways in ZFEs than HepG2 cells, and all of the 15 SCCPs were more potent in HepG2 cells compared to ZFEs. Despite these general differences, the transcriptional potency of SCCPs in both model systems showed a significant linear relationship (p = 0.0017, r² = 0.57), and the average ratios of transcriptional potency for each SCCP in RZT to that in RHT were ∼100,000. C₁₀H₁₄Cl₈ was the most potent SCCP, while C₁₀H₁₇Cl₅ was the least potent in both ZFEs and HepG2 cells. An adverse outcome pathway network-based analysis demonstrated model-specific responses, such as xenobiotic metabolism that may be mediated by different nuclear receptor-mediated pathways between HepG2 cells (e.g., CAR and AhR activation) and ZFEs (e.g., PXR activation). Moreover, induced transcriptional changes in ZFEs associated with pathways and molecular initiating events (e.g., activation of nicotinic acetylcholine receptor) suggest that SCCPs may disrupt neural development processes. The cross-model comparison of concentration-dependent transcriptomics represents a promising approach to assess and prioritize SCCPs.

Adverse Outcome Pathway Development for Assessment of Lung Carcinogenicity by Nanoparticles

Lung cancer, one of the most common and deadly forms of cancer, is in some cases associated with exposure to certain types of particles. With the rise of nanotechnology, there is concern that some engineered nanoparticles may be among such particles. In the absence of epidemiological evidence, assessment of nanoparticle carcinogenicity is currently performed on a time-consuming case-by-case basis, relying mainly on animal experiments. Non-animal alternatives exist, including a few validated cell-based methods accepted for regulatory risk assessment of nanoparticles. Furthermore, new approach methodologies (NAMs), focused on carcinogenic mechanisms and capable of handling the increasing numbers of nanoparticles, have been developed. However, such alternative methods are mainly applied as weight-of-evidence linked to generally required animal data, since challenges remain regarding interpretation of the results. These challenges may be more easily overcome by the novel Adverse Outcome Pathway (AOP) framework, which provides a basis for validation and uptake of alternative mechanism-focused methods in risk assessment. Here, we propose an AOP for lung cancer induced by nanosized foreign matter, anchored to a selection of 18 standardized methods and NAMs for in silico- and in vitro-based integrated assessment of lung carcinogenicity. The potential for further refinement of the AOP and its components is discussed in relation to available nanosafety knowledge and data. Overall, this perspective provides a basis for development of AOP-aligned alternative methods-based integrated testing strategies for assessment of nanoparticle-induced lung cancer.

Nanomaterials and hepatic disease: toxicokinetics, disease types, intrinsic mechanisms, liver susceptibility, and influencing factors

The widespread use of nanomaterials (NMs) has raised concerns that exposure to them may introduce potential risks to the human body and environment. The liver is the main target organ for NMs. Hepatotoxic effects caused by NMs have been observed in recent studies but have not been linked to liver disease, and the intrinsic mechanisms are poorly elucidated. Additionally, NMs exhibit varied toxicokinetics and induce enhanced toxic effects in susceptible livers; however, thus far, this issue has not been thoroughly reviewed. This review provides an overview of the toxicokinetics of NMs. We highlight the possibility that NMs induce hepatic diseases, including nonalcoholic steatohepatitis (NASH), fibrosis, liver cancer, and metabolic disorders, and explore the underlying intrinsic mechanisms. Additionally, NM toxicokinetics and the potential induced risks in the livers of susceptible individuals, including subjects with liver disease, obese individuals, aging individuals and individuals of both sexes, are summarized. To understand how NM type affect their toxicity, the influences of the physicochemical and morphological (PCM) properties of NMs on their toxicokinetics and toxicity are also explored. This review provides guidance for further toxicological studies on NMs and will be important for the further development of NMs for applications in various fields.

Transcriptomics-Based and AOP-Informed Structure-Activity Relationships to Predict Pulmonary Pathology Induced by Multiwalled Carbon Nanotubes

This study presents a novel strategy that employs quantitative structure-activity relationship models for nanomaterials (Nano-QSAR) for predicting transcriptomic pathway level response using lung tissue inflammation, an essential key event (KEs) in the existing adverse outcome pathway (AOP) for lung fibrosis, as a model response. Transcriptomic profiles of mouse lungs exposed to ten different multiwalled carbon nanotubes (MWCNTs) are analyzed using statistical and bioinformatics tools. Three pathways "agranulocyte adhesion and diapedesis," "granulocyte adhesion and diapedesis," and "acute phase signaling," that (1) are commonly perturbed across the MWCNTs panel, (2) show dose response (Benchmark dose, BMDs), and (3) are anchored to the KEs identified in the lung fibrosis AOP, are considered in modelling. The three pathways are associated with tissue inflammation. The results show that the aspect ratio (κ) of MWCNTs is directly correlated with the pathway BMDs. The study establishes a methodology for QSAR construction based on canonical pathways and proposes a MWCNTs grouping strategy based on the κ-values of the specific pathway associated genes. Finally, the study shows how the AOP framework can help guide QSAR modelling efforts; conversely, the outcome of the QSAR modelling can aid in refining certain aspects of the AOP in question (here, lung fibrosis).

Non-Animal Strategies for Toxicity Assessment of Nanoscale Materials: Role of Adverse Outcome Pathways in the Selection of Endpoints

Faster, cheaper, sensitive, and mechanisms-based animal alternatives are needed to address the safety assessment needs of the growing number of nanomaterials (NM) and their sophisticated property variants. Specifically, strategies that help identify and prioritize alternative schemes involving individual test models, toxicity endpoints, and assays for the assessment of adverse outcomes, as well as strategies that enable validation and refinement of these schemes for the regulatory acceptance are needed. In this review, two strategies 1) the current nanotoxicology literature review and 2) the adverse outcome pathways (AOPs) framework, a systematic process that allows the assembly of available mechanistic information concerning a toxicological response in a simple modular format, are presented. The review highlights 1) the most frequently assessed and reported ad hoc in vivo and in vitro toxicity measurements in the literature, 2) various AOPs of relevance to inhalation toxicity of NM that are presently under development, and 3) their applicability in identifying key events of toxicity for targeted in vitro assay development. Finally, using an existing AOP for lung fibrosis, the specific combinations of cell types, exposure and test systems, and assays that are experimentally supported and thus, can be used for assessing NM-induced lung fibrosis, are proposed.

Combined In Vitro and In Vivo Approaches to Propose a Putative Adverse Outcome Pathway for Acute Lung Inflammation Induced by Nanoparticles: A Study on Carbon Dots

With the growth of nanotechnologies, concerns raised regarding the potential adverse effects of nanoparticles (NPs), especially on the respiratory tract. Adverse outcome pathways (AOP) have become recently the subject of intensive studies in order to get a better understanding of the mechanisms of NP toxicity, and hence hopefully predict the health risks associated with NP exposure. Herein, we propose a putative AOP for the lung toxicity of NPs using emerging nanomaterials called carbon dots (CDs), and in vivo and in vitro experimental approaches. We first investigated the effect of a single administration of CDs on mouse airways. We showed that CDs induce an acute lung inflammation and identified airway macrophages as target cells of CDs. Then, we studied the cellular responses induced by CDs in an in vitro model of macrophages. We observed that CDs are internalized by these cells (molecular initial event) and induce a series of key events, including loss of lysosomal integrity and mitochondrial disruption (organelle responses), as well as oxidative stress, inflammasome activation, inflammatory cytokine upregulation and macrophage death (cellular responses). All these effects triggering lung inflammation as tissular response may lead to acute lung injury.

Benchmark dose analyses of toxic endpoints in lung cells provide sensitivity and toxicity ranking across metal oxide nanoparticles and give insights into the mode of action

INTRODUCTION

The benchmark dose (BMD) is a dose that produces a predetermined change in the response rate of an adverse effect. This approach is increasingly utilized to analyze quantitative dose-response relationships. To proof this concept, statistical analysis was compared with the BMD approach in order to rank the sensitivity as well as the toxicity and to describe the mode of action.

METHODS

Bronchial (BEAS-2B) and alveolar epithelial cells (A549) were exposed to a wide concentration range (0.4-100 μg/mL) of five metal oxide nanoparticles (CeO₂, CuO, TiO₂, ZnO, ZrO₂). Eight toxicity endpoints were determined representing integrity of lysosomal and cell membrane, oxidative stress level, glutathione based detoxification (glutathione S-transferase), oxidative metabolism (cytochrome P450), alteration of the mitochondrial membrane potential, alteration of phase II antioxidative enzyme (NAD(P)H:quinone oxidoreductase), and de novo DNA synthesis.

RESULTS

Based on the BMD calculated for the most sensitive test, the toxicity decreased in the following order: ZnO > CuO > TiO₂>ZrO₂>CeO₂ in BEAS-2B. Both statistical evaluation methods revealed a higher sensitivity of BEAS-2B cells. The BMD-derived mode of action for CuO confirmed the existing hypotheses and provided insights into less known mechanisms.

CONCLUSION

The findings proofed that BMD analysis is an effective tool to evaluate different aspects of risk assessment.

21st Century Tools for Nanotoxicology: Transcriptomic Biomarker Panel and Precision-Cut Lung Slice Organ Mimic System for the Assessment of Nanomaterial-Induced Lung Fibrosis

There is an urgent need for reliable toxicity assays to support the human health risk assessment of an ever increasing number of engineered nanomaterials (ENMs). Animal testing is not a suitable option for ENMs. Sensitive in vitro models and mechanism-based targeted in vitro assays that enable accurate prediction of in vivo responses are not yet available. In this proof-of-principle study, publicly available mouse lung transcriptomics data from studies investigating xenobiotic-induced lung diseases are used and a 17-gene biomarker panel (PFS17) applicable to the assessment of lung fibrosis is developed. The PFS17 is validated using a limited number of in vivo mouse lung transcriptomics datasets from studies investigating ENM-induced responses. In addition, an ex vivo precision-cut lung slice (PCLS) model is optimized for screening of potentially inflammogenic and pro-fibrotic ENMs. Using bleomycin and a multiwalled carbon nanotube, the practical application of the PCLS method as a sensitive alternative to whole animal tests to screen ENMs that may potentially induce inhalation toxicity is shown. Conditional to further optimization and validation, it is established that a combination of PFS17 and the ex vivo PCLS method will serve as a robust and sensitive approach to assess lung inflammation and fibrosis induced by ENMs.

An Alternative Perspective towards Reducing the Risk of Engineered Nanomaterials to Human Health

To elucidate the impact of human exposure to engineered nanomaterials, advanced in vitro models are a valid non-animal alternative. Despite significant gains over the last decade, implementation of these approaches remains limited. This work discusses the current state-of-the-art and how future developments can lead to advanced in vitro models better supporting nano-hazard assessment.

An Inflamed Human Alveolar Model for Testing the Efficiency of Anti-inflammatory Drugs in vitro

A large number of prevalent lung diseases is associated with tissue inflammation. Clinically, corticosteroid therapies are applied systemically or via inhalation for the treatment of lung inflammation, and a number of novel therapies are being developed that require preclinical testing. In alveoli, macrophages and dendritic cells play a key role in initiating and diminishing pro-inflammatory reactions and, in particular, macrophage plasticity (M1 and M2 phenotypes shifts) has been reported to play a significant role in these reactions. Thus far, no studies with in vitro lung epithelial models have tested the comparison between systemic and direct pulmonary drug delivery. Therefore, the aim of this study was to develop an inflamed human alveolar epithelium model and to test the resolution of LPS-induced inflammation in vitro with a corticosteroid, methylprednisolone (MP). A specific focus of the study was the macrophage phenotype shifts in response to these stimuli. First, human monocyte-derived macrophages were examined for phenotype shifts upon exposure to lipopolysaccharide (LPS), followed by treatment with MP. A multicellular human alveolar model, composed of macrophages, dendritic cells, and epithelial cells, was then employed for the development of inflamed models. The models were used to test the anti-inflammatory potency of MP by monitoring the secretion of pro-inflammatory mediators (interleukin [IL]-8, tumor necrosis factor-α [TNF-α], and IL-1β) through four different approaches, mimicking clinical scenarios of inflammation and treatment. In macrophage monocultures, LPS stimulation shifted the phenotype towards M1, as demonstrated by increased release of IL-8 and TNF-α and altered expression of phenotype-associated surface markers (CD86, CD206). MP treatment of inflamed macrophages reversed the phenotype towards M2. In multicellular models, increased pro-inflammatory reactions after LPS exposure were observed, as demonstrated by protein secretion and gene expression measurements. In all scenarios, among the tested mediators the most pronounced anti-inflammatory effect of MP was observed for IL-8. Our findings demonstrate that our inflamed multicellular human lung model is a promising tool for the evaluation of anti-inflammatory potency of drug candidates in vitro. With the presented setup, our model allows a meaningful comparison of the systemic vs. inhalation administration routes for the evaluation of the efficacy of a drug in vitro.

Meta-analysis of transcriptomic datasets using benchmark dose modeling shows value in supporting radiation risk assessment

PURPOSE

Benchmark dose (BMD) modeling is used to determine the dose of a stressor at which a predefined increase in any biological effect above background occurs (e.g. 10% increase from control values). BMD analytical tools have the capacity to model transcriptional dose-response data to derive BMDs for genes, pathways and gene ontologies. We recently demonstrated the value of this approach to support various areas of radiation research using predominately 'in-house' generated datasets.

MATERIALS AND METHODS

As a continuation of this work, transcriptomic studies of relevance to ionizing radiation were retrieved through the Gene Expression Omnibus (GEO). The datasets were compiled and filtered, then analyzed using BMDExpress. The objective was to determine the reproducibility of BMD values in relation to pathways and genes across different exposure scenarios and compare to those derived using cytogenetic endpoints. A number of graphic visualization approaches were used to determine if BMD outputs could be correlated to parameters such as dose-rate, radiation quality and cell type.

RESULTS

Curated studies were diverse and derived from experiments with varied design and intent. Despite this, common genes and pathways were identified with low and high dose thresholds. The higher BMD values were associated with immune response and cell death, while transcripts with lower BMD values were generally related to the classic DNA damage response/repair processes, centered on TP53 signaling. Analysis of datasets with relatively similar dose-ranges under comparable experimental conditions showed a bi-modal distribution with a high degree of consistency in BMD values across shared genes and pathways, particularly for those below the 25th percentile of total distribution by dose. The median BMD values were noted to be approximately 0.5 Gy for genes/pathways that comprised mode 1. Furthermore, transcriptional BMD values derived from a subset of genes using in vivo and in vitro datasets were in accord to those using cytogenetic endpoints.

CONCLUSION

Overall, the results from this work highlight the value of the BMD methodology to derive meaningful outputs that are consistent across different models, provided the studies are conducted using a similar dose-range.

Translating Scientific Advances in the AOP Framework to Decision Making for Nanomaterials

Much of the current innovation in advanced materials is occurring at the nanoscale, specifically in manufactured nanomaterials (MNs). MNs display unique attributes and behaviors, and may be biologically and physically unique, making them valuable across a wide range of applications. However, as the number, diversity and complexity of MNs coming to market continue to grow, assessing their health and environmental risks with traditional animal testing approaches is too time- and cost-intensive to be practical, and is undesirable for ethical reasons. New approaches are needed that meet current requirements for regulatory risk assessment while reducing reliance on animal testing and enabling safer-by-design product development strategies to be implemented. The adverse outcome pathway (AOP) framework presents a sound model for the advancement of MN decision making. Yet, there are currently gaps in technical and policy aspects of AOPs that hinder the adoption and use for MN risk assessment and regulatory decision making. This review outlines the current status and next steps for the development and use of the AOP framework in decision making regarding the safety of MNs. Opportunities and challenges are identified concerning the advancement and adoption of AOPs as part of an integrated approach to testing and assessing (IATA) MNs, as are specific actions proposed to advance the development, use and acceptance of the AOP framework and associated testing strategies for MN risk assessment and decision making. The intention of this review is to reflect the views of a diversity of stakeholders including experts, researchers, policymakers, regulators, risk assessors and industry representatives on the current status, needs and requirements to facilitate the future use of AOPs in MN risk assessment. It incorporates the views and feedback of experts that participated in two workshops hosted as part of an Organization for Economic Cooperation and Development (OECD) Working Party on Manufactured Nanomaterials (WPMN) project titled, "Advancing AOP Development for Nanomaterial Risk Assessment and Categorization", as well as input from several EU-funded nanosafety research consortia.

Polarization of Immune Cells in the Pathologic Response to Inhaled Particulates

Polarization of immune cells is commonly observed in host responses associated with microbial immunity, inflammation, tumorigenesis, and tissue repair and fibrosis. In this process, immune cells adopt distinct programs and perform specialized functions in response to specific signals. Accumulating evidence indicates that inhalation of micro- and nano-sized particulates activates barrier immune programs in the lung in a time- and context-dependent manner, including type 1 and type 2 inflammation, and T helper (Th) 17 cell, regulatory T cell (Treg), innate lymphoid cell (ILC), and myeloid-derived suppressor cell (MDSC) responses, which highlight the polarization of several major immune cell types. These responses facilitate the pulmonary clearance and repair under physiological conditions. When exposure persists and overwhelms the clearance capacity, they foster the chronic progression of inflammation and development of progressive disease conditions, such as fibrosis and cancer. The pulmonary response to insoluble particulates thus represents a distinctive disease process wherein non-infectious, persistent exposures stimulate the polarization of immune cells to orchestrate dynamic inflammatory and immune reactions, leading to pulmonary and pleural chronic inflammation, fibrosis, and malignancy. Despite large variations in particles and their associated disease outcomes, the early response to inhaled particles often follows a common path. The initial reactions entail a barrier immune response dominated by type 1 inflammation that features active phagocytosis by M1 macrophages and recruitment of neutrophils, both of which are fueled by Th1 and proinflammatory cytokines. Acute inflammation is immediately followed by resolution and tissue repair mediated through specialized pro-resolving mediators (SPMs) and type 2 cytokines and cells including M2 macrophages and Th2 lymphocytes. As many particles and fibers cannot be digested by phagocytes, resolution is often extended and incomplete, and type 2 inflammation becomes heightened, which promotes interstitial fibrosis, granuloma formation, and tumorigenesis. Recent studies also reveal the involvement of Th17-, Treg-, ILC-, and MDSC-mediated responses in the pathogenesis caused by inhaled particulates. This review synopsizes the progress in understanding the interplay between inhaled particles and the pulmonary immune functions in disease pathogenesis, with focus on particle-induced polarization of immune cells and its role in the development of chronic inflammation, fibrosis, and cancer in the lung.

Organomodified nanoclays induce less inflammation, acute phase response, and genotoxicity than pristine nanoclays in mice lungs

Surface modification by different quaternary ammonium compounds (QAC) makes nanoclays more compatible with various polymeric matrices, thereby expanding their potential applications. The growing industrial use of nanoclays could potentially pose a health risk for workers. Here, we assessed how surface modification of nanoclays modulates their pulmonary toxicity. An in vitro screening of the unmodified nanoclay Bentonite (montmorillonite) and four organomodified nanoclays (ONC); coated with various QAC, including benzalkonium chloride (BAC), guided the selection of the materials for the in vivo study. Mice were exposed via a single intratracheal instillation to 18, 54, and 162 µg of unmodified Bentonite or dialkyldimethyl-ammonium-coated ONC (NanofilSE3000), or to 6, 18, and 54 µg of a BAC-coated ONC (Nanofil9), and followed for one, 3, or 28 days. All materials induced dose- and time-dependent responses in the exposed mice. However, all doses of Bentonite induced larger, but reversible, inflammation (BAL neutrophils) and acute phase response (Saa3 gene expression in lung) than the two ONC. Similarly, highest levels of DNA strand breaks were found in BAL cells of mice exposed to Bentonite 1 day post-exposure. A significant increase of DNA strand breaks was detected also for NanofilSE3000, 3 days post-exposure. Only mice exposed to Bentonite showed increased Tgf-β gene expression in lung, biomarker of pro-fibrotic processes and hepatic extravasation, 3 days post-exposure. This study indicates that Bentonite treatment with some QAC changes main physical-chemical properties, including shape and surface area, and may decrease their pulmonary toxicity in exposed mice.

Mode of action-based risk assessment of genotoxic carcinogens

The risk assessment of chemical carcinogens is one major task in toxicology. Even though exposure has been mitigated effectively during the last decades, low levels of carcinogenic substances in food and at the workplace are still present and often not completely avoidable. The distinction between genotoxic and non-genotoxic carcinogens has traditionally been regarded as particularly relevant for risk assessment, with the assumption of the existence of no-effect concentrations (threshold levels) in case of the latter group. In contrast, genotoxic carcinogens, their metabolic precursors and DNA reactive metabolites are considered to represent risk factors at all concentrations since even one or a few DNA lesions may in principle result in mutations and, thus, increase tumour risk. Within the current document, an updated risk evaluation for genotoxic carcinogens is proposed, based on mechanistic knowledge regarding the substance (group) under investigation, and taking into account recent improvements in analytical techniques used to quantify DNA lesions and mutations as well as "omics" approaches. Furthermore, wherever possible and appropriate, special attention is given to the integration of background levels of the same or comparable DNA lesions. Within part A, fundamental considerations highlight the terms hazard and risk with respect to DNA reactivity of genotoxic agents, as compared to non-genotoxic agents. Also, current methodologies used in genetic toxicology as well as in dosimetry of exposure are described. Special focus is given on the elucidation of modes of action (MOA) and on the relation between DNA damage and cancer risk. Part B addresses specific examples of genotoxic carcinogens, including those humans are exposed to exogenously and endogenously, such as formaldehyde, acetaldehyde and the corresponding alcohols as well as some alkylating agents, ethylene oxide, and acrylamide, but also examples resulting from exogenous sources like aflatoxin B1, allylalkoxybenzenes, 2-amino-3,8-dimethylimidazo[4,5-f] quinoxaline (MeIQx), benzo[a]pyrene and pyrrolizidine alkaloids. Additionally, special attention is given to some carcinogenic metal compounds, which are considered indirect genotoxins, by accelerating mutagenicity via interactions with the cellular response to DNA damage even at low exposure conditions. Part C finally encompasses conclusions and perspectives, suggesting a refined strategy for the assessment of the carcinogenic risk associated with an exposure to genotoxic compounds and addressing research needs.

Adverse outcome pathways as a tool for the design of testing strategies to support the safety assessment of emerging advanced materials at the nanoscale

Toxicity testing and regulation of advanced materials at the nanoscale, i.e. nanosafety, is challenged by the growing number of nanomaterials and their property variants requiring assessment for potential human health impacts. The existing animal-reliant toxicity testing tools are onerous in terms of time and resources and are less and less in line with the international effort to reduce animal experiments. Thus, there is a need for faster, cheaper, sensitive and effective animal alternatives that are supported by mechanistic evidence. More importantly, there is an urgency for developing alternative testing strategies that help justify the strategic prioritization of testing or targeting the most apparent adverse outcomes, selection of specific endpoints and assays and identifying nanomaterials of high concern. The Adverse Outcome Pathway (AOP) framework is a systematic process that uses the available mechanistic information concerning a toxicological response and describes causal or mechanistic linkages between a molecular initiating event, a series of intermediate key events and the adverse outcome. The AOP framework provides pragmatic insights to promote the development of alternative testing strategies. This review will detail a brief overview of the AOP framework and its application to nanotoxicology, tools for developing AOPs and the role of toxicogenomics, and summarize various AOPs of relevance to inhalation toxicity of nanomaterials that are currently under various stages of development. The review also presents a network of AOPs derived from connecting all AOPs, which shows that several adverse outcomes induced by nanomaterials originate from a molecular initiating event that describes the interaction of nanomaterials with lung cells and involve similar intermediate key events. Finally, using the example of an established AOP for lung fibrosis, the review will discuss various in vitro tests available for assessing lung fibrosis and how the information can be used to support a tiered testing strategy for lung fibrosis. The AOPs and AOP network enable deeper understanding of mechanisms involved in inhalation toxicity of nanomaterials and provide a strategy for the development of alternative test methods for hazard and risk assessment of nanomaterials.

Neurotoxicology of Nanomaterials

The remarkable advances coming about through nanotechnology promise to revolutionize many aspects of modern life; however, these advances come with a responsibility for due diligence to ensure that they are not accompanied by adverse consequences for human health or the environment. Many novel nanomaterials (having at least one dimension <100 nm) could be highly mobile if released into the environment and are also very reactive, which has raised concerns for potential adverse impacts including, among others, the potential for neurotoxicity. Several lines of evidence led to concerns for neurotoxicity, but perhaps none more than observations that inhaled nanoparticles impinging on the mucosal surface of the nasal epithelium could be internalized into olfactory receptor neurons and transported by axoplasmic transport into the olfactory bulbs without crossing the blood-brain barrier. From the olfactory bulb, there is concern that nanomaterials may be transported deeper into the brain and affect other brain structures. Of course, people will not be exposed to only engineered nanomaterials, but rather such exposures will occur in a complex mixture of environmental materials, some of which are incidentally generated particles of a similar inhalable size range to engineered nanomaterials. To date, most experimental studies of potential neurotoxicity of nanomaterials have not considered the potential exposure sources and pathways that could lead to exposure, and most studies of nanomaterial exposure have not considered potential neurotoxicity. Here, we present a review of potential sources of exposures to nanoparticles, along with a review of the literature on potential neurotoxicity of nanomaterials. We employ the linked concepts of an aggregate exposure pathway (AEP) and an adverse outcome pathway (AOP) to organize and present the material. The AEP includes a sequence of key events progressing from material sources, release to environmental media, external exposure, internal exposure, and distribution to the target site. The AOP begins with toxicant at the target site causing a molecular initiating event and, like the AEP, progress sequentially to actions at the level of the cell, organ, individual, and population. Reports of nanomaterial actions are described at every key event along the AEP and AOP, except for changes in exposed populations that have not yet been observed. At this last stage, however, there is ample evidence of population level effects from exposure to ambient air particles that may act similarly to engineered nanomaterials. The data give an overall impression that current exposure levels may be considerably lower than those reported experimentally to be neurotoxic. This impression, however, is tempered by the absence of long-term exposure studies with realistic routes and levels of exposure to address concerns for chronic accumulation of materials or damage. Further, missing across the board are "key event relationships", which are quantitative expressions linking the key events of either the AEP or the AOP, making it impossible to quantitatively project the likelihood of adverse neurotoxic effects from exposure to nanomaterials or to estimate margins of exposure for such relationships.

TinderMIX: Time-dose integrated modelling of toxicogenomics data

BACKGROUND

Omics technologies have been widely applied in toxicology studies to investigate the effects of different substances on exposed biological systems. A classical toxicogenomic study consists in testing the effects of a compound at different dose levels and different time points. The main challenge consists in identifying the gene alteration patterns that are correlated to doses and time points. The majority of existing methods for toxicogenomics data analysis allow the study of the molecular alteration after the exposure (or treatment) at each time point individually. However, this kind of analysis cannot identify dynamic (time-dependent) events of dose responsiveness.

RESULTS

We propose TinderMIX, an approach that simultaneously models the effects of time and dose on the transcriptome to investigate the course of molecular alterations exerted in response to the exposure. Starting from gene log fold-change, TinderMIX fits different integrated time and dose models to each gene, selects the optimal one, and computes its time and dose effect map; then a user-selected threshold is applied to identify the responsive area on each map and verify whether the gene shows a dynamic (time-dependent) and dose-dependent response; eventually, responsive genes are labelled according to the integrated time and dose point of departure.

CONCLUSIONS

To showcase the TinderMIX method, we analysed 2 drugs from the Open TG-GATEs dataset, namely, cyclosporin A and thioacetamide. We first identified the dynamic dose-dependent mechanism of action of each drug and compared them. Our analysis highlights that different time- and dose-integrated point of departure recapitulates the toxicity potential of the compounds as well as their dynamic dose-dependent mechanism of action.

Use of EpiAlveolar Lung Model to Predict Fibrotic Potential of Multiwalled Carbon Nanotubes

Expansion in production and commercial use of nanomaterials increases the potential human exposure during the lifecycle of these materials (production, use, and disposal). Inhalation is a primary route of exposure to nanomaterials; therefore it is critical to assess their potential respiratory hazard. Herein, we developed a three-dimensional alveolar model (EpiAlveolar) consisting of human primary alveolar epithelial cells, fibroblasts, and endothelial cells, with or without macrophages for predicting long-term responses to aerosols. Following thorough characterization of the model, proinflammatory and profibrotic responses based on the adverse outcome pathway concept for lung fibrosis were assessed upon repeated subchronic exposures (up to 21 days) to two types of multiwalled carbon nanotubes (MWCNTs) and silica quartz particles. We simulate occupational exposure doses for the MWCNTs (1-30 μg/cm²) using an air-liquid interface exposure device (VITROCELL Cloud) with repeated exposures over 3 weeks. Specific key events leading to lung fibrosis, such as barrier integrity and release of proinflammatory and profibrotic markers, show the responsiveness of the model. Nanocyl induced, in general, a less pronounced reaction than Mitsui-7, and the cultures with human monocyte-derived macrophages (MDMs) showed the proinflammatory response at later time points than those without MDMs. In conclusion, we present a robust alveolar model to predict inflammatory and fibrotic responses upon exposure to MWCNTs.

Transcriptomics in Toxicogenomics, Part I: Experimental Design, Technologies, Publicly Available Data, and Regulatory Aspects

The starting point of successful hazard assessment is the generation of unbiased and trustworthy data. Conventional toxicity testing deals with extensive observations of phenotypic endpoints in vivo and complementing in vitro models. The increasing development of novel materials and chemical compounds dictates the need for a better understanding of the molecular changes occurring in exposed biological systems. Transcriptomics enables the exploration of organisms' responses to environmental, chemical, and physical agents by observing the molecular alterations in more detail. Toxicogenomics integrates classical toxicology with omics assays, thus allowing the characterization of the mechanism of action (MOA) of chemical compounds, novel small molecules, and engineered nanomaterials (ENMs). Lack of standardization in data generation and analysis currently hampers the full exploitation of toxicogenomics-based evidence in risk assessment. To fill this gap, TGx methods need to take into account appropriate experimental design and possible pitfalls in the transcriptomic analyses as well as data generation and sharing that adhere to the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. In this review, we summarize the recent advancements in the design and analysis of DNA microarray, RNA sequencing (RNA-Seq), and single-cell RNA-Seq (scRNA-Seq) data. We provide guidelines on exposure time, dose and complex endpoint selection, sample quality considerations and sample randomization. Furthermore, we summarize publicly available data resources and highlight applications of TGx data to understand and predict chemical toxicity potential. Additionally, we discuss the efforts to implement TGx into regulatory decision making to promote alternative methods for risk assessment and to support the 3R (reduction, refinement, and replacement) concept. This review is the first part of a three-article series on Transcriptomics in Toxicogenomics. These initial considerations on Experimental Design, Technologies, Publicly Available Data, Regulatory Aspects, are the starting point for further rigorous and reliable data preprocessing and modeling, described in the second and third part of the review series.

An integrated pathway based on in vitro data for the human hazard assessment of nanomaterials

In line with the 3R concept, nanotoxicology is shifting from a phenomenological to a mechanistic approach based on in vitro and in silico methods, with a consequent reduction in animal testing. Risk Assessment (RA) and Life Cycle Assessment (LCA) methodologies, which traditionally rely on in vivo toxicity studies, will not be able to keep up with the pace of development of new nanomaterials unless they adapt to use this new type of data. While tools and models are already available and show a great potential for future use in RA and LCA, currently none is able alone to quantitatively assess human hazards (i.e. calculate chronic NOAEL or ED₅₀ values). By highlighting which models and approaches can be used in a quantitative way with the available knowledge and data, we propose an integrated pathway for the use of in vitro data in RA and LCA. Starting with the characterization of nanoparticles' properties, the pathway then investigates how to select relevant in vitro human data, and how to bridge in vitro dose-response relationships to in vivo effects. If verified, this approach would allow RA and LCA to stir up the development of nanotoxicology by giving indications about the data and quality requirements needed in risk methodologies.

NanoSolveIT Project: Driving nanoinformatics research to develop innovative and integrated tools for in silico nanosafety assessment

Nanotechnology has enabled the discovery of a multitude of novel materials exhibiting unique physicochemical (PChem) properties compared to their bulk analogues. These properties have led to a rapidly increasing range of commercial applications; this, however, may come at a cost, if an association to long-term health and environmental risks is discovered or even just perceived. Many nanomaterials (NMs) have not yet had their potential adverse biological effects fully assessed, due to costs and time constraints associated with the experimental assessment, frequently involving animals. Here, the available NM libraries are analyzed for their suitability for integration with novel nanoinformatics approaches and for the development of NM specific Integrated Approaches to Testing and Assessment (IATA) for human and environmental risk assessment, all within the NanoSolveIT cloud-platform. These established and well-characterized NM libraries (e.g. NanoMILE, NanoSolutions, NANoREG, NanoFASE, caLIBRAte, NanoTEST and the Nanomaterial Registry (>2000 NMs)) contain physicochemical characterization data as well as data for several relevant biological endpoints, assessed in part using harmonized Organisation for Economic Co-operation and Development (OECD) methods and test guidelines. Integration of such extensive NM information sources with the latest nanoinformatics methods will allow NanoSolveIT to model the relationships between NM structure (morphology), properties and their adverse effects and to predict the effects of other NMs for which less data is available. The project specifically addresses the needs of regulatory agencies and industry to effectively and rapidly evaluate the exposure, NM hazard and risk from nanomaterials and nano-enabled products, enabling implementation of computational 'safe-by-design' approaches to facilitate NM commercialization.