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There is an urgent need to apply effective, data-driven approaches to reliably predict engineered nanomaterial (ENM) toxicity. Here we introduce a predictive computational framework based on the molecular and phenotypic effects of a large panel of ENMs across multiple in vitro and in vivo models. Our methodology allows for the grouping of ENMs based on multi-omics approaches combined with robust toxicity tests. Importantly, we identify mRNA-based toxicity markers and extensively replicate them in multiple independent datasets. We find that models based on combinations of omics-derived features and material intrinsic properties display significantly improved predictive accuracy as compared to physicochemical properties alone. Nanomaterials have a range of potential applications, however, toxicity remains a concern, limiting application and requiring extensive testing. Here, the authors report on a predictive framework made using a range of tests linking materials properties with toxicity, allowing the prediction of toxicity from physiochemical and biological properties. [ABSTRACT FROM AUTHOR]

Toxicogenomics opens novel opportunities for hazard assessment by utilizing computational methods to map molecular events and biological processes. In this study, the transcriptomic and immunopathological changes associated with airway exposure to a total of 28 engineered nanomaterials (ENM) are investigated. The ENM are selected to have different core (Ag, Au, TiO2, CuO, nanodiamond, and multiwalled carbon nanotubes) and surface chemistries (COOH, NH2, or polyethylene glycosylation (PEG)). Additionally, ENM with variations in either size (Au) or shape (TiO2) are included. Mice are exposed to 10 µg of ENM by oropharyngeal aspiration for 4 consecutive days, followed by extensive histological/cytological analyses and transcriptomic characterization of lung tissue. The results demonstrate that transcriptomic alterations are correlated with the inflammatory cell infiltrate in the lungs. Surface modification has varying effects on the airways with amination rendering the strongest inflammatory response, while PEGylation suppresses toxicity. However, toxicological responses are also dependent on ENM core chemistry. In addition to ENM‐specific transcriptional changes, a subset of 50 shared differentially expressed genes is also highlighted that cluster these ENM according to their toxicity. This study provides the largest in vivo data set currently available and as such provides valuable information to be utilized in developing predictive models for ENM toxicity. [ABSTRACT FROM AUTHOR]

The presence of nanomaterials (NMs) in the environment may represent a serious risk to human health, especially in a scenario of chronic exposure. To evaluate the potential relationship between NM-induced epigenetic alterations and carcinogenesis, the present study analyzed a panel of 33 miRNAs related to the cell transformation process in BEAS-2B cells transformed by TiO2NP and long-term MWCNT exposure. Our battery revealed a large impact on miRNA expression profiling in cells exposed to both NMs. From this analysis, a small set of five miRNAs (miR-23a, miR-25, miR-96, miR-210, and miR-502) were identified as informative biomarkers of the transforming effects induced by NM exposures. The usefulness of this reduced miRNA battery was further validated in other previously generated transformed cell systems by long-term exposure to other NMs (CoNP, ZnONP, MSiNP, and CeO2NP). Interestingly, the five selected miRNAs were consistently overexpressed in all cell lines and NMs tested. These results confirm the suitability of the proposed set of mRNAs to identify the potential transforming ability of NMs. Particular attention should be paid to the epigenome and especially to miRNAs for hazard assessment of NMs, as wells as for the study of the underlying mechanisms of action. [ABSTRACT FROM AUTHOR]

Highlights: [•] Drosophila was used to determine the genotoxic risk of several nanomaterials. [•] Titanium, zirconium and aluminium nanoparticles, and their ions were tested. [•] Mutation/recombination effects in wing somatic cells were determined. [•] No increases in genetic damage levels were observed in any treatment. [•] Our results contribute to increase the genotoxicity database on nanomaterials. [ABSTRACT FROM AUTHOR]