Open AccessArticle
Alternative Testing Methods for Predicting Health Risk from Environmental Exposures
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Annamaria Colacci, Monica Vaccari, Maria Grazia Mascolo, Francesca Rotondo, Elena Morandi, Daniele Quercioli, Stefania Perdichizzi, Cristina Zanzi, Stefania Serra, Vanes Poluzzi, Paola Angelini, Sandro Grilli and Franco Zinoni
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Abstract
Alternative methods to animal testing are considered as promising tools to support the prediction of toxicological risks from environmental exposure. Among the alternative testing methods, the cell transformation assay (CTA) appears to be one of the most appropriate approaches to predict the carcinogenic
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Alternative methods to animal testing are considered as promising tools to support the prediction of toxicological risks from environmental exposure. Among the alternative testing methods, the cell transformation assay (CTA) appears to be one of the most appropriate approaches to predict the carcinogenic properties of single chemicals, complex mixtures and environmental pollutants. The BALB/c 3T3 CTA shows a good degree of concordance with the
in vivo rodent carcinogenesis tests. Whole-genome transcriptomic profiling is performed to identify genes that are transcriptionally regulated by different kinds of exposures. Its use in cell models representative of target organs may help in understanding the mode of action and predicting the risk for human health. Aiming at associating the environmental exposure to health-adverse outcomes, we used an integrated approach including the 3T3 CTA and transcriptomics on target cells, in order to evaluate the effects of airborne particulate matter (PM) on toxicological complex endpoints. Organic extracts obtained from PM
2.5 and PM
1 samples were evaluated in the 3T3 CTA in order to identify effects possibly associated with different aerodynamic diameters or airborne chemical components. The effects of the PM
2.5 extracts on human health were assessed by using whole-genome 44 K oligo-microarray slides. Statistical analysis by GeneSpring GX identified genes whose expression was modulated in response to the cell treatment. Then, modulated genes were associated with pathways, biological processes and diseases through an extensive biological analysis. Data derived from
in vitro methods and omics techniques could be valuable for monitoring the exposure to toxicants, understanding the modes of action via exposure-associated gene expression patterns and to highlight the role of genes in key events related to adversity.
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