High-throughput imaging-based nephrotoxicity prediction for xenobiotics with diverse chemical structures.
Arch Toxicol
; 90(11): 2793-2808, 2016 Nov.
Article
em En
| MEDLINE
| ID: mdl-26612367
ABSTRACT
The kidney is a major target for xenobiotics, which include drugs, industrial chemicals, environmental toxicants and other compounds. Accurate methods for screening large numbers of potentially nephrotoxic xenobiotics with diverse chemical structures are currently not available. Here, we describe an approach for nephrotoxicity prediction that combines high-throughput imaging of cultured human renal proximal tubular cells (PTCs), quantitative phenotypic profiling, and machine learning methods. We automatically quantified 129 image-based phenotypic features, and identified chromatin and cytoskeletal features that can predict the human in vivo PTC toxicity of 44 reference compounds with ~82 % (primary PTCs) or 89 % (immortalized PTCs) test balanced accuracies. Surprisingly, our results also revealed that a DNA damage response is commonly induced by different PTC toxicants that have diverse chemical structures and injury mechanisms. Together, our results show that human nephrotoxicity can be predicted with high efficiency and accuracy by combining cell-based and computational methods that are suitable for automation.
Palavras-chave
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Citoesqueleto
/
Xenobióticos
/
Modelos Moleculares
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Montagem e Desmontagem da Cromatina
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Túbulos Renais Proximais
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Mutagênicos
Tipo de estudo:
Prognostic_studies
/
Risk_factors_studies
Limite:
Humans
Idioma:
En
Revista:
Arch Toxicol
Ano de publicação:
2016
Tipo de documento:
Article
País de afiliação:
Singapura