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Article

Amorphous silica nanoparticles induce malignant transformation and tumorigenesis of human lung epithelial cells via P53 signaling

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Pages 1176-1194 | Received 12 Aug 2016, Accepted 27 Oct 2017, Published online: 22 Nov 2017
 

Abstract

Rapid development and deployment of engineered nanomaterials, such as amorphous silica nanoparticles (SiNPs) in various commercial and biomedical applications have raised concerns about their potential adverse health effects, especially their chronic effects which have not been well addressed. In this study, human lung epithelial cells, BEAS-2B were continuously exposed to amorphous SiNPs, 5 μg/mL for 40 passages. We demonstrated here that prolonged exposure of BEAS-2B cells to amorphous SiNPs induced malignant transformation as indicated by enhanced cellular proliferation, anchorage-independent cell growth, and increased cell migration. The transformed cells induced tumorigenesis in nude mice. Furthermore, a comprehensive understanding of genome-wide transcriptional analysis was performed to clarify the molecular mechanisms based on microarray and bioinformatics analysis. Microarray data analysis demonstrated that chronic exposure of SiNPs affected expression of 821 genes, including 5 up-regulated and 816 down-regulated genes. Gene ontology and pathway analysis showed that SiNPs caused significant changes in gene expression patterns related to many important functions and pathways, mainly including response to cellular processes, oxidative stress, DNA damage, and cancer. In addition, Signal-net analysis indicated the most prominent significant role of tumor protein p53 in amorphous SiNPs-induced transformation. Further, data confirmed the inactivated p53 and aberrant p53 signaling under chronic amorphous SiNPs exposure. In summary, our data firstly demonstrated chronically low-dose amorphous SiNPs exposure resulted in malignant transformation of human lung epithelial cell via p53 signaling, which provides new in vitro evidence for the carcinogenicity of amorphous SiNPs.

Acknowledgments

The authors thank Prof. Wensheng Yang from Jilin University for the preparation of the SiNPs, and Weiping Tang of Cnkingbio biotechnology Co. Ltd for bioinformatics assistance.

Disclosure statement

The authors declare they have no conflict of interest.

Additional information

Funding

This work was supported by National Natural Science Foundation of China (No. 81202242, No. 81573176), General Program of Beijing Natural Science Foundation (7162021, 7162022); Science and Technology Development Program of the Beijing Municipal Commission of Education (KM201510025005).

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