Journal
ENVIRONMENTAL POLLUTION
Volume 254, Issue -, Pages -Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.envpol.2019.07.043
Keywords
miRNAs; Serum; PM2.5; Lung cancer; Microarray analysis
Categories
Funding
- National Natural Science Foundation of China [91643108, 81573190]
- National Natural Science Foundation of Hebei Province of China [H2015206326]
- National Natural Science Foundation of Education Department of Hebei Province of China [ZD2015008]
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Ambient fine particulate matter (PM2.5) as an environmental pollution has been associated with the lung cancer. However, the mechanism of epigenetics such as miRNAs deregulation between PM2.5-exposure and lung cancer has not been elucidated clearly. Twenty C57BL/6 mice were divided randomly into 2 groups and exposed to the filtered air (FA) and the concentrated air (CA), respectively. The FA mice were exposed to filtered air in chambers with a high-efficient particulate air filter (HEPA-filter), and the CA mice were exposed to concentration ambient PM2.5. The total duration of exposure was performed 6 h per day from December 1st, 2017 to January 27th, 2018. The mice exposed 900.21 mu g/m(3) PM2.5 for 6 h per day in CA chamber, which was nearly equaled to 225.05 mu g/m(3) for 24-h calculatingly. After exposure, the serum miRNAs levels were detected by microarray. Genetic and pathological alterations in lung of mice with/without PM2.5 exposure were detected. 38 differential miRNAs in serum of mice were found after PM2.5 exposure for 8 weeks. Among of them, 13 miRNAs related with lung cancer were consistent in serum and lung of mice. The target genes of 13 deregulated miRNAs including CRK, NR2F2, VIM, RASSF1, CCND2, PRKCA, SIRT1, CDK6, MAP3K7, HIF1A, UBE2V2, ATG10, BAX, E2F1, RASSF5 and CTNNB1, could involve in the pathway of lung cancer developing. Compared with the FA group, the significantly increases of histopathological changes, ROS and DNA damage were observed in lung of mice in CA group. Our study suggested that miRNAs in serum could be identified as candidate biomarkers to predict the lung cancer development during early PM2.5 exposure. (C) 2019 Elsevier Ltd. All rights reserved.
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