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Cationic liposomes induce cytotoxicity in HepG2 via regulation of lipid metabolism based on whole-transcriptome sequencing analysis

dc.contributor.authorLi, Ying
dc.contributor.authorCui, Xiu-Liang
dc.contributor.authorChen, Qing-Shan
dc.contributor.authorYu, Jing
dc.contributor.authorZhang, Hai
dc.contributor.authorGao, Jie
dc.contributor.authorSun, Du-Xin
dc.contributor.authorZhang, Guo-Qing
dc.date.accessioned2018-07-15T03:28:09Z
dc.date.available2018-07-15T03:28:09Z
dc.date.issued2018-07-11
dc.identifier.citationBMC Pharmacology and Toxicology. 2018 Jul 11;19(1):43
dc.identifier.urihttps://doi.org/10.1186/s40360-018-0230-5
dc.identifier.urihttps://hdl.handle.net/2027.42/144776
dc.description.abstractAbstract Backgroud Cationic liposomes (CLs) can be used as non-viral vectors in gene transfer and drug delivery. However, the underlying molecular mechanism of its cytotoxicity has not been well elucidated yet. Methods We herein report a systems biology approach based on whole-transcriptome sequencing coupled with computational method to identify the predominant genes and pathways involved in the cytotoxicity of CLs in HepG2 cell line. Results Firstly, we validated the concentration-dependent cytotoxicity of CLs with an IC50 of 120 μg/ml in HepG2 exposed for 24 h. Subsequently, we used whole-transcriptome sequencing to identify 220 (77 up- and 143 down-regulated) differentially expressed genes (DEGs). Gene ontology (GO) and pathway analysis showed that these DEGs were mainly related to cholesterol, steroid, lipid biosynthetic and metabolic processes. Additionally, “key regulatory” genes were identified using gene act, pathway act and co-expression network analysis, and expression levels of 11 interested altered genes were confirmed by quantitative real time PCR. Interestingly, no cell cycle arrest was observed through flow cytometry. Conclusions These data are expected to provide deep insights into the molecular mechanism of CLs cytotoxicity.
dc.titleCationic liposomes induce cytotoxicity in HepG2 via regulation of lipid metabolism based on whole-transcriptome sequencing analysis
dc.typeArticleen_US
dc.description.bitstreamurlhttps://deepblue.lib.umich.edu/bitstream/2027.42/144776/1/40360_2018_Article_230.pdf
dc.language.rfc3066en
dc.rights.holderThe Author(s).
dc.date.updated2018-07-15T03:28:11Z
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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