RNA-seq analysis provide new insights into mapk signaling of apolipoproteinciii-induced inflammation in porcine vascular endothelial cells.
Yuan YueHao JiangShouqing YanYao FuChang LiuXulei SunMenglong ChaiYan GaoBao YuanChengzhen ChenLisheng DaiJiabao ZhangYu DingPublished in: Cell cycle (Georgetown, Tex.) (2017)
Apolipoprotein CIII (ApoCIII) has been shown to be associated with the inflammatory response, but the mechanism of its inflammatory effects remains unclear. Because vascular endothelial cells (VECs) play a key role in the development of inflammation, the present study was performed to investigate inflammatory mechanisms induced by ApoCIII in VECs. In this study, we screened differentially expressed genes (DEGs) using RNA-sequencing. The results identified 390 up-regulated genes and 257 down-regulated genes. We performed GO functional classification and KEGG pathway analysis for DEGs. Analysis of sequencing data showed that 21 genes were related to the MAPK pathway. Finally, we investigated whether ApoCIII regulates the expression of pro-inflammatory cytokines via MAPK signaling pathway. The results showed that ApoCIII increased the expression levels of IL-6, TNF-α, VCAM-1 and ICAM-1 in VECs. ApoCIII activated the phosphorylation of ERK1/2 and p38 MAPK. An inhibitor of ERK1/2 and p38 MAPK decreased the protein levels of IL-6 and TNF-α. Our findings demonstrate that ApoCIII induces pro-inflammatory cytokine production in VECs via activation of ERK1/2 and p38 MAPK phosphorylation.
Keyphrases
- signaling pathway
- pi k akt
- oxidative stress
- single cell
- endothelial cells
- rna seq
- genome wide
- inflammatory response
- epithelial mesenchymal transition
- high glucose
- induced apoptosis
- poor prognosis
- bioinformatics analysis
- cell proliferation
- rheumatoid arthritis
- diabetic rats
- machine learning
- deep learning
- protein kinase
- dna methylation
- lipopolysaccharide induced
- gene expression
- lps induced
- genome wide analysis
- vascular endothelial growth factor
- data analysis
- drug induced
- big data
- mass spectrometry