Emodin suppresses activation of hepatic stellate cells through p38 mitogen-activated protein kinase and Smad signaling pathways in vitro.
Xiaoli WangChengu NiuXiaojie ZhangMiao-Xian DongPublished in: Phytotherapy research : PTR (2018)
The aim of this study was to evaluate the hypothesis that emodin inhibits extracellular matrix (ECM)-related gene expression in activated hepatic stellate cells (HSCs) by blocking canonical or/and noncanonical components of transforming growth factor β1 (TGFβ1) intracellular signaling. Here, we demonstrate that emodin suppressed the gene expression of HSCs activation markers type I collagen, fibronectin, and α-smooth muscle actin, as well as HSCs proliferation. Mechanistically, emodin suppresses TGFβ1, TGFβ receptor II, TGFβ receptor I, and Smad4 gene expression, as well as Smad luciferase activity. Simultaneously, emodin reduced p38 mitogen-activated protein kinase (p38MAPK ) activity but not c-Jun N-terminal kinases and extracellular signal-regulated kinases 1 and 2 phosphorylation in HSC-T6 cells. Interestingly, deprivation of TGFβ using a neutralizing antibody abolished emodin-mediated inhibitions of the both Smad transcriptional activity and p38MAPK phosphorylation. Furthermore, emodin-mediated inhibition of HSCs activation could be partially blocked by PD98059 inhibition of p38MAPK or short hairpin RNA-imposed knockdown of Smad4. Conversely, simultaneous inhibition of Smad4 and p38MAPK pathways completely reverses the effects of emodin, suggesting that Smad and p38MAPK locate downstream of TGFβ1 and regulate collagen genes expression in HSCs. Collectively, these data suggest that emodin is a promising candidate for the treatment of hepatic fibrosis.
Keyphrases
- transforming growth factor
- epithelial mesenchymal transition
- gene expression
- signaling pathway
- induced apoptosis
- extracellular matrix
- dna methylation
- smooth muscle
- protein kinase
- cell cycle arrest
- transcription factor
- genome wide
- endoplasmic reticulum stress
- tyrosine kinase
- pi k akt
- oxidative stress
- long non coding rna
- binding protein
- electronic health record
- deep learning
- reactive oxygen species
- artificial intelligence