scholarly journals Activation of TGF-β1-CD147 positive feedback loop in hepatic stellate cells promotes liver fibrosis

2015 ◽  
Vol 5 (1) ◽  
Author(s):  
Hai-Yan Li ◽  
Di Ju ◽  
Da-Wei Zhang ◽  
Hao Li ◽  
Ling-Min Kong ◽  
...  
2013 ◽  
Vol 144 (5) ◽  
pp. S-994-S-995
Author(s):  
Akiko Sugiyama ◽  
Keishi Kanno ◽  
Norihisa Nishimichi ◽  
Nobusuke Kishikawa ◽  
Shinichiro Sumii ◽  
...  

Cell Reports ◽  
2020 ◽  
Vol 30 (5) ◽  
pp. 1310-1318.e5 ◽  
Author(s):  
Yetao Xu ◽  
Xiaoli Sun ◽  
Ruling Zhang ◽  
Tiefeng Cao ◽  
Shi-Ying Cai ◽  
...  

2018 ◽  
Vol 27 (2) ◽  
pp. 115-121
Author(s):  
Mona A. Abu El Makarem ◽  
Ghada M. El-Sagheer ◽  
Moustafa A. Abu El-Ella

Objective: To investigate the possible role of signal transducer and activator of transcription 5 (STAT5) in the pathogenesis of liver fibrosis in Egyptian patients with chronic hepatitis C (CHC) virus infection and its relation to hepatic stellate cells (HSC). Subjects and Methods: Sixty-five patients (46 males and 19 females) were divided into 4 groups based on the severity of fibrosis as detected by Fibroscan as follows: F1, n = 15; F2, n = 21; F3, n = 13; and F4, n = 16. Twenty age- and gender-matched healthy persons volunteered as controls. The serum levels of STAT5, TGF-β1, α-smooth muscle actin (α-SMA), fasting blood sugar, and fasting insulin, as well as homeostasis model assessment of insulin resistance (HOMA-IR), were determined and compared for all groups. The usefulness of the studied serum biomarkers for predicting liver fibrosis was evaluated using a receiver operating characteristic curve. Results: Serum levels of STAT5 were significantly lower in patients compared to controls (9.69 ± 5.62 vs. 14.73 ± 6.52, p ≤ 0.001); on the contrary, TGF-β1, α-SMA, and HOMA-IR were significantly higher in patients compared to controls (mean: 1,796.04 vs. 1,636.94; 14.94 vs. 8.1; and 7.91 vs. 4.18; p ≤ 0.01 and 0.001, respectively). TGF-β1 and α-SMA showed a progressive increase with advancing severity of hepatic fibrosis (mean TGF-β1: 2,058.4 in F1-F2 and 1,583.8 in F3-F4, p ≤ 0.04; mean α-SMA: 13.59 in F1-F2 and 16.62 in F3-F4, p ≤ 0.05). STAT5 had a significant negative correlation with TGF-β1 (p ≤ 0.001), while no correlation was detected with α-SMA (p ≤ 0.8). Conclusions: STAT5 may play a significant role in hepatic fibrogenesis through the induction of TGF-β1 but not through the activation of hepatic stellate cells.


2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Qi Wang ◽  
Song Wei ◽  
Lei Li ◽  
Qingfa Bu ◽  
Haoming Zhou ◽  
...  

AbstractLiver fibrosis is a patho-physiological process which can develop into cirrhosis, and hepatic carcinoma without intervention. Our study extensively investigated the mechanisms of lncRNA NEAT1 and miR-139-5p in regulating liver fibrosis progression. Our results demonstrated that the expression of lncRNA NEAT1 was increased and the expression of miR-139-5p was decreased in fibrotic liver tissues. LncRNA NEAT1 could sponge miR-139-5p and promoted hepatic stellate cells (HSCs) activation by directly inhibiting the expression of miR-139-5p. The co-localization of lncRNA NEAT1 with miR-139-5p was shown in the cytosols of activated HSCs. miR-139-5p upregulation could suppress the expression of β-catenin. The overexpression of β-catenin promoted HSCs activation. Moreover, we found that β-catenin could interact with SOX9 promoted HSCs activation. Our further studies demonstrated that SOX9 could bind with the TGF-β1 promoter and promoted the transcription activity of TGF-β1. The upregulation of TGF-β1 further promoted HSCs activation. In vivo study also suggested that lncRNA NEAT1 knockdown and miR-139-5p overexpression alleviated murine liver fibrosis. LncRNA NEAT1 exacerbated liver fibrosis by suppressing the expression of miR-139-5p. Collectively, our study suggested that miR-139-5p sponged by lncRNA NEAT1 regulated liver fibrosis via targeting β-catenin/SOX9/TGF-β1 Pathway.


2018 ◽  
Vol 234 (5) ◽  
pp. 6263-6273 ◽  
Author(s):  
Di Wu ◽  
Di Huang ◽  
Liang-Liang Li ◽  
Ping Ni ◽  
Xiu-Xian Li ◽  
...  

2018 ◽  
Vol 42 (10) ◽  
pp. 1370-1376 ◽  
Author(s):  
Xiao Feili ◽  
Shuang Wu ◽  
Weiwei Ye ◽  
Juncai Tu ◽  
Lianqing Lou

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