Alpha-fetoprotein accelerates the progression of hepatocellular carcinoma by promoting Bcl-2 gene expression through an RA-RAR signalling pathway.
Chao ZhangJiangtao ZhangJing WangYing YanChuanbao ZhangPublished in: Journal of cellular and molecular medicine (2020)
Previous studies have found that alpha-fetoprotein (AFP) can promote the proliferation of hepatoma cells and accelerate the progression of hepatocellular carcinoma (HCC). However, the exact mechanism of action remains unclear. Recent bioinformatics studies have predicted the possible interaction between AFP and retinoic acid receptors (RARs). Thus, the purpose of this study was to investigate the molecular mechanism through which AFP promotes tumour cell proliferation by interfering with the RA-RAR signal pathway. Our data indicated that AFP could significantly promote the proliferation and weaken ATRA-induced apoptosis of hepatoma cells. Besides, cytoplasmic AFP interacts with RAR, disrupting its entrance into the nucleus, which in turn affects the expression of the Bcl-2 gene. In addition, knockdown of AFP in HepG2 cells was synchronously associated with an incremental increase of RAR binding to DNA, as well as down-regulation of Bcl-2; the opposite effect was observed in AFP gene-transfected HLE cells. Moreover, a similar effect of AFP was detected in tumour tissues with high serum AFP, but not in adjacent non-cancerous liver tissues, or HCC tissues with low serum AFP levels. These results indicate that AFP acts as signalling molecule and prevents RAR from entering into the nucleus by interacting with RAR, thereby promoting the expression of Bcl-2. Our data reveal a novel mechanism through which AFP regulates Bcl-2 expression and further suggest that AFP may be used as a novel target for treating HCC.
Keyphrases
- induced apoptosis
- gene expression
- signaling pathway
- endoplasmic reticulum stress
- cell proliferation
- poor prognosis
- oxidative stress
- rheumatoid arthritis
- genome wide
- cell cycle arrest
- dna methylation
- binding protein
- machine learning
- big data
- mouse model
- case control
- disease activity
- systemic sclerosis
- circulating tumor