Inhibition of UBA52 induces autophagy via EMC6 to suppress hepatocellular carcinoma tumorigenesis and progression.
Li TongXiaofei ZhengTianqi WangWang GuTingting ShenWenkang YuanSiyu WangSonglin XingXiaoying LiuChong ZhangChao ZhangPublished in: Journal of cellular and molecular medicine (2024)
Ubiquitin A-52 residue ribosomal protein fusion product 1 (UBA52) has a role in the occurrence and development of tumours. However, the mechanism by which UBA52 regulates hepatocellular carcinoma (HCC) tumorigenesis and progression remains poorly understood. By using the Cell Counting Kit (CCK-8), colony formation, wound healing and Transwell assays, we assessed the effects of UBA52 knockdown and overexpression on the proliferation and migration of HCC cells in vitro. By establishing subcutaneous and metastatic tumour models in nude mice, we evaluated the effects of UBA52 on HCC cell proliferation and migration in vivo. Through bioinformatic analysis of data from the Gene Expression Profiling Interactive Analysis (GEPIA) and The Cancer Genome Atlas (TCGA) databases, we discovered that UBA52 is associated with autophagy. In addition, we discovered that HCC tissues with high UBA52 expression had a poor prognosis in patients. Moreover, knockdown of UBA52 reduced HCC cell growth and metastasis both in vitro and in vivo. Mechanistically, knockdown of UBA52 induced autophagy through EMC6 in HCC cells. These findings suggest that UBA52 promoted the proliferation and migration of HCC cells through autophagy regulation via EMC6 and imply that UBA52 may be a viable novel treatment target for HCC patients.
Keyphrases
- poor prognosis
- induced apoptosis
- endoplasmic reticulum stress
- cell death
- single cell
- cell cycle arrest
- end stage renal disease
- oxidative stress
- signaling pathway
- ejection fraction
- chronic kidney disease
- long non coding rna
- cell therapy
- genome wide
- prognostic factors
- small cell lung cancer
- risk assessment
- wound healing
- gene expression
- peritoneal dialysis
- mesenchymal stem cells
- adipose tissue
- high throughput
- skeletal muscle
- binding protein
- diabetic rats
- electronic health record
- machine learning
- patient reported outcomes
- dna methylation
- artificial intelligence