ABSTRACT
ObjectiveTo investigate the expression and significance of the ABAT gene in hepatocellular carcinoma (HCC) using related databases. MethodsThe Oncomine database and GEPIA were used to analyze the expression of ABAT in HCC tissue. GEPIA was used to investigate the correlation of ABAT mRNA with the survival time and pathological stage of HCC patients. The MethHC database was used to analyze the methylation level of ABAT promoter region. The String database was used to analyze the network of proteins interacting with ABAT protein. The Human Protein Atlas was used to analyze the expression of ABAT protein in HCC tissue and the influence of the protein expression of ABAT on prognosis. ResultsThe mRNA expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue; patients with lower mRNA expression tended to have a poorer prognosis (log-rank, P=0.002 1) and a higher degree of malignancy (P=0.002 34). The protein expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue, and patients with lower protein expression tended to have a poorer prognosis (log-rank, P=2.14×10-3). The methylation level of ABAT promoter region in HCC tissue was significantly higher than that in normal liver tissue (P＜0.005). The proteins interacting with ABAT included ALDH1A3, ALDH9A1, ALDH3A2, GAD1, and GAD2, which might be involved in cell functions such as cell apoptosis, redox, and neurotransmitter secretion. ConclusionData mining of tumor gene databases shows that there are low levels of mRNA and protein expression of ABAT in HCC tissue, which is associated with patient’s survival time. At present, database mining can provide a reference for the diagnosis and prognosis evaluation of HCC and a theoretical basis for tumor research in the future.
ABSTRACT
ObjectiveTo investigate the expression and significance of the ABAT gene in hepatocellular carcinoma (HCC) using related databases. MethodsThe Oncomine database and GEPIA were used to analyze the expression of ABAT in HCC tissue. GEPIA was used to investigate the correlation of ABAT mRNA with the survival time and pathological stage of HCC patients. The MethHC database was used to analyze the methylation level of ABAT promoter region. The String database was used to analyze the network of proteins interacting with ABAT protein. The Human Protein Atlas was used to analyze the expression of ABAT protein in HCC tissue and the influence of the protein expression of ABAT on prognosis. ResultsThe mRNA expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue; patients with lower mRNA expression tended to have a poorer prognosis (log-rank, P=0.002 1) and a higher degree of malignancy (P=0.002 34). The protein expression of ABAT in HCC tissue was significantly lower than that in normal liver tissue, and patients with lower protein expression tended to have a poorer prognosis (log-rank, P=2.14×10-3). The methylation level of ABAT promoter region in HCC tissue was significantly higher than that in normal liver tissue (P＜0.005). The proteins interacting with ABAT included ALDH1A3, ALDH9A1, ALDH3A2, GAD1, and GAD2, which might be involved in cell functions such as cell apoptosis, redox, and neurotransmitter secretion. ConclusionData mining of tumor gene databases shows that there are low levels of mRNA and protein expression of ABAT in HCC tissue, which is associated with patient’s survival time. At present, database mining can provide a reference for the diagnosis and prognosis evaluation of HCC and a theoretical basis for tumor research in the future.