Metabolic characteristics analysis of liver cancer metastasis using bioinformatics / 国际外科学杂志

ABSTRACT

Objective:Using bioinformatics analysis methods, the differential genes in situ hepatocellular carcinoma and metastatic foci and their involved metabolic pathways were screened to find new metabolic targets for liver cancer metastasis treatment. Methods:The data numbered GSE40367 of primary and metastasis liver cancer were downloaded from the gene expression omnibus (GEO) database. After the differential expressed genes were screened out, the differential expressed genes were enriched with gene ontology (GO) functions and the Kyoto encyclopedia of genes and genomes (KEGG) pathway analysis. The STRING database and cytoscape software were used to analyze protein interactions. The changed metabolites in liver cancer metastasis were obtained from the research. Then the differential genes and metabolites were analyzed by MetaboAnalyst 4.0. Kaplan-Meier survival curve was used for survival analysis of the key genes on line.Results:A total of 564 differential expressed genes were selected from GSE40367, compared with tumors in situ, there were 287 up-regulated and 277 down-regulated in metastasis tumors. GO functions were enriched in processes such as monocarboxylic acid metabolism, fatty acid metabolism, and lipid transport. KEGG enrichment analysis showed that these differential genes were mainly concentrated in bile secretion, ABC transporters, cysteine and methionine metabolism, and gluconeogenesis. The combined analysis showed that the mainly relevant metabolic pathways were nicotinate and nicotinamide metabolism, phenylalanine metabolism, arginine biosynthesis and glycolysis and gluconeogenesis. Survival analysis of key genes found that CTH downregulation may be associated with a poor prognosis of liver cancer, while the high expression of PCK1 and AOX1 may be associated with a poor prognosis of liver cancer. Conclusion:The bioinformatics analysis reveals metabolic pathways related to liver cancer metastasis and the changed genes and metabolites in the pathway, which helps to understand the molecular mechanism of metastasis, and provides new targets for the treatment of metastasis liver cancer.