Gene mining of immune microenvironment in hepatocellular carcinoma

Background: Hepatocellular carcinoma (HCC) is a common malignant tumor worldwide with a poor prognosis. Recent studies have shown that the occurrence, development and prognosis of liver cancer are closely related to tumor microenvironment (TME) and tumor immune infiltration. Methods: Therefore, important information on various diseases can be obtained from public databases such as The Cancer Gene Atlas (TCGA), and ideas or schemes that may be effective for the treatment of various diseases can be screened and analyzed by screening various conditions. In this study, 424 cases of liver hepatocellular carcinoma (LIHC) in the TCGA database and CIBERSORT algorithm were used to calculate the proportion of tumor-invasive immune cells. Combined with the clinical data from TCGA database, it was concluded that T cells regulatory (Tregs) were correlated with the development and prognosis of HCC. Cox regression analysis was used to screen differentially expressed genes, and survival analysis was performed according to the screened differentially expressed genes to see whether there was a significant association with the prognosis of HCC. Then gene ontology and kyoto encyclopedia of genes and genomes analysis of differentially expressed genes were carried out to explore the possibility of differentially expressed genes becoming potential therapeutic targets of HCC. Results: Finally, I identified the gene centromere protein o (CENPO), which is associated with immune cells and improve the prognosis of HCC. Conclusion: CENPO may be a potential biological therapeutic target for hepatocellular treatment.