PPI Identification of Immune-Related Biomarkers in Esophageal Cancer on the Basis of Gene Co-Expression Network.

Background: The mortality rate of esophageal cancer is on the continuous increase. Fortunately, with the development of immunotherapy, the prognosis and survival rate of patients with esophageal cancer have been improved gradually. Objective: Immune markers have a crucial part in immunotherapy. Therefore, it is of great meaning to delve further into immune-related biomarkers of esophageal cancer for better treatment. Materials and Methods: In this study, gene co-expression networks were established using weighted gene co-expression network analysis, thus forming gene modules with different clusters. The tumor immune microenvironment was assessed with the ESTIMATE algorithm. Results: Analysis of the module Eigen gene -immune score trait indicated that the black module was markedly associated with immune score, with the top 80 genes regarding correlation ranking as the candidate hub gene set. Enrichment analysis revealed that genes within the black module were primarily enriched in tumor immune-related functions. To mine the hub genes that were closely connected with immunity, protein-protein interaction networks were constructed by STRING for genes within the black module, and genes with the interaction score top10 were retained. They were intersected with hub genes to finally obtain four hub genes: Conclusion: Altogether, we identified four biomarkers that may have connection with tumor immunity, and speculated that these genes may influence patient prognosis by affecting pathways related to esophageal cancer immunity. This study will pave the way for the research of immune mechanisms of esophageal cancer and the analysis of patient's prognosis.