Title of article :
PPI Identification of Immune-Related Biomarkers in Esophageal Cancer on the Basis of Gene Co-Expression Network
Author/Authors :
Chen ، Shengjia Department of Thoracic Medical Oncology - Fujian Cancer Hospital - Fujian Medical University Cancer Hospital , Zeng ، Hongfu Department of Thoracic Medical Oncology - Fujian Cancer Hospital - Fujian Medical University Cancer Hospital , Zhang ، Aiping Department of Pharmacy - Fujian Cancer Hospital - Fujian Medical University Cancer Hospital , Lin ، Jinlan Department of Thoracic Medical Oncology - Fujian Cancer Hospital - Fujian Medical University Cancer Hospital , Zhu ، Kai Department of Thoracic Medical Oncology - Fujian Cancer Hospital - Fujian Medical University Cancer Hospital
From page :
53
To page :
65
Abstract :
Background: The mortality rate of esophageal cancer is on the continuous increase. Fortunately, with the development ofimmunotherapy, 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 intoimmune-related biomarkers of esophageal cancer for better treatment.Materials and Methods: In this study, gene co-expression networks were established using weighted gene co-expressionnetwork analysis, thus forming gene modules with different clusters. The tumor immune microenvironment was assessedwith the ESTIMATE algorithm.Results: Analysis of the module Eigen gene -immune score trait indicated that the black module was markedly associatedwith 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: CCR5, LCP2, PTPRC and TYROBP. The samples were divided into highand low-expression groups by the median expression of hub gene, and survival analysis was performed in combination with clinical information. The results revealed that the high-expression groups of genes LCP2 and PTPRC had a poor prognosis. TIMER immune cell infiltration analysis revealed that the expression levels of the 4 hub genes were positively correlated with immune cell infiltration and negatively correlated with tumor purity. In addition, these 4 hub genes were correlated with the expression of immune checkpoint genes CTLA-4 and PDCD1 positively. Gene set enrichment analysis enrichment analysis demonstrated that there were differences in tumor immunity and cancer-related pathways between high and low expression of 4 hub genes.Conclusion: Altogether, we identified four biomarkers that may have connection with tumor immunity, and speculatedthat 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.
Keywords :
Esophageal Cancer , immune score , Immune cell infiltration , immune checkpoint , Protein , protein interaction , weighted gene co , expression network analysis
Journal title :
Iranian Journal of Biotechnology (IJB)
Journal title :
Iranian Journal of Biotechnology (IJB)
Record number :
2744820
Link To Document :
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