Development of a Novel Prognostic Model for Esophageal Squamous Cell Carcinoma: Insights into Immune Cell Interactions and Drug Sensitivity

Abstract

Esophageal squamous cell carcinoma (ESCC) is a highly aggressive upper gastrointestinal tumor with a 5-year survival rate of less than 20%. Therefore, developing new effective prognostic markers is of great clinical signi cance. In this study, we utilized datasets speci c to ESCC and analyzed differentially expressed genes in each dataset. By conducting Venn analysis, we identi ed genes that exhibited signi cant differential expression across multiple datasets.Through gene interaction network analysis, we identi ed a core set of genes (23 genes) and established a prognostic model for ESCC using the COX algorithm (p=0.000245, 3-year AUC=0.98). The high-risk group of patients showed a signi cantly worse prognosis compared to the low-risk group. Furthermore, immune interaction network analysis revealed a strong association between increased risk values and an elevated presence of M2 macrophages within tumor tissues. Drug sensitivity analysis indicated that the high-risk group of patients exhibited poorer sensitivity to rst-line chemotherapy drugs for ESCC. Notably, there was a signi cant positive correlation between the expression of core genes and immune checkpoint genes such as SIGLEC15, PDCD1LG2, and HVCR2. The highrisk group exhibits decreased Tumor Immune Dysfunction and Exclusion (TIDE) values, indicating that immune checkpoint blockade therapy might result in more favorable outcomes for these individuals. The immune checkpoint blockade (ICB) therapy may potentially yield better outcomes for these patients. In summary, through comprehensive bioinformatics analysis, we have established a highly effective prognostic model consisting of 23 genes for ESCC. An increased risk score in this model indicates a stronger in ltration of M2 macrophages and poorer sensitivity to chemotherapy drugs. Moreover, immune checkpoint blockade therapy may hold greater bene ts for patients in the high-risk group.