Background: As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC).
Methods: ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC.
Results: Based on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function. Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis. Kaplan-Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. The risk score was negatively correlated with plasma cells, while positively correlated with the proportions of activated CD4 memory T cells, M1 Macrophages and M2 Macrophages (p < 0.001 for each comparison). Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group.
Conclusions: Our study provided a comprehensive understanding of the TME in ESCC patients. The establishment of the risk model is valuable for the early identification of high-risk patients to facilitate individualized treatment and improve the possibility of immunotherapy response.
Keywords: Esophageal squamous cell carcinoma; Overall survival; Prognosis; Tumor microenvironment; Tumor-infiltrating immune cells.