Based on DNA copy number, ESTIMATE (Estimation of Stromal and Immune cells in Malignant Tumor tissues using Expression data) uses gene expression signatures to infer the fraction of stromal and immune cells in different tumor samples. Thus, identifying the TME related therapeutic targets may improve immunotherapy efficacy and give a new clue for clinical strategy. Recently, more researches have paid attention to antitumor immunity regulated by immune microenvironment, but the mechanism regulating the infiltration of immunocytes in ESCC is poorly understood. Tumor-infiltrating immune cells (TIICs), as the main components of the tumor microenvironment (TME) which composed of stromal cells, endothelial cells, and TIICs, have a significant impact on tumor progression, treatment, and outcomes of patients. Instead of two well-known immune checkpoint molecules PD-1 (programmed cell death protein 1, also named CD279) and PD-L1 (programmed cell death-ligand 1), other molecules such as CD155, CD226, and LAG3 are also recognized as new immune-related molecules which contribute to tumor-mediated immune suppression and promote tumor immunity escape in ESCC. As an effective therapeutic option, immunotherapy, especially immune checkpoint inhibitors, shows obviously clinical benefits in various cancers.
Therefore, it is still important to identify potential biomarkers to increase the effectiveness of therapy and survival rate of ESCC patients. Although recent developments have improved prognosis and survivorship, the molecular mechanism behind ESCC is not clear till now. The effective methods for treatment of ESCC include chemotherapy or chemoradiotherapy followed by extensive surgery, which will obviously reduce health-related quality of life. Classified by histology, esophageal cancer is divisible into adenocarcinoma and squamous cell carcinoma (ESCC). In Iran, esophageal cancer is more popular than any other countries or regions in the world. It is the eighth most common cancer and the sixth most common cause of cancer death globally. 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.Įsophageal cancer is a gastrointestinal malignancy with extremely aggressive nature and poor prognosis. Our study provided a comprehensive understanding of the TME in ESCC patients. Gene set enrichment analysis suggested that both immune response and immune system process gene sets were significantly enriched in high-risk group. 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). The area under the curve for the risk model in predicting 1- and 3- year survival rates were 0.660 and 0.942, respectively. Kaplan–Meier survival analysis showed that the expression of COL9A3 was significantly correlated with the overall survival of ESCC patients. Then multivariate analysis showed that COL9A3 was an independent discriminator of a better prognosis.
Prognostic genes including COL9A3, GFRA2, and VSIG4 were used to establish a risk prediction model using Cox regression analyses. Functional enrichment analysis showed that these genes were mainly involved in muscle-related function.
Resultsīased on the immune and stromal scores, ESCC samples were divided into high and low score groups and 299 overlapping differentially expressed genes were identified. MethodsĮSTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC.
As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC).