Key Laboratory of Pathobiology, Ministry of Education, Jilin University, Changchun, 130021, Jilin, People's Republic of China.
Department of Urology, The First Hospital of Jilin University, Changchun, 130021, Jilin, People's Republic of China.
BMC Med Genomics. 2021 Mar 10;14(1):75. doi: 10.1186/s12920-021-00928-9.
As a complex system participating in tumor development and progression, the tumor microenvironment was poorly understood in esophageal cancer especially squamous cell carcinoma (ESCC).
ESTIMATE algorithm is used to investigate tumor-infiltrating immune cells and prognostic genes which were associated with the tumor microenvironment in ESCC.
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.
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.
作为参与肿瘤发生和发展的复杂系统，食管癌（尤其是食管鳞状细胞癌，ESCC）的肿瘤微环境仍知之甚少。
ESTIMATE 算法用于研究与 ESCC 肿瘤微环境相关的肿瘤浸润免疫细胞和预后基因。
基于免疫和基质评分，将 ESCC 样本分为高分和低分组，鉴定出 299 个重叠差异表达基因。功能富集分析表明，这些基因主要与肌肉相关功能有关。使用 Cox 回归分析，预后基因包括 COL9A3、GFRA2 和 VSIG4，建立风险预测模型。然后多变量分析表明 COL9A3 是预后更好的独立判别因素。Kaplan-Meier 生存分析表明，COL9A3 的表达与 ESCC 患者的总生存率显著相关。风险模型预测 1 年和 3 年生存率的曲线下面积分别为 0.660 和 0.942。风险评分与浆细胞呈负相关，而与活化 CD4 记忆 T 细胞、M1 巨噬细胞和 M2 巨噬细胞的比例呈正相关（每种比较的 p<0.001）。基因集富集分析表明，高风险组中免疫反应和免疫系统过程基因集均显著富集。
本研究全面了解了 ESCC 患者的 TME。风险模型的建立对于早期识别高危患者具有重要价值，有助于实现个体化治疗并提高免疫治疗反应的可能性。
