Jiang Yi, Zeng Zhenhao, Xiong Situ, Jiang Ming, Huang Gaomin, Zhang Chiyu, Xi Xiaoqing
Department of Urology, The Second Affiliated Hospital of Nanchang University, Nanchang, China.
Department of Urology, The First Affiliated Hospital of Nanchang University, Nanchang, China.
Front Cell Dev Biol. 2022 May 12;10:775417. doi: 10.3389/fcell.2022.775417. eCollection 2022.
The immune microenvironment profoundly affects tumor prognosis and therapy. The present study aimed to reveal potential immune escape mechanisms and construct a novel prognostic signature systematic bioinformatic analysis of the bladder cancer (BLCA) immune microenvironment. The transcriptomic data and clinicopathological information for patients with BLCA were obtained from The Cancer Genome Atlas (TCGA). Consensus clustering analysis based on the CIBERSORT and ESTIMATE algorithms was performed with patients with BLCA, which divided them into two clusters. Subsequently, the differentially expressed genes (DEGs) in the two were subjected to univariate Cox and least absolute shrinkage and selection operator (LASSO) regression analyses to identify prognostic genes, which were used to construct a prognostic model. The predictive performance of the model was verified by receiver operating characteristic (ROC) and Kaplan-Meier (K-M) analyses. In addition, we analyzed the differentially altered immune cells, mutation burden, neoantigen load, and subclonal genome fraction between the two clusters to reveal the immune escape mechanism. Based on the ESTIMATE and clustering analyses, patients with BLCA were classified into two heterogeneous clusters: ImmuneScoreH and ImmuneScoreL. Univariate Cox and LASSO regression analyses identified CD96 (HR = 0.83) and IBSP (HR = 1.09), which were used to construct a prognostic gene signature with significant predictive accuracy. Regarding potential immune escape mechanisms, ImmuneScoreH and ImmuneScoreL were characterized by inactivation of innate immune cell chemotaxis. In ImmuneScoreL, a low tumor antigen load might contribute to immune escape. ImmuneScoreH featured high expression of immune checkpoint molecules. CD96 and IBSP were considered prognostic factors for BLCA. Innate immune inactivation and a low tumor antigen load may be associated with immune escape mechanisms in both clusters. Our research complements the exploration of the immune microenvironment in BLCA.
免疫微环境对肿瘤预后和治疗有深远影响。本研究旨在通过对膀胱癌（BLCA）免疫微环境进行系统的生物信息学分析，揭示潜在的免疫逃逸机制并构建一种新的预后特征。从癌症基因组图谱（TCGA）获取了BLCA患者的转录组数据和临床病理信息。基于CIBERSORT和ESTIMATE算法对BLCA患者进行了一致性聚类分析，将他们分为两个聚类。随后，对这两个聚类中的差异表达基因（DEG）进行单变量Cox和最小绝对收缩和选择算子（LASSO）回归分析以鉴定预后基因，这些基因用于构建预后模型。通过受试者操作特征（ROC）和Kaplan-Meier（K-M）分析验证了该模型的预测性能。此外，我们分析了两个聚类之间差异改变的免疫细胞、突变负担、新抗原负荷和亚克隆基因组分数，以揭示免疫逃逸机制。基于ESTIMATE和聚类分析，BLCA患者被分为两个异质性聚类：免疫评分高（ImmuneScoreH）和免疫评分低（ImmuneScoreL）。单变量Cox和LASSO回归分析确定了CD96（HR = 0.83）和骨桥蛋白（IBSP，HR = 1.09），它们被用于构建具有显著预测准确性的预后基因特征。关于潜在的免疫逃逸机制，ImmuneScoreH和ImmuneScoreL的特征是固有免疫细胞趋化性失活。在ImmuneScoreL中，低肿瘤抗原负荷可能导致免疫逃逸。ImmuneScoreH的特征是免疫检查点分子的高表达。CD96和IBSP被认为是BLCA的预后因素。固有免疫失活和低肿瘤抗原负荷可能与两个聚类中的免疫逃逸机制有关。我们的研究补充了对BLCA免疫微环境的探索。
