Lin Cha, Chen Jian, Su Zhaoying, Liu Pei, Liu Zheyu, Zhu Chenchen, Xu Dan, Lin Zhongda, Xu Pei, Liu Ganqiang, Liu Xinjian
Department of Biochemistry, Molecular Cancer Research Center, School of Medicine, Sun Yat-sen University, Shenzhen, China.
Neurobiology Research Center, School of Medicine, Sun Yat-sen University, Shenzhen, China.
Front Cell Dev Biol. 2021 Sep 28;9:723103. doi: 10.3389/fcell.2021.723103. eCollection 2021.
Immune checkpoint inhibitors have been successfully used in a variety of tumors, however, the efficacy of immune checkpoint blockade therapy for patients with glioma is limited. In this study, we tried to clarify gene expression signatures related to the prognosis of gliomas and construct a signature to predict the survival of patients with gliomas. Calcium-related differential expressed genes (DEGs) between gliomas and normal brain tissues were comprehensively analyzed in two independent databases. Univariate, multivariate Cox regression analysis and proportional hazards model were used to identify the prognostic of calcium-related risk score signature. The CIBERSORT algorithm and association analysis were carried out to evaluate the relationship between calcium-related signature and characteristic clinical features, tumor-infiltrating immune cell signatures as well as immune checkpoint molecules in glioma. A nomogram model was developed for predicting the overall survival for patients with gliomas. We found the intersection of 415 DEGs between gliomas and normal brain tissues, and identified that an eighteen calcium-related gene panel was significantly enriched in these DEGs. A calcium-related signature derived risk score was developed to divide patients into high- and low-risk groups. Low levels of calcium-related gene expression in high-risk score cases were accompanied with worse outcomes of patients. Calcium-related risk scores were significantly associated with characteristic clinical features, immune infiltrating signatures of tumor microenvironment, and exhausted T cell markers including programmed cell death 1 (PD-1), lymphocyte activating 3 (LAG3), and T cell membrane protein 3 (TIM-3), which contribute to an adverse therapeutic effect of immunotherapy. Calcium-related signature risk score was considered as an independent prognostic parameter to predict the of overall survival of patients with gliomas in nomogram model. Our study demonstrated that calcium signaling pathway is highly associated with immunosuppression of gliomas and overall survival of patients. Targeting the calcium signaling pathway might be a new strategy to reverse the immunosuppressive microenvironment of gliomas and improve the efficacy of glioma immunotherapy.
免疫检查点抑制剂已成功应用于多种肿瘤，然而，免疫检查点阻断疗法对胶质瘤患者的疗效有限。在本研究中，我们试图阐明与胶质瘤预后相关的基因表达特征，并构建一个特征来预测胶质瘤患者的生存情况。在两个独立数据库中全面分析了胶质瘤与正常脑组织之间的钙相关差异表达基因（DEGs）。使用单变量、多变量Cox回归分析和比例风险模型来确定钙相关风险评分特征的预后情况。采用CIBERSORT算法和关联分析来评估钙相关特征与胶质瘤特征性临床特征、肿瘤浸润免疫细胞特征以及免疫检查点分子之间的关系。开发了一种列线图模型来预测胶质瘤患者的总生存期。我们发现了胶质瘤与正常脑组织之间415个DEGs的交集，并确定一个包含18个钙相关基因的基因集在这些DEGs中显著富集。开发了一个基于钙相关特征的风险评分，将患者分为高风险组和低风险组。高风险评分病例中钙相关基因表达水平较低与患者较差的预后相关。钙相关风险评分与特征性临床特征、肿瘤微环境的免疫浸润特征以及包括程序性细胞死亡蛋白1（PD-1）、淋巴细胞激活分子3（LAG3）和T细胞膜蛋白3（TIM-3）在内的耗竭性T细胞标志物显著相关，这些因素导致免疫治疗产生不良疗效。在列线图模型中，钙相关特征风险评分被视为预测胶质瘤患者总生存期的独立预后参数。我们的研究表明，钙信号通路与胶质瘤的免疫抑制和患者的总生存期高度相关。靶向钙信号通路可能是一种逆转胶质瘤免疫抑制微环境并提高胶质瘤免疫治疗疗效的新策略。
