Ma Xiao-Bo, Xu Yuan-Yuan, Zhu Meng-Xuan, Wang Lu
Department of General Surgery, The First Hospital of Shanxi Medical University, Taiyuan, China.
Department of Day Surgery Centre, The First Hospital of Shanxi Medical University, Taiyuan, China.
Front Oncol. 2021 Feb 19;10:591739. doi: 10.3389/fonc.2020.591739. eCollection 2020.
The immunosuppressive microenvironment is closely related to tumorigenesis and cancer development, including colorectal cancer (CRC). The aim of the current study was to identify new immune biomarkers for the diagnosis and treatment of CRC.
CRC data were downloaded from the Gene Expression Omnibus and The Cancer Genome Atlas databases. Sequences of immune-related genes (IRGs) were obtained from the ImmPort and InnateDB databases. Gene set enrichment analysis (GSEA) and transcription factor regulation analysis were used to explore potential mechanisms. An immune-related classifier for CRC prognosis was conducted using weighted gene co-expression network analysis (WGCNA), Cox regression analysis, and least absolute shrinkage and selection operator (LASSO) analysis. ESTIMATE and CIBERSORT algorithms were used to explore the tumor microenvironment and immune infiltration in the high-risk CRC group and the low-risk CRC group.
By analyzing the IRGs that were significantly associated with CRC in the module, a set of 13 genes (CXCL1, F2RL1, LTB4R, GPR44, ANGPTL5, BMP5, RETNLB, MC1R, PPARGC1A, PRKDC, CEBPB, SYP, and GAB1) related to the prognosis of CRC were identified. An IRG-based prognostic signature that can be used as an independent potentially prognostic indicator was generated. The ROC curve analysis showed acceptable discrimination with AUCs of 0.68, 0.68, and 0.74 at 1-, 3-, and 5- year follow-up respectively. The predictive performance was validated in the train set. The potential mechanisms and functions of prognostic IRGs were analyzed, i.e., NOD-like receptor signaling, and transforming growth factor beta (TGFβ) signaling. Besides, the stromal score and immune score were significantly different in high-risk group and low-risk group (p=4.6982e-07, p=0.0107). Besides, the proportions of resting memory CD4 T cells was significantly higher in the high-risk groups.
The IRG-based classifier exhibited strong predictive capacity with regard to CRC. The survival difference between the high-risk and low-risk groups was associated with tumor microenvironment and immune infiltration of CRC. Innovative biomarkers for the prediction of CRC prognosis and response to immunological therapy were identified in the present study.
免疫抑制微环境与肿瘤发生及癌症发展密切相关，包括结直肠癌（CRC）。本研究的目的是鉴定用于CRC诊断和治疗的新免疫生物标志物。
从基因表达综合数据库（Gene Expression Omnibus）和癌症基因组图谱数据库（The Cancer Genome Atlas）下载CRC数据。从免疫表位数据库（ImmPort）和先天性免疫数据库（InnateDB）获取免疫相关基因（IRG）的序列。采用基因集富集分析（GSEA）和转录因子调控分析来探索潜在机制。使用加权基因共表达网络分析（WGCNA）、Cox回归分析和最小绝对收缩和选择算子（LASSO）分析构建用于CRC预后的免疫相关分类器。采用ESTIMATE和CIBERSORT算法探索高危CRC组和低危CRC组的肿瘤微环境和免疫浸润情况。
通过分析模块中与CRC显著相关的IRG，鉴定出一组与CRC预后相关的13个基因（CXCL1、F2RL1、LTB4R、GPR44、ANGPTL5、BMP5、RETNLB、MC1R、PPARGC1A、PRKDC、CEBPB、SYP和GAB1）。生成了一种基于IRG的预后特征，可作为独立的潜在预后指标。ROC曲线分析显示，在1年、3年和5年随访时，AUC分别为0.68、0.68和0.74，具有可接受的区分度。在训练集中验证了预测性能。分析了预后IRG的潜在机制和功能，即NOD样受体信号通路和转化生长因子β（TGFβ）信号通路。此外，高危组和低危组的基质评分和免疫评分存在显著差异（p = 4.6982e - 07，p = 0.0107）。此外，高危组中静息记忆CD4 T细胞的比例显著更高。
基于IRG的分类器对CRC具有较强的预测能力。高危组和低危组之间的生存差异与CRC的肿瘤微环境和免疫浸润有关。本研究鉴定出了用于预测CRC预后和免疫治疗反应的创新性生物标志物。
