Academy of Medical Engineering and Translational Medicine, Tianjin University, Tianjin, 300072, China.
Department of General Surgery, Hebei Key Laboratory of Colorectal Cancer Precision Diagnosis and Treatment, The First Hospital of Hebei Medical University, Donggang Road 89, Shijiazhuang, 050031, Hebei, China.
BMC Cancer. 2021 Aug 8;21(1):905. doi: 10.1186/s12885-021-08629-3.
The tumor microenvironment (TME) has significantly correlation with tumor occurrence and prognosis. Our study aimed to identify the prognostic immune-related genes (IRGs)in the tumor microenvironment of colorectal cancer (CRC).
Transcriptome and clinical data of CRC cases were downloaded from TCGA and GEO databases. Stromal score, immune score, and tumor purity were calculated by the ESTIMATE algorithm. Based on the scores, we divided CRC patients from the TCGA database into low and high groups, and the differentially expressed genes (DEGs) were identified. Immune-related genes (IRGs) were selected by venn plots. To explore underlying pathways, protein-protein interaction (PPI) networks and functional enrichment analysis were used. After utilizing LASSO Cox regression analysis, we finally established a multi-IRGs signature for predicting the prognosis of CRC patients. A nomogram consists of the thirteen-IRGs signature and clinical parameters was developed to predict the overall survival (OS). We investigated the association between prognostic validated IRGs and immune infiltrates by TIMER database.
Gene expression profiles and clinical information of 1635 CRC patients were collected from the TCGA and GEO databases. Higher stromal score, immune score and lower tumor purity were observed positive correlation with tumor stage and poor OS. Based on stromal score, immune score and tumor purity, 1517 DEGs, 1296 DEGs, and 1892 DEGs were identified respectively. The 948 IRGs were screened by venn plots. A thirteen-IRGs signature was constructed for predicting survival of CRC patients. Nomogram with a C-index of 0.769 (95%CI, 0.717-0.821) was developed to predict survival of CRC patients by integrating clinical parameters and thirteen-IRGs signature. The AUC for 1-, 3-, and 5-year OS were 0.789, 0.783 and 0.790, respectively. Results from TIMER database revealed that CD1B, GPX3 and IDO1 were significantly related with immune infiltrates.
In this study, we established a novel thirteen immune-related genes signature that may serve as a validated prognostic predictor for CRC patients, thus will be conducive to individualized treatment decisions.
肿瘤微环境（TME）与肿瘤的发生和预后有显著的相关性。本研究旨在鉴定结直肠癌（CRC）肿瘤微环境中的预后免疫相关基因（IRGs）。
从 TCGA 和 GEO 数据库下载 CRC 病例的转录组和临床数据。使用 ESTIMATE 算法计算基质评分、免疫评分和肿瘤纯度。根据评分，我们将 TCGA 数据库中的 CRC 患者分为低分组和高分组，并确定差异表达基因（DEGs）。通过 venn 图选择免疫相关基因（IRGs）。为了探索潜在的途径，我们使用蛋白质-蛋白质相互作用（PPI）网络和功能富集分析。利用 LASSO Cox 回归分析，最终建立了一个多 IRGs signature 来预测 CRC 患者的预后。建立了一个包含 13 个 IRGs 签名和临床参数的列线图来预测总生存期（OS）。我们通过 TIMER 数据库研究了验证的预后 IRGs 与免疫浸润之间的关系。
从 TCGA 和 GEO 数据库收集了 1635 例 CRC 患者的基因表达谱和临床信息。较高的基质评分、免疫评分和较低的肿瘤纯度与肿瘤分期和较差的 OS 呈正相关。基于基质评分、免疫评分和肿瘤纯度，分别鉴定了 1517 个 DEGs、1296 个 DEGs 和 1892 个 DEGs。通过 venn 图筛选出 948 个 IRGs。构建了一个十三基因免疫相关基因 signature，用于预测 CRC 患者的生存情况。通过整合临床参数和十三基因免疫相关基因 signature，建立了一个预测 CRC 患者生存的列线图，C 指数为 0.769（95%CI，0.717-0.821）。1 年、3 年和 5 年 OS 的 AUC 分别为 0.789、0.783 和 0.790。TIMER 数据库的结果表明，CD1B、GPX3 和 IDO1 与免疫浸润显著相关。
本研究建立了一个新的十三基因免疫相关基因 signature，可作为 CRC 患者的验证性预后预测指标，有助于个体化治疗决策。
