Identification of prognostic immune-related gene signature associated with tumor microenvironment of colorectal cancer

BMC Cancer

Xiaosong Gu¹  Yuanyuan Wang²  Shang Guo³  Zengren Zhao³  Xia Jiang³  Wei Li³  Xingkai Su³  Fei Xu³  Guiqi Wang³  Xiaojing Jin⁴ 

[1] Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072, Tianjin, China;Academy of Medical Engineering and Translational Medicine, Tianjin University, 300072, Tianjin, 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, 050031, Shijiazhuang, Hebei, 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, 050031, Shijiazhuang, Hebei, China;Departments of Emergency, The First Hospital of Hebei Medical University, Shijiazhuang, Hebei, China;

关键词: Colorectal cancer;    Immune-related gene signature;    Tumor microenvironment;    TCGA;    GEO;    Prognosis;   

DOI  :  10.1186/s12885-021-08629-3

来源: Springer

【 摘 要 】

BackgroundThe 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).MethodsTranscriptome 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.ResultsGene 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.ConclusionsIn 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.

【 授权许可】

CC BY