An Immune Related Gene Signature from Chemokines and Chemokine Receptors to Predict Tumor Prognosis and Immune Microenvironment Alteration in Lower-Grade Glioma (LGG) Based on Large-Scale Transcriptome Profile Analyses

Abstract Chemokines and receptors are well known for their roles in mediating immune cell trafficking and lymphoid development; however, whether they can determine prognosis and immune microenvironment alterations in lower-grade glioma (LGG) remains uncertain. In this study, we acquired transcriptomic data from the Cancer Genome Atlas (TCGA), Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) databases using a series of bioinformatics methods to estimate the prognostic value and potential biological function of candidate genes. We identified a four-gene (CCR4, CX3CL1, CXCL10 and CXCL11) signature to compose a risk score model. Kaplan-Meier curves and ROC curves verified the performance of risk score model in the TCGA, CGGA and GSE16011 datasets. The prognostic signature showed fair accuracy for 1-, 3- and 5-year overall survival (OS). The TIMER, TIP and CIBERSORT algorithms revealed different immune cell infiltration levels between the high- and low-risk score groups. LGG patients with high-risk scores had more malignant phenotypes and higher immune checkpoints expression as well as presented immunotherapeutic resistance. Therefore, we comprehensively analyzed the important role of chemokines and receptors in LGG patients; created a novel immune risk score model that could effectively reflect the prognosis and immune microenvironment alteration and presented a valuable indicator for immunotherapy in LGG patients.