International Journal of General Medicine (Feb 2022)
Analysis of Gene Co-Expression Network to Identify the Role of CD8 + T Cell Infiltration-Related Biomarkers in High-Grade Glioma
Abstract
Peng Feng,1,* Yuchen Li,2,* Zhijie Tian,1,* Yuan Qian,1 Xingyu Miao,1 Yuelin Zhang3 1Neurosurgery, Shaanxi Provincial People’s Hospital, Xian, 710068, People’s Republic of China; 2Hengyang Medical School, University of South China, Hengyang, 421001, People’s Republic of China; 3Xi’an Medical University, Xian, 710021, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xingyu Miao; Yuelin Zhang, Email [email protected]; [email protected]: High-grade glioma is a type of heterogeneous lethal brain tumor most common in adults. At present, immune checkpoint inhibitors (ICIs) are being considered for first-line therapeutics for malignant GBM. Nonetheless, molecular markers for malignant GBM are unavailable at present. As a result, it is important to explore molecular markers related to immunity for GBM.Materials and Methods: The present study adopted a deconvolution algorithm for quantifying immunocyte composition and measuring gene expression, and used weighted gene co-expression network analysis (WGCNA) to analyze GBM expression data obtained from Gene Expression Omnibus (GEO), Chinese Glioma Genome Atlas (CGGA), and the Cancer Genome Atlas Glioblastoma Multiforme (TCGA-GBM) databases. Thereafter, key CD8+ T cell infiltration-related genes and modules were identified, and database analysis was conducted to verify the therapeutic and immune features of the selected genes.Results: From this study, CD8+ T cell-related modules were identified. By using consistent clustering analysis, two panels of genes (red and green) with the highest correlation with CD8+ T cells infiltration were used to construct high-, low-expression groups, silent and/or mixed group of T cell infiltrations. In the high and low CD8+ T cell infiltration groups, a total of 535 differential genes were obtained, of which ten genes (RPS5, RPS6, FAU, RPS19, RPS23, RPS15A, RPS29, RPS14, RPS16, RPS27A) were identified through protein–protein interactions and co-expression network analysis. Post Cox regression and Kaplan–Meier (K-M) survival analysis, RPS5, RPS6, and RPS16 were selected as candidate prognostic biomarkers related to CD8+ T cells.Conclusion: The three associated genes RPS5, RPS6, and RPS16 were markedly related to degree of T cell infiltration and immune-related activated. We identified their potential biomarkers and therapeutic targets associated with the extent of CD8+ T cell infiltration in GBM.Keywords: prognosis, mutation, glioblastoma, gene, WGCNA
