Identification of prognosis-related gene features in low-grade glioma based on ssGSEA - He, Yuanzhi; Lin, Zhangping; Tan, Sanyang (Frontiers in Oncology, 2022)
Low-grade glioma (LGG) are commonly seen in clinical practice, and the prognosis is often poor. Therefore, determination of immune-related risk scores and immune-related targets for predicting prognoses in patients with LGG is crucial. A single-sample gene set enrichment analysis (ssGSEA) was performed on 22 immune gene sets to calculate immune-based prognostic scores. The prognostic value of the 22 immune cells for predicting overall survival (OS) was assessed using the least absolute shrinkage and selection operator (LASSO) and univariate and multivariate Cox analyses. Subsequently, we constructed a validated effector T-cell risk score (TCRS) to identify the immune subtypes and inflammatory immune features of LGG patients. We divided an LGG patient into a high-risk-score group and a low-risk-score group based on the optimal cut-off value. Kaplan-Meier survival curve showed that patients in the low-risk-score group had higher OS. Then, we identified the differentially expressed genes (DEGs) between the high-risk-score group and a low-risk-score group, and got 799 up-regulated genes and 348 down-regulated genes. The analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) show that DEGs were mainly concentrated in immune-related processes. In order to further explore the immune-related genes related to prognosis, we constructed a protein-protein interaction (PPI) network using Cytoscape, and then identified the 50 most crucial genes. Subsequently, 9 DEGs were found to be significantly associated with OS based on univariate and multivariate Cox analysis. It was further confirmed that CD2, SPN, IL18, PTPRC, GZMA, and TLR7 were independent prognostic factors for LGG through batch survival analysis and Nomogram prediction model. In addition, we used an RT-qPCR assay to validate the bioinformatics results. The results showed that CD2, SPN, IL18, PTPRC, GZMA, and TLR7 were highly expressed in LGG. Our study can provide reference value for the prediction of prognosis in LGG patients and may help in the clinical development of effective therapeutic agents.