AUTHOR=Lin Zhiying , Wang Rongsheng , Huang Cuilan , He Huiwei , Ouyang Chenghong , Li Hainan , Zhong Zhiru , Guo Jinghua , Chen Xiaohong , Yang Chunli , Yang Xiaogang 

TITLE=Identification of an Immune-Related Prognostic Risk Model in Glioblastoma

JOURNAL=Frontiers in Genetics

VOLUME=Volume 13 - 2022

YEAR=2022

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2022.926122

DOI=10.3389/fgene.2022.926122

ISSN=1664-8021

ABSTRACT=Abstract
Background
Glioblastoma (GBM) is the most common and malignant type of brain tumour. A large number of studies have shown that the immunotherapy of tumors is effective, but the immunotherapy effect of GBM is not poor. Thus, further research of the immune-related hub genes of GBM is extremely urgent. 
Methods
The GBM highly correlated gene clusters were screened out by differential expression,  mutation analysis, and Weighted gene co-expression network analysis (WGCNA). least absolute shrinkage and selection operator (LASSO) and proportional hazards model (COX) regressions were implemented to construct prognostic risk models. Survival, the receiver operating characteristic (ROC) curve and compound difference analysis of tumor mutation burden were used to further verify the prognostic risk model. Then we predicted GBM patient responses to immunotherapy by the ESTIMATE algorithm, GSEA , and tumor immune dysfunction and Exclusion (TIDE) algorithm.
Results
A total of 834 immune-related differentially expressed genes (DEGs) were identificated. The five hub genes (STAT3, SEMA4F, GREM2, MDK, and SREBF1) were identified as the prognostic risk model (PRM) screened out by WGCNA and LASSO analysis of DEGs. In addition, the PRM is significant positive correlation with immune cells infiltration of tumour microenvironment (TME), and expression of critical immune checkpoints, indicating that the poor prognosis of patients is due to TIDE.
Conclusions
We constructed the PRM composed of five hub genes, which provided a new strategy for developing tumor immunotherapy.