AUTHOR=Wang Shuowen , Wang Zijun , Liu Zhuo , Wu Jianxin 

TITLE=Prognostic value of four immune-related genes in lower-grade gliomas: a biomarker discovery study

JOURNAL=Frontiers in Genetics

VOLUME=Volume 15 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2024.1403587

DOI=10.3389/fgene.2024.1403587

ISSN=1664-8021

ABSTRACT=The tumor microenvironment and IRGs are highly correlated with tumor occurrence, progression, and prognosis. However, their roles in grade II and III gliomas, termed  LGGs in this study, remain to be fully elucidated. Our research aims to develop immune-related features for risk stratification and prognosis prediction in LGG. Here, we found that the ESTIMATE score, immune score and stromal score of high-immunity, high-grade and isocitrate dehydrogenase (IDH) wild-type glioma were higher than those of the corresponding group, and the tumor purity was lower. Higher ESTIMATE scores, stromal scores and immune scores indicated a poor prognosis in patients with LGG. We found that the patient's immune states were associated with overall survival, and we established a risk model to predict the prognosis of LGG. A total of 412 differentially expressed immune-related genes (DEIRGs) were obtained by differential analysis using LGG samples in the TCGA database and normal samples in the GTEx database. Through univariate Cox, LASSO, and multivariate Cox regression analyses, We ultimately identified four optimal prognostic DEIRGs (KLRC3, MR1, PDIA2 and RFXAP) and established a predictive model. Compared to other molecular features, our predictive model demonstrates superior accuracy. Furthermore, the prognostic value of the model was shown to be good and was verified by testing using both the Chinese Glioma Genome Atlas (CGGA) as a testing set and the entire set of TCGA and CGGA. In addition, we built a nomogram with the prognostic model and clinical variables, and it showed a better prognostic value. The current results show that the risk model of the four identified prognostic DEIRGs (PDEIRGs) is a valuable prognostic model in LGG patients. The predictive four-gene signature and the nomogram established in this study can assist personalized treatment for patients with LGG.