Open AccessDevelopment and Validation of an IDH1-Associated Immune Prognostic Signature for Diffuse Lower-Grade Glioma
Author(s) -
Xiaoyun Deng,
Dongdong Lin,
Bo Chen,
Xiaojia Zhang,
Xingxing Xu,
Zhisheng Yang,
Xuchao Shen,
Liang Yang,
Xiaoyong Lu,
Song Huang,
Bo Yin,
Nu Zhang,
Jian Lin
Publication year - 2019
Publication title -
frontiers in oncology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.834
H-Index - 83
ISSN - 2234-943X
DOI - 10.3389/fonc.2019.01310
Subject(s) - immune system , idh1 , isocitrate dehydrogenase , nomogram , proportional hazards model , glioma , oncology , immunotherapy , tumor microenvironment , medicine , biology , mutation , cancer research , gene , immunology , genetics , biochemistry , enzyme
A mutation in the isocitrate dehydrogenase 1 (IDH1) gene is the most common mutation in diffuse lower-grade gliomas (LGGs), and it is significantly related to the prognosis of LGGs. We aimed to explore the influence of the IDH1 mutation on the immune microenvironment and develop an IDH1-associated immune prognostic signature (IPS) for predicting prognosis in LGGs. IDH1 mutation status and RNA expression were investigated in two different public cohorts. To develop an IPS, LASSO Cox analysis was conducted for immune-related genes that were differentially expressed between IDH1 wt and IDH1 mut LGG patients. Then, we systematically analyzed the influence of the IPS on the immune microenvironment. A total of 41 immune prognostic genes were identified based on the IDH1 mutation status. A four-gene IPS was established and LGG patients were effectively stratified into low- and high-risk groups in both the training and validation sets. Stratification analysis and multivariate Cox analysis revealed that the IPS was an independent prognostic factor. We also found that high-risk LGG patients had higher levels of infiltrating B cells, CD4+ T cells, CD8+ T cells, neutrophils, macrophages and dendritic cells, and expressed higher levels of CTLA-4, PD-1 and TIM-3. Moreover, a novel nomogram model was established to estimate the overall survival in LGG patients. The current study provides novel insights into the LGG immune microenvironment and potential immunotherapies. The proposed IPS is a clinically promising biomarker that can be used to classify LGG patients into subgroups with distinct outcomes and immunophenotypes, with the potential to facilitate individualized management and improve prognosis.