An Immune-Related Signature for Predicting the Prognosis of Lower-Grade Gliomas

Abstract

BackgroundLower-grade gliomas (LGGs) have more favorable outcomes than glioblastomas; however, LGGs often progress to process glioblastomas within a few years. Numerous studies have proven that the tumor microenvironment (TME) is correlated with the prognosis of glioma.MethodsLGG RNA-Sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and the Chinese Glioma Genome Atlas (CGGA) were extracted and then divided into training and testing cohorts, respectively. Immune-related differentially expressed genes (DEGs) were screened to establish a prognostic signature by a multivariate Cox proportional hazards regression model. The immune-related risk score and clinical information, such as age, sex, World Health Organization (WHO) grade, and isocitrate dehydrogenase 1 (IDH1) mutation, were used to independently validate and develop a prognostic nomogram. GO and KEGG pathway analyses to DEGs between immune-related high-risk and low-risk groups were performed.ResultsSixteen immune-related genes were screened for establishing a prognostic signature. The risk score had a negative correlation with prognosis, with an area under the receiver operating characteristic (ROC) curve of 0.941. The risk score, age, grade, and IDH1 mutation were identified as independent prognostic factors in patients with LGGs. The hazard ratios (HRs) of the high-risk score were 5.247 [95% confidence interval (CI) = 3.060–8.996] in the multivariate analysis. A prognostic nomogram of 1-, 3-, and 5-year survival was established and validated internally and externally. Go and KEGG pathway analyses implied that immune-related biological function and pathways were involved in the TME.ConclusionThe immune-related prognostic signature and the prognostic nomogram could accurately predict survival.

Identification and Validation of a Gene Signature for Lower-Grade Gliomas Based on Pyroptosis-Related Genes to Predict Survival and Response to Immune Checkpoint Inhibitors

“…Many studies have focused on the prediction of patient prognosis and efficacies of treatments that include chemotherapy, radiotherapy, and immunotherapy, by establishing immune-related, tumor microenvironment- (TME-) related, and tumor mutation-related gene signatures related to prognosis [ 11 – 13 ]. However, few studies have explored the relationship between pyroptosis-related biomarkers and the prediction of prognosis and efficacy of LGG treatments.…”

A Novel CRISPR/Cas9 Screening Potential Index for Prognostic and Immunological Prediction in Low-Grade Glioma

“…C-index was calculated to evaluate the consistency of real and predicting survival outcomes. To further verify the performance of CCSPI, we compared different risk systems from other studies ( Supplementary Table S2 ) measured by AUCs and C-index ( Zhang et al, 2020 ; Luo et al, 2021 ; Zhao et al, 2021 ; Zhou et al, 2021 ; Wu et al, 2022 ; Zheng et al, 2022 ) in the CGGA validation cohort.…”

APOLLO: An accurate and independently validated prediction model of lower-grade gliomas overall survival and a comparative study of model performance

“… 4 As a crucial milestone, the WHO Classification of Tumors of the Central Nervous System synthesized molecular and histological information to reclassify gliomas, by using well recognized molecular biomarkers. 2 Recent evidence has emerged that gene expressions may pose inducible and reversible effects on LGG prognosis via several channels, including immunity, 5 , 6 stemness, 7 and autophagy. 8 , 9 …”

“… 9 , 14 Therefore, most of these existing models have limited model robustness and transportability to accommodate independent populations. 6 , 15 , 16 …”