Abstract
Immune-related gene pairs (IRGPs) have been associated with prognosis in various cancer types, but few studies have examined their prognostic capabilities in glioma patients. Here, we gathered the gene expression and clinical profile data of primary lower-grade glioma (LGG) patients from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA, containing CGGAseq1 and CGGAseq2), the Gene Expression Omnibus (GEO: GSE16011), and Rembrandt datasets. In the TCGA dataset, univariate Cox regression was performed to detect overall survival (OS)-related IRGs, Lasso regression, and multivariate Cox regression were used to screen robust prognosis-related IRGs, and 19 IRGs were selected for the construction of an IRGP prognostic signature. All patients were allotted to high- and low-risk subgroups based on the TCGA dataset median value risk score. Validation analysis indicated that the IRGP signature returned a stable prognostic value among all datasets. Univariate and multivariate Cox regression analyses indicated that the IRG -signature could efficiently predict the prognosis of primary LGG patients. The IRGP-signature-based nomogram model was built, revealing the reliable ability of the IRGP signature to predict clinical prognosis. The single-sample gene set enrichment analysis (ssGSEA) suggested that high-risk samples contained higher numbers of immune cells but featured lower tumor purity than low-risk samples. Finally, we verified the prognostic ability of the IRGP signature using experiments performed in LGG cells. These results indicated that the IRGP signature could be regarded as a stable prognostic assessment predictor for identifying high-risk primary LGG patients.
Highlights
Gliomas are characterized by high recurrence rates and high mortality and are the most common primary intracranial tumors that occur in the adult central nervous system (1)
In order to build the relationship between overall survival (OS) outcomes and Immune-related gene pairs (IRGPs), univariate Cox regression analysis was performed and recognized 101 IRGPs that were noticeably correlated with patient prognosis
Using the determined cut-off value as the threshold, patients were divided into low- and high-risk subgroups in the The Cancer Genome Atlas (TCGA) dataset, and the Kaplan-Meier survival curves showed that primary lowergrade glioma (LGG) patients with lower risk scores had better clinical outcomes
Summary
Gliomas are characterized by high recurrence rates and high mortality and are the most common primary intracranial tumors that occur in the adult central nervous system (1). Despite advances in diagnostic and therapeutic modalities for primary LGGs, patient prognosis has not improved (5). Some elements of the immune system, such as the tumor microenvironment (TME), immune-related genes (IRGs) and immune cells have been found to play key roles in the formation and progression of tumors (6–8). The TME is highly associated with tumorigenesis, development, and prognosis, and immune cells play critical roles on tumor formation and progression (6, 9, 10). IRGs have been regarded as biomarkers to predict prognosis of cancer patients (12). A recent study constructed a stable IRG signature that was found to serve as an effective and predictive prognostic model among primary LGG patients (13)
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
