Abstract
BACKGROUND: Lower-grade gliomas (LGGs) patients presented seizure-free have a worse survival than those presented with seizures. However, the current knowledge on its potential value in LGGs remains scarce. PURPOSE: This study aimed to identify a novel gene signature associated with seizures-free for predicting poor prognosis for LGGs patients. MATERIALS AND METHODS: The RNA expression and clinical information of LGGs patients were downloaded from the Cancer Genome Atlas database. Differentially expressed genes (DEGs) were screened out between LGGs patients presented seizures-free and seizures. The novel gene signature was constructed by Lasso and multivariate regression analyses for predicting prognosis in LGGs. Its prognostic value was assessed and validated by Kaplan-Meier analyses and receiver operating characteristic (ROC) curves. Multivariate regression analysis was applied to identify the independent prognostic value of the gene signature. Furthermore, bioinformatics analysis was performed to elucidate the molecular mechanisms. RESULTS: A total of 253 DEGs were screened out between LGG patients presented with seizures and free of seizures. A 5-gene signature (HIST1H4F, HORMAD2, LILRA3, PRSS33, and TBX20 genes) was constructed from these 253 DEGs. Kaplan-Meier analyses and ROC curves assessed and validated the good performance of the 5-gene signature in differentiating and predicting prognosis of high- and low-risk patients. Multivariate regression analysis determined the independent prognostic value of the 5-gene signature. According to bioinformatics analysis, DEGs were mainly enriched in biological processes related to positive regulation of transcription from RNA polymerase II promoter, G-protein coupled receptor signaling pathway, and pathways of cytokine-cytokine receptor interaction, chemokine signaling pathway. CONCLUSION: Our findings suggested that the 5-gene signature might serve as a potential prognostic biomarker and provide guidance for the personalized LGGs management.