RESUMO
PURPOSE: Glioma is a common malignant tumor of the central nervous system, which is characterized by a low cure rate, high morbidity, and high recurrence rate. Consequently, it is imperative to explore some indicators for prognostic prediction in glioma. METHODS: We obtained glioma data from The Cancer Genome Atlas (TCGA). Differentially expressed genes (DEGs) were obtained by R software from TCGA data sets. Through Cox regression analysis, risk scores were obtained to assess the weighted gene-expression levels, which could predict the prognosis of patients with glioma. The validity and the prognostic value of this model in glioma were confirmed by the manifestation of receiver-operating characteristic (ROC) curves, area under the curve (AUC), and 5-year overall survival (OS). RESULTS: In total, 920 DEGs of transcriptome genes in glioma were extracted from the TCGA database. We identified a novel seven-gene signature associated with glioma. Among them, AL118505.1 and SMOC1 were positively related to the 5-year OS of patients with glioma, showing a better prognosis for glioma; however, RAB42, SHOX2, IGFBP2, HIST1H3G, and IGF2BP3 were negatively related to 5-year OS, displaying a worse prognosis. In addition, according to risk scores, AL118505.1 was also a protective factor, while others were risk factors. Furthermore, the expression levels of SHOX2, IGFBP2, and IGF2BP3 were significantly positively correlated with glioma grades. Receiver-operating characteristic (ROC) curve assessed the accuracy and sensitivity of the gene signature. Each of the seven genes for patients with the distribution of the risk score was presented in the heat map. CONCLUSION: We identified a novel seven-gene signature in patients with glioma, which could be used as a predictor for the prognosis of patients with glioma in the future.
