A Radiosensitivity Gene Signature and XPO1 Predict Clinical Outcomes for Glioma Patients - Wu, Shan; Qiao, Qiao; Li, Guang (Frontiers in Oncology, 2020)
Objective: Glioma is the most common and fatal primary brain tumor with high risk of recurrence in adults. Identification of predictive biomarkers is of great necessity for the optimization of therapeutic strategies. The present study investigated the predictive efficacy of a previously identified radiosensitivity signature and the Exportin 1 (XPO1) expression. Methods: Among 1552 patients suffering from glioma in Chinese Glioma Genome Atlas dataset and The Cancer Genome Atlas dataset, radiosensitive group and radioresistant group were identified according to radiosensitivity signature, and patients were also stratified into XPO1-high and XPO1-low groups according to XPO1 mRNA expression levels. The overall survival rates were compared across patient groups. Differential gene expression was detected and analyzed through pathway enrichment and Gene Set Enrichment Analysis. To predict the 1, 3 and 5-year survival rates of glioma patients, a nomogram was established combining radiosensitivity gene signature, XPO1 status and clinical characters. Results: The proposed classification based on radiosensitivity gene signature and XPO1 expression provides an independent prognostic factor in glioma. The RR-XPO1-high group shows the poorest prognosis and may benefit most from radiotherapy-combined anti-XPO1 treatment. The nomogram based on radiosensitivity gene signature, XPO1 expression and clinical characters performs better than WHO classification and IDH status in predicting survival rates of glioma patients. The cell cycle pathway, p53 signaling pathway and focal adhesion pathway are essential pathways associated with more invasive glioma. Conclusion: To combine radiosensitivity signature and XPO1 expression is a favorable approach to predict outcomes and to determine optimal therapeutic strategies for glioma patients.