Prognostic Impact of a Lymphocyte Activation-Associated Gene Signature in GBM based on Transcriptome Analysis

Abstract Background Glioblastoma multiforme (GBM) is the most aggressive primary central nervous system malignant tumor that has poor prognosis. Lymphocyte activation played important roles in cancer and therapy. Objective To identify an efficient lymphocyte activation-associated gene signature that could predict the progression and prognosis of GBM. Methods We used univariate Cox proportional hazards regression and stepwise regression algorithm to develop a lymphocyte activation-associated gene signature in the training data set (TCGA, n = 525). Then, the signature was validated in two data sets, including GSE16011 (n = 150) and GSE13041 (n = 191) by the Kaplan Meier method. Univariate and multivariate Cox proportional hazards regression models were used to adjust for clinicopathological factors. Results In the training data set, we identified a lymphocyte activation-associated gene signature (TCF3, IGFBP2, TYRO3 and NOD2), which classified the patients into high-risk and low-risk groups with significant differences in overall survival (median survival 15.33 months vs 12.57 months, HR = 1.55, 95% CI = 1.28-1.87, logrank test P < 0.001). In the other two data sets, this signature showed similar prognostic values. Further, univariate and multivariate Cox proportional hazards regression models analysis indicated that the signature was an independent prognostic factor for GBM patients.Moreover, we found that there were differences in lymphocyte activity between the high- and low-risk groups of GBM patients among all data sets. Furthermore, by longitudinal analysis, the lymphocyte activationassociated gene signature could significantly predict the survival of patients with some features, such as IDH-wildtype patients and patients with radiotherapy. In addition, the signature could improve prognostic power of age. Conclusions In summary, our results suggested that the lymphocyte activation-associated gene signature is a promising factor for the survival of patients, which may be helpful for diagnosis, prognosis, and treatment of GBM patients.