Background:
Glioma is the most common
primary brain tumor with a dismal prognosis. It is urgent to develop novel molecular
biomarkers and conform to individualized schemes. Methods: Differentially expressed pseudogenes between low grade
glioma (LGG) and
glioblastoma multiforme (GBM) were identified in the training cohort. Least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox proportional hazards regression analyses were used to select pseudogenes associated with prognosis of
glioma. A risk signature was constructed based on the selected pseudogenes for predicting the survival of
glioma patients. A pseudogene-
miRNA-
mRNA regulatory network was established and visualized using Cytoscape 3.5.1. Gene Oncology (GO) and signaling pathway analyses were performed on the targeted genes to investigate functional roles of the risk signature. Results: Five pseudogenes (ANXA2P2, EEF1A1P9, FER1L4, HILS1, and RAET1K) correlating with
glioma survival were selected and used to establish a risk signature. Time-dependent receiver operating characteristic (ROC) curves revealed that the risk signature could accurately predict the 1, 3, and 5-year survival of
glioma patients. GO and signaling pathway analyses showed that the risk signature was involved in regulation of proliferation, migration, angiogenesis, and apoptosis in
glioma. Conclusions: In this study, a risk signature with five pseudogenes was constructed and shown to accurately predict 1-, 3-, and 5-year survival for
glioma patient. The risk signature may serve as a potential target against
glioma.