Background
Glioma is the most common central nervous system (CNS) cancer with a short survival period and a poor prognosis. The S100 family gene, comprising 25 members, relates to diverse biological processes of human malignancies. Nonetheless, the significance of S100 genes in predicting the prognosis of glioma remains largely unclear. We aimed to build an S100 family-based signature for glioma prognosis.
Conclusions
We constructed and verified a novel S100 family-based signature associated with tumor immune microenvironment (TIME), which may shed novel light on the glioma diagnosis and treatment.
Methods
We downloaded 665 and 313 glioma patients, respectively, from The Cancer Genome Atlas (TCGA) and Chinese Glioma Genome Atlas (CGGA) database with RNAseq data and clinical information. This study established a prognostic signature based on the S100 family genes through multivariate COX and LASSO regression. The Kaplan-Meier curve was plotted to compare overall survival (OS) among groups, whereas Receiver Operating Characteristic (ROC) analysis was performed to evaluate model accuracy. A representative gene S100B was further verified by in vitro experiments.
Results
An S100 family-based signature comprising 5 genes was constructed to predict the glioma that stratified TCGA-derived cases as a low- or high-risk group, whereas the significance of prognosis was verified based on CGGA-derived cases. Kaplan-Meier analysis revealed that the high-risk group was associated with the dismal prognosis. Furthermore, the S100 family-based signature was proved to be closely related to immune microenvironment. In vitro analysis showed S100B gene in the signature promoted glioblastoma (GBM) cell proliferation and migration. Conclusions: We constructed and verified a novel S100 family-based signature associated with tumor immune microenvironment (TIME), which may shed novel light on the glioma diagnosis and treatment.