Background: Glioma is the most common malignant primary tumor with a poor prognosis. Infiltration of tumor-associated macrophages (TAMs) is a hallmark of glioma. However, the regulatory mechanism of TAMs and the prognostic value of related signature in glioma remain unclear.

Methods: TAMs were analyzed by EPIC, MCPCOUNTER and XCELL methods in multiple cohorts, including the TCGA merged GBMLGG, CGGA mRNAseq-325, and CGGA mRNAseq-693. Weighted correlation network analysis (WGCNA) were performed to identify candidate hub genes that might be related to TAMs. The prognostic genes were selected by Univariate Cox regression, Kaplan-Meier analysis and the least absolute shrinkage and selection operator (LASSO) multivariate Cox regression algorithm, and were used to construct a high efficacy prediction model.

Results: Compared with LGG, TAMs of GBM in the TCGA merged GBMLGG, CGGA mRNAseq-693, and CGGA mRNAseq-325 cohorts were increased, and high TAMs levels predicted poorer overall survival for gliomas. The prediction model constructed by nine prognostic genes was highly efficient. The TAMs related risk-score was an independent risk factor for glioma. Moreover, high risk score was correlated with an increased population of TAMs in glioma, as well as the high immune scores, stromal scores and ESTIMATE scores.

Conclusions: Increased TAMs might be an immune evasion mechanism of glioma. In addition, our findings suggested that TAMs-related signature was a valuable prognostic biomarker in glioma and provided therapeutic targets for glioma.