Gliomas represent the most common and aggressive brain malignancy. Interferon-gamma (IFNG) is a potent inducer of immune response, developing IFNG-related gene signature may promote the diagnosis and treatment of this disease.
Bulk tumor and single-cell mRNA-seq datasets of glioma ranging from WHO grade II to IV with corresponding demographics were included. Multiple bioinformatics and machine learning algorithms were performed to develop an IFNG-related prognostic signature and evaluate immune checkpoint blockade (ICB) therapy response.
IFNGR1 and IFNGR2 were used as concise IFNG-related gene signature based on which the IFNGR score well-characterized the IFNG response in the glioma microenvironment. Increased IFNGR score was associated with clinicopathological parameters relating to tumor malignancy and prevailing molecular pathological markers. Notably, K-M and Cox regression analysis found that the IFNGR score was an effective prognostic biomarker, and was associated with tumor relapse for a subset of patients. Notably, IFNGR1 and IFNGR2 were preferentially expressed by the Mono/Macro cells in the glioma microenvironment and were significantly correlated with M2 macrophage. Thus, the IFNGR score-high group had increased expression of immune checkpoints and had the potential to predict ICB responsiveness.
In conclusion, we have developed a concise IFNG-related gene signature of clinical significance, which may improve the current diagnosis and treatment of glioma.