The predictive value of a prognostic risk model constructed for three aging-associated genes in glioma
Background:
Gliomas are malignant brain tumors with poor prognosis, and aging is believed to play a role in their malignant transformation. However, the relationship between aging and glioma prognosis remains unclear.
Objective:
This study aims to construct and validate a prognostic risk model based on aging-related differential expression genes (ARDEGs) to understand their role in glioma prognosis and tumorigenesis, with a particular focus on immune responses.
Methods:
ARDEGs were identified between LGG and HGG through LASSO regression and Cox regression. A prognostic risk model was developed and validated. GSEA and KEGG pathway analyses were performed to explore tumorigenic mechanisms in high- and low-risk groups. The correlation between the model genes and immune cell infiltration, as well as immune checkpoint molecules, was also analyzed. The protein expression of NOG was evaluated in glioma cells using WB and IHC.
Results:
Three aging-related genes-IGFBP2, AGTR1, and NOG-were identified, and a prognostic model was established. KEGG and GSEA analysis revealed that the high-risk group enriched pathways related to inflammation and immune responses, while the low-risk group showed enrichment in oxidative phosphorylation and metabolism pathways. IGFBP2 and AGTR1 expression correlated positively with immunosuppressive cells and immune checkpoint molecules, whereas NOG showed an opposite trend. NOG protein expression was reduced in glioma cells and lower in high-grade gliomas compared to low-grade gliomas.
Conclusions:
The prognostic risk model based on aging-related genes shows strong predictive power for glioma prognosis, highlighting the potential role of immune-related pathways and NOG in tumor progression.
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