Pathway-Based Survival Modeling Reveals Prognostic Signatures in Glioblastoma

Key Points

• This research aims to develop a survival modeling framework using pathway activity to predict outcomes in glioblastoma patients.
• Utilized TCGA transcriptomic data to derive gene expression profiles.
• Transformed gene expression data into pathway activity scores for analysis.
• Applied Cox proportional hazards models to identify significant prognostic pathways.
• Patient stratification into high-risk and low-risk groups was achieved, indicating significant differences in overall survival. The model demonstrated effective prognostic capabilities.