OSgbm

OSgbm performs consensus survival analysis of glioblastoma transcriptomic and clinical data to evaluate and validate prognostic biomarkers.

Key Features:

• Comprehensive data integration: Integrates 684 samples of transcriptome profiles and clinical information from The Cancer Genome Atlas (TCGA), Gene Expression Omnibus (GEO), and the Chinese Glioma Genome Atlas (CGGA).
• Prognostic biomarker evaluation: Assesses candidate genes for prognostic value in glioblastoma using survival analysis.
• Graphical results: Presents Kaplan-Meier plots with hazard ratios (HR) and log-rank p-values for visualizing survival associations.
• Validation of reported biomarkers: Confirms prognostic value of 51 previously reported survival-associated biomarkers, including PROM1 (HR = 2.4120, p = 0.0071) and CXCR4 (HR < 0.001).

Scientific Applications:

• Biomarker discovery and validation: Identification and validation of prognostic genes in glioblastoma cohorts.
• Translational research: Supports development of prognostic signatures relevant to personalized medicine in GBM.
• Exploratory and hypothesis-driven studies: Enables survival-based exploration and testing of gene–outcome associations using integrated datasets.

Methodology:

Applies survival analysis to integrated transcriptomic and clinical data using Kaplan-Meier plots, hazard ratio calculation, and log-rank tests.