OSlgg

OSlgg performs consensus survival analysis of gene expression in low-grade glioma (LGG) to evaluate and prioritize prognostic biomarkers using long-term follow-up data.

Key Features:

• Data integration: Integrates gene expression profiling with long-term follow-up data from 720 LGG cases across two independent cohorts.
• Survival analysis metrics: Uses Kaplan-Meier plots alongside hazard ratios and p-values to assess prognostic significance.
• Consensus analysis: Implements a consensus survival analysis approach specifically for LGG cohorts.
• Biomarker validation: Reliability was assessed by analysis of 86 previously published prognostic biomarkers for LGG.
• Biomarker discovery: Identified CD302 and FABP5 as novel candidate prognostic biomarkers associated with unfavorable survival when highly expressed.

Scientific Applications:

• Patient risk stratification: Stratifies LGG patients into risk subgroups based on gene expression–survival associations.
• Prognostic biomarker validation: Validates reported LGG prognostic biomarkers using integrated cohorts and survival metrics.
• Biomarker discovery and prioritization: Identifies and prioritizes candidate prognostic genes such as CD302 and FABP5 for further study.

Methodology:

Integrates gene expression profiling with long-term follow-up data from 720 LGG cases across two independent cohorts and performs consensus survival analysis using Kaplan-Meier plots, hazard ratios, and p-values, with validation against 86 previously published prognostic biomarkers and identification of CD302 and FABP5 as candidates.