OSgc

OSgc evaluates prognostic biomarkers in gastric cancer by integrating gene expression profiling and clinical follow-up data to assess associations between gene expression and patient survival.

Key Features:

• Extensive data integration: Integrates gene expression profiling data with clinical follow-up information from 1,824 gastric cancer cases compiled from seven independent public datasets, including Gene Expression Omnibus (GEO) and The Cancer Genome Atlas (TCGA).
• Survival analysis outputs: Generates Kaplan–Meier survival plots and reports hazard ratios (HR) and log-rank p-values for queried genes.
• Multiple survival end points: Supports analysis of overall survival, progression-free survival, progression-free interval, relapse-free survival, and disease-free survival.
• Biomarker scope: Enables assessment of both known and novel prognostic biomarker candidates.

Scientific Applications:

• Prognostic biomarker evaluation: Assess associations between gene expression and patient survival outcomes in gastric cancer cohorts.
• Molecular research: Support investigation of molecular mechanisms linked to prognosis through gene-level survival associations.
• Translational development: Inform development and prioritization of targeted therapies and clinical biomarkers based on prognostic signals.

Methodology:

Integrates gene expression profiling and clinical follow-up from seven public datasets (including GEO and TCGA) covering 1,824 gastric cancer cases and performs Kaplan–Meier survival analyses reporting hazard ratios (HR) and log-rank p-values across five specified survival end points.