PrognoScan

PrognoScan performs meta-analysis of cancer microarray datasets annotated with clinical data to evaluate associations between gene expression and patient survival outcomes.

Key Features:

• Extensive Database: Houses a large collection of publicly available cancer microarray datasets annotated with clinical data.
• Analytical tool for biological relationships: Implements a minimum P-value approach to identify optimal cutpoints in continuous gene expression measurements for stratifying patients in survival analysis without prior biological assumptions.
• Meta-analysis capability: Supports systematic meta-analysis across multiple microarray datasets to consolidate prognostic associations and increase statistical power.

Scientific Applications:

• Prognostic biomarker evaluation: Associates gene expression with patient survival outcomes to assess potential tumor markers.
• Therapeutic target identification: Identifies genes whose expression correlates with prognosis as candidate therapeutic targets.
• Cross-study validation: Consolidates findings across datasets to validate consistent prognostic gene expression patterns.

Methodology:

Integration of publicly available cancer microarray datasets with clinical annotations; application of a minimum P-value approach to determine optimal expression cutpoints for patient grouping in survival analysis; and systematic meta-analysis across multiple datasets.