OCTAD

OCTAD matches cancer-specific gene expression signatures to perturbagen-induced expression profiles to prioritize small molecules for precision oncology.

Key Features:

• Virtual Screening: Leverages public cancer patient gene expression data to create disease-specific expression signatures and match them against perturbagen-induced gene expression profiles from drug libraries.
• Expression Signature Generation: Generates cancer-specific differential gene expression signatures from public cancer patient gene expression data.
• Perturbagen Matching: Compares disease signatures to perturbagen-induced profiles to identify compounds predicted to reverse signature gene expression.
• Prioritization: Ranks small molecules based on predicted ability to reverse signature genes for downstream validation.
• Data Integration: Consolidates datasets and metadata into files such as CCLE_OCTAD.RData and metadata.RData for downstream analysis.

Scientific Applications:

• Precision oncology: Prioritizes therapeutic compounds tailored to molecular expression profiles of cancer patient groups.
• Drug candidate prioritization for experimental validation: Identifies and ranks small molecules predicted to reverse disease-associated gene expression for downstream testing.
• In silico reduction of experimental screens: Narrows candidate lists from drug libraries to reduce resources required for high-throughput screening.

Methodology:

Computational steps include generating disease-specific gene expression signatures from public cancer patient data, comparing those signatures to perturbagen-induced expression profiles from drug libraries, and ranking small molecules by predicted reversal of signature gene expression.