NGSEA: Network-Based Gene Set Enrichment Analysis for Interpreting Gene Expression Phenotypes with Functional Gene...

Area of Science:

• Bioinformatics
• Systems Biology
• Computational Biology

Background:

• Gene set enrichment analysis (GSEA) is widely used to interpret gene expression data by identifying enriched biological pathways.
• However, GSEA may be limited as differentially expressed genes (DEGs) might not be the direct cause of observed phenotypes.

Purpose of the Study:

• To develop and evaluate a novel network-based GSEA (NGSEA) method that incorporates gene network information.
• To assess NGSEA's performance in pathway enrichment analysis and anti-cancer drug discovery compared to existing methods.

Main Methods:

• NGSEA calculates enrichment scores based on the expression differences of genes and their network neighbors.
• Performance was evaluated by comparing NGSEA with GSEA for pathway identification and with Connectivity Map for drug retrieval using gene expression data.

Main Results:

• NGSEA demonstrated superior performance over GSEA in identifying relevant pathway gene sets from gene expression data.
• NGSEA significantly improved the retrieval of known anti-cancer drugs from patient-derived expression data.
• The study successfully repurposed FDA-approved drugs, validating budesonide for colorectal cancer treatment.

Conclusions:

• NGSEA offers a more robust approach for pathway interpretation of gene expression phenotypes.
• NGSEA facilitates enhanced anti-cancer drug repositioning and discovery.
• The NGSEA tool is publicly available for research use.