Integrative analysis with expanded DNA methylation data reveals common key regulators and pathways in cancers

Area of Science:

• Genomics
• Cancer Biology
• Epigenetics

Background:

• Genomic and DNA methylation data integration is crucial for understanding cancer mechanisms and identifying therapeutic targets.
• The Cancer Genome Atlas (TCGA) consortium's Illumina 450K array data covers only ~1.5% of human genome CpGs, limiting comprehensive methylome analysis.
• Expanding DNA methylome coverage is essential to fully leverage existing TCGA data.

Purpose of the Study:

• To introduce EAGLING, a novel computational model for expanding Illumina 450K array DNA methylation data.
• To increase DNA methylation coverage to approximately 30% of human genome CpGs.
• To identify novel cancer biomarkers and therapeutic targets through integrative analysis of expanded methylation, gene expression, and somatic mutation data.

Main Methods:

• Development and application of the EAGLING model to expand Illumina 450K array data 18-fold.
• Analysis of 13 cancer types from TCGA using integrated expanded methylation, gene expression, and somatic mutation data.
• Identification of triple-evidenced genes and pathway enrichment analysis.

Main Results:

• EAGLING successfully expanded DNA methylation data coverage to ~30% of CpGs.
• Identified numerous triple-evidenced genes across 13 TCGA cancers, many serving as potential biomarkers.
• Discovered enriched pathways, including axonal guidance and inflammation-related pathways.
• Specific genes (e.g., TNXB, RRM2, CELSR3) demonstrated strong predictive power for tumor diagnosis and prognosis.

Conclusions:

• Integrative analysis with expanded DNA methylation data is a powerful approach for identifying critical cancer genes and pathways.
• EAGLING significantly enhances the utility of TCGA methylation data for biomarker and therapeutic target discovery.
• The identified triple-evidenced genes and pathways offer promising avenues for novel cancer diagnostics and therapeutics.