pDriver

pDriver identifies personalized cancer drivers by detecting coding genes and microRNAs (miRNAs) that drive tumor progression at the individual patient level.

Key Features:

• Personalized Cancer Driver Discovery: Identifies cancer driver genes at the individual patient level to account for distinct driver profiles across patients with the same cancer type.
• Integration of Coding and miRNA Drivers: Incorporates both coding genes and microRNAs (miRNAs) in its analyses to detect non-coding and coding contributors to cancer.
• Two-Stage Methodology: Constructs a personalized gene network for each patient and then discovers potential cancer drivers from that network.
• Validation and Comparative Performance: Tested across five TCGA cancer datasets with comparative analyses reporting improved identification of both coding and miRNA drivers and many miRNA predictions corroborated by literature.
• Biological Relevance in Case Studies: In breast cancer cases, predicted drivers show significant enrichment in Gene Ontology (GO) processes and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways implicated in breast cancer.

Scientific Applications:

• Personalized oncology research: Provides patient-level coding and miRNA driver profiles to investigate individual cancer driver mechanisms.
• Therapeutic strategy development: Supports identification of patient-specific targets that can inform therapeutic decision making.
• Precision medicine and population studies: Enables exploration of genetic underpinnings of cancer across diverse populations to facilitate precision medicine approaches.

Methodology:

Uses a two-stage computational approach that first constructs a gene network for each patient capturing gene interactions and then identifies potential cancer drivers from these personalized networks; validated across five TCGA cancer datasets.