- CancerPro is a sophisticated bioinformatics platform designed to unravel the pan-cancer prognostic landscape by integrating diverse biomedical data into a unified analytical framework. It leverages ontology and knowledge graph technologies to provide researchers with a user-friendly interface for exploring prognostic genes, drug interactions, and disease pathways across multiple cancer types.
- At its core, CancerPro offers three powerful modules. The first, X-enrich, performs gene set enrichment analysis using Over-Representation Analysis (ORA). This module maps input genes to a wide array of annotations—including Gene Ontology (GO), biological pathways, drug regulations, and disease associations—and applies statistical tests to identify significantly enriched terms. This allows researchers to uncover functional themes and biological processes that are overrepresented in their gene lists, offering insights into the molecular underpinnings of cancer prognosis.
- The second module, Drug Clue, provides a novel perspective on drug analysis. It examines how drugs interact with genes—whether by targeting, upregulating, or downregulating them—and identifies associated pathways, diseases, and phenotypes. This module is particularly valuable for discovering drugs that may modulate unfavorable prognostic genes across cancers, potentially revealing therapeutic candidates or side effect profiles.
- The third module, Gene List Insight (GL Insight), connects genes using high-confidence protein–protein interaction networks and regulatory relationships. It enables the extraction of drugs and biological pathways linked to multiple genes, and supports network analysis using centrality metrics to identify key regulatory nodes. This module has been used to analyze prostate cancer-specific prognostic genes, revealing connections to immune deficiency and alternative splicing abnormalities.
- CancerPro’s backend is powered by a Neo4j graph database, which stores intricate relationships among genes, proteins, drugs, diseases, and phenotypes. This structure allows for flexible graph retrieval and visualization, making it easier to interpret complex biomolecular interactions. The platform has successfully identified 43 genes that are prognostically unfavorable in at least five different cancer types, highlighting its utility in cross-cancer comparisons and biomarker discovery.
- Overall, CancerPro stands out as a versatile and integrative tool for pan-cancer research. Its modular design and rich data sources empower researchers to explore the molecular basis of cancer prognosis, identify therapeutic targets, and generate hypotheses for personalized treatment strategies.
