ExposoGraph: An Interactive Platform for Carcinogen Bioactivation and Detoxification Pathway Visualization

Area of Science:

• Bioinformatics
• Genomics
• Toxicology

Background:

• Limited platforms integrate carcinogenic exposures, metabolic activation/detoxification, DNA damage, and genetic annotations.
• This gap hinders systematic evaluation of gene-environment interactions in cancer risk assessment.

Purpose of the Study:

• To develop ExposoGraph, an interactive knowledge-graph platform for carcinogen metabolism and DNA damage pathways.
• To unify data from IARC, KEGG, PharmVar, CPIC, and CTD for a comprehensive view of gene-environment interactions.

Main Methods:

• Developed a knowledge graph with 96 nodes (Carcinogens, Enzymes, Metabolites, DNA Adducts, Pathways) and 102 edges (activates, detoxifies, transports, forms adduct, repairs).
• Integrated curated data and annotations from multiple reputable resources.
• Implemented interactive exploration features including filtering and detailed views with provenance.

Main Results:

• The graph captures metabolic activation/detoxification for 9 carcinogen classes and 15 index carcinogens.
• Represents 36 enzymes involved in Phase I, II, III metabolism, and DNA repair.
• Demonstrated cross-pathway connectivity, linking androgen metabolism to estrogen quinone formation and DNA adducts via CYP19A1.

Conclusions:

• ExposoGraph offers an integrated, interactive framework linking exposures to metabolic fates and genetic factors.
• Supports hypothesis generation for gene-environment interaction studies and potential individualized risk modeling.
• Currently a research framework, not a clinically validated risk-assessment tool.