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

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

Julhash U Kazi1,2,3,4, Kenneth J Pienta5,4

  • 1Division of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, 22363, Sweden.

Biorxiv : the Preprint Server for Biology
|April 3, 2026
PubMed
Summary
This summary is machine-generated.

ExposoGraph integrates carcinogen exposure, metabolism, and genetic data into an interactive knowledge graph. This tool aids in understanding gene-environment interactions for cancer risk assessment.

Keywords:
D3 HTMLcarcinogenesischemical carcinogenesisgene-environment interactioninteractive platformknowledge graphmetabolic activationnetwork visualizationpharmacogenomics

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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.