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Related Concept Videos

Bioactivation and Tissue Toxicity01:25

Bioactivation and Tissue Toxicity

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Bioactivation is a metabolic process that transforms less reactive substances into highly reactive metabolites, initiating tissue toxicity. This transformation can lead to various toxic effects, including carcinogenesis and teratogenesis. Reactive metabolites are classified into two main types: electrophiles and free radicals.Electrophiles are electron-deficient species and are produced primarily by the enzyme cytochrome P-450 during the metabolism of compounds containing carbon, nitrogen, or...
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Mutagenicity and carcinogenicity refer to the ability of drugs to cause genetic defects and induce cancer, respectively. The International Agency for Research on Cancer (IARC) classifies agents into four groups based on their carcinogenic potential. Group 1 agents are known human carcinogens; group 2A agents are probably carcinogenic to humans; group 3 agents lack data to support their role in carcinogenesis; and group 4 includes agents for which data support that they are not likely to be...
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Glutathione, a tripeptide made up of glutamate, cysteine, and glycine, is a critical player in the detoxification of drugs and xenobiotics via a process known as glutathione conjugation or mercapturic acid formation. This phase II biotransformation reaction involves the covalent binding of glutathione to a drug or its metabolite, enhancing the compound's water solubility and enabling its excretion.
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Toxic Reactions: Overview01:26

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When toxic substances penetrate the human body, they disseminate to various tissues, undergoing metabolic changes. This process yields reactive metabolites that may covalently bind with specific target molecules, resulting in toxicity.
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Related Experiment Video

Updated: Apr 4, 2026

A Web Tool for Generating High Quality Machine-readable Biological Pathways
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ExposoGraph: An Interactive Platform for Carcinogen Bioactivation and Detoxification Pathway Visualization.

Julhash Kazi1, Kenneth Pienta2

  • 1Lund University.

Research Square
|April 3, 2026
PubMed
Summary
This summary is machine-generated.

ExposoGraph is a new interactive platform that links carcinogens to their metabolic pathways and genetic factors. This tool aids in understanding gene-environment interactions for cancer risk assessment.

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

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Area of Science:

  • Bioinformatics and Computational Biology
  • Genomics and Genetic Engineering
  • Toxicology and Environmental Health

Background:

  • Existing resources catalog carcinogens (IARC) and pharmacogenomic variations (PharmVar, CPIC) but lack integration.
  • A unified framework for exposure, metabolism, DNA damage, and genetic annotation is needed for systematic gene-environment interaction evaluation in cancer risk.
  • This gap hinders comprehensive cancer risk assessment.

Purpose of the Study:

  • To develop an interactive knowledge-graph platform, ExposoGraph, for visualizing carcinogen metabolism and DNA damage pathways.
  • To integrate data from multiple sources (IARC, KEGG, PharmVar, CPIC, CTD) into a unified framework.
  • To facilitate the systematic evaluation of gene-environment interactions in cancer.

Main Methods:

  • Development of the CarcinoGenomic Knowledge Graph, ExposoGraph, as an interactive platform.
  • Integration of curated data on carcinogens, enzymes, metabolites, DNA adducts, and pathways.
  • Implementation of interactive features including filtering, search, and detailed views with provenance and pharmacogenomic annotations.

Main Results:

  • The first-generation ExposoGraph contains 96 nodes and 102 edges, representing carcinogen metabolism and DNA damage pathways for 15 index carcinogens across 9 classes.
  • It includes 36 enzymes involved in Phase I, II, and III metabolism, as well as DNA repair.
  • Interactive exploration revealed cross-pathway connectivity, such as androgen metabolism linking to estrogen quinone formation and DNA adducts via CYP19A1.

Conclusions:

  • ExposoGraph provides an integrated, interactive framework connecting carcinogenic exposures to metabolic fates and genetic modulators.
  • The platform supports hypothesis generation for gene-environment interaction studies.
  • It may inform future individualized cancer risk modeling, serving as a research tool.