Evidence map›Paper›PMID 42138795›Full record

ArticleMedical oncology (Northwood, London, England)2026

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

Julhash U Kazi, Kenneth J Pienta

Abstract read
In one paragraph

Article in Medical oncology (Northwood, London, England), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

2 authors.

Julhash U KaziDivision of Translational Cancer Research, Department of Laboratory Medicine, Lund University, Lund, 22363, Sweden. kazi.uddin@med.lu.se.ORCID http://orcid.org/0000-0002-0719-5336
Kenneth J PientaThe Cancer Ecology Center, Brady Urological Institute, Johns Hopkins School of Medicine, Baltimore, MD, 21287, USA. kpienta1@jhmi.edu.ORCID http://orcid.org/0000-0002-4138-2186

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite extensive cataloging of carcinogenic exposures by the International Agency for Research on Cancer (IARC) and pharmacogenomic variation by resources such as PharmVar and CPIC, few platforms unify exposure, metabolic activation and detoxification, DNA damage, and genetic annotation within a single interactive visualization framework. This gap limits systematic evaluation of gene-environment interactions in cancer risk assessment. We developed the Carcino-Genomic Knowledge Graph, ExposoGraph, an interactive knowledge-graph platform for carcinogen metabolism and DNA damage pathways. The reference graph integrates curated data and annotations from IARC, KEGG, PharmVar, CPIC, CTD, and supporting literature/resources. The current reference graph contains 98 nodes across 5 entity types (Carcinogens, Enzymes, Metabolites, DNA Adducts, and Pathways) and 118 edges across 6 relationship types (activates, detoxifies, transports, forms adduct, repairs, and pathway). The first-generation reference graph captures metabolic activation and detoxification pathways for 9 carcinogen classes spanning 15 index carcinogens. It represents 38 enzymes across Phase I activation (n = 14), Phase II conjugation and detoxification (n = 14), Phase III transport (n = 3), and DNA repair (n = 7). Interactive exploration supports carcinogen-class filtering, node- and edge-type filtering, metadata-based search, and detailed hover/detail views with provenance and pharmacogenomic annotations. The androgen branch highlights cross-pathway connectivity by linking androgen metabolism to estrogen quinone formation and DNA adduct generation through CYP19A1-mediated aromatization and downstream catechol estrogen chemistry. In the optional androgen-focused extension, additional receptor, tissue, and variant context further connects this branch to androgen receptor signaling and genotype-specific annotations. ExposoGraph provides a first-generation integrated, interactive framework linking carcinogenic exposures to metabolic fates and genetic modulators. The platform supports hypothesis generation for gene-environment interaction studies and may inform future individualized risk modeling, while remaining a research-use framework rather than a clinically validated risk-assessment tool.

Indexed as

CarcinogensNeoplasmsActivation, MetabolicDNA DamageGene-Environment InteractionHumansInactivation, MetabolicMetabolic Networks and PathwaysCarcinogensCarcinogenesisChemical carcinogenesisD3 HTMLGene-environment interactionInteractive platformKnowledge graphMetabolic activationNetwork visualizationPharmacogenomics

Identifiers

PMID42138795
PMCPMC13179218

What Socratic holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the Socratic graph.