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Abstract A028: Exploring exposure to and metabolism of polycyclic aromatic hydrocarbons (PAHs) in patients with cancer predisposition syndromes (CPS): research in progress

2025· article· en· W7113898421 on OpenAlexaboutno aff

Bibliographic record

VenueClinical Cancer Research · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsnot available
Fundersnot available
KeywordsCarcinogenCancerPopulationUrineAryl hydrocarbon receptorGenetic predispositionPolycyclic aromatic hydrocarbon

Abstract

fetched live from OpenAlex

Abstract Background: Cancer predisposition syndromes (CPS) like Li-Fraumeni syndrome increase lifetime cancer risk up to 100% and leave patients susceptible to DNA damage from environmental carcinogens. Polycyclic aromatic hydrocarbons (PAHs) are carcinogens and global health hazards. Populations are exposed by inhaling airborne PAHs and ingesting grilled, smoked, barbecued, and fried foods. PAHs become carcinogenic when they are metabolized. These metabolites form DNA adducts and cause mutations in the P53 oncogene, which accelerates tumor development. This mechanism is highly relevant to patients with Li-Fraumeni syndrome that have altered P53 function. While activation of the aryl hydrocarbon receptor generally initiates the formation of PAH metabolites, new in vitro studies report that the metabolism of PAHs and the formation of subsequent PAH-DNA adducts is affected by a P53-related pathway. This may alter the metabolism of PAHs and risk for PAH-associated cancers in patients with Li-Fraumeni syndrome. Aim: We aim to assess the impact of PAH exposure on PAH metabolites in urine among CPS patients with and without Li-Fraumeni syndrome. Methods: We are implementing a pilot study that will recruit a sample of patients (n=20) from a CPS clinic at Huntsman Cancer Institute (HCI) in Utah, which has the nation’s largest nonsmoking population and among the highest releases of air toxics including carcinogenic PAHs. Over a 48 hour period, participants will wear passive samplers to measure airborne PAHs and report their diet. At the end of the observational period, participants will provide a urine sample and complete a survey that includes items about demographics and other lifestyle questions. We will describe exposure to PAHs according to demographics and compare correlations between exposure to PAHs and levels of excreted PAH metabolites between patients with and without Li-Fraumeni syndrome. Anticipated results: We anticipate that correlation coefficients between each unit of airborne PAH exposure or frequency of consumption of grilled, smoked, barbecued, and fried foods and the outcome of PAH urinary metabolites will be lower among Li-Fraumeni patients than non-Li-Fraumeni patients. Citation Format: Judy Ou, Nancy Daher, Jennie Vagher, Casey Mehrhoff, Luke Maese. Exploring exposure to and metabolism of polycyclic aromatic hydrocarbons (PAHs) in patients with cancer predisposition syndromes (CPS): research in progress [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: The Rise in Early-Onset Cancers—Knowledge Gaps and Research Opportunities; 2025 Dec 10-13; Montreal, QC, Canada. Philadelphia (PA): AACR; Clin Cancer Res 2025;31(23_Suppl):Abstract nr A028.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.130
GPT teacher head0.443
Teacher spread0.313 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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