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Record W2317425283 · doi:10.1158/1538-7445.am2013-4795

Abstract 4795: N-hydroxylation of 4-aminobiphenyl (ABP) and associated oxidative stress may influence ABP carcinogenicity in the mouse liver.

2013· article· en· W2317425283 on OpenAlexaff
Shuang Wang, Kim S. Sugamori, Denis M. Grant

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEicosanoids and Hypertension Pharmacology
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsOxidative stressCarcinogenesisCarcinogenLiver cancerInternal medicineCancerEndocrinologyDNA damageLiver cellBiologyCancer researchMedicineBiochemistryDNA

Abstract

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Abstract Liver cancer is the 3rd most common cause of death from cancer worldwide due to poor prognosis and lack of treatment options. A prominent sex difference is observed in human liver cancer such that men have a 3 to 5 fold higher incidence than women even after accounting for known etiological factors. In a tumor study carried out previously in our laboratory, two doses of the human carcinogen 4-aminobiphenyl (ABP) given to mice on postnatal days 8 and 15 resulted in the formation of liver tumors at 1 year. Moreover, female mice were dramatically protected from liver tumors compared to males, which parallels the sex difference found in human liver cancer. Our goal is to elucidate the molecular mechanisms behind the sex differences in ABP carcinogenesis in mouse liver with the hope of extrapolating to the human condition. Oxidative stress may play an important role in human liver carcinogenesis since all major etiological factors for human liver cancer, including viral hepatitis, alcohol, obesity and chemical carcinogens have been shown to be associated with oxidative stress. To determine whether oxidative stress is involved in ABP-mediated carcinogenesis in the mouse, we first assessed the ability of ABP to generate oxidative stress in the mouse Hepa1c1c7 hepatoma cell line. ABP did not produce reactive oxygen species (ROS) or oxidative DNA damage in Hepa1c1c7 cells. However, N-hydroxy-ABP (HOABP), an in vivo metabolite of ABP, was a potent inducer of both ROS and oxidative DNA damage. Furthermore, HOABP-induced oxidative stress was dose-dependent and could be blocked by co-treatment with the antioxidant N-acetylcysteine. These results suggest that HOABP may be a potential source of oxidative stress in mouse liver. We subsequently characterized the kinetics of ABP N-hydroxylation by mouse liver microsomes, and found that more than one cytochrome P450 (CYP) appears to be involved in the reaction. As predicted by the traditional model of ABP bioactivation, the high affinity ABP N-hydroxylation reaction is mediated by CYP1A2, while at least one additional low affinity site belonging to an as yet unidentified CYP is responsible for significant ABP N-hydroxylation at higher concentrations of ABP that would be expected following the doses of ABP used in our tumor study. However, no sex difference was found in either high or low affinity ABP N-hydroxylation activities between liver microsomes from male and female postnatal (day 15) or adult mice. Future studies will focus on quantifying both acute and chronic changes in oxidative stress and antioxidant levels in the mouse liver following carcinogenic doses of ABP, and correlating such changes to tumor formation. Citation Format: Shuang Wang, Kim S. Sugamori, Denis M. Grant. N-hydroxylation of 4-aminobiphenyl (ABP) and associated oxidative stress may influence ABP carcinogenicity in the mouse liver. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 4795. doi:10.1158/1538-7445.AM2013-4795

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.047
GPT teacher head0.363
Teacher spread0.316 · 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 designBench or experimental
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
Published2013
Admission routes1
Has abstractyes

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