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Record W2885171554 · doi:10.1158/1538-7445.am2018-4327

Abstract 4327: The epigenetic effects of benzo[<i>a</i>]pyrene exposure

2018· article· en· W2885171554 on OpenAlexaff
Francesca Galea, Paul A. White, Volker M. Arlt, Paolo Vineis, James M. Flanagan

Bibliographic record

VenueCancer Research · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicHealth, Environment, Cognitive Aging
Canadian institutionsHealth Canada
Fundersnot available
KeywordsDNA methylationEpigeneticsMethylationMolecular biologyBiologyDifferentially methylated regionsCpG siteBisulfite sequencingBenzo(a)pyreneCarcinogenGeneticsDNAGeneGene expression

Abstract

fetched live from OpenAlex

Abstract Polycyclic aromatic hydrocarbons (PAHs) are ubiquitous environmental carcinogens formed from the incomplete combustion of organic materials. Exposure to PAHs can be linked to at least 9 different cancer types, including lung and breast cancer. PAH are genotoxic and can form DNA adducts which can either be repaired or lead to mutations. DNA repair can lead to aberrant DNA methylation, however, few studies have investigated the link between PAH exposure and DNA methylation modifications. Here, we have used a mouse model to investigate the epigenetic consequences of PAH exposure. Mice (n=3/group) were treated by oral gavage with 0, 25, 50 and 75 mg/kg bodyweight/day of benzo[a]pyrene (BaP) for 28 days. Lung DNA from these mice was used to prepare Reduced Representation Bisulphite Sequencing (RRBS) libraries which were then sequenced using Illumina HiSeq2500to an average depth of 25x. For each mouse, DNA methylation was averaged over 500 bp tiled windows and differentially methylated regions (DMRs) were identified by comparing the controls (untreated) with all BaP-exposed mice (treated) irrespective of dose. In the treated vs untreated we identified 1815 windows (>25% methylation difference, p<0.05). Of these, we found that DMRs were under-represented in 5' untranslated regions (UTR), promoter, long interspersed nuclear elements (LINEs) regions and CpG islands compared with the genomic distribution of windows. DMRs were found to occur significantly more frequently in transcription termination regions. In addition, we found significantly more hypomethylation events in exon, intergenic, intronic and promoter regions, long terminal repeats (LTR) and short interspersed nuclear elements (SINE) and more hypermethylation in LINEs. Pyrosequencing validation on a selection of these DMRs is ongoing, using DNA from the same mice used in RRBS, plus mice exposed to BaP and other PAHs in lung and other tissues. In summary, these results show that PAHs have an effect on DNA methylation, and that these changes happen mostly within the gene body or intergenically, with significantly less differences observed at traditional gene expression regulators such as promoters. This implies that the DNA methylation changes effected by BaP exposure may serve another purpose other than gene expression regulation. Citation Format: Francesca Galea, Paul A. White, Volker M. Arlt, Paolo Vineis, James M. Flanagan. The epigenetic effects of benzo[a]pyrene exposure [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 4327.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.045
GPT teacher head0.376
Teacher spread0.330 · 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
Published2018
Admission routes1
Has abstractyes

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