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Record W2315103005 · doi:10.1158/1538-7445.am10-942

Abstract 942: Effects of maternal and postnatal folic acid supplementation on genomic DNA methylation in the mammary glands in a chemical rat model of mammary tumorigenesis

2010· article· en· W2315103005 on OpenAlexaff
Anna Ly, Hanna Lee, Jianmin Chen, Kyoung‐Jin Sohn, Karen K. Y. Sie, Ruth Croxford, Richard Renlund, Lilian U. Thompson, Young‐In Kim

Bibliographic record

VenueCancer Research · 2010
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsHealth Sciences CentreSunnybrook Health Science CentreUniversity of Toronto
Fundersnot available
KeywordsDNA methylationOffspringDMBAEndocrinologyInternal medicineBiologyMammary glandCarcinogenesisLactationWeaningMethylationEpigeneticsCancerBreast cancerPregnancyMedicineGeneticsGene expressionDNAGene

Abstract

fetched live from OpenAlex

Abstract Background: Widespread loss of genomic DNA methylation is an early and consistent epigenetic event in cancer development including breast carcinogenesis. Folate, an essential co-factor in the transfer of one-carbon units, has been shown to modulate both cancer risk and genomic DNA methylation. We recently observed that folic acid (FA) supplementation provided in utero and in early postnatal life significantly increased risk of mammary tumors in the offspring in the dimethylbenzanthracene (DMBA) rat model. To determine a potential underlying mechanism of FA-mediated mammary tumor development, we investigated the association between global DNA methylation, DNA methyltransferase (DNMT) activity, FA supplementation, and mammary tumor status in the offspring. Methods: Female Sprague-Dawley rats were placed on a control diet (2 mg FA/kg diet) or a supplemented (5 mg) diet for 3 weeks prior to breeding and throughout pregnancy and lactation. At weaning, female pups were randomized to the control or supplemented diet. At 7 weeks of age, all pups received a single intragastric dose (5 mg) of DMBA to induce mammary tumors. At 28 weeks of age, plasma, mammary gland and liver folate and plasma homocysteine concentrations were determined and mammary tumors were enumerated and histologically confirmed. Genomic DNA methylation and DNMT activity were determined in non-neoplastic mammary glands. Results: Plasma, liver, and mammary folate and homocysteine concentrations accurately reflected dietary FA levels at weaning and 28 weeks of age (p<0.05). A significant interaction was observed between genomic DNA methylation and mammary adenocarcinoma status in the offspring (p<0.001), indicating that among tumor-free offspring, genomic DNA methylation was significantly decreased by maternal FA supplementation. In addition, in offspring bearing at least one adenocarcinoma, genomic DNA methylation was significantly decreased regardless of dietary FA intervention. Postweaning FA supplementation independently decreased DNMT activity in the offspring (p=0.05). Conclusions: Our data suggest that decreased genomic DNA methylation and DNMT activity associated with maternal and postweaning FA supplementation might be a mechanism by which maternal and postweaning FA supplementation increased mammary tumorigenesis in the offspring. Given the drastic increase in FA intake among women of childbearing age in North America, future studies are need to determine whether or not FA supplementation increases the risk of breast cancer through epigenetic mechanisms. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr 942.

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 score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.023
GPT teacher head0.345
Teacher spread0.322 · 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
Published2010
Admission routes1
Has abstractyes

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