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Record W2000879435 · doi:10.3747/co.v15i2.210

The Role of DNA Hypermethylation and Demethylation in Cancer and Cancer Therapy

2008· article· en· W2000879435 on OpenAlexaffvenue
Moshe Szyf

Bibliographic record

VenueCurrent Oncology · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsMcGill University
Fundersnot available
KeywordsDNA methylationMethylationEpigeneticsBiologyCancerCancer epigeneticsRegulation of gene expressionEpigenomicsCancer researchGeneticsDNA demethylationRNA-Directed DNA MethylationEpigenetics of physical exerciseGeneGene expression

Abstract

fetched live from OpenAlex

Methylation of DNA is known to be an important mechanism of gene regulation. A hallmark of cancer is the deregulation of the DNA methylation machinery and aberrant DNA methylation patterns 1. In vertebrate genomes, a large fraction of the CG dinucleotide sequence is modified by methylation in gene- and tissuespecific patterns 2. Methylation of critical regulatory regions silences gene expression; loss of methylation is associated with gene activation 3. Because cancer progression requires many changes in the normal program of gene expression, it stands to reason that aberrations in DNA methylation play a critical role in the changes in gene expression involved in cancer progression and metastasis. Methylation changes in DNA play a role very similar to that of genetic mutations in cancer; however, unlike a genetic alteration, DNA methylation is potentially reversible with pharmacologic intervention. The DNA methylation machinery was therefore proposed—almost a decade and a half ago—to be an attractive anticancer target 4.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.061
GPT teacher head0.373
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 designNot applicable
Domainnot available
GenreReview

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

Citations52
Published2008
Admission routes2
Has abstractyes

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