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Record W2101671356 · doi:10.2217/14622416.9.2.215

Epigenetics of Cancer Progression

2008· review· en· W2101671356 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePharmacogenomics · 2008
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEpigeneticsDNA methylationBiologyGene silencingCancerMethylationGeneCpG siteEpigenetic therapyCancer epigeneticsCancer researchGeneticsBioinformaticsComputational biologyGene expression

Abstract

fetched live from OpenAlex

Alteration in epigenetic regulation of gene expression is a frequent event in human cancer. CpG island hypermethylation and downregulation is observed for many genes involved in a diverse range of functions and pathways that become deregulated in cancer. Paradoxically, global hypomethylation is a hallmark of almost all human cancers. Methylation profiles can be used as molecular markers to distinguish subtypes of cancers and potentially as predictors of disease outcome and treatment response. The role of epigenetics in diagnosis and treatment is likely to increase as mechanisms leading to the transcriptional silencing of genes involved in human cancers are revealed. Drugs that inhibit methylation are used both as a research tool to assess reactivation of genes silenced in cancer by hypermethylation and in the treatment of some hematological malignancies. Multidimensional analysis, evaluating genetic and epigenetic alterations on a global and locus-specific scale in human cancer, is imperative to understand mechanisms driving changes in gene dosage, and as a means towards identifying pathways driving cancer initiation and progression.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.059
GPT teacher head0.431
Teacher spread0.372 · 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