MétaCan
Menu
Back to cohort
Record W4414706702 · doi:10.1016/j.trecan.2025.09.001

How structural variation shapes the cancer epigenome

2025· review· en· W4414706702 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueTrends in cancer · 2025
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEpigenetics and DNA Methylation
Canadian institutionsCanada's Michael Smith Genome Sciences Centre
FundersTerry Fox Research InstituteCanadian Institutes of Health ResearchTerry Fox Foundation
KeywordsEpigenomeEpigeneticsStructural variationGenomeCancerEpigenesisMalignancyMalignant transformation

Abstract

fetched live from OpenAlex

It is widely recognized that cancer develops through a series of changes that modify the genomes of normal cells, enabling them to acquire new malignant properties. Epigenetic disruptions, which do not directly change the genetic sequence but rather influence how the genome is interpreted, have garnered significant attention as contributors to malignant transformation and progression. With the advent of new technologies to profile both the genome and epigenome of cancer cells simultaneously, the interplay between structural variation (SV) and epigenetic changes in malignancy is now an expanding field. In this review, we describe the key technological advances and highlight recent research exploring the relationship between SV and the epigenome in cancer.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.998
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.048
GPT teacher head0.389
Teacher spread0.341 · 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