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Record W4407240157 · doi:10.1158/1541-7786.mcr-24-0710

PAX8 Interacts with the SWI/SNF Complex at Enhancers to Drive Proliferation in Ovarian Cancer

2025· article· en· W4407240157 on OpenAlexaff
Kostianna Sereti, Anna E. Russo, Ryan Raisner, P. Taylur, Karen E. Gascoigne

Bibliographic record

VenueMolecular Cancer Research · 2025
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicChromatin Remodeling and Cancer
Canadian institutionsMicrosemi (Canada)Discovery Centre
FundersGenentech
KeywordsPAX8SWI/SNFTranscription factorBiologyEnhancerSMARCA4Cancer researchGeneChromatin remodelingChromatinCell biologyGenetics

Abstract

fetched live from OpenAlex

Activation of lineage-specific gene expression programs is mediated by the recruitment of lineage-specific transcription factors and their coactivators to chromatin. The lineage factor PAX8 drives essential gene expression in ovarian cancer cells and is required for tumor proliferation. However, the molecular details surrounding cofactor recruitment and specific activation of transcription by PAX8 remain unknown. Here, we identify an important functional interaction between PAX8 and the switch/sucrose nonfermentable (SWI/SNF) chromatin remodeling complex. We show that PAX8 can recruit SWI/SNF complexes to DNA, in which they function to open chromatin and facilitate the expression of PAX8 target genes. Genetic deletion of PAX8 results in loss of SWI/SNF from PAX8-bound enhancers, loss of expression of associated target genes, and reduced proliferation. These results can be phenocopied by pharmacological inhibition of SWI/SNF ATPase activity. These data indicate that PAX8 mediates the expression of an essential ovarian cancer proliferative program in part by the recruitment of the SWI/SNF complex, highlighting a novel vulnerability in PAX8-dependent ovarian cancer. Implications: PAX8 recruits SWI/SNF complexes to enhancers to mediate the expression of genes essential for ovarian cancer proliferation.

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

Direct model labels (unvalidated)

Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.

Model armCategoriesStudy designConfidence
gemmano category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
gptno category
Domain: not available · Genre: Empirical
About the Canadian research system: no · About a Canadian topic: no
Bench or experimentallow
models agreeAgreement compares identical category sets and study designs across arms.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.017
Threshold uncertainty score0.581

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.032
GPT teacher head0.393
Teacher spread0.360 · 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

Labeled directly by 2 models reading the full record.

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

Citations2
Published2025
Admission routes1
Has abstractyes

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