MétaCan
Menu
← Back to cohort
Record W1980136907 · doi:10.1158/1078-0432.ovca13-a81

Abstract A81: Estrogen-responsiveness of the TFIID subunit TAF4B and its potential function in ovarian cancer, epigenetic regulation and meiotic DNA repair

2013· article· en· W1980136907 on OpenAlexaff
Jennifer R. Wardell, Kathryn J. Grive, Kendra Hodgkinson, April K. Binder, Kimberly A. Seymour, Lindsay A. Lovasco, Ken S. Korach, Barbara C. Vanderhyden, Richard N. Freiman

Bibliographic record

VenueClinical Cancer Research · 2013
Typearticle
Languageen
FieldMedicine
TopicReproductive Biology and Fertility
Canadian institutionsOttawa HospitalUniversity of Ottawa
Fundersnot available
KeywordsBiologyEstrogenEpigeneticsEstrogen receptorEndocrinologyInternal medicineCancerGeneticsMedicineBreast cancerGene

Abstract

fetched live from OpenAlex

Abstract Female infertility affects approximately 10.9% of women ages 15-44 in the US, and the molecular mechanisms leading to this disorder are multifaceted and varied. We have previously demonstrated that the gonadal-enriched TFIID subunit TAF4B, a paralog of the general transcription factor TAF4A, is required for fertility in mice. Female mice deficient for TAF4B exhibit a phenotype resembling premature ovarian failure, including early oocyte loss, follicular atresia and severely reduced granulosa cell proliferation when treated with 17β-estradiol. The inability of estrogen to stimulate granulosa cell proliferation led us to hypothesize that TAF4B is involved in an estrogen signaling pathway within the ovary. A large percentage of Taf4b-knockout oocytes die by apoptosis immediately after birth, and this germ cell loss is attenuated by estrogen supplementation, further suggesting a connection between TAF4B and estrogen. Taf4b-knockout ovaries also display deregulated epigenetic marks, which can affect DNA repair during meiotic homologous recombination. Furthermore, estrogen is known to regulate epigenetic changes in the ovary, leading us to hypothesize that the estrogen rescue may occur via modulation of the epigenetic state and consequent repair of double-strand breaks during meiosis. Here, we show that Taf4b mRNA and TAF4B protein expression are upregulated by estrogens in whole ovaries and purified granulosa cells of the ovary and that this increase occurs via nuclear estrogen receptors. We observe significant increases of Taf4b mRNA in estrogen-exposed mouse ovarian tumors, and the mice exposed to estradiol had significantly diminished survival compared to those receiving a placebo pellet. Combined with the fact that epigenetic deregulation and DNA repair processes play a key role in tumorigenesis, these results suggest that in addition to fertility defects, TAF4B could also affect ovarian tumorigenesis later in life. Our preliminary data suggest that the loss of oocytes in Taf4b-knockout ovaries may occur due to deficiencies in epigenetic regulation and/or a deficiency in DNA repair during meiotic prophase, since DNA repair and meiosis related genes are significantly reduced in Taf4b-knockout ovaries. Future studies will determine if estrogen treatment of neonatal Taf4b-knockout ovaries ameliorates these epigenetic and DNA repair deficits, leading to the observed oocyte rescue, and will explore if ovarian tumorigenesis is altered in the absence of TAF4B. Citation Format: Jennifer R. Wardell, Kathryn J. Grive, Kendra M. Hodgkinson, April K. Binder, Kimberly A. Seymour, Lindsay A. Lovasco, Ken S. Korach, Barbara C. Vanderhyden and Richard N. Freiman. Estrogen-responsiveness of the TFIID subunit TAF4B and its potential function in ovarian cancer, epigenetic regulation and meiotic DNA repair. [abstract]. In: Proceedings of the AACR Special Conference on Advances in Ovarian Cancer Research: From Concept to Clinic; Sep 18-21, 2013; Miami, FL. Philadelphia (PA): AACR; Clin Cancer Res 2013;19(19 Suppl):Abstract nr A81.

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 score0.009

Distilled classifier scores by category (both heads)

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)0.0030.000

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 head0.145
GPT teacher head0.450
Teacher spread0.305 · 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
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueClinical Cancer Research→Same topicReproductive Biology and Fertility→French-language works237,207→