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Record W3178794077 · doi:10.1158/1538-7445.am2021-2472

Abstract 2472: Effective ER antagonists resist conformational restrictions imposed by somatic mutation but do not correlate with effects on receptor stability in live cells

2021· article· en· W3178794077 on OpenAlexaff
David J. Hosfield, Nan‐Sheng Li, Ross Han, Muriel Lainé, Sandra Weber, Madaline Sauvage, Sylvie Madar, Geoffrey L. Greene, Sean W. Fanning

Bibliographic record

VenueCancer Research · 2021
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicEstrogen and related hormone effects
Canadian institutionsUniversité de Montréal
Fundersnot available
KeywordsEstrogen receptorReceptorEstrogen receptor alphaMutantBiologyMutationCancer researchCell biologyChemistryGeneticsCancerBreast cancer

Abstract

fetched live from OpenAlex

Abstract Approximately 50% of luminal breast cancer patients become resistant to first-line endocrine therapies after an average of 5 years. Acquired activating mutations to the ESR1 ligand binding domain enable hormone therapy resistance in approximately 25-40% of these patients. Competitive estrogen antagonists function by maintaining the receptor in a transcriptionally inactive state by forcing estrogen receptor alpha ligand binding domain (ERα LBD) helix 12 into the AF-2 cleft to prevent the docking of LXXLL-containing transcriptional coactivators. Multiple next-generation ERα antagonists that function as molecular degraders of the receptor have been described and shown activity in breast cancers harboring the activating ESR1 mutations. To understand whether ERα antagonism correlates with receptor stability, we examined a comprehensive panel of structurally diverse antagonists in live breast cancer cell assays using WT, Y537S, and D538G-mutant receptors. We found that potent antagonists are able to both stabilize and degrade the receptor and further demonstrate that the D538G mutation reduces turnover with ICI due to specific defects in receptor ubiquitination and SUMOylation. High resolution x-ray crystal structures of WT and Y537S ERα LBD in complex with stabilizing and degrading antiestrogens suggest that modulators that enforce the classical antagonist-like helix 12 conformation in the mutant receptor achieve the greatest activity in transcriptional assays, regardless of their effects on receptor stability Citation Format: David Hosfield, Nan-Sheng Li, Ross Han, Muriel Laine, Sandra Weber, Madaline Sauvage, Sylvie Madar, Geoffrey Greene, Sean Fanning. Effective ER antagonists resist conformational restrictions imposed by somatic mutation but do not correlate with effects on receptor stability in live cells [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 2472.

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 score0.008
Threshold uncertainty score0.026

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)0.0080.002

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 head0.013
GPT teacher head0.308
Teacher spread0.295 · 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
Published2021
Admission routes1
Has abstractyes

Explore more

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