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Record W2976879024 · doi:10.15252/emmm.201910659

The novel BET‐CBP/p300 dual inhibitor NEO2734 is active in SPOP mutant and wild‐type prostate cancer

2019· article· en· W2976879024 on OpenAlexaff
Yuqian Yan, Jian Ma, Dejie Wang, Dong Lin, Xiaodong Pang, Shangqian Wang, Yu Zhao, Lei Shi, Hui Xue, Yunqian Pan, Jun Zhang, Claes Wahlestedt, Francis J. Giles, Yu Chen, Martin Gleave, Collin C. Collins, Dingwei Ye, Yuzhuo Wang, Haojie Huang

Bibliographic record

VenueEMBO Molecular Medicine · 2019
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsUniversity of British ColumbiaBC Cancer Agency
FundersNational Natural Science Foundation of ChinaNational Cancer InstituteFoundation for the National Institutes of Health
KeywordsMutantProstate cancerCancer researchWild typeCancerBiologyChemistryGeneticsGene

Abstract

fetched live from OpenAlex

CULLIN3-based E3 ubiquitin ligase substrate-binding adaptor gene SPOP is frequently mutated in prostate cancer (PCa). PCa harboring SPOP hotspot mutants (e.g., F133V) are resistant to BET inhibitors because of aberrant elevation of BET proteins. Here, we identified a previously unrecognized mutation Q165P at the edge of SPOP MATH domain in primary and metastatic PCa of a patient. The Q165P mutation causes structural changes in the MATH domain and impairs SPOP dimerization and substrate degradation. Different from F133V hotspot mutant tumors, Q165P mutant patient-derived xenografts (PDXs) and organoids were modestly sensitive to the BET inhibitor JQ1. Accordingly, protein levels of AR, BRD4 and downstream effectors such as RAC1 and phosphorylated AKT were not robustly elevated in Q165P mutant cells as in F133V mutant cells. However, NEO2734, a novel dual inhibitor of BET and CBP/p300, is active in both hotspot mutant (F133V) and non-hotspot mutant (Q165P) PCa cells in vitro and in vivo. These data provide a strong rationale to clinically investigate the anti-cancer efficacy of NEO2734 in SPOP-mutated PCa patients.

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 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 score0.359
Threshold uncertainty score0.612

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 head0.014
GPT teacher head0.316
Teacher spread0.301 · 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 teacher head, 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

Citations90
Published2019
Admission routes1
Has abstractyes

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