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Record W4220696512 · doi:10.1016/j.celrep.2022.110534

The mTOR chromatin-bound interactome in prostate cancer

2022· article· en· W4220696512 on OpenAlexaff
Catherine R. Dufour, Charlotte Scholtes, Ming Yan, Yonghong Chen, Lingwei Han, Ting Li, Hui Xia, Qiyun Deng, Mathieu Vernier, Vincent Giguère

Bibliographic record

VenueCell Reports · 2022
Typearticle
Languageen
FieldMedicine
TopicProstate Cancer Treatment and Research
Canadian institutionsMcGill University Health CentreMcGill University
Fundersnot available
KeywordsInteractomeProstate cancerChromatinPI3K/AKT/mTOR pathwayCancer researchComputational biologyBiologyCancerCell biologyGeneticsDNASignal transductionGene

Abstract

fetched live from OpenAlex

A growing number of studies support a direct role for nuclear mTOR in gene regulation and chromatin structure. Still, the scarcity of known chromatin-bound mTOR partners limits our understanding of how nuclear mTOR controls transcription. Herein, comprehensive mapping of the mTOR chromatin-bound interactome in both androgen-dependent and -independent cellular models of prostate cancer (PCa) identifies a conserved 67-protein interaction network enriched for chromatin modifiers, transcription factors, and SUMOylation machinery. SUMO2/3 and nuclear pore protein NUP210 are among the strongest interactors, while the androgen receptor (AR) is the dominant androgen-inducible mTOR partner. Further investigation reveals that NUP210 facilitates mTOR nuclear trafficking, that mTOR and AR form a functional transcriptional module with the nucleosome remodeling and deacetylase (NuRD) complex, and that androgens specify mTOR-SUMO2/3 promoter-enhancer association. This work identifies a vast network of mTOR-associated nuclear complexes advocating innovative molecular strategies to modulate mTOR-dependent gene regulation with conceivable implications for PCa and other diseases.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.771
Threshold uncertainty score0.778

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)0.0010.000

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 head0.018
GPT teacher head0.320
Teacher spread0.302 · 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 designObservational
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

Citations21
Published2022
Admission routes1
Has abstractyes

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