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Record W2581662090 · doi:10.1101/096271

Regulation of eIF4F complex by the peptidyl prolyl isomerase FKBP7 in taxane-resistant prostate cancer

2016· preprint· en· W2581662090 on OpenAlexaff
Marine F. Garrido, Nicolas Martin, Catherine Gaudin, Frédéric Commo, Nader Al Nakouzi, Ladan Fazli, Elaine Del Nery, Jacques Camonis, Franck Perez, Stéphanie Lerondel, Alain Le Pape, Hussein Abou‐Hamdan, Martin Gleave, Yohann Loriot, Laurent Désaubry, Stéphan Vagner, Karim Fizazi, Anne Chauchereau

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2016
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicSignaling Pathways in Disease
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCabazitaxelProstate cancerDocetaxelCancer researchGene silencingTaxaneCancerBiologyMedicineInternal medicineBreast cancerAndrogen deprivation therapyGene

Abstract

fetched live from OpenAlex

ABSTRACT Targeted therapies that exploit the signaling pathways involved in prostate cancer are required to overcome chemoresistance and improve treatment outcomes for men. Molecular chaperones play a key role in the regulation of protein homeostasis and are potential targets to alleviate chemoresistance. Using image-based high content siRNA functional screening based on a gene expression signature, we identified FKBP7, a molecular chaperone overexpressed in docetaxel-resistant and in cabazitaxel-resistant prostate cancer cells. FKBP7 was upregulated in human prostate cancers and correlated with the recurrence in patients receiving Docetaxel. FKBP7 silencing showed that FKBP7 is required to maintain the growth of chemoresistant cell lines and of chemoresistant tumors in mice. Mass spectrometry analysis revealed that FKBP7 interacts with the eIF4G component of the eIF4F translation initiation complex to mediate survival of chemoresistant cells. Using small molecule inhibitors of eIF4A, the RNA helicase component of eIF4F, we were able to overcome docetaxel and cabazitaxel resistance.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.049
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 science0.0010.000
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 head0.013
GPT teacher head0.235
Teacher spread0.222 · 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.

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
Published2016
Admission routes1
Has abstractyes

Explore more

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