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Record W3132594621 · doi:10.1093/nar/gkab081

Hsp70 acts as a fine-switch that controls E3 ligase CHIP-mediated TAp63 and ΔNp63 ubiquitination and degradation

2021· article· en· W3132594621 on OpenAlexafffund
Hong Wu, Benfan Wang, Stephen Armstrong, Yasser Abuetabh, Sarah Leng, Wilson Roa, Azeddine Atfi, Adriano Marchese, Beverly Wilson, Consolato Sergi, Elsa R. Flores, David D. Eisenstat, Roger Leng

Bibliographic record

VenueNucleic Acids Research · 2021
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Alberta
FundersCanadian Institutes of Health ResearchWomen and Children's Health Research Institute
KeywordsUbiquitin ligaseUbiquitinBiologyHsp70Cell biologyCarcinogenesisRegulatorCancer researchGene isoformCancerHeat shock proteinGeneticsGene

Abstract

fetched live from OpenAlex

The major clinical problem in human cancer is metastasis. Metastases are the cause of 90% of human cancer deaths. TAp63 is a critical suppressor of tumorigenesis and metastasis. ΔNp63 acts as a dominant-negative inhibitor to block the function of p53 and TAp63. Although several ubiquitin E3 ligases have been reported to regulate p63 stability, the mechanism of p63 regulation remains partially understood. Herein, we show that CHIP, an E3 ligase with a U-box domain, physically interacts with p63 and promotes p63 degradation. Notably, Hsp70 depletion by siRNA stabilizes TAp63 in H1299 cells and destabilizes ΔNp63 in SCC9 cells. Loss of Hsp70 results in a reduction in the TAp63-CHIP interaction in H1299 cells and an increase in the interaction between ΔNp63 and CHIP in SCC9 cells. Our results reveal that Hsp70 acts as a molecular switch to control CHIP-mediated ubiquitination and degradation of p63 isoforms. Furthermore, regulation of p63 by the Hsp70-CHIP axis contributes to the migration and invasion of tumor cells. Hence, our findings demonstrate that Hsp70 is a crucial regulator of CHIP-mediated ubiquitination and degradation of p63 isoforms and identify a new pathway for maintaining TAp63 or ΔNp63 stability in cancers.

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)0.003
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 score0.088
Threshold uncertainty score0.789

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.003
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 integrity0.0000.001
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 head0.048
GPT teacher head0.341
Teacher spread0.293 · 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

Citations40
Published2021
Admission routes2
Has abstractyes

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