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Record W2013587251 · doi:10.1126/science.1250255

Ubiquitylome analysis identifies dysregulation of effector substrates in SPOP-mutant prostate cancer

2014· article· en· W2013587251 on OpenAlexaff
Jean‐Philippe Theurillat, Namrata D. Udeshi, Wesley J. Errington, Tanya Svinkina, Sylvan C. Baca, Marius Pop, Peter J. Wild, Mirjam Blattner, Anna C. Groner, Mark A. Rubin, Holger Moch, Gilbert G. Privé, Steven A. Carr, Levi A. Garraway

Bibliographic record

VenueScience · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsPrincess Margaret Cancer CentreUniversity of TorontoUniversity Health Network
FundersNational Institute of General Medical SciencesNational Cancer Institute
KeywordsEffectorUbiquitinUbiquitin ligaseBiologyMutantCarcinogenesisMutationCell biologyProstate cancerUbiquitin-Protein LigasesCancerCancer researchGeneticsGene

Abstract

fetched live from OpenAlex

Cancer genome characterization has revealed driver mutations in genes that govern ubiquitylation; however, the mechanisms by which these alterations promote tumorigenesis remain incompletely characterized. Here, we analyzed changes in the ubiquitin landscape induced by prostate cancer-associated mutations of SPOP, an E3 ubiquitin ligase substrate-binding protein. SPOP mutants impaired ubiquitylation of a subset of proteins in a dominant-negative fashion. Of these, DEK and TRIM24 emerged as effector substrates consistently up-regulated by SPOP mutants. We highlight DEK as a SPOP substrate that exhibited decreases in ubiquitylation and proteasomal degradation resulting from heteromeric complexes of wild-type and mutant SPOP protein. DEK stabilization promoted prostate epithelial cell invasion, which implicated DEK as an oncogenic effector. More generally, these results provide a framework to decipher tumorigenic mechanisms linked to dysregulated ubiquitylation.

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 score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.009
GPT teacher head0.269
Teacher spread0.261 · 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

Citations256
Published2014
Admission routes1
Has abstractyes

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