MétaCan
Menu
Back to cohort
Record W2113902100 · doi:10.1530/erc-14-0516

Deubiquitinases and the new therapeutic opportunities offered to cancer

2015· review· en· W2113902100 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueEndocrine Related Cancer · 2015
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsYork University
FundersCanadian Institutes of Health ResearchUniversity of Sydney
KeywordsNeurodegenerationProstate cancerCarcinogenesisCancerThyroid cancerBiologyCancer researchDeubiquitinating enzymeMedicineBioinformaticsNeuroscienceComputational biologyDiseaseUbiquitinInternal medicineGeneGenetics

Abstract

fetched live from OpenAlex

Deubiquitinases (DUBs) play important roles and therefore are potential drug targets in various diseases including cancer and neurodegeneration. In this review, we recapitulate structure-function studies of the most studied DUBs including USP7, USP22, CYLD, UCHL1, BAP1, A20, as well as ataxin 3 and connect them to regulatory mechanisms and their growing protein interaction networks. We then describe DUBs that have been associated with endocrine carcinogenesis with a focus on prostate, ovarian, and thyroid cancer, pheochromocytoma, and adrenocortical carcinoma. The goal is enhancing our understanding of the connection between dysregulated DUBs and cancer to permit the design of therapeutics and to establish biomarkers that could be used in diagnosis and prognosis.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.977
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.095
GPT teacher head0.364
Teacher spread0.269 · 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