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Record W2773135401 · doi:10.3390/cancers9120167

Ubiquitin Specific Peptidase 22 Regulates Histone H2B Mono-Ubiquitination and Exhibits Both Oncogenic and Tumor Suppressor Roles in Cancer

2017· review· en· W2773135401 on OpenAlexafffund
Lucile M. Jeusset, Kirk J. McManus

Bibliographic record

VenueCancers · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicUbiquitin and proteasome pathways
Canadian institutionsUniversity of ManitobaResearch Institute in Oncology and HematologyCancerCare Manitoba
FundersCanadian Institutes of Health ResearchNatural Sciences and Engineering Research Council of CanadaCancerCare Manitoba FoundationStrongResearch Manitoba
KeywordsUbiquitinCarcinogenesisDeubiquitinating enzymeCancer researchSuppressorCancerHistone H2BBiologyHistoneGeneGenetics

Abstract

fetched live from OpenAlex

Ubiquitin-Specific Peptidase 22 (USP22) is a ubiquitin hydrolase, notably catalyzing the removal of the mono-ubiquitin moiety from histone H2B (H2Bub1). Frequent overexpression of USP22 has been observed in various cancer types and is associated with poor patient prognosis. Multiple mechanisms have been identified to explain how USP22 overexpression contributes to cancer progression, and thus, USP22 has been proposed as a novel drug target in cancer. However, gene re-sequencing data from numerous cancer types show that USP22 expression is frequently diminished, suggesting it may also harbor tumor suppressor-like properties. This review will examine the current state of knowledge on USP22 expression in cancers, describe its impact on H2Bub1 abundance and present the mechanisms through which altered USP22 expression may contribute to oncogenesis, including an emerging role for USP22 in the maintenance of genome stability in cancer. Clarifying the impact aberrant USP22 expression and abnormal H2Bub1 levels have in oncogenesis is critical before precision medicine therapies can be developed that either directly target USP22 overexpression or exploit the loss of USP22 expression in cancer cells.

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 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 score0.978
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
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 head0.051
GPT teacher head0.343
Teacher spread0.292 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations64
Published2017
Admission routes2
Has abstractyes

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