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Record W2146940336 · doi:10.1158/0008-5472.can-06-3436

p53-Independent Abrogation of a Postmitotic Checkpoint Contributes to Human Papillomavirus <i>E6</i> -Induced Polyploidy

2007· article· en· W2146940336 on OpenAlexaff
Yingwang Liu, Susan A. Heilman, Diego Illanes, Greenfield Sluder, Jason J. Chen

Bibliographic record

VenueCancer Research · 2007
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsImmunovaccine (Canada)
FundersNational Cancer InstituteNational Institutes of Health
KeywordsCarcinogenesisMitosisBiologyCell biologyCancer researchCell cycle checkpointAneuploidyMutationCell cycleGeneticsCancerChromosomeGene

Abstract

fetched live from OpenAlex

Polyploidy is often an early event during cervical carcinogenesis, and it predisposes cells to aneuploidy, which is thought to play a causal role in tumorigenesis. Cervical and anogenital cancers are induced by the high-risk types of human papillomavirus (HPV). The HPV E6 oncoprotein induces polyploidy in human keratinocytes, yet the mechanism is not known. It was believed that E6 induces polyploidy by abrogating the spindle checkpoint after mitotic stress. We have tested this hypothesis using human keratinocytes in which E6 expression induces a significant amount of polyploidy. We found that E6 expression does not affect the spindle checkpoint. Instead, we provide direct evidence that E6 is capable of abrogating the subsequent G(1) arrest after adaptation of the mitotic stress. E6 targets p53 for degradation, and previous studies have shown an important role for p53 in modulation of the G(1) arrest after mitotic stress. Importantly, we have discovered that E6 mutants defective in p53 degradation also induce polyploidy, although with lower efficiency. These results suggest that E6 is able to induce polyploidy via both p53-dependent and p53-independent mechanisms. Therefore, our studies highlight a novel function of HPV E6 that may contribute to HPV-induced carcinogenesis and improve our understanding of the onset of the disease.

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)0.002
metaresearch head score (Gemma)0.000
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 score0.030
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.078
GPT teacher head0.429
Teacher spread0.350 · 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

Citations46
Published2007
Admission routes1
Has abstractyes

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