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Record W2067697669 · doi:10.1158/0008-5472.can-06-0984

Critical Roles for Non-pRb Targets of Human Papillomavirus Type 16 E7 in Cervical Carcinogenesis

2006· article· en· W2067697669 on OpenAlexaff
Scott Balsitis, Frederick A. Dick, Nicholas J. Dyson, Paul F. Lambert

Bibliographic record

VenueCancer Research · 2006
Typearticle
Languageen
FieldMedicine
TopicCervical Cancer and HPV Research
Canadian institutionsWestern University
FundersNational Institute of General Medical SciencesNational Cancer InstituteNational Institutes of Health
KeywordsCarcinogenesisCancer researchE2FBiologyRetinoblastoma proteinDysplasiaCervical cancerContext (archaeology)Cervical intraepithelial neoplasiaCell cycleCancerGenetics

Abstract

fetched live from OpenAlex

High-risk human papillomaviruses (HPV) encode two oncogenes, E6 and E7, expressed in nearly all cervical cancers. In vivo, HPV-16 E7 has been shown to induce multiple phenotypes in the context of transgenic mice, including cervical cancer. E7 is a multifunctional protein known best for its ability to inactivate the tumor suppressor pRb. To determine the importance of pRb inactivation by E7 in cervical cancer, we pursued studies with genetically engineered mice. E7 expression in estrogen-treated murine cervix induced dysplasia and invasive cancers as reported previously, but targeted Rb inactivation in cervical epithelium was not sufficient to induce any cervical dysplasia or neoplasia. Furthermore, E7 induced cervical cancer formation even when the E7-pRb interaction was disrupted by the use of a knock-in mouse carrying an E7-resistant mutant Rb allele. pRb inactivation was necessary but not sufficient for E7 to overcome differentiation-induced or DNA damage-induced cell cycle arrest, and expression patterns of the E2F-responsive genes Mcm7 and cyclin E indicate that other E2F regulators besides pRb are important targets of E7. Together, these data indicate that non-pRb targets of E7 play critical roles in cervical carcinogenesis.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.351
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0040.000

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 head0.105
GPT teacher head0.476
Teacher spread0.371 · 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 designObservational
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

Citations77
Published2006
Admission routes1
Has abstractyes

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