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Record W2954678167 · doi:10.1002/hed.25868

The role of CIP2A as a therapeutic target of rapamycin in radioresistant head and neck cancer with TP53 mutation

2019· article· en· W2954678167 on OpenAlexaff
Song Hee Kim, Won Hyeok Lee, Daseul Seong, Jae Hee An, Hyoung Uk Je, Hae Yun Nam, Sang Yoon Kim, Seong Who Kim, Myung Woul Han

Bibliographic record

VenueHead & Neck · 2019
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsLondon Health Sciences CentreWestern University
FundersNational Research Foundation of Korea
KeywordsRadioresistanceRadiosensitivityCancer researchMutationDownregulation and upregulationSenescenceCancerCell cultureBiologyRadiation therapyMedicineCell biologyGeneticsGeneInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: CIP2A may activate multiple oncogenic proteins and promote the proliferation of various cancer cells. METHODS: We investigated that the role of CIP2A in radioresistant head and neck cancer (HNC) cell line with TP53 mutation and the effect of the rapamycin on the response of HN31 with TP53 mutation cells to irradiation related to CIP2A expression. RESULTS: CIP2A expression was stimulated by p53 mutation and critical for the inhibition of senescence induction in response to radiation. The treatment with radiation alone neither induced cytotoxicity in HN31 cells nor completely suppressed the activation of CIP2A. However, the combination of radiation and rapamycin increase the radiosensitivity through the induction of senescence with downregulation of CIP2A expression both in vivo and in vitro. CONCLUSION: Our results suggest that CIP2A may serve as a therapeutic target of rapamycin through induction of senescence in radioresistant HNC with TP53 mutation.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.007
GPT teacher head0.259
Teacher spread0.252 · 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

Citations7
Published2019
Admission routes1
Has abstractyes

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