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Record W1995216594 · doi:10.1073/pnas.0530308100

Characterization of cells and gene-targeted mice deficient for the p53-binding kinase homeodomain-interacting protein kinase 1 (HIPK1)

2003· article· en· W1995216594 on OpenAlexaff
Seiji Kondo, Ying Lu, Michael E. Debbas, Athena W. Lin, Ildiko Sarosi, Annick Itié, Andrew Wakeham, JoAnn Tuan, Chris Saris, Gary Elliott, Weili Ma, Samuel Benchimol, Scott W. Lowe, Tak W. Mak, Sushil K. Thukral

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2003
Typearticle
Languageen
FieldMedicine
TopicCancer-related Molecular Pathways
Canadian institutionsUniversity of Toronto
FundersNational Cancer Institute
KeywordsBiologyHomeoboxMolecular biologyCarcinogenesisKinaseEmbryonic stem cellGeneTranscription factorCell biologyCancer researchGenetics

Abstract

fetched live from OpenAlex

The tumor suppressor p53 is regulated in part by binding to cellular proteins. We used p53 as bait in the yeast two-hybrid system and isolated homeodomain-interacting protein kinase 1 (HIPK1) as a p53-binding protein. Deletion analysis showed that amino acids 100-370 of p53 and amino acids 885-1093 of HIPK1 were sufficient for HIPK1-p53 interaction. HIPK1 was capable of autophosphorylation and specific serine phosphorylation of p53. The HIPK1 gene was highly expressed in human breast cancer cell lines and oncogenically transformed mouse embryonic fibroblasts. HIPK1 was localized to human chromosome band 1p13, a site frequently altered in cancers. Gene-targeted HIPK1-/- mice were grossly normal but oncogenically transformed HIPK1 -/- mouse embryonic fibroblasts exhibited reduced transcription of Mdm2 and were more susceptible than transformed HIPK1+/+ cells to apoptosis induced by DNA damage. Carcinogen-treated HIPK1 -/- mice developed fewer and smaller skin tumors than HIPK1+/+ mice. HIPK1 may thus play a role in tumorigenesis, perhaps by means of the regulation of p53 and/or Mdm2.

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)0.001
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 score0.004
Threshold uncertainty score0.283

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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

Citations79
Published2003
Admission routes1
Has abstractyes

Explore more

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