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Record W2316346096 · doi:10.1126/sciadv.1501290

TIE2-mediated tyrosine phosphorylation of H4 regulates DNA damage response by recruiting ABL1

2016· article· en· W2316346096 on OpenAlexaff
Mohammad B. Hossain, Rehnuma Shifat, D. Gale Johnson, Mark T. Bedford, Konrad Gabrusiewicz, Nahir Cortes‐Santiago, Xuemei Luo, Zhimin Lu, Ravesanker Ezhilarasan, Erik P. Sulman, Hong Jiang, Shawn S.‐C. Li, Frederick F. Lang, Jessica K. Tyler, Mien‐Chie Hung, Juàn Fueyo, Candelaria Gomez‐Manzano

Bibliographic record

VenueScience Advances · 2016
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmunotherapy and Immune Responses
Canadian institutionsWestern University
FundersNational Institute of Neurological Disorders and StrokeNational Cancer InstituteNational Institutes of HealthCancer Prevention and Research Institute of Texas
KeywordsChromatinDNA damagePhosphorylationCell biologyDNATyrosine phosphorylationBiologyChemistryCancer researchBiochemistry

Abstract

fetched live from OpenAlex

DNA repair pathways enable cancer cells to survive DNA damage induced after genotoxic therapies. Tyrosine kinase receptors (TKRs) have been reported as regulators of the DNA repair machinery. TIE2 is a TKR overexpressed in human gliomas at levels that correlate with the degree of increasing malignancy. Following ionizing radiation, TIE2 translocates to the nucleus, conferring cells with an enhanced nonhomologous end-joining mechanism of DNA repair that results in a radioresistant phenotype. Nuclear TIE2 binds to key components of DNA repair and phosphorylates H4 at tyrosine 51, which, in turn, is recognized by the proto-oncogene ABL1, indicating a role for nuclear TIE2 as a sensor for genotoxic stress by action as a histone modifier. H4Y51 constitutes the first tyrosine phosphorylation of core histones recognized by ABL1, defining this histone modification as a direct signal to couple genotoxic stress with the DNA repair machinery.

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 score0.065
Threshold uncertainty score0.764

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 studies0.0000.002
Scholarly communication0.0000.001
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 head0.010
GPT teacher head0.260
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

Citations41
Published2016
Admission routes1
Has abstractyes

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