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Record W4393861470 · doi:10.1038/s44276-024-00048-8

Characterizing functional DNA damage and response caused by the combination of CHK1 and WEE1 inhibitors in ovarian and breast cancer models

2024· article· en· W4393861470 on OpenAlexfundno aff
Adam Stewart, Jiin Song, Lisa Pickard, Giovanna Muggiolu, Sylvie Sauvaigo, Alexis de Haven Brandon, Florence I. Raynaud, Udai Banerji

Bibliographic record

VenueBJC Reports · 2024
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
FundersNational Institute for Health and Care ResearchSierra OncologyCancer Research UK
KeywordsDNA damageOvarian cancerWee1CancerBreast cancerOncologyMedicineCancer researchDNABiologyInternal medicineGeneticsCell cycle

Abstract

fetched live from OpenAlex

BACKGROUND: We proposed to quantify reduction of functional DNA damage response (DDR) mechanisms caused by the combination of CHK1 and WEE1 inhibitors. METHODS: Survival of cells and tumor growth in-vitro and in-vivo caused by the combination of the CHK1 inhibitor SRA737 and the WEE1 inhibitor adavosertib was studied in OVCAR3 and MDA-MB 436 cells. Functional DNA damage was quantified using in vitro cell free DNA assays. RESULTS: The combination of SRA737 and adavosertib caused significant reduction of survival of cells and DNA damage in-vitro and growth inhibition in-vivo. Studies using functional DDR assays found significant changes in the functional capacity of OVCAR3 but not MDA-MB 436 cells to repair DNA damage using multiple mechanisms including intra strand cross link repair, nucleotide excision repair, homologous recombination and non-homologous end joining. This study, for the first time provides a mechanistic insight into differences in the reduction in functional capacity of cells to repair DNA when exposed to CHK1 and WEE1 inhibitors. CONCLUSION: The combination of the CHK1 inhibitor SRA737 and WEE1 inhibitor adavosertib causes growth inhibition in-vitro and in-vivo, but differential functional inhibition of DDR in the models studied.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.245
Threshold uncertainty score0.256

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 head0.009
GPT teacher head0.228
Teacher spread0.219 · 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

Citations3
Published2024
Admission routes1
Has abstractyes

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