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Record W2610280068 · doi:10.1002/ijc.30764

RAD51 as a potential surrogate marker for DNA repair capacity in solid malignancies

2017· review· en· W2610280068 on OpenAlexfundno aff
Mariam Gachechiladze, Jozef Škarda, Alex Soltermann, Markus Joerger

Bibliographic record

VenueInternational Journal of Cancer · 2017
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA Repair Mechanisms
Canadian institutionsnot available
FundersKrebsliga SchweizPublic Health Agency of Canada
KeywordsSurrogate endpointRAD51DNA repairDNAMedicineCancer researchBiologyGeneticsInternal medicine

Abstract

fetched live from OpenAlex

Targeting deficient mechanisms of cellular DNA repair still represents the basis for the treatment of the majority of solid tumors, and increased DNA repair capacity is a hallmark mechanism of resistance not only to DNA-damaging treatments such as cytotoxic drugs and radiotherapy, but also to small molecule targeted drugs such as inhibitors of poly-ADP ribose polymerase (PARP). Hence, there is substantial medical need for potent and convenient biomarkers of individual response to DNA-targeted treatment in personalized cancer care. RAD51 is a highly conserved protein that catalyzes DNA repair via homologous recombination, a major DNA repair pathway which directly modulates cellular sensitivity to DNA-damaging treatments. The clinical and biological significance of RAD51 protein expression is still under investigation. Pre-clinical studies consistently show the important role of nuclear RAD51 immunoreactivity in chemo- and radioresistance. Validating data from clinical trials however is limited at present, and some clinical studies show controversial results. This review gives a comprehensive overview on the current knowledge about the prognostic and predictive value of RAD51 protein expression and genetic variability in patients with solid malignancies.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.985
Threshold uncertainty score0.911

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.060
GPT teacher head0.388
Teacher spread0.327 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations107
Published2017
Admission routes1
Has abstractyes

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