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Record W2063513563 · doi:10.1038/bjc.2012.87

Mutation analysis of RAD51D in non-BRCA1/2 ovarian and breast cancer families

2012· article· en· W2063513563 on OpenAlexafffundabout
Deidra J Osher, Kim De Leeneer, G Michils, Nancy Hamel, Eva Tomiak, Bruce Poppe, Karin Leunen, Eric Legius, Andrew Y. Shuen, E. Smith, Jocelyne Arseneau, Patricia N. Tonin, Gert Matthijs, Kathleen Claes, Marc Tischkowitz, William D. Foulkes

Bibliographic record

VenueBritish Journal of Cancer · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsJewish General HospitalUniversity of OttawaMcGill University Health CentreChildren's Hospital of Eastern OntarioMcGill University
FundersVlaamse regeringUniversiteit GentSusan G. KomenFonds Wetenschappelijk OnderzoekMcGill University
KeywordsOvarian cancerBreast cancerMissense mutationProbandOncologyBiologyOvarian carcinomaAlleleGeneticsCancerMutationInternal medicineCancer researchMedicineGene

Abstract

fetched live from OpenAlex

BACKGROUND: Recent data show that mutations in RAD51D have an aetiological role in ovarian carcinoma, yet mutations do not appear to be associated with an increased risk for breast cancer. We studied ovarian and breast cancer families having at least one woman affected by ovarian carcinoma, to assess the importance of RAD51D mutations in such families. METHODS: The coding region of the RAD51D gene was analysed in 175 BRCA1/2-negative families with family histories of both ovarian and breast cancer ascertained from two Canadian and two Belgian institutions. RESULTS: We identified one previously reported deleterious mutation, p.Arg186(*) (c.556C>T), and two novel variants; missense substitution p.Cys119Arg and an intronic variant c.83-26A>G. p.Arg186(*) segregated with the disease in the family and two ovarian carcinomas available for analysis showed loss of the wild-type allele, but the novel variants are likely neutral. CONCLUSION: RAD51D should be included in genetic screening of ovarian cancer families that do not have BRCA1/BRCA2 mutations. We show that mutations are more likely to be found in families with two or more ovarian cancers, or in probands with first-degree relatives with ovarian cancer, and we feel testing should be preferentially offered to affected women from such families.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.410
Threshold uncertainty score0.383

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 head0.006
GPT teacher head0.277
Teacher spread0.270 · 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 designObservational
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

Citations53
Published2012
Admission routes3
Has abstractyes

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