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Record W3173586783 · doi:10.3747/co.v16i5.529

Selected Abstracts Submitted to the Third International Symposium on Hereditary Breast and Ovarian Cancer

2009· article· en· W3173586783 on OpenAlexvenueno aff
G. Banneau, Mickaël Guedj, Renaud Schiappa, Fabien Petel, Nicolas Sévenet, I. de Mascarel, G. Mac Grogan, Michel Longy, Fabrice Bonnet

Bibliographic record

VenueCurrent Oncology · 2009
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsnot available
Fundersnot available
KeywordsBreast cancerBRCA2 ProteinGermline mutationMedicineComparative genomic hybridizationOvarian cancerMutationCancerGermlineOncologyGeneticsGeneInternal medicineBiologyGenome

Abstract

fetched live from OpenAlex

Background: Germline mutation screening of BRCA1 and BRCA2 genes is performed in suspected familial breast cancer cases, but a causative mutation is found in only 30% of patients. The development of additional methods to identify good candidates for BRCA1 and BRCA2 analysis would therefore increase the efficacy of diagnostic mutation screening. With this in mind, we developed a study to determine molecular signatures of BRCA1—or BRCA2—mutated breast cancers. Materials and Methods: Array-cgh (comparative genomic hybridization) and transcriptomic analysis were performed on a series of 103 familial breast cancers. The series included 7 breast cancers with a BRCA1 mutation and 5 breast cancers with a BRCA2 mutation. The remaining 91 cases were obtained from 73 families selected on the basis of at least 3 affected first-degree relatives or at least 2 affected first-degree relatives with breast cancer at an average age of 45 years. Array-cgh analyses were performed on a 4407 BAC-array (CIT-V8) manufactured by IntegraGen. Transcriptomic analyses were performed using an Affymetrix Human Genome U133 Plus 2.0 chip. Results: Using supervised clustering analyses we identified two transcriptomic signatures: one for BRCA1-mutated breast cancers consisting of 600 probe sets and another for BRCA2-mutated breast cancers also consisting of 600 probes sets. We also defined cgh-array signatures, based on the presence of specific genomic rearrangements, one for BRCA1-mutated breast cancers and one for BRCA2-mutated breast cancers. Conclusions: This study identified molecular signatures of breast cancers with BRCA1 or BRCA2 germline mutations. Genes present in these signatures could be exploited to find new markers for such breast cancers. We also identified specific genomic rearrangements in these breast cancers, which could be screened for in a diagnostic setting using fluorescence in situ hybridization, thus improving patient selection for BRCA1 and BRCA2 molecular genetic analysis.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.234
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.2340.068

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 head0.026
GPT teacher head0.344
Teacher spread0.318 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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

Citations2
Published2009
Admission routes1
Has abstractyes

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