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Record W2043696314 · doi:10.1158/1538-7445.am2013-1931

Abstract 1931: Development of a functional assay for the determination of BRCA1 carrier status.

2013· article· en· W2043696314 on OpenAlexaff
Lauren Bathurst, Paolo Uy, Harriet Feilotter, Scott Davey

Bibliographic record

VenueCancer Research · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicNutrition, Genetics, and Disease
Canadian institutionsQueen's University
Fundersnot available
KeywordsBiologyGeneGermline mutationMutationBreast cancerGeneticsCancerCancer researchMolecular biology

Abstract

fetched live from OpenAlex

Abstract Germline mutations in the breast cancer susceptibility gene BRCA1 confer an overall lifetime risk of developing breast cancer of up to 80%. Given the high risk of cancer development associated with BRCA1 mutation carriers, it is important that they be identified early and accurately. However, identification is impeded by the number of Variants of Unknown Significance (VUS), therefore there is compelling rationale for a functional assay that will identify pathogenic mutations. Previous work in our lab developed a novel functional assay to predict BRCA1 status based on gene expression profiles. That study analyzed EBV-transformed lymphoblastoid cell lines (LCLs) of BRCA1 mutation carriers (BRCA1+/−) and controls (BRCA1+/+) and found that lymphocytes from BRCA1 carriers could be distinguished with high fidelity (∼90% accuracy) from individuals with two wild type copies of the gene. Interestingly, carriers were recognized through their basal gene expression profiles. Global gene expression level changes following ionizing radiation (IR) to induce the DNA damage response (DDR) did not support the development of an accurate class predictor. The final predictor included a set of 43 genes. Many of these genes were also markers of differentiation in blood cells. A subset of these genes have now been validated in LCLs using qRT-PCR and protein-based methods including single reaction monitoring mass spec (SRM-MS) and flow cytometry. These assays were able to distinguish BRCA1 mutation carriers from controls based on the expression levels of specific markers, including genes with known roles in lymphocyte differentiation. Using these techniques, ongoing work is being done to test the ability of these markers to discriminate BRCA1 mutation carriers from controls using lymphocytes isolated from fresh blood samples. Citation Format: Lauren Bathurst, Paolo Uy, Harriet Feilotter, Scott Davey. Development of a functional assay for the determination of BRCA1 carrier status. [abstract]. In: Proceedings of the 104th Annual Meeting of the American Association for Cancer Research; 2013 Apr 6-10; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2013;73(8 Suppl):Abstract nr 1931. doi:10.1158/1538-7445.AM2013-1931

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: none
Teacher disagreement score0.005
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.005

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 head0.369
Teacher spread0.310 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

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