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Record W2153024722 · doi:10.1186/1477-7827-1-72

The role of the breast cancer susceptibility gene 1 (BRCA1) in sporadic epithelial ovarian cancer

2003· review· en· W2153024722 on OpenAlexafffund
Marcia L. McCoy, Christopher R. Mueller, Calvin D. Roskelley

Bibliographic record

VenueReproductive Biology and Endocrinology · 2003
Typereview
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsQueen's UniversityUniversity of British Columbia
FundersCanadian Institutes of Health Research
KeywordsOvarian cancerCancer researchEpigeneticsBiologyCarcinogenesisTumor suppressor geneBreast cancerCancerDNA methylationAlleleGeneGene expressionGenetics

Abstract

fetched live from OpenAlex

Mutations within the BRCA1 tumor suppressor gene occur frequently in familial epithelial ovarian carcinomas but they are a rare event in the much more prevalent sporadic form of the disease. However, decreased BRCA1 expression occurs frequently in sporadic tumors, and the magnitude of this decrease has been correlated with increased disease progression. The near absence of somatic mutations consequently suggests that there are alternative mechanisms that may contribute to the observed loss of BRCA1 in sporadic tumors. Indeed, both allelic loss at the BRCA1 locus and epigenetic hypermethylation of the BRCA1 promoter play an important role in BRCA1 down-regulation; yet these mechanisms alone or in combination do not always account for the reduced BRCA1 expression. Alternatively, misregulation of specific upstream factors that control BRCA1 transcription may be a crucial means by which BRCA1 is lost. Therefore, determining how regulators of BRCA1 expression may be co-opted during sporadic ovarian tumorigenesis will lead to a better understanding of ovarian cancer etiology and it may help foster the future development of novel therapeutic strategies aimed at halting ovarian tumor progression.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.989
Threshold uncertainty score0.939

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
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 head0.018
GPT teacher head0.320
Teacher spread0.301 · 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

Citations44
Published2003
Admission routes2
Has abstractyes

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