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Record W7055284967

Common breast cancer susceptibility alleles are associated with tumor subtypes in BRCA1 and BRCA2 mutation carriers: results from the Consortium of Investigators of Modifiers of BRCA1/2.

2011· article· en· W7055284967 on OpenAlexfundno aff

Bibliographic record

VenueFlorence Research (University of Florence) · 2011
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic confinement fusion research
Canadian institutionsnot available
FundersHelen Diller Family Comprehensive Cancer Center, University of California, San FranciscoNational Cancer InstituteNational Health and Medical Research CouncilCanadian Institutes of Health ResearchCancer Center, University of KansasZonMwCentre Léon BérardNational Institutes of HealthCentre Hospitalier Universitaire de NantesUniversiteit LeidenInstitut Claudius RegaudFondazione Italiana per la Ricerca sul CancroRadboud Universitair Medisch CentrumInstitut BergoniéDeutsche KrebshilfeLeids Universitair Medisch CentrumAssociazione Italiana per la Ricerca sul CancroRoyal Marsden NHS Foundation TrustUmeå UniversitetIstituto Oncologico VenetoLietuvos Mokslo TarybaLunds UniversitetCreighton UniversityUniversity of California, San FranciscoMinistero della SaluteUniversity of PennsylvaniaInstitut Gustave-RoussySahlgrenska UniversitetssjukhusetErasmus Medisch CentrumVrije Universiteit AmsterdamHuntsman Cancer InstituteCancer AustraliaNational Breast Cancer FoundationNational Institute for Health and Care ResearchAvon Foundation for WomenUniversitair Medisch Centrum GroningenDeutsches KrebsforschungszentrumLinköpings UniversitetAlleanza Contro il CancroCanadian Breast Cancer Research AllianceHelsingin ja Uudenmaan SairaanhoitopiiriFox Chase Cancer CenterMedical Research CouncilUppsala UniversitetMemorial Sloan-Kettering Cancer CenterOhio State UniversityRadboud UniversiteitKansas Bioscience AuthorityAkademiska SjukhusetCancer Care OntarioCancer Research UKGeorgetown UniversityBreast Cancer Research Foundation
KeywordsAlleleBreast cancerMutationCancerTumor suppressor geneBRCA2 ProteinGenetic predispositionGeneDisease
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Previous studies have demonstrated that common breast cancer susceptibility alleles are differentially associated with breast cancer risk for BRCA1 and/or BRCA2 mutation carriers.It is currently unknown how these alleles are associated with different breast cancer subtypes in BRCA1 and BRCA2 mutation carriers defined by estrogen (ER) or progesterone receptor (PR) status of the tumour.Methods: We used genotype data on up to 11,421 BRCA1 and 7,080 BRCA2 carriers, of whom 4,310 had been affected with breast cancer and had information on either ER or PR status of the tumour, to assess the associations of 12 loci with breast cancer tumour characteristics.Associations were evaluated using a retrospective cohort approach.Results: The results suggested stronger associations with ER-positive breast cancer than ER-negative for 11 loci in both BRCA1 and BRCA2 carriers.Among BRCA1 carriers, single nucleotide polymorphism (SNP) rs2981582 (FGFR2) exhibited the biggest difference based on ER status (per-allele hazard ratio (HR) for ER-positive = 1.35, 95% CI: 1.17 to 1.56 vs HR = 0.91, 95% CI: 0.85 to 0.98 for ER-negative, P-heterogeneity = 6.5 × 10 -6 ).In contrast, SNP rs2046210 at 6q25.1 near ESR1 was primarily associated with ER-negative breast cancer risk for both BRCA1 and BRCA2 carriers.In BRCA2 carriers, SNPs in FGFR2, TOX3, LSP1, SLC4A7/NEK10, 5p12, 2q35, and 1p11.2 were significantly associated with ER-positive but not ER-negative disease.Similar results were observed when differentiating breast cancer cases by PR status.Conclusions: The associations of the 12 SNPs with risk for BRCA1 and BRCA2 carriers differ by ER-positive or ERnegative breast cancer status.The apparent differences in SNP associations between BRCA1 and BRCA2 carriers, and non-carriers, may be explicable by differences in the prevalence of tumour subtypes.As more risk modifying variants are identified, incorporating these associations into breast cancer subtype-specific risk models may improve clinical management for mutation carriers.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.045
GPT teacher head0.265
Teacher spread0.220 · 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 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".

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Citations0
Published2011
Admission routes1
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