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Record W1999140678 · doi:10.1002/pros.20729

Analysis of the gene coding for the BRCA2‐Interacting protein PALB2 in hereditary prostate cancer

2008· article· en· W1999140678 on OpenAlexaff
Marc Tischkowitz, Nelly Sabbaghian, Anna M. Ray, Ethan M. Lange, William D. Foulkes, Kathleen A. Cooney

Bibliographic record

VenueThe Prostate · 2008
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBRCA gene mutations in cancer
Canadian institutionsMcGill UniversityJewish General HospitalMcGill University Health Centre
FundersNational Cancer InstituteNational Institutes of HealthU.S. Department of Defense
KeywordsPALB2Prostate cancerProbandMedicineProstateCancerGeneticsBreast cancerBRCA2 ProteinMutationMale breast cancerGeneOncologyCancer researchInternal medicineBiologyGermline mutation

Abstract

fetched live from OpenAlex

BACKGROUND: The genetic basis of susceptibility to prostate cancer (PRCA) remains elusive. Mutations in BRCA2 have been associated with increased prostate cancer risk and account for around 2% of young onset (<56 years) prostate cancer cases. PALB2 is a recently identified breast cancer susceptibility gene whose protein is closely associated with BRCA2 and is essential for BRCA2 anchorage to nuclear structures. This functional relationship made PALB2 a candidate PRCA susceptibility gene. METHODS: We sequenced PALB2 in probands from 95 PRCA families, 77 of which had two or more cases of early onset PRCA (age at diagnosis <55 years), and the remaining 18 had one case of early onset PRCA and five or more total cases of PRCA. RESULTS: Two previously unreported variants, K18R and V925L were identified, neither of which is in a known PALB2 functional domain and both of which are unlikely to be pathogenic. No truncating mutations were identified. CONCLUSIONS: These results indicate that deleterious PALB2 mutations are unlikely to play a significant role in hereditary prostate cancer.

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)0.000
metaresearch head score (Gemma)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

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

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 head0.019
GPT teacher head0.286
Teacher spread0.267 · 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".

Quick stats

Citations40
Published2008
Admission routes1
Has abstractyes

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