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Record W2142835045 · doi:10.1158/1055-9965.epi-12-1110

Catenin Family Genes Are Not Commonly Mutated in Hereditary Diffuse Gastric Cancer

2012· article· en· W2142835045 on OpenAlexaff
Johanna M. Schuetz, Stephen Leach, Pardeep Kaurah, Jennifer Jeyes, Yaron S.N. Butterfield, David G. Huntsman, Angela Brooks‐Wilson

Bibliographic record

VenueCancer Epidemiology Biomarkers & Prevention · 2012
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicWnt/β-catenin signaling in development and cancer
Canadian institutionsCanada's Michael Smith Genome Sciences CentreSimon Fraser UniversityUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsCDH1Nonsynonymous substitutionGeneticsGermline mutationMutationGeneBiologyCancerGermlineCancer researchCadherinGenomeCell

Abstract

fetched live from OpenAlex

BACKGROUND: Approximately one third of the hereditary diffuse gastric cancer (HDGC) families carry germline mutations in the E-cadherin gene (CDH1). Risk prediction in members of families with this rare but deadly cancer could be improved by the identification of additional HDGC genes in non-CDH1 families. METHODS: Affected individuals from 22 CDH1 mutation-negative families were screened for germline mutations in four catenin genes: CTNNA1, CTNNB1, JUP, and CTNND1. Catenins interact closely with E-cadherin molecules in cells, and are therefore logical candidate genes for mutation screening in HDGC families. RESULTS: No nonsynonymous variants were seen in CTNNA1, CTNNB1, or CTNND1; only JUP contained nonsynonymous variants, of which only two rare variants were predicted to be deleterious. CONCLUSION: Catenin genes are not commonly mutated in non-CDH1 HDGC families. IMPACT: Germline mutations in CTNNA1, CTNNB1, JUP, or CTNND1 are unlikely to play a major role in HDGC.

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)0.001
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.057
GPT teacher head0.336
Teacher spread0.279 · 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

Citations25
Published2012
Admission routes1
Has abstractyes

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