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Multiple granular cell tumors are an associated feature of LEOPARD syndrome caused by mutation in <i>PTPN11</i>

2009· article· en· W2106484863 on OpenAlexaff
Kasmintan A. Schrader, Tanya N. Nelson, Alessandro De Luca, DG Huntsman, BC McGillivray

Bibliographic record

VenueClinical Genetics · 2009
Typearticle
Languageen
FieldMedicine
TopicTumors and Oncological Cases
Canadian institutionsChildren's & Women's Health Centre of British ColumbiaUniversity of British ColumbiaBC Cancer Agency
Fundersnot available
KeywordsPTPN11Missense mutationPTENMutationExonBiologyLoss of heterozygosityCancer researchNoonan syndromeGeneticsGene mutationGeneMolecular biologyPI3K/AKT/mTOR pathwaySignal transductionAllele

Abstract

fetched live from OpenAlex

We report a patient with a clinical and molecular diagnosis of LEOPARD syndrome (LS) associated with multiple granular cell tumors (MGCT). Bidirectional sequencing of exons 7, 12, and 13 of the PTPN11 gene revealed the T468M missense mutation in exon 12. This mutation has been previously reported in patients with LS. To our knowledge, this is the first report of MGCT associated with molecularly characterized LS and provides the first molecular evidence linking granular cell tumors (GCT) to the Ras/mitogen-activated protein (MAP) kinase pathway. We propose that MGCT can be associated with LS. Analysis of GCT from this case tested negatively for loss of heterozygosity (LOH) at the PTPN11 and NF1 loci and did not show deletions of the PTEN gene. The absence of LOH of PTPN11 supports published functional data that T468M is a dominant-negative mutation.

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: Case report · Consensus signal: Case report
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.001
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 head0.043
GPT teacher head0.342
Teacher spread0.299 · 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 designCase report
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

Citations78
Published2009
Admission routes1
Has abstractyes

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