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Record W2164736957 · doi:10.1309/ajcpepx1c7hhfelk

Aberrant Nuclear p53 Expression Predicts Hemizygous 17p (<i>TP53)</i>Deletion in Chronic Lymphocytic Leukemia

2009· article· en· W2164736957 on OpenAlexaff
Hong Chang, Allan Jiang, Connie Qi

Bibliographic record

VenueAmerican Journal of Clinical Pathology · 2009
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsToronto General HospitalUniversity of TorontoUniversity Health Network
Fundersnot available
KeywordsChronic lymphocytic leukemiaImmunohistochemistryFluorescence in situ hybridizationBiologyTrisomyNuclear proteinIn situ hybridizationLeukemiaGene expressionGeneCancer researchPathologyMolecular biologyMedicineChromosomeImmunologyTranscription factorGenetics

Abstract

fetched live from OpenAlex

Hemizygous TP53 gene deletion is the most important adverse risk factor in chronic lymphocytic leukemia (CLL), but its relationship with p53 protein expression is unclear. We investigated 110 CLL cases and correlated nuclear p53 protein immunoreactivity with TP53 gene deletion status and other CLL-associated genetic risk factors. Fluorescence in situ hybridization detected hemizygous TP53 deletions in 15 cases (13.6%), whereas immunohistochemical analysis detected nuclear p53 protein expression in 14 (12.7%). All cases expressing nuclear p53 protein had hemizygous TP53 deletions. Hemizygous TP53 gene deletion and p53 protein expression were strongly correlated (P < .001). There was no association between p53 expression and del(13q), del(11q) or trisomy 12 in CLL cases. Our data indicate that nuclear p53 protein expression, detected by a widely available immunohistochemical method, is strongly associated with TP53 deletion and that p53 immunohistochemical analysis may be adopted as a rapid, robust diagnostic tool for risk stratification of CLL.

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)0.003
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.774
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
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 head0.030
GPT teacher head0.379
Teacher spread0.349 · 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.

Study designOther design
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

Citations26
Published2009
Admission routes1
Has abstractyes

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