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Record W2995292698 · doi:10.1002/path.5375

p53 immunohistochemistry is an accurate surrogate for <i>TP53</i> mutational analysis in endometrial carcinoma biopsies

2019· article· en· W2995292698 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Pathology · 2019
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCancer Genomics and Diagnostics
Canadian institutionsUniversity of CalgaryVancouver General Hospital
FundersCancer Research UK
KeywordsImmunohistochemistryBiologyAmpliconSerous carcinomaSerous fluidConcordanceCarcinomaPathologyStainingOvarian carcinomaPolymerase chain reactionCancerMedicineGeneticsGeneOvarian cancer

Abstract

fetched live from OpenAlex

TP53 mutations are considered a surrogate biomarker of the serous-like 'copy number high' molecular subtype of endometrial carcinoma (EC). In ovarian carcinoma, p53 immunohistochemistry (IHC) accurately reflects mutational status with almost 100% specificity but its performance in EC has not been established. This study tested whether p53 IHC reliably predicts TP53 mutations identified by next-generation sequencing (NGS) in EC biopsy samples for all ECs and as part of a molecular classification algorithm after exclusion of cases harbouring mismatch repair defects (MMRd) or pathogenic DNA polymerase epsilon exonuclease domain mutations (POLEmut). A secondary aim assessed inter-laboratory variability in p53 IHC. From a total of 207 cases from five centres (37-49 cases per centre), p53 IHC carried out at a central reference laboratory was compared with local IHC (n = 164) and curated tagged-amplicon NGS TP53 sequencing results (n = 177). Following consensus review, local and central p53 IHC results were concordant in 156/164 (95.1%) tumours. Discordant results were attributable to both interpretive and technical differences in staining between the local and central laboratories. When results were considered as any mutant pattern versus wild-type pattern staining, however, there was disagreement between local and central review in only one case. The concordance between p53 IHC and TP53 mutation was 155/168 (92.3%) overall, and 117/123 (95.1%) after excluding MMRd and POLEmut EC. Three (3/6) discordant results were in serous carcinomas with complete absence of p53 staining but no detectable TP53 mutation. Subclonal mutant p53 IHC expression was observed in 9/177 (5.1%) cases, of which four were either MMRd or POLEmut. Mutant pattern p53 IHC was observed in 63/63 (100%) serous carcinomas that were MMR-proficient/POLE exonuclease domain wild-type. Optimised p53 IHC performs well as a surrogate test for TP53 mutation in EC biopsies, demonstrates excellent inter-laboratory reproducibility, and has high clinical utility for molecular classification algorithms in EC. © 2019 Pathological Society of Great Britain and Ireland. Published by John Wiley & Sons, Ltd.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.126
Threshold uncertainty score0.359

Codex and Gemma teacher scores by category

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

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 head0.014
GPT teacher head0.286
Teacher spread0.272 · 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