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Record W2994917102 · doi:10.1002/path.5373

Clinicopathological and molecular characterisation of ‘multiple‐classifier’ endometrial carcinomas

2019· article· en· W2994917102 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
FieldMedicine
TopicGenetic factors in colorectal cancer
Canadian institutionsVancouver General HospitalUniversity of British ColumbiaBC Cancer Agency
FundersNational Institutes of HealthNational Cancer InstituteKWF KankerbestrijdingAcademy of Medical SciencesCancer Research UK
KeywordsClassifier (UML)BiologyEndometrial cancerCarcinomaCancer researchPathologyMedicineCancerGeneticsArtificial intelligenceComputer science

Abstract

fetched live from OpenAlex

Endometrial carcinoma (EC) molecular classification based on four molecular subclasses identified in The Cancer Genome Atlas (TCGA) has gained relevance in recent years due to its prognostic utility and potential to predict benefit from adjuvant treatment. While most ECs can be classified based on a single classifier (POLE exonuclease domain mutations - POLEmut, MMR deficiency - MMRd, p53 abnormal - p53abn), a small but clinically relevant group of tumours harbour more than one molecular classifying feature and are referred to as 'multiple-classifier' ECs. We aimed to describe the clinicopathological and molecular features of multiple-classifier ECs with abnormal p53 (p53abn). Within a cohort of 3518 molecularly profiled ECs, 107 (3%) tumours displayed p53abn in addition to another classifier(s), including 64 with MMRd (MMRd-p53abn), 31 with POLEmut (POLEmut-p53abn), and 12 with all three aberrations (MMRd-POLEmut-p53abn). MMRd-p53abn ECs and POLEmut-p53abn ECs were mostly grade 3 endometrioid ECs, early stage, and frequently showed morphological features characteristic of MMRd or POLEmut ECs. 18/28 (60%) MMRd-p53abn ECs and 7/15 (46.7%) POLEmut-p53abn ECs showed subclonal p53 overexpression, suggesting that TP53 mutation was a secondary event acquired during tumour progression. Hierarchical clustering of TCGA ECs by single nucleotide variant (SNV) type and somatic copy number alterations (SCNAs) revealed that MMRd-p53abn tumours mostly clustered with single-classifier MMRd tumours (20/23) rather than single-classifier p53abn tumours (3/23), while POLEmut-p53abn tumours mostly clustered with single-classifier POLEmut tumours (12/13) and seldom with single-classifier p53abn tumours (1/13) (both p ≤ 0.001, chi-squared test). Finally, the clinical outcome of patients with MMRd-p53abn and POLEmut-p53abn ECs [stage I 5-year recurrence-free survival (RFS) of 92.2% and 94.1%, respectively] was significantly different from single-classifier p53abn EC (stage I RFS 70.8%, p = 0.024 and p = 0.050, respectively). Our results support the classification of MMRd-p53abn EC as MMRd and POLEmut-p53abn EC as POLEmut. © 2019 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of Pathological Society of Great Britain and Ireland.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.680
Threshold uncertainty score0.220

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 head0.035
GPT teacher head0.297
Teacher spread0.263 · 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