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Record W2116411136 · doi:10.1002/path.2659

Characterization of the molecular differences between ovarian endometrioid carcinoma and ovarian serous carcinoma

2009· article· en· W2116411136 on OpenAlexafffund
Jason Madore, Fengge Ren, Ali Filali‐Mouhim, Lilia Sánchez, Martin Köbel, Patricia N. Tonin, David G. Huntsman, Diane Provencher, Anne‐Marie Mes‐Masson

Bibliographic record

VenueThe Journal of Pathology · 2009
Typearticle
Languageen
FieldMedicine
TopicOvarian cancer diagnosis and treatment
Canadian institutionsMcGill University Health CentreBC Cancer AgencyUniversité de MontréalVancouver General HospitalHôtel-Dieu de MontréalUniversity of British ColumbiaMcGill UniversityCentre Hospitalier de l’Université de Montréal
FundersCanadian Institutes of Health ResearchMichael Smith Health Research BCUniversity of Michigan
KeywordsOvarian carcinomaCarcinomaSerous carcinomaSerous fluidOvaryMedicineInternal medicineOncologyPathologyOvarian cancerCancer

Abstract

fetched live from OpenAlex

The histopathological diagnosis of high-grade endometrioid and serous carcinoma of the ovary is poorly reproducible under the current morphology based classification system, especially for anaplastic, high-grade tumours. The transcription factor Wilms' tumour-1 (WT1) is differentially expressed among the gynaecological epithelia from which epithelial ovarian cancers (EOCs) are believed to originate. In EOCs, WT1 protein is observed in the majority of serous carcinomas and in up to 30% of endometrioid carcinomas. It is unclear whether the latter is a reflection of the actual incidence of WT1 protein expression in endometrioid carcinomas, or whether a significant number of high-grade serous carcinomas have been misclassified as endometrioid carcinoma. Several genetic aberrations are reported to occur in EOCs. These include mutation of the TP53 gene, aberrant activation of beta-catenin signalling and loss of PTEN protein expression, among others. It is unclear whether these aberrations are histotype-specific. The aim of this study was to better define the molecular characteristics of serous and endometrioid carcinomas in an attempt to address the problems with the current histopathological classification methods. Gene expression profiles were analysed to identify reproducible gene expression phenotypes for endometrioid and serous carcinomas. Tissue microarrays (TMA) were used to assess the incidence of TP53, beta-catenin and PTEN aberrations in order to correlate their occurrence with WT1 as an immunohistochemistry based biomarker of serous histotype. It was found that nuclear WT1 protein expression can identify misclassified high-grade endometrioid carcinomas and these tumours should be reassigned to serous histotype. Although low-grade endometrioid carcinomas rarely progress to high-grade carcinomas, a combined WT1-negative, TP53-positive immunophenotype may identify an uncommon high-grade subtype of ovarian endometrioid carcinoma. GEO database: array data accession number GSE6008.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

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)0.0010.000

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 head0.018
GPT teacher head0.249
Teacher spread0.231 · 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

Citations107
Published2009
Admission routes2
Has abstractyes

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