Characterization of the Endometrial MSC Marker Ectonucleoside Triphosphate Diphosphohydrolase-2 (NTPDase2/CD39L1) in Low- and High-Grade Endometrial Carcinomas: Loss of Stromal Expression in the Invasive Phenotypes
Bibliographic record
Abstract
Ectonucleoside triphosphate diphosphohydrolase-2 (NTPDase2/CD39L1) has been described in human non-pathological endometrium in both epithelial and stromal components without changes along the cycle. It was identified as a stromal marker of basalis. In the present study, we aimed to evaluate NTPDase2 distribution, using immunolabeling and in situ enzyme activity approaches, in endometrial carcinoma (EC) at different tumor grades. NTPDase2 was present in tumor epithelial EC cells, as in the non-pathological endometria, but the expression underwent changes in subcellular distribution and also tended to decrease with the tumor grade. In stroma, NTPDase2 was identified exclusively at the tumor-myometrial junction but this expression was lost in tumors of invasive phenotype. We have also identified in EC samples the presence of the perivascular population of endometrial mesenchymal stem cells (eMSCs) positive for sushi domain containing 2 (SUSD2) and for NTPDase2, already described in non-tumoral endometrium. Our results point to NTPDase2 as a histopathological marker of tumor invasion in EC, with diagnostic relevance especially in cases of EC coexisting with other endometrial disorders, such as adenomyosis, which occasionally hampers the assessment of tumor invasion parameters.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".