Three‐dimensional nuclear telomere architecture changes during endometrial carcinoma development
Bibliographic record
Abstract
Endometrioid or type-I endometrial carcinoma (EC) develops from hyperproliferative glandular pathologies. Inactivation of the tumor suppressor gene PTEN is frequently associated with type-I EC. Using a previously characterized Pten heterozygous (Pten+/-) mouse model, this study investigates the three-dimensional (3D) telomere profiles during progression from hyperplastic lesions to EC to test the hypothesis that altered 3D telomere profiles can be detected prior to Pten loss in early hyperproliferative lesions. We used immunohistochemistry and 3D-telomere fluorescent in-situ hybridization to investigate Pten expression, telomere length and signal distribution, average number and spatial distribution of telomeres and formation of telomere aggregates in uterine glandular epithelial cells from wildtype and Pten+/- mice. Pten showed nuclear and cytoplasmic localization in WT, predominantly cytoplasmic staining in simple hyperplasia (SH) and was markedly reduced in atypical hyperplasia (AH). Telomere length in glandular epithelial cells does not shorten with age. The average number of telomeres per nucleus was not different in WT and Pten+/- mice indicating the lack of substantial numeric chromosome aberrations during EC development. We observed telomere aggregates in lesions of AH and EC. SH lesions in Pten+/- mice differed from normal glandular epithelium by an increased relative number of shorter telomeres and by a telomere signal distribution indicative of a heterogeneous cell population. Our study revealed that alterations in the nuclear 3D telomere architecture are present in early proliferative lesions of mouse uterine tissues indicative of EC development. The changes in telomere length distribution and nuclear signal distribution precede the loss of Pten.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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) | 0.002 | 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 teacher head, 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".