Uterine Tumor Resembling Ovarian Sex Cord Tumor (UTROSCT)
Bibliographic record
Abstract
Uterine tumor resembling ovarian sex cord tumor (UTROSCT) is a rare mesenchymal neoplasm, of uncertain biological potential, that was recently reported to exhibit recurrent gene fusions involving NCOA2-3. The purpose of this study was to, using a larger sample size, better characterize the histopathologic and molecular diversity of UTROSCT. Twenty-six cases of UTROSCT from 5 institutions were selected for further study. Fluorescence in situ hybridization for NCOA1, NCOA2, NCOA3, ESR1 and GREB1, and targeted RNA sequencing was performed on 17 and 8 UTROSCTs, respectively. Eight cases underwent massively parallel sequencing to detect single nucleotide variants (SNV), copy number variations, and structural variants using a targeted hybrid-capture based assay. NCOA1-3 rearrangement was identified in 81.8% (18/22) of cases. The most common fusion was ESR1-NCOA3, occurring in 40.9% (9/22). GREB1-NCOA1 (n=4), ESR1-NCOA2 (n=3), and GREB1-NCOA2 (n=1) rearrangements were also identified. No recurrent SNVs were identified and no tumor had SNVs in FOXL2, DICER1, STK11, or AKT1, which can be seen in ovarian sex cord-stromal tumors. Copy number variations were infrequent. Clinical follow-up was available for 11 cases with a mean follow-up interval of 94.4 (range, 1 to 319) months. Only one case had a recurrence 66 months after the initial diagnosis and this was the single case with a GREB1-NCOA2 fusion. This study reports the morphologic spectrum of UTROSCT and confirms the recently reported recurrent NCOA2-3 gene fusions, in addition to identifying novel rearrangements involving NCOA1 in these tumors.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".