Gene fusions characterize a subset of uterine cellular leiomyomas
Bibliographic record
Abstract
Uterine leiomyomas are the most common benign tumor of the female genital tract. Previous studies have shown that conventional leiomyomas often harbor-specific alterations including rearrangements involving HMGA2. Cellular leiomyomas are a variant of uterine leiomyoma that are less well-studied from a genomic point of view. Morphologically and immunohistochemically, cellular leiomyomas may be confused with low-grade endometrial stromal neoplasms, a group of tumors which frequently harbor a number of recurrent gene fusions. Ancillary molecular testing may be used to investigate tumors where low-grade endometrial stromal neoplasms enter into the differential diagnosis. At our institution, we identified a uterine cellular leiomyoma harboring a HMGA2-TRAF3IP2 fusion. After a retrospective review 11 additional tumors were identified. All included cases were reviewed and evaluated for immunohistochemical expression of smooth muscle actin, desmin, h-caldesmon, CD10, estrogen receptor, and progesterone receptor. RNA sequencing using the TruSight RNA Fusion Panel was performed on formalin-fixed paraffin-embedded tissue samples. In addition to the index case, two other cases harbored fusions: HMGA2-NAA11 and TPCN2-YAP1, of which the latter is novel and was confirmed with reverse transcriptase-polymerase chain reaction. In conclusion, a subset of cellular leiomyomas harbor rearrangements involving HMGA2, suggesting molecular kinship with conventional uterine leiomyomas. In addition, the prevalence of the novel TPCN2-YAP1 gene fusion in cellular leiomyomas requires further study. The fusions reported here, when identified, may be useful when the diagnosis of cellular leiomyoma is in question.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".