GLI1 Gene Alterations in Neoplasms of the Genitourinary and Gynecologic Tract
Bibliographic record
Abstract
We report 4 neoplasms of the kidney (2 cases) and uterus (2 cases) harboring rearrangements or amplifications of the GLI1 gene, which because of their unusual clinical presentation, morphology, and immunoprofile mimicked other neoplasms, causing significant diagnostic challenge. The neoplasms occurred in 4 female patients ages 33 to 88 years. Histologically they all demonstrated nodular growth, solid architecture, bland epithelioid to ovoid-spindle cells with pale cytoplasm set in a variably myxoid or hyalinized stroma. One uterine tumor also demonstrated a focal round cell pattern, while another demonstrated focal pleomorphism. Unlike most previously reported neoplasms with these genetic abnormalities, the neoplasms in the current series were negative for S100 protein and minimally reactive for actin. All labeled for CD10 and cyclin D1, while 2 labeled for estrogen receptor and BCOR and 1 labeled for desmin, raising consideration of endometrial stromal sarcoma, myxoid leiomyosarcoma, metastatic breast carcinoma, and glomus tumor. One renal neoplasm demonstrated a GLI1-FOXO4 gene fusion and the other harbored a GLI1 gene rearrangement (unknown partner). The 2 uterine neoplasms exhibited GLI1 gene amplifications. GLI1-altered neoplasms (particularly those with GLI1 amplification) show variable morphology and lack a consistent immunophenotype, and thus may trigger diagnostic challenges which can be resolved by molecular testing.
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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".