RARE-38. CLINICAL PRESENTATION OF MGA-NUTM1 FUSION TRANSCRIPT SARCOMA
Bibliographic record
Abstract
Abstract BACKGROUND MGA-NUTM1 fusion gene tumor are recently described as new subtype of NUTM1-rearranged tumors. Regarding its rarity, standard treatment has not been reported. Here we described clinical presentation, radiologic finding, immunohistological profile, and treatment of a boy with MGA-NUTM1 fusion gene tumor. CASE REPORT: A 13-year-old boy with 2-month history of progressive right hemiparesis and headache. Magnetic resonance imaging (MRI) revealed 7.8 x10.6 x 8.0 cm well defined heterogeneous enhancing mass at left fronto-parietal lobe. CT chest and abdomen, bone scan, MRI spine, and CSF studies were unremarkable. He underwent craniotomy with total tumor removal. Pathology demonstrated high grade spindle cell sarcoma. The immunohistological profile was positive for BCOR, NUT1, and TEL1, but negative for CD34, STAT6, desmin, SMA, actin sarcomeric, EMA, PR, S100, SOX10, BCL 6, and SABT2. The INI-1 showed nuclear expression and Ki-67 was positive in 50% of tumor nuclei. Molecular test for MGA-NUTM1 fusion transcript was positive, while SYT-SSX1, SYT-SSX2, and SYT-SSX4 fusion transcripts were negative. Four months after operation, MRI showed newly-seen two small enhancing foci at lateral and inferior aspects of the surgical cavity. He underwent re-surgery. Then focal radiation (54Gy and boost up to 60Gy at recurrent area) to the resection cavity was decided. Post-radiation chemotherapy including ifosfamide 3 g/m2 and etoposide 150 mg/m2 on Day 1–2, and carboplatin 500 mg/m2 on Day 3, every 21–28 days was started. He has completed the first course of chemotherapy without any complication. CONCLUSION MGA-NUTM1 fusion CNS sarcoma is rare. Treatment may require surgery, radiation and chemotherapy.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".