EPID-33. EPITHELOID SARCOMA IN A LONG-TERM SURVIVOR OF AN ATYPICAL TERATOID / RHABDOID TUMOR WITH RHABDOID TUMOR PREDISPOSITION SYNDROME
Bibliographic record
Abstract
Abstract INTRODUCTION Rhabdoid tumor predisposition syndrome (RTPS) predisposes to a high risk of developing Rhabdoid tumors in Brain, kidney; and is defined by a germline mutation in SMARCB1 (rarely SMARCA4) gene. The most frequent pediatric tumor associated with RTPS is atypical teratoid/rhabdoid tumor (ATRT), commonly diagnosed in children < 3 years of age. Epitheloid Sarcoma (ES) is a rare soft tissue sarcoma, arising in any age group and histologically defined by loss of SMARCB1 in tumor cells. METHODS We describe a long- term survivor of ATRT with RTPS presenting 12 years later with ES. Data was collected from medical chart review. RESULTS Our patient was diagnosed with ATRT and RTPS (SMARCB1) at 6 months of age and treated with chemotherapy as per ACNS0333 at diagnosis; by chemotherapy / focal radiation at first relapse and with alisertib on second relapse. At 10yrs of age she presented with multiple firm, skin-colored dermal nodules in both her hands (palms and fingers). She was diagnosed to have palmar warts and treated with topical cantharidin with a waxing and waning course. Subsequently the hand lesions were diagnosed as granuloma annulare and followed up with no therapy. At 12 years of age, lesion in tip of the right thumb increased in size and a punch biopsy was done which revealed ES with IHC showing loss of SMARCB1 in tumor cells. Staging CT of the chest showed multiple bilateral (b/l) small (<1cm) axillary lymph nodes with a negative PET scan. Bilateral axillary lymph node biopsies were negative for ES. She underwent excision of all the hand lesions with negative margins with no further therapy. CONCLUSION Based on our case and single case report in literature, we hypothesize that ES is likely a primary malignancy of RTPS and should be included in the spectrum of malignancies of RTPS.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".