ATRT-10. Epithelioid Sarcoma in patients with Rhabdoid Tumor Predisposition Syndrome (RTPS): a novel cancer in the RTPS spectrum
Bibliographic record
Abstract
Abstract Background Rhabdoid tumor predisposition syndrome (RTPS) is characterized by germline biallelic loss of SMARCB1(RTPS1) or SMARCA4(RTPS2) genes, leading to early-onset tumors primarily in the brain and kidneys. Epithelioid sarcoma (EpS) is a rare malignant soft tissue sarcoma observed in children and young adults, characterized by loss of nuclear SMARCB1 expression. Here, we describe survivors of atypical teratoid/rhabdoid tumors (ATRT) with RTPS1 who developed EpS during follow-up. Methods Data were collected through a retrospective chart review of three patients with RTPS and ATRT diagnosed with EpS during routine follow-up. A literature review on RTPS and EpS was also conducted. Results All three patients (2M / 1F) were diagnosed with ATRT and RTPS1 in infancy and treated with surgery, high-dose chemotherapy, and autologous stem cell transplantation. Relapse occurred in all patients, with two undergoing surgery followed by focal radiation. EpS was diagnosed at a median follow-up age of 12 years (range:3.5 to 14 years), with all patients presenting with multiple skin lesions on their hands. Histopathological analysis confirmed EpS with characteristic loss of SMARCB1 expression. Staging scans showed no evidence of disseminated disease. All patients underwent surgical excision with negative margins. Two patients subsequently experienced local recurrence, managed with wide surgical excision of the recurrent lesions. One additional case reported in the literature (Baker et.al. 2021) described a male patient with RTPS1 and metachronous ATRT and late-onset EpS. The patient also presented with multiple papules on the hands and feet nine years after ATRT diagnosis. All four patients were alive without any evidence of disease at last follow up. Conclusions We report 3 additional cases to support EpS as part of the RTPS1 cancer phenotype. Recognizing this predisposition is critical for implementing appropriate long-term surveillance and early intervention in patients with RTPS1.
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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 | 0.000 | 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".