Fusion-Negative Rhabdomyosarcoma: Clinical Application of Targeted RNA Sequencing
Bibliographic record
Abstract
Background: Rhabdomyosarcoma (RMS) is the most common soft tissue sarcoma of childhood. For stratification purposes, rhabdomyosarcoma is classified into fusion-positive RMS (alveolar rhabdomyosarcoma) and fusion-negative RMS (embryonal or spindle cell/sclerosing, FN-RMS) subtypes according to its PAX::FOXO1 fusion status. This study aims to highlight the pathologic and molecular characteristics of a cohort of FN-RMS using a targeted NGS RNA-Seq assay. Methods: Twelve tumors were analyzed through targeted RNA-Seq using the Trusight Pancancer panel from Illumina. Molecular alterations were then correlated with the clinicopathological features. Results: Of the 12 tumors analyzed, we identified 6 embryonal rhabdomyosarcomas (ERMSs) harboring mutations in key signaling molecules ( KRAS, HRAS, NRAS , and FGFR4 ), oncogenic DICER1 mutations in 2 ERMS, pathogenic TP53 and NF1 mutations in an ERMS with features of anaplasia, a TEAD1::NCOA2 gene fusion in a congenital spindle cell and sclerosing rhabdomyosarcoma (SSRMS), and a FUS::TFCP2 gene fusion in a skull base SSRMS. Only 1 ERMS in the bladder showed no reportable molecular alterations. Conclusion: We illustrate case examples demonstrating how a combined morphological and molecular approach with targeted RNA-Seq can aid in diagnosis and identify clinically actionable alterations in pediatric FN-RMS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 teacher head, 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".