Abstract B008: Decoding the primary site-specific regulation of rhabdomyosarcoma metastasis
Bibliographic record
Abstract
Abstract The prognosis for patients with high-risk rhabdomyosarcoma (RMS), a pediatric sarcoma characterized in part by defective skeletal muscle (myogenic) differentiation, has remained stagnant at <30% for over forty years. With >15% of patients presenting at diagnosis with metastasis, a defining factor of high-risk disease, there is an urgent need for new therapies. Some primary tumor locations are associated with a higher incidence of metastasis and poorer outcomes. However, the biology (and potential for therapeutic intervention) driving this prognostic factor is poorly defined.To analyze the influence of the primary tumor location on RMS invasion and metastasis, we evaluated cell line xenografts (CDX) implanted in a favorable site, the tongue, versus an unfavorable site, the hindlimb. We evaluated invasion and metastasis from each primary tumor site by histopathology and measured gene expression changes by bulk RNAseq.Despite the tongue being deemed a favorable primary site, perineural invasion or intravascular tumor emboli (60% versus 0%), sentinel lymph node metastasis (25-100% versus 0%), and clinically significant lung metastases (>10% lung area or symptomatic mice; 20% versus 0%) were observed more frequently in tongue xenograft-bearing mice than hindlimb xenograft-bearing mice. The expression of myogenic differentiation markers is higher in tongue CDX than in hindlimb CDX, but expression of these markers is reduced upon metastasis. These phenotypes are maintained when cells are returned to 2D culture, suggesting a stable shift in the differentiation state. Interestingly, CDX of sentinel lymph node metastasis-derived cells were more invasive and metastatic than parental CDX when implanted in the tongue, but not when implanted in the hindlimb.Our work, the first direct evaluation of RMS invasion and metastasis by primary tumor location, demonstrates that the primary tumor location influences RMS metastasis and that tumor cell-intrinsic properties alone are insufficient to increase invasion and metastasis. Ongoing work aims to identify the mechanisms by which the primary tumor microenvironment regulates invasion, enhancing our understanding of the biology of RMS metastasis and offering an opportunity to employ a precision medicine-based approach to targeting metastasis. Citation Format: Katie E. Hebron, Kristine Isanogle, Elijah F. Edmondson, Amy James, Simone Difilippantonio, Marielle E. Yohe. Decoding the primary site-specific regulation of rhabdomyosarcoma metastasis [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr B008.
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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 | 0.000 |
| 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) | 0.004 | 0.001 |
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".