Advancing Preclinical Biology for Ewing Sarcoma: An International Effort
Bibliographic record
Abstract
Ewing sarcoma is an aggressive bone and soft-tissue cancer affecting adolescents and young adults. In vitro and in vivo models of Ewing sarcoma have been instrumental in advancing our understanding of Ewing sarcoma biology and essential in evaluating potential therapies, particularly for metastatic or relapsed disease for which effective treatment options remain limited. Through an international collaborative effort between the Children's Oncology Group Bone Tumor Committee and the Euro Ewing Consortium, we review the current landscape of preclinical modeling used in Ewing sarcoma research encompassing both in vitro (cell lines and tumor organoids) and in vivo (mouse and nonmammalian xenografts) model systems. We discuss factors that can influence experimental results, provide testing considerations for both in vitro and in vivo studies, and descriptions of existing preclinical data repositories. We highlight current needs in Ewing sarcoma modeling and the importance of enhanced international cooperative research and patient advocacy efforts which will be critical in expanding our resources of biologically relevant Ewing sarcoma models to enable translation of preclinical findings into effective therapeutic strategies for patients with Ewing sarcoma.
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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 | 0.107 | 0.036 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.006 | 0.005 |
| Science and technology studies | 0.001 | 0.005 |
| Scholarly communication | 0.010 | 0.013 |
| Open science | 0.004 | 0.009 |
| Research integrity | 0.003 | 0.009 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".