Ewing‐like sarcoma: An emerging family of round cell sarcomas
Bibliographic record
Abstract
Ewing-like sarcomas are an emerging subgroup of small round blue cell sarcomas that share various degrees of morphological, immunohistochemical, molecular, and clinical similarity with Ewing sarcoma. Despite these similarities, Ewing-like sarcomas lack the pathognomonic molecular hallmark of Ewing sarcoma: A translocation between a gene of the RNA-binding TET family (EWSR1 or FUS) with a gene of the ETS-transcription family ( FLI1, ERG, ETV1, ETV4, or FEV). Recently, increased use of modern molecular methods based on next-generation sequencing have enabled the identification of distinct subgroups within this previously uncharacterized group of Ewing-like sarcomas based on the discovery of novel molecular driving events. The focus of this review is to provide an update on the main subcategories of Ewing-like sarcomas discovered to date: CIC-rearranged sarcomas, BCOR-rearranged sarcomas, sarcomas with a rearrangement between EWSR1 and a non-ETS family gene, and the substantial fraction of tumors which remain uncharacterized by molecular methods. There is increasing evidence that these tumors represent stand-alone entities with unique characteristics rather than simply a subgroup of Ewing sarcoma; thus, the question of the best therapeutic approach for these often aggressive sarcomas remains of primary importance. Ultimately, large collaborative efforts will be necessary to better determine the characteristics of this rare, heterogeneous family of tumors.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".