The hegemonic EWSR1::ETS oncoprotein overrules core regulatory circuitry principles in Ewing sarcoma
Bibliographic record
Abstract
Ewing sarcoma is an aggressive bone tumor of adolescence characterized by a hallmark EWSR1::ETS fusion oncogene. The resulting chimeric oncoprotein drives tumorigenesis by reshaping transcriptional and epigenetic landscapes. However, how it is transcriptionally regulated and whether additional master transcription factors (MTFs) form a core regulatory circuit (CRC) in Ewing sarcoma remain unclear. Using an extensive panel of Ewing sarcoma cell lines and primary tumors, we mapped super-enhancers and identified enrichment of GGAA microsatellites, confirming their specificity to Ewing sarcoma as compared to other pediatric cancers and normal tissues. Integrating transcriptomic, epigenetic, 3D chromatin conformation, and dependency data, we predicted a set of MTFs potentially forming a CRC. However, functional validation demonstrated that these MTFs neither establish auto-regulatory loops nor confer robust proliferative dependencies typical of CRCs in other pediatric tumors. Instead, EWSR1::FLI1 emerged as an "hegemonic" oncoprotein, regulating expression of these MTFs without reciprocal regulation. Knockdown of EWSR1::FLI1 strongly shifted H3K27ac profiles toward mesenchymal states, whereas silencing individual or combined MTFs did not alter cell growth or EWSR1::FLI1 expression. These findings highlight the absence of a classical CRC in Ewing sarcoma and emphasize EWSR1::FLI1 as the dominant oncoprotein and a major vulnerability in this disease.
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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) | 0.001 | 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".