Abstract B23: EWS-FLI1 partners with EWSR1 to regulate transcription in Ewing sarcoma
Bibliographic record
Abstract
Abstract Transcription factors are important regulators in normal cell proliferation and cancer. Ewing sarcoma is a pediatric bone cancer driven by a translocation between two transcription factor genes, EWSR1 and FLI1, leading to the expression of an aberrant transcription factor, EWS-FLI1. While FLI1 is not expressed, constitutive expression of EWSR1 is retained in Ewing sarcoma cells. However, very little is known about the effect of wild-type EWSR1 on EWS-FLI1 transcriptional activity. EWSR1 and EWS-FLI1 coimmunoprecipitate in a complex together in Ewing sarcoma cells and HEK293T cells. RNA-sequencing in Ewing sarcoma cells revealed a pool of genes coregulated by EWS-FLI1 and EWSR1. Furthermore, loss of EWSR1 in Ewing sarcoma cells inhibits anchorage-independent growth. Taken together, this suggests EWSR1 may play a key role in the transcriptional activity of EWS-FLI1 in Ewing sarcoma biology. Citation Format: Nasiha Ahmed, Jacob Schwartz. EWS-FLI1 partners with EWSR1 to regulate transcription in Ewing sarcoma [abstract]. In: Proceedings of the AACR Special Conference on the Advances in Pediatric Cancer Research; 2019 Sep 17-20; Montreal, QC, Canada. Philadelphia (PA): AACR; Cancer Res 2020;80(14 Suppl):Abstract nr B23.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.017 | 0.010 |
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".