Abstract A43: Effects of transcriptional dysregulation on the DNA damage response in Ewing’s sarcoma
Bibliographic record
Abstract
Abstract Ewing’s sarcoma is a soft-tissue bone malignancy characterized by a translocation event wherein the N-terminal low complexity domain of EWSR1 is fused with the DNA binding domain of the ETS transcription factor Fli1. The resulting EWS-Fli1 fusion protein drives expression of oncogenes and knockdown of tumor-suppressor proteins. More specifically, EWS-Fli1 acts as transcriptional regulator by helping recruit RNA Pol II to promoter regions, which is subsequently phosphorylated by CDK9 to escape initiation into elongation. Interestingly, Ewing’s sarcoma is particularly susceptible to chemotherapy compared to other cancers; however, the underlying reason for this sensitivity to DNA damage has not been elucidated. Given EWS-Fli1’s role in disrupting transcription, it was hypothesized that EWS-Fli1 is concurrently disrupting the DNA damage response. Here, a combination of CDK9 inhibition with DNA damage was found to drastically diminish cell viability in Ewing’s cell lines but not in non-Ewing’s osteosarcoma or HEK293 cells. Ordinarily, after DNA damage γH2A.X phosphorylation occurs on histones near sites of damaged DNA early during the DNA damage response to signal DNA damage repair initiation. Further work has shown Ewing’s cells undergoing the combination treatment above have a marked decrease in the DNA damage marker γH2A.X as compared to non-Ewing’s cells. Together, these results suggest Ewing’s sarcoma cells are sensitized to DNA damage due in part to transcriptional dysregulation. Citation Format: Matthew G. Rollins, Jacob C. Schwartz. Effects of transcriptional dysregulation on the DNA damage response in Ewing’s 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 A43.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".