Abstract A056 Intertumoral epigenetic heterogeneity in response to a novel therapy in Ewing sarcoma
Bibliographic record
Abstract
Abstract Like many pediatric cancers, Ewing sarcoma (EwS) is a genomically quiet disease. Driven by an oncogenic fusion protein, usually EWSR1-FLI1, the epigenome of this genetically homogenous cancer is a driver of clinical outcomes, where heightened epigenetic heterogeneity within tumors is associated with metastatic disease. While prognosis for localized disease is moderate, outcomes are dismal for patients who present with advanced, relapsed, or refractory disease and there is a lack of targeted therapies in this setting. We have previously described a targeted combination therapy harnessing DDK and WEE1 inhibition exploits elevated endogenous replication stress in EwS to force cells into mitotic catastrophe in vitro. While our experiments evaluating the efficacy of this combination in vivo have been extremely encouraging, the data have shown that individual mice receiving the same treatment have variable patterns of outgrowth after treatment cessation, with some mice demonstrating moderate increases in tumor volume and some mice demonstrating little to no tumor outgrowth. This differential response to therapy is most likely to occur through epigenetic dysregulation. Thus, we aim to interrogate intertumoral epigenetic heterogeneity and examine epigenetic profiles associated with treatment response using samples from in vivo studies. Samples were analyzed from a CDX model using TC32 cells injected subcutaneously. Reduced representation bisulfite sequencing was performed on a control arm (n = 5) and the following three treatment arms, where the DDK inhibitor is TAK-931 (simurosertib) and the WEE1 inhibitor is MK1775 (adavosertib): 1) Irinotecan + Temozolomide (n=9), 2) Irinotecan (full dose) + DDKi + WEE1i (n=7), 3) Irinotecan (half dose) + DDKi + WEE1i (n=9), for a total of 30 samples. Our analysis of this data evaluates epigenetic changes between treatment conditions and increases our understanding of epigenetic heterogeneity in EwS. Citation Format: Emily Isenhart, Ajay Gupta, Joyce Ohm. Intertumoral epigenetic heterogeneity in response to a novel therapy in Ewing sarcoma [abstract]. In: Proceedings of the AACR Special Conference in Cancer Research: Advances in Pediatric Cancer Research; 2024 Sep 5-8; Toronto, Ontario, Canada. Philadelphia (PA): AACR; Cancer Res 2024;84(17 Suppl):Abstract nr A056.
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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) | 0.002 | 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".