Abstract A060 Investigating underlying efficacy and mechanism of action of the KIF11 inhibitor filanesib in Ewing and clear cell sarcomas
Bibliographic record
Abstract
Abstract Ewing (ES) and clear cell (CCS) sarcomas are bone and soft tissue malignances and in advanced and relapsed disease overall survival rates remain dismal. For metastatic ES, five-year survival rates are between 15% and 30%. In CCS, the five-year survival rates are between 30% and 67%. Accordingly, there is a critical need for the development of novel targeted therapeutics for the treatment of these rare cancers. Both cancers are driven by fusion proteins; EWS-FLI1 in ES and EWS-ATF1 in CCS, which arise from separate chromosomal translocations: t(11;22)(q24;q12) and t(12;22)(q13;q12) respectively. Current approaches for developing new treatments focus on targeting the fusion proteins or their downstream targets. We performed a small molecule compound library screen of clinically used drugs and identified ES and CCS cells to be extremely sensitive to filanesib, a kinesin spindle protein (KIF11) inhibitor. KIF11 is known to play roles in cell cycle progression and mitotic spindle stability. Our preclinical efficacy studies demonstrated that filanesib promotes potent tumor growth inhibition in both EWS-FLI1 and EWS-ATF1 xenograft models in mice. We are currently investigating the mechanism underlying the relationship between KIF11 and EWS-FLI1 and EWS-ATF1. Prior studies have identified KIF11 within a EWS-ATF1 transcriptional complex and KIF11 has been shown to interact with the histone acetyltransferase (HAT) p300/CBP-Associated Factor (PCAF). HATs are necessary components for chromatin remodeling, which the oncogenic fusion proteins regulate. Future research directions involve elucidating the role of KIF11 in regulating the EWS-ATF1 and EWS-FlI1 transcriptional complexes. Additionally, to further improve the therapeutic response to filanesib, we are investigating potential synergistic relationships with other compounds. This work has been supported in part by the Flow Cytometry and the Molecular Genomics Cores at the H. Lee Moffitt Cancer Center & Research Institute, a comprehensive cancer center designated by the National Cancer Institute and funded in part by Moffitt’s Cancer Center Support Grant (P30-CA076292) Citation Format: Hannah L. Walker-Mimms, Nicole Londono, Yi Liao, Neelkamal Chaudhary, Mingxiang Teng, Fumi Kinose, Xueli Li, Andrii Monastyrskyi, Uwe Rix, Derek Duckett. Investigating underlying efficacy and mechanism of action of the KIF11 inhibitor filanesib in Ewing and clear cell sarcomas [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 A060.
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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".