Cooperative treatment effectiveness of ATR and HSP90 inhibition in Ewing’s sarcoma cells
Bibliographic record
Abstract
Abstract Introduction: Ewing's sarcoma is an aggressive childhood malignancy whose outcome has not substantially improved over the last two decades. In this study, combination treatments of the HSP90 inhibitor AUY922 with either the ATR inhibitor VE821 or the ATM inhibitor KU55933 were investigated for their effectiveness in Ewing's sarcoma cells.Methods: Effects were determined in p53 wild-type and p53 null Ewing's sarcoma cell lines by flow cytometric analyses of cell death, mitochondrial depolarization and cell-cycle distribution. They were molecularly characterized by gene and protein expression profiling, and by quantitative whole proteome analysis.Results: AUY922 alone induced DNA damage, apoptosis and ER stress, while reducing the abundance of DNA repair proteins. The combination of AUY922 with VE821 led to strong apoptosis induction independent of the cellular p53 status, yet based on different molecular mechanisms. p53 wild-type cells activated pro-apoptotic gene transcription and underwent mitochondria-mediated apoptosis. p53 null cells, however, accumulated higher levels of DNA damage, ER stress and autophagy, eventually leading to apoptosis. Impaired PI3K/AKT/mTOR signaling further contributed to the antineoplastic combination effects of AUY922 and VE821 in p53 null cells. In contrast, the combination of AUY922 with KU55933 did not produce a cooperative effect.Conclusion: Our study reveals that HSP90 and ATR inhibitor combination treatment may be an effective therapeutic approach for Ewing's sarcoma irrespective of the p53 status.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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".