Preclinical study of a PARP inhibitor in neuroblastoma.
Bibliographic record
Abstract
9570 Background: Neuroblastoma (NB) is the most common extracranial solid tumor of childhood. In spite of many therapeutic improvements, only 60% survive long term despite aggressive combinations of multi-agent chemotherapy. In previous studies, we have demonstrated that tumor initiating cells (TIC) expressing CD133 (CD133high) in NB are more resistant to chemotherapy. Moreover, these cells express higher levels of PARP-1, a central protein involved in DNA repair. PARP-1 expression is significantly lower in NB usually showing spontaneous regression than in standard NB, suggesting an implication of PARP-1 in NB progression. The objective of this study is to determine the efficacy in vitro of AG-014699 (AG), a PARP- inhibitor, used in monotherapy or in combination to cisplatine (CP) and doxorubicine (DR), classical chemotherapeutic agents used in NB treatment, on NB cell survival. Methods: Six NB cell lines (parental or CD133high purified by flow cytometry (FACS)) were treated with AG alone or in association to CP or DR. PARP-1 ELISA protein assay was used to determine the optimal drug concentration needed to inhibit the protein. Cell survival was measured by MTT test. Western Blots were done to evaluate any apoptotic or autophagic pathway modulations. Quantification of DNA damage in treated cell was done by immunofluorescence of H2A-X protein. Results: We showed that a 4µM concentration of AG is sufficient for PARP-1 inhibition. One third of celllines presented a sensitivity to AG when used in monotherapy with an IC50 lower than 5µM. However, AG demonstrated synergistic effects when associated to DR, decreasing the IC50 by half, although none is observed when combined to CP. Sentitivity of the TIC did not appear to be more important than the bulk cells. With increasing concentration of AG, our WB showed no increase in cleaved Caspase-3 suggesting no modulation of the apoptotic pathway. However, autophagy seemed to be upregulated confirmed by an increase in cleaved LC3 II protein. Double strand breaks increased 2.5 folds when 4µM AG is added to the IC50 of DR. Conclusions: AG used in combination at potentially therapeutic doses shows promising results in NB. These results will allow for the improvement of NB treatments by introducing a new therapeutic strategy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".