Additive Interaction between Oxaliplatin and DMAG in Pediatric Acute Lymphoblastic Leukemia (ALL) Cells. Evidence for Interference with Multiple Signaling Pathways.
Bibliographic record
Abstract
Abstract Oxaliplatin is an analogue from diaminocyclohexanae platinum family of agents that has been found to have significant antitumour activity against a number of aggressive malignancies. However, its effectiveness in the treatment of leukemia has not been widely explored. Studies conducted in a number of solid tumour models indicate that the activity of oxaliplatin is significantly increased when combined with other antineoplastic agents. This provides a unique approach to develop combined treatment protocols with minimum toxicity. We tested the hypothesis that oxaliplatin induced cytotoxicity may be facilitated by a decrease in specific pro-survival signals found in leukemic cells. We took advantage of the observation that ansamycin antibiotics such as 17- (dimethylaminoethylamino) -17-demethoxygeldanamycin (DMAG) affect many of the critical survival pathways by virtue of their ability to induce degradation of critical signaling molecules that are also Hsp-90 client proteins. Cell lines were established from pediatric ALL patients with a spectrum of molecular abnormalities including Bcr-Abl fusion gene (n=8). The ability of oxaliplatin and DMAG to induce apoptosis in these cells was analyzed by cell growth assays using Alamar blue. Western blot analysis was used to detect changes in apoptosis related proteins Bax, BCL-2, p53 and survivin. Preliminary experiments with each agent were used to establish the inhibitory concentrations in culture. The effects of combining oxaliplatin and DMAG were analyzed by isobologram analysis for each cell line. Changes in signaling pathways were identified by an antibody array technique in which changes in phosphorylation and expression of approximately 50 signaling molecules in cells treated with oxaliplatin and DMAG. Results indicate that both agents were able induce apoptosis in all leukemic cell lines. However, IC50 for both agents varied between cell lines and appears to be marginally higher for DMAG compared to oxaliplatin (0.001 to 5 uM/L vs. 0.01 to 10 uM/L). Oxaliplatin had no significant inhibitory effect on one of the cell lines examined. This line was derived from a patient who was originally diagnosed with JMML who then recurred with ALL. The leukemic cell line from Ph chromosome positive ALL showed the highest IC50 for both agents. Isobologram analysis of the data from experiments where both agents were used together suggested an additive effect on most of the lines with some notable exceptions. Antibody arrays showed significant variations in the loss or dephosphorylation of signaling molecules in the presence of oxaliplatin or oxaliplatin and DMAG, most notable Akt1/2, B-catenin and p38 MAPK. We describe strong in vitro data to suggest the potential use of oxaloplatin in combination with DMAG for the treatment of pediatric leukemias. Our methodology also provides an experimental model to conduct in vitro biological correlative studies to monitor the effectiveness of these agents. Finally we provide evidence for the existence of multiple signaling pathways in pediatric ALL cells that are differentially affected by different anti-neoplastic agents and discuss, in detail, the utility of this approach to understand the biology of leukemic growth and survival.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".