MDM2 antagonist nutlin plus proteasome inhibitor velcade combination displays a synergistic anti-myeloma activity
Bibliographic record
Abstract
Mutliple myeloma (MM) has one of the poorest prognosis of the hematological malignancies and novel therapeutic approaches are needed. Therapeutic induction of p53 might be important to evaluate the drugs either individually or in combination. Direct inhibition of MDM2 function by an MDM2 antagonist nutlin or blocking proteasomal degradation of p53 by a selective proteasome inhibitor velcade can stabilize p53 and activate the p53 apoptotic signaling pathway. We examined if inhibition of p53-MDM2 interaction by nutlin might potentiate the cytotoxic effects of velcade in MM cell lines and primary MM samples. Nutlin or velcade resulted in a reduction in cell proliferation or viability in MM cells harboring wild type p53. Nutlin plus velcade showed a synergistic anti-myeloma activity as evidenced by a significant increase of cytotoxicity with respect to each agonist alone. These effects were accompanied by accumulation of p53 and its two immediate downstream targets, p21 and MDM2, as well as caspase activation and induction of proapoptotic targets, PUMA, BAX and BAK. The induction of p53 target genes induced by nutlin and/or velcade was further validated by gene expression profiling and expression of some selective targets was quantified by qRT-PCR. These preclinical studies provide the framework for clinical trial of nutlin, alone and in combination with conventional and novel therapies such as velcade to increase efficacy and improve patient outcome in MM.
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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 | 0.000 |
| 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".