PRIMA-1Met/APR-246 Displays High Antitumor Activity in Multiple Myeloma By Induction of p73 and Noxa
Bibliographic record
Abstract
Targeting p53 by the small-molecule PRIMA-1(Met)/APR-246 has shown promising preclinical activity in various cancer types. However, the mechanism of PRIMA-1(Met)-induced apoptosis is not completely understood and its effect on multiple myeloma cells is unknown. In this study, we evaluated antitumor effect of PRIMA-1(Met) alone or its combination with current antimyeloma agents in multiple myeloma cell lines, patient samples, and a mouse xenograft model. Results of our study showed that PRIMA-1(Met) decreased the viability of multiple myeloma cells irrespective of p53 status, with limited cytotoxicity toward normal hematopoietic cells. Treatment of multiple myeloma cells with PRIMA-1(Met) resulted in induction of apoptosis, inhibition of colony formation, and migration. PRIMA-1(Met) restored wild-type conformation of mutant p53 and induced activation of p73 upregulating Noxa and downregulating Mcl-1 without significant modulation of p53 level. siRNA-mediated silencing of p53 showed a little effect on apoptotic response of PRIMA-1(Met), whereas knockdown of p73 led to substantial attenuation of apoptotic activity in multiple myeloma cells, indicating that PRIMA-1(Met)-induced apoptosis is, at least in part, p73-dependent. Importantly, PRIMA-1(Met) delayed tumor growth and prolonged survival of mice bearing multiple myeloma tumor. Furthermore, combined treatment of PRIMA-1(Met) with dexamethasone or doxorubicin displayed synergistic effects in both multiple myeloma cell lines and primary multiple myeloma samples. Consistent with our in vitro observations, cotreatment with PRIMA-1(Met) and dexamethasone resulted in enhanced antitumor activity in vivo. Our study for the first time shows antimyeloma activity of PRIMA-1(Met) and provides the rationale for its clinical evaluation in patients with multiple myeloma, including the high-risk group with p53 mutation/deletion.
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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) | 0.001 | 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".