Mezigdomide combined with bortezomib disrupts the cell cycle and elicits superior antitumor effects in multiple myeloma
Bibliographic record
Abstract
Triplet regimens that include an immunomodulatory agent, proteasome inhibitor, and dexamethasone are widely used in newly diagnosed and relapsed/refractory (R/R) multiple myeloma (MM). Mezigdomide (MEZI; CC-92480) is a cereblon E3 ubiquitin ligase modulator that is being clinically investigated in combination with bortezomib (BTZ) and low-dose dexamethasone (DEX) for safety and efficacy in pretreated R/RMM. The single-agent mechanism of action (MOA) of MEZI has been defined by the recruitment and degradation of essential MM transcription factors Ikaros and Aiolos, leading to cell autonomous antitumor effects and immune modulation. These effects were confirmed in patients based on pharmacodynamic measurements of Ikaros/Aiolos degradation in biomarker evaluations of immune subsets. However, the MOA of triplet regimens, including that of MEZI/BTZ/DEX remain poorly defined. To better understand the MOA of this triplet combination, we compared the mechanistic contributions of MEZI, BTZ, or DEX alone, or in combination, in preclinical MM models in vitro and in vivo. Additionally, we have compared these results with similar combinations with the immunomodulatory agent pomalidomide (POM). Our studies indicate that the MEZI/BTZ/DEX triplet is superior to all single agents and POM/BTZ/DEX in terms of potency of antiproliferative and proapoptotic activities, substrate degradation depth and kinetics in the presence of BTZ, and in vivo efficacy. We show that the combination of MEZI with BTZ increases cell death through disruption of multiple phases of the cell cycle and this thereby enhances the direct cytotoxic effects of the combination treatment.
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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 | 0.001 |
| 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".