Biomarker Analyses of the CC-92480-MM-001 Trial to Guide Combinatorial Strategies for Mezigdomide
Bibliographic record
Abstract
Introduction: Mezigdomide (MEZI) is a novel, oral CELMoD™ agent that induces rapid and potent degradation of Ikaros and Aiolos. Reduction of these transcription factors results in direct tumoricidal and immunomodulatory effects in multiple myeloma (MM). MEZI showed promising efficacy and safety when combined with dexamethasone (DEX) in the phase 1/2 CC-92480-MM-001 trial (NCT03374085) in relapsed/refractory MM (RRMM). However, there is still a need for new combination strategies for patients refractory to multiple other therapies. Here we report pharmacodynamic (PD) biomarker analyses from blood and bone marrow of patients with RRMM to help guide combinatorial strategies for MEZI. Methods:Clinical PD biomarker analyses focused on cohorts of MEZI plus DEX (MEZI-d) in patients with RRMM with dosing from 0.8 to 1.0 mg on the 21/28-day schedule or MEZI monotherapy at 0.6 mg on the 21/28-day dosing schedule. Biomarker analyses included peripheral blood samples collected on treatment cycle (C)1 day (D)1 through mid-C2 for Aiolos expression in T cells and immunomodulation by flow cytometry. Bone marrow samples were collected for immunohistochemistry at screening and mid-C2, and for genomics analyses at screening. Biomarker analyses were evaluated in patients with RRMM (n = 124) who had received pomalidomide or daratumumab in their last prior line of treatment (POM-L [n = 49] or DARA-L [n = 32], respectively) or with prior exposure to CAR T cell/T-cell engager (TCE) therapies (n = 11). Results:MEZI-d was pharmacodynamically active in RRMM independent of prior therapies. In patients with POM-L, MEZI induced >80% substrate degradation in peripheral blood and tumor cells (median H-score % change POM-L: −22%; non-POM-L: −49%). Comparable baseline T-cell counts (CD3+, CD4+, CD8+), % proliferative CD4+ T cells (Ki67+), % effector memory CD4+ T cells (CD45RA−CD45RO+CCR7−), and % activated CD4+T cells (HLA-DR+) were observed in MEZI-d patients independent of POM-L, DARA-L, or prior exposure to CAR T cell/TCE therapies. Gradual immunostimulation of T and NK cells was observed during the first 2 weeks of MEZI dosing, peaking between D15 and D21 of the dosing cycle, and returned to baseline after drug holidays. These included increased proliferative CD4+ T cells (median at C1D15: 146.4%), increased effector memory CD4+ T cells (median at C1D15: 31.4%) and increased activated CD4+ T cells (median at C1D15: 80.4%) independent of prior therapies. Moreover, changes in immunomodulation were observed in both responders and non-responders. Immune PD between MEZI monotherapy versus MEZI-d doublet combination was comparable. Whole-genome sequencing analyses showed hypodiploidy was the most common abnormality. Analyses of high-risk molecular features showed responses to MEZI-d in patients with TP53 mutations, del17p, 1qAmp, t4:14, and cereblon defects; RAS/RAF mutations appeared to be enriched in responders. RNAseq analyses showed that high baseline EZH2 expression was significantly (P < 0.05) associated with inferior progression-free survival (PFS). Conclusions: Our data show MEZI-d was pharmacodynamically active in both responders and non-responders, and independent of prior therapies. Gradual changes of immunophenotype peaked around mid-C1, suggesting that MEZI treatment may maximize T-cell effects within the first 2 weeks, and may have implications for the optimal sequencing of T cell-redirecting therapies. MEZI showed potent immunomodulation as a monotherapy and in combination with DEX, highlighting the potential to enhance immune redirecting therapies with or without DEX. We also identified MEZI-induced responses across various high-risk molecular features. Inferior PFS was associated with high baseline EZH2 expression, which highlighted potential combinatorial therapy of MEZI with EZH2 inhibition to improve clinical efficacy.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".