Longitudinal Correlative Profiles of Responders, Nonresponders, and Those with Relapse on Treatment with Teclistamab in the Phase 1/2 MajesTEC-1 Study of Patients with Relapsed/Refractory Multiple Myeloma
Notice bibliographique
Résumé
Introduction: Teclistamab (tec) is the only approved B-cell maturation antigen (BCMA) × CD3 bispecific antibody with a personalized, weight-based dosing schedule for the treatment of triple-class exposed relapsed/refractory multiple myeloma (RRMM). In the phase 1/2 MajesTEC-1 study (NCT03145181/NCT04557098), tec demonstrated deep and durable responses. To better understand mechanisms of resistance and relapse in MajesTEC-1, we assessed longitudinal BCMA expression and immune profiles. Methods: Patients (N=165) with RRMM received subcutaneous tec 1.5 mg/kg weekly after step-up doses of 0.06 and 0.3 mg/kg, with the option to switch to every-other-week dosing if they achieved at least a partial response after ≥4 cycles of therapy in phase 1 or a complete response or better for ≥6 months in phase 2. Bone marrow and peripheral blood samples at baseline, on treatment, and at disease progression (PD) were analyzed by flow cytometry for BCMA expression and immune cell populations. Bone marrow aspirates were analyzed by cytometry by time of flight (CyTOF) for immune cell populations. Soluble BCMA (sBCMA) was analyzed in serum samples by electrochemiluminescence ligand binding. Results: Patients who responded to tec had a greater recovery of CD3+ T cells in the periphery and bone marrow during the first treatment cycles, which was sustained over time compared with nonresponders. Greater activation during the first cycle was observed in responders, indicated by a transient increase in CD38 on CD8+ T cells. In contrast, an exhausted T-cell phenotype in the blood and bone marrow was observed longitudinally in nonresponders vs responders, indicated by increasing and sustained levels of activation and exhaustion markers including persistence of CD38+ T cells and expression of LAG-3, PD-1 (Figure 1A), PD-1/LAG-3, and PD-1/TIM-3 on CD4+ or CD8+ T cells. Higher levels of immunosuppressive regulatory T cells (Tregs), including CD38+ Tregs, were also sustained in the periphery in nonresponders compared with responders. BCMA expression and sBCMA levels were assessed in a subset of patients who initially responded then relapsed on tec, who had matched baseline and end-of-treatment/PD samples. There were no significant changes in the frequency of BCMA+ plasma cells, BCMA receptor density, or sBCMA levels at PD relative to baseline, suggesting BCMA loss was not a mechanism of relapse in these patients. In contrast, higher proportions of peripheral CD4+ and/or CD8+ T cells expressing CD38, TIM-3, PD-1, and PD-1/TIM-3 were observed at relapse vs baseline. Analysis of bone marrow progression samples using CyTOF in patients who relapsed showed significantly lower CD28 expression on CD8+ T cells, significantly higher expression of exhaustion markers (CD38, PD-1, TIM-3, EOMES, and TOX) and perforin on CD4+ and/or CD8+ T cells, a higher frequency of CD4+ and CD8+ T cells expressing TIM-3 and co-expressing CD38/TOX, PD-1/TIM-3, and TOX/TIM-3 (Figure 1B), and significantly higher CD38 expression on T-cell receptor gamma delta T cells, at PD than at baseline. PD-1 and TIGIT expression was also significantly higher at PD than at baseline across CD25hiCD127dim and/or CD25hiCD127dimFoxP3+ Tregs in patients who relapsed. Conclusions: Patients responding to tec exhibited a differential immune profile in early cycles compared with nonresponders, with greater transient T-cell activation. In contrast, an exhausted T-cell phenotype was sustained in nonresponders during the first 2 treatment cycles. While mutations in BCMA cannot be excluded, we did not detect BCMA loss as a mechanism of relapse, but observed a dysfunctional immune phenotype at PD, with increased T-cell exhaustion and higher frequency of gamma delta T cells and immunosuppressive Tregs. These results suggest the importance of immune fitness and T-cell function in achieving and maintaining a response to tec. Ongoing studies will evaluate these correlatives in earlier treatment lines, where patients may have more favorable immune profiles.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».