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Enregistrement W2908473823 · doi:10.1182/blood-2018-99-111554

Immune Profiling of Relapsed or Refractory Multiple Myeloma Patients Treated with Pomalidomide and Low-Dose Dexamethasone in Combination with Daratumumab

2018· article· en· W2908473823 sur OpenAlexaffabout
William E. Pierceall, Nizar J. Bahlis, David S. Siegel, Gary J. Schiller, Christy Samaras, Michaël Sébag, Jesús G. Berdeja, Siddhartha Ganguly, Jeffrey Matous, Kevin Song, Christopher S. Seet, Giampaolo Talamo, Shanti Srinivas, Mirelis Acosta-Rivera, Michael Bär, Donald P. Quick, Bertrand Anz, Gustavo Fonseca, Donna Reece, Weiyuan Chung, Natalya V. Serbina, Faiza Zafar, Amit Agarwal, Anjan Thakurta

Notice bibliographique

RevueBlood · 2018
Typearticle
Langueen
DomaineMedicine
ThématiqueMultiple Myeloma Research and Treatments
Établissements canadiensPrincess Margaret Cancer CentreVancouver General HospitalMcGill University Health CentreUniversity of Calgary
Organismes subventionnairesnon disponible
Mots-clésPomalidomideDaratumumabLenalidomideMedicineMultiple myelomaImmunologyImmune systemDexamethasoneOncologyInternal medicineCancer research

Résumé

récupéré en direct d'OpenAlex

Abstract Background: Multiple myeloma clinical trial CC-4047-MM-014 (NCT01946477) is a Phase II study designed to test the safety and efficacy of pomalidomide and low-dose dexamethasone alone (arm A) or in combination with daratumumab, an anti-CD38 antibody, (arm B) subjects with relapsed or refractory multiple myeloma who have received a first or second line treatment of lenalidomide-based therapy. Immunomodulatory agents (IMiD® compounds) continue to be the backbone of multiple myeloma therapy especially when combined with monoclonal antibodies, more specifically pomalidomide had been shown previously to enhance T cell- and NK cell-mediated immunity. We sought to characterize on-treatment pharmacodynamic changes of immune biomarkers associated with POM + LoDEX + DARA administration (arm B) using multicolor flow cytometry panels designed to characterize T-cell subsets and CD38+ expressing cells. IMiD agents are the backbone of combination regimens in the treatment of patients with newly diagnosed or relapsed and/or refractory multiple myeloma. The anti-myeloma properties of these agents derive from a dual mechanism of pro-apoptotic effects on tumor cells as well as enhanced immune stimulation. An understanding of how IMiD agents interact with new monoclonal antibodies to modify patient immune profiles offers key insights into the role of such in innate and adaptive immunity in determining patient outcomes. Methods and Results: Peripheral blood samples were collected at screening, Cycle1 Days 1, 8, and 15, and Cycle 2 Days 1 and 15 to monitor pharmacodynamic changes in populations of T cells, NK cells, monocytes and MDSCs by flow cytometry. From 112 patients enrolled in Arm B, 98 patients had baseline and post-treatment specimens available for these analyses. As expected, combination treatment with POM + LoDEX + DARA led to decreased peripheral counts of CD56+CD16+ NK cells as well as CD4+CD38+ and CD8+CD38+ T cell subpopulations. Decreased counts were also noted in CD3-CD19+ B cells. In contrast, total counts of CD14+ monocytes and CD3+CD4+ or CD3+CD8+ T cells were stably maintained and pronounced increases were observed in proliferating CD4+Ki-67+ and CD8+Ki-67+ T cells. Further, when examined as a percent of total counts, increases were observed in CD14+ monocytes, CD3+CD4+ and CD3+CD8+ T-cells, with decreases in CD3-CD19+ B-cells and CD3-CD56+CD16+ NK cells. Correlation of these pharmacodynamic changes with clinical outcomes will be presented. In addition, baseline immune profiling of specific cell population subsets and associations with best overall response and progression-free survival is currently being analyzed. Conclusions: The triplet regimen POM + LoDEX + DARA has shown notable clinical activity with deep and durable responses in relapsed multiple myeloma patients progressed and are or refractory to lenalidomide. Immune characterization here is consistent with a model for clinical activity in which the loss of CD56+CD16+ NK cells along with a concomitant immune suppression by loss of CD38+CD4+ and CD38+CD8+ T- cells is offset by an increase in proliferating cytotoxic CD4+Ki-67+ and CD8+Ki-67+ T-cell populations. Our results demonstrate that patients treated with the POM + LoDEX + DARA combination do not demonstrate impairment in the innate and adaptive immune compartments and, in contrast, show significant proliferative activity in the subsets of CD4, CD8 and NK cells following treatment. Pomalidomide had been shown previously to enhance T cell- and NK cell-mediated immunity; these data are consistent with a mechanism of action in which pomalidomide administration facilitates the ability to overcome immunosuppressive effects of Dara and LoDex. Potential associations of immune biomarkers with patient outcomes is ongoing and will be updated. Disclosures Pierceall: Celgene Corporation: Employment, Equity Ownership. Bahlis:Janssen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding. Siegel:Merck: Consultancy, Honoraria, Speakers Bureau; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau; Karyopharm: Consultancy, Honoraria; Amgen: Consultancy, Honoraria, Speakers Bureau; BMS: Consultancy, Honoraria, Speakers Bureau; Novartis: Honoraria, Speakers Bureau; Janssen: Consultancy, Honoraria, Speakers Bureau; Takeda: Consultancy, Honoraria, Speakers Bureau. Schiller:Astellas Pharma: Membership on an entity's Board of Directors or advisory committees, Research Funding; bluebird bio: Research Funding. Sebag:Amgen Canada: Membership on an entity's Board of Directors or advisory committees; Takeda Canada: Membership on an entity's Board of Directors or advisory committees; Janssen Inc.: Membership on an entity's Board of Directors or advisory committees; Celgene Canada: Membership on an entity's Board of Directors or advisory committees. Berdeja:Takeda: Research Funding; Genentech: Research Funding; Sanofi: Research Funding; Bristol-Myers Squibb: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Glenmark: Research Funding; Amgen: Research Funding; Novartis: Research Funding; Poseida Therapeutics, Inc.: Research Funding; Bluebird: Research Funding; Teva: Research Funding. Ganguly:Amgen: Consultancy; Daiichi Sankyo: Research Funding; Janssen: Consultancy; Seattle Genetics: Speakers Bureau. Matous:Celgene: Consultancy, Honoraria, Speakers Bureau. Srinivas:VAHCSNJ: Employment. Bar:Celgene: Consultancy. Quick:CTI BioPharma: Research Funding. Fonseca:Celgene: Speakers Bureau. Reece:Janssen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Celgene: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Merck: Honoraria, Research Funding; Otsuka: Research Funding. Serbina:Celgene: Employment. Zafar:Celgene: Employment. Agarwal:Celgene Corporation: Employment, Equity Ownership. Thakurta:Celgene Corporation: Employment, Equity Ownership.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,002
Score d'incertitude au seuil0,006

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0020,000

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.

Tête enseignante Opus0,016
Tête enseignante GPT0,267
Écart entre enseignants0,251 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations6
Publié2018
Routes d'admission2
Résumé présentoui

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