Immune and Tumor Mediators of Resistance to Daratumumab-IMiDs Based Therapies in Relapsed Multiple Myeloma
Notice bibliographique
Résumé
Background: The use of the anti-CD38 monoclonal antibody daratumumab (Dara) together with IMiDs agents such as pomalidomide and lenalidomide has demonstrated high efficacy in newly diagnosed and relapsed multiple myeloma (MM) patients. However, MM eventually relapses and the mechanisms underlying acquired resistance to Dara-IMiDs based therapies are yet to fully defined. In this project, we aimed to identify at the single cell level the immune and tumor mediators of resistance to these therapies in MM. Methods: Serial bone marrow (BM) aspirates were collected from 31 RRMM patients treated with daratumumab-IMiDs combinations before initiation of therapy, at C3D1, and at time of relapse. Patients were considered as responders if achieving ≥ partial response (PR) for at least 4 months. BM mononuclear fractions were isolated via Ficoll density gradients coupled with magnetic sorting of CD138+ and CD138- cells. Unbiased single cell mRNA profiling of CD138+ and CD138- cells was performed using the GemCode system (10x Genomics) and paired-end sequencing done on the NexSeq Illumina platform. CellRanger and Seurat were used for sample de-multiplexing, barcode processing, single-cell 3′ gene counting and data analysis. A total of 270,835 cells were annotated based on their gene expression signature using scGate and ProjecTILs packages. Results: We first compared the baseline immunome profiling of 74,800 CD138- cells obtained from 29 patients (24 responders and 5 non-responders). An activated innate and adaptive immune microenvironment was observed in responders with significant enrichment of highly cytotoxic NK cells (CD56dim, CD16+, NCR3+, PRF1+, CD38-), CD4 CTLs (GNLY+, CX3CR1+, PRF1+, GZM+), central memory CD8 T cells (GZMB+, GZMH+, TOX-), and CD16 M1 monocytes (CD16+, TNF+, IL1B+, CLL3+). In contrast, the non-responders had a highly inflammatory microenvironment enriched of INF-secreting cDC2 cells (CLEC10A+, ISG15+, IFI6+, IFI44L+) and classical CD14+ monocytes (CCR1+, SELL+, CX3CR1-, CD16-) together with low cytotoxic NK cells (CD56+, CD16-, KLRB1+, CD38+) and more exhausted CD8 T cells (GZMB-, TCF7-, TOX+, LAG3+). Of interest, the non-responders were also characterized by a significantly high proportion of tolerogenic cDC1 CLEC9A+ expressing IDO1, known to interfere with T-cell activation and induce immune suppression. Among the 24 responders 4 patients relapsed after achieving PR for a minimum of 7 months. Comparison of the immunome profiling of CD138- cells at time of progression vs baseline revealed a loss of activation of the innate and adaptive immunity with reduction of cytotoxic NK cells (CD56+, CD16+, NCR3+, CD38+), loss of naive CD4 and CD8 T cells (TCF7+, CCR7+) together with an enrichment of exhausted CD4 and CD8 T cells (GZMB+, TOX+, LAG3+). In addition, an enrichment of CD16 monocytes lacking TNF and IL1B expression and increase of immunosuppressive cDC1 (CLEC9A+, IDO1+) were also observed at relapse. Lastly, the analysis of the MM cells transcriptome performed by comparing samples prior starting therapy and at the time of relapse revealed loss or downregulation of CD38 expression in 75% of the patients. In one patient, we observed a decrease of CD38 as well as increased expression of the complement inhibitor molecule CD59 and CD47 (“don't eat me” signal). In addition, significant MYC transcript amplification was noted in a primary refractory patient. Analysis of cell-cell interactions between tumor and immune cells using CellChat is currently ongoing and will be updated at the meeting. Conclusions: Through single cell transcriptomic studies, we have characterized the tumor microenvironment of RRMM patients treated with Dara-IMiDs based therapies and identified an activated immune microenvironment in responding patients. In contrast a highly inflammatory microenvironment with enrichment of exhausted T cells and increased numbers of immunosuppressive cDC1 and CD14 monocytes were observed in resistant patients. Amongst tumor-intrinsic factors, target CD38 downregulation was commonly noted. Taken together our findings underline the influence of the BM immune composition in promoting Dara-IMiDs resistance and support the integration of novel therapeutic strategies targeting the underlying inflammatory BM environment.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 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 | 0,000 |
| 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 ».