Single-cell transcriptomic analysis of NK cell dynamics in myeloma patients reveal persistent reduction of cytotoxic NK cells from diagnosis to relapse

Published: 11 July 2023| Version 1 | DOI: 10.17632/fk84v36dz2.1
Contributors:
, Tom Cupedo, Madelon de Jong

Description

Single-cell transcriptomics was performed to investigate the bone marrow NK cell compartment of myeloma patients at diagnosis (n=19), during treatment (n=21) and at relapse (n=6). The bone marrow of myeloma patients is characterized by a reduction in conventional cytotoxic NK cells that persists throughout treatment. We show in 20% of newly diagnosed myeloma patients that an altered balance between cytotoxic and cytokine-producing NK cells translates into a reduced cytotoxic ability in response to therapeutic antibodies. The relative loss of cytotoxic NK cells persists at relapse and is accompanied by an expansion of IFN-responsive NK cells. These findings reveal previously unappreciated alterations in bone marrow NK cell composition and highlight the importance of understanding the bone marrow immune system in patients receiving immunotherapies.

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Important notices NK cells were identified in silico from a CD38-positive immune dataset previously generated at Myeloma Research Rotterdam (De Jong et al. Nat Immunol. 2021 Jun;22(6):769-780) which was further supplemented by 6 NDMM, 21 post-therapy and 6 RRMM patient samples. The CD38.zip folder contains subfolders per timepoint. Within the timepoint subfolders there are subfolders per patient which contain the filtered_feature_bc_matrix output directories for the CD38-positive immune dataset. We first processed each individual patient separately prior to combining data from multiple patients; low-quality cells were excluded. Datasets from individual patients were then merged by integration in Seurat. NK cells were identified based upon transcription of KLRF1, KLRD1, NKG7 and GNLY; these cells were then subsetted. We checked well-defined marker genes for each cluster to identify potential contaminating cell populations such as T cells (CD8A, CD8B, CD4), B cells (MS4A1, CD19, VPREB1), plasma cells (SDC1, LAMP5, SLAMF7) and myeloid cells (LYZ, CD14, FCGR3B, ELANE, FCER1A, CD1C). One cluster contained an admixture of cell types and was removed prior to subsequent analysis. A basic script is included for R analyses. More details regarding the scripts generated during this study can be found at https://github.com/MyelomaRotterdam/Tahri-et-al.-2023 With any questions, please contact us at t.cupedo@erasmusmc.nl or s.tahri@erasmusmc.nl

Institutions

Erasmus Universiteit Rotterdam

Categories

Multiple Myeloma, Natural Killer Cell

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