DOI: 10.5061/dryad.44j0zpcn7
title: Reconstitution of the multiple myeloma microenvironment following lymphodepletion with BCMA CAR-T therapy

description: BCMA-targeted CAR-T therapy has shown potent treatment outcomes in
 treating multiple myeloma (MM), a disease characterized by malignant bone
 marrow (BM) plasma cells. However, the remodeling of MM microenvironment
 after CAR-T therapy remains poorly understood. Here, we report the
 reconstitution of MM microenvironment by obtaining single-cell
 transcriptomes for paired BM specimens (n = 14) from 7 MM patients before
 (i.e., baseline, ''day −4'') and after (i.e.,
 ''day 28'') post-lymphodepleted BCMA CAR-T therapy.
 Our analysis revealed heterogeneity in driver gene expression among MM
 cells, even those harboring the same cytogenetic abnormalities. The best
 overall responses of patients over the 15-month follow-up are positively
 correlated with the abundance and targeted cytotoxic activity of CD8+
 effector CAR-T cells on day 28 after CAR-T cell infusion. Additionally,
 favorable responses are associated with attenuated immunosuppression
 mediated by regulatory T cells (Tregs), enhanced CD8+ effector T cell
 cytotoxic activity, and elevated type 1 conventional dendritic cell (cDC1)
 antigen presentation ability. DC re-clustering inferred
 intramedullary-originated cDC3s with extramedullary migration. Cell-cell
 communication network analysis indicated BCMA CAR-T therapy mitigates
 BAFF/GALECTIN/MK pathway-mediated immunosuppression and activates MIF
 pathway-mediated anti-MM immunity. Our study sheds light on MM
 microenvironment dynamics after BCMA CAR-T therapy, offering clues for
 predicting treatment responsivity.
description: The collected paired BM specimens from MM patients before and
 after BCMA CAR-T therapy were isolated into single cell suspensions, and
 3'-scRNA-seq (Chromium Single Cell 3′ v3 Libraries) analysis was
 performed on each sample. The analysis included 7 MM
 patients (P1-P7). We collected baseline BM aspirate specimens (P1_B, P2_B,
 P3_B, P4_B, P5_B, P6_B, and P7_B) from each patient before
 (<em>i.e.</em>, baseline, ''day −4'') BCMA
 CAR-T cell infusion (<em>i.e.</em>, ''day
 0''), and the BM aspirate specimens (P1_R, P2_R, P3_R, P4_R,
 P5_R, P6_R, and P7_R) after BCMA CAR-T therapy were collected on day 28.
 These patients had received 2 or 3 previous lines of therapies, including
 two patients (P2 and P6) with extramedullary disease; the other patients
 did not experience extramedullary progression. All patients received
 cyclophosphamide-mediated lymphodepletion on day −3 with the aim of
 potentiating the expansion of CAR-T cells. Efficacy assessments based on
 the International Myeloma Working Group (IMWG) criteria displayed that the
 patients had achieved varying degrees of remission by day 28: P3 achieved
 stringent complete remission (sCR); P1 and P4 achieved very good partial
 remission (VGPR); the other patients achieved partial remission
 (PR). The BM aspirate samples were collected during the
 diagnostic procedure. Bone marrow mononuclear cells (BMMCs) were isolated
 using Ficoll Paque Plus (Cytiva) and washed three times with Hanks
 Balanced Salt Solution (HBSS, Solarbio). Following centrifugation at 1,000
 rpm for 5 min, the supernatant was discarded, and the sediment was
 resuspended in 1 ml phosphate-buffered saline (PBS, Solarbio). To
 eliminate red blood cells, 1-2 ml red blood cell lysis buffer (BD) was
 added at 4°C for 10 min. After centrifugation at 500 g for 5 min, the
 cells were suspended in PBS. The cell viability was assessed using trypan
 blue (Sigma) and examined under a microscope. Utilizing
 the 10x Genomics Chromium Single Cell 3′ v3 Library Kit and Chromium
 instrument, approximately 17,500 cells were partitioned into nanoliter
 droplets to achieve single-cell resolution for a maximum of 10,000
 individual cells per sample. The resulting cDNA was tagged with a common
 16 nt cell barcode and 10 nt Unique Molecular Identifier during the RT
 reaction. Full-length cDNA from poly-A mRNA transcripts was enzymatically
 fragmented and size selected to optimize the cDNA amplicon size
 (approximately 400 bp) for library construction (10x Genomics). The
 concentration of the 10x single-cell library was accurately determined
 through qPCR (Kapa Biosystems) to produce cluster counts appropriate for
 the HiSeq4000 or NovaSeq6000 platform (Illumina). In all, 26 × 98 bp (3′
 v3 libraries) sequence data were generated targeting between 25 and 50K
 read pairs/cell, which provided digital gene expression profiles for each
 individual cell. For single-cell RNA-seq analysis, we
 used CellRanger (10x Genomics, v.6.1.2) to pre-process the single-cell
 RNA-seq data after obtaining the paired-end raw reads. Cell barcodes and
 unique molecular identifiers (UMIs) of the library were extracted from
 read 1. Then, the reads were split according to their cell (barcode) IDs,
 and the UMI sequences from read 2 were simultaneously recorded for each
 cell. Quality control on these raw readings was subsequently performed to
 eliminate adapter contamination, duplicates, and low-quality bases. After
 filtering barcodes and low-quality readings that were not related to
 cells, we mapped the cleaned readings to the human genome (GRCh38) and
 retained the uniquely mapped readings for UMIs counts. Next, we estimated
 the accurate molecular counts and generated a UMI count matrix for each
 cell by counting UMIs for each sample. Finally, we generated a
 gene-barcode matrix that showed the barcoded cells and gene expression
 counts.
description: # Reconstitution of the Multiple Myeloma Microenvironment Following
 Lymphodepletion with BCMA CAR-T Therapy
 [https://doi.org/10.5061/dryad.44j0zpcn7](https://doi.org/10.5061/dryad.44j0zpcn7) The collected paired BM specimens from MM patients before and after BCMA CAR-T therapy were isolated into single cell suspensions, and 3'-scRNA-seq (Chromium Single Cell 3' v3 Libraries) analysis was performed on each sample. ## Description of the data and file structure The dataset includes '.mtx' files, each of which is for creating a Seurat object in R. The naming convention of the '.mtx' files was following the sampling time points of the MM patients receiving BCMA CAR-T therapy. Specifically, the 14 BM specimens that performed scRNA-seq were collected from 7 relapsed or refractory MM patients (i.e. 'P1, P2, P3, P4, P5, P6, and P7') before and after BCMA CAR-T therapy. For these specimens, the baseline (i.e. 'B') specimens (P1_B, P2_B, P3_B, P4_B, P5_B, P6_B, and P7_B) were collected from P1-P7 on day -4 before BCMA CAR-T therapy, and the remission stage (i.e. 'R') specimens (P1_R, P2_R, P3_R, P4_R, P5_R, P6_R, and P7_R) were collected from P1-P7 on day 28 after BCMA CAR-T cell infusion. The '.mtx' files contained gene-barcode matrix that showed the barcoded cells and gene expression counts. In these matrices, each row represents a barcoded cell name, and each column represents a gene name. Thus, the analysis of the expression level of each gene in each cell was available. ## Sharing/Access information Human transcriptome reference used for our analysis is available at 10x Genomics website ([https://cf.10xgenomics.com/supp/cell-exp/refdata-cellranger-GRCh38-3.0.0.tar.gz](https://cf.10xgenomics.com/supp/cell-exp/refdata-cellranger-GRCh38-3.0.0.tar.gz)); the code used for scRNA-seq analysis is available at 10x Genomics website ([https://www.10xgenomics.com/support/software/cell-ranger/latest/analysis/running-pipelines/cr-gex-count](https://www.10xgenomics.com/support/software/cell-ranger/latest/analysis/running-pipelines/cr-gex-count) and at GitHub website ([https://github.com/satijalab/seurat/releases/tag/v4.0.2).](https://github.com/satijalab/seurat/releases/tag/v4.0.2\).) ## Code/Software The single-cell RNA sequencing data was processed using cellranger (v.6.1.2) and analyzed with the R package Seurat (v.4.0.2). To analyze the data, firslty running the packages that provided in the code under the R Studio operating environment. Then, inputting all of the '.mtx' files for creating the Seurat object, for which the custom storage path of the downloaded data needing to be changed in the provided script to input the data. The downstream analyses can fully followed the provided code.