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| Status |
Public on Jul 29, 2024 |
| Title |
Myeloma_patient_03_T_cells, Surface protein (T4_CSFL) |
| Sample type |
SRA |
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| Source name |
Bone Marrow
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| Organism |
Homo sapiens |
| Characteristics |
individual: Myeloma_patient_03
cell subtype: T cells
cell type: Immune and tumor cells
tissue: Bone Marrow
timepoint: 270d post treatment
library type: Antibody-derived oligonucleotide (ADT)
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| Extracted molecule |
protein |
| Extraction protocol |
Bone marrow aspirates were diluted 1:1 in FACS buffer (PBS without magnesium or calcium, with 0.1% BSA and 2 mM EDTA). Peripheral blood samples were diluted 1:2 in FACS buffer. Mononuclear cell separation was performed by density centrifugation (Ficollpauqe, GE) with diluted bone marrow cells. Cells were manually aspirated and washed with FACS buffer. Red blood cells were lysed using RBC lysis buffer (Invitrogen) for 5 min at 4C. Within 1 hour of processing, cells were stained and sorted (Aria Fusion, BD) based on forward and side scatter, gated on CD45+ CD19- CD3+ (T cells) and CD45+ CD19- CD3- (nonB nonT cells).
Droplet-based single cell RNA sequencing (scRNAseq) was performed using the 10x 5ʹ Reagent Kits version 1, according to manufacturer instructions. 10X 5’ kits for TCR amplification were used to generate libraries per manufacturer instructions.
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| Library strategy |
OTHER |
| Library source |
other |
| Library selection |
other |
| Instrument model |
Illumina NovaSeq 6000 |
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| Description |
10x Genomics
T4_barcodes.tsv.gz, T4_features.tsv.gz, T4_matrix.mtx.gz
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| Data processing |
All sequencing was performed on an Illumina NovaSeq S4 sequencer with paired end 200 base pair read length and 25,000 reads per droplet for gene expression and 5,000 reads for TCR libraries.
CellRanger version 5 (10x Genomics, Genome Build: GRCh38 3.0.0) was used to align the raw sequencing data.
Doublet detection scoring was performed on the filtered gene expression matrices from Cell Ranger using DoubletDetection with default parameters, and then the combined gene expression matrix were analyzed by Scanpy pipeline. The following filters were set to retain high-quality cells: 1) cells with less than 10% mitochondrial transcripts, 2) number of detected genes per cell was above 100 but below 2,500 genes, 3) genes expressed in at least 3 cells were kept, 4) platelets (PF4 UMI>0), red blood cells (HBB UMI>1), and doublets were removed. We then used scanpy to normalize, logarithmize, and scale the data, identify highly variable genes, and perform principal component analysis. We used Combat and Harmony for batch correction prior to Leiden clustering and UMAP visualization
Assembly: GRCh38 3.0.0
Supplementary files format and content: 10x Genomics cellranger output files: barcodes.tsv.gz, features.tsv.gz, matrix.mtx.gz; VDJ cellranger output: comma separated values files
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| Submission date |
Oct 26, 2023 |
| Last update date |
Jul 29, 2024 |
| Contact name |
Lawrence Fong |
| Organization name |
UCSF
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| Department |
Helen Diller Family Comprehensive Cancer Center
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| Lab |
Fong Lab
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| Street address |
513 Parnassus Ave, HSE 301
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| City |
San Francisco |
| State/province |
California |
| ZIP/Postal code |
94143 |
| Country |
USA |
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| Platform ID |
GPL24676 |
| Series (2) |
| GSE246342 |
CD4+ CAR-T cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR-T cell therapy I |
| GSE274187 |
CD4+ CAR-T cell exhaustion associated with early relapse of multiple myeloma after BCMA CAR-T cell therapy |
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| Relations |
| BioSample |
SAMN37999474 |
| SRA |
SRX22240641 |
| Supplementary data files not provided |
SRA Run Selector |
| Raw data are available in SRA |
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