Expansion of Tumor-Infiltrating CD8+ T Cell Clonotypes Occurs in the Spleen in Response to Immune Checkpoint Blockade
Single-cell RNA-seq · mouse · 29 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
- Organism
- Mus musculus (mouse)
- Samples
- 29 samples: 8 conditions, mostly in duplicateGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE270050_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.
Also filed as BioProject PRJNA1124914 and SRA study SRP514351. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 21 samples.
How we read this: 8 replicated groups read from 29 sample titles; they account for 21 of them. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8333770 Untreated_HTO_Tumor
- GSM8333771 Untreated_HTO_TdLN
- GSM8333772 Untreated_HTO_Spleen1 Untreated_HTO_Spleen
- GSM8333773 Untreated_HTO_Spleen2 Untreated_HTO_Spleen
- GSM8333774 CBT_HTO_Tumor
- GSM8333775 CBT_HTO_TdLN1 CBT_HTO_TdLN
- GSM8333776 CBT_HTO_TdLN2 CBT_HTO_TdLN
- GSM8333777 CBT_HTO_Spleen1 CBT_HTO_Spleen
- GSM8333778 CBT_HTO_Spleen2 CBT_HTO_Spleen
- GSM8333779 CBT_HTO_Spleen3 CBT_HTO_Spleen
- GSM8333780 Untreated_DEG_Tumor
- GSM8333781 Untreated_DEG_TdLN
- GSM8333782 Untreated_DEG_Spleen1 Untreated_DEG_Spleen
- GSM8333783 Untreated_DEG_Spleen2 Untreated_DEG_Spleen
- GSM8333784 CBT_DEG_Tumor
- GSM8333785 CBT_DEG_TdLN1 CBT_DEG_TdLN
- GSM8333786 CBT_DEG_TdLN2 CBT_DEG_TdLN
- GSM8333787 CBT_DEG_Spleen1 CBT_DEG_Spleen
- GSM8333788 CBT_DEG_Spleen2 CBT_DEG_Spleen
- GSM8333789 CBT_DEG_Spleen3 CBT_DEG_Spleen
- GSM8333790 Untreated_TCR
- GSM8333791 CBT_TCR
- GSM8445080 INT_1 INT
- GSM8445081 INT_2 INT
- GSM8445082 INT_3 INT
- GSM8445083 KLR_1 KL
- GSM8445084 INT_4 INT
- GSM8445085 KLR_2 KL
- GSM8445086 KLR_3 KL
- GSE269347 Daunorubicin-induced T cell remodeling facilitates a high antitumor response to PD-1 blockade therapy by promoting the expansion and effector function of CD8+ prolifeating T cells [scRNA-Seq] 16 samples shares cd8, expansion, blockade
- GSE207029 Blockade of avb8 integrin synergizes with checkpoint inhibition to enhance anti-tumor immunity through Cxcl9-dependent augmentation of CD8+ T cell cytotoxicity 12 samples shares cd8, checkpoint, blockade
- GSE304763 A pan-immunotherapy signature to predict intratumoral CD8+ T cell expansions [scTCR_immunotherapies] 91 samples shares cd8, expansion
- GSE223164 Osr2 functions as a biomechanical checkpoint to aggravate CD8+ T cell exhaustion in tumor 49 samples shares cd8, checkpoint
- GSE157232 The CD8+ T cell tolerance checkpoint triggers a transcriptionally and epigenetically distinct differentiation state defined by protein translation defects 30 samples shares cd8, checkpoint
- GSE316541 α2,6-Sialoglycan-regulated anti-tumor immunity of tumor-infiltrating CD8+ T cells in the tumor microenvironment [CD8+T] 27 samples shares cd8, tumor-infiltrating
- GSE290839 PD-1 regulates tumor-infiltrating CD8+ T cells in both a cell-intrinsic and cell-extrinsic fashion [scRNA-seq] 20 samples shares cd8, tumor-infiltrating
- GSE223157 Osr2 functions as a mechanical checkpoint to augment CD8+ T cell exhaustion [YODA1_vs_DMSO_ATAC_CD8] 12 samples shares cd8, checkpoint
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.