α2,6-Sialoglycan-regulated anti-tumor immunity of tumor-infiltrating CD8+ T cells in the tumor microenvironment
Single-cell RNA-seq · mouse · 9 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
- 9 samples: 3 × RNA-seq, Sia2,6hiPD-1−CD8+ T, replication vs 3 × RNA-seq, Sia2,6hiPD-1+CD8+ T, replication vs 3 × RNA-seq, Sia2,6loPD-1+CD8+ T, replicationGroups 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 GSE316540_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 PRJNA1403295 and SRA study SRP662660. Searching any of these in the dataset finder brings you back here.
Supports a between-group comparison across 9 samples.
How we read this: 3 replicated groups read from 9 sample titles; they account for 9 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.
- GSM9455546 RNA-seq, Sia2,6hiPD-1−CD8+ T, replication 1 RNA-seq, Sia2,6hiPD-1−C…
- GSM9455547 RNA-seq, Sia2,6hiPD-1−CD8+ T, replication 2 RNA-seq, Sia2,6hiPD-1−C…
- GSM9455548 RNA-seq, Sia2,6hiPD-1−CD8+ T, replication 3 RNA-seq, Sia2,6hiPD-1−C…
- GSM9455549 RNA-seq, Sia2,6hiPD-1+CD8+ T, replication 1 RNA-seq, Sia2,6hiPD-1+C…
- GSM9455550 RNA-seq, Sia2,6hiPD-1+CD8+ T, replication 2 RNA-seq, Sia2,6hiPD-1+C…
- GSM9455551 RNA-seq, Sia2,6hiPD-1+CD8+ T, replication 3 RNA-seq, Sia2,6hiPD-1+C…
- GSM9455552 RNA-seq, Sia2,6loPD-1+CD8+ T, replication 1 RNA-seq, Sia2,6loPD-1+C…
- GSM9455553 RNA-seq, Sia2,6loPD-1+CD8+ T, replication 2 RNA-seq, Sia2,6loPD-1+C…
- GSM9455554 RNA-seq, Sia2,6loPD-1+CD8+ T, replication 3 RNA-seq, Sia2,6loPD-1+C…
- GSE316541 α2,6-Sialoglycan-regulated anti-tumor immunity of tumor-infiltrating CD8+ T cells in the tumor microenvironment [CD8+T] 27 samples shares cd8, 6-sialoglycan-regulated, tumor-infiltrating, microenvironment, anti-tumor, immunity
- GSE234974 Pan-cancer mapping of single CD8+ T cell profiles reveals a TCF1:CXCR6 axis regulating CD28 co-stimulation and anti-tumor immunity I 24 samples shares cd8, anti-tumor, immunity
- GSE277610 Endothelial PD-L1 brakes CD8+ T cell exhaustion, empowering anti-tumor immunity in non-small cell lung cancer 17 samples shares cd8, anti-tumor, immunity
- 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, anti-tumor, immunity
- 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
- GSE299133 Host MTDH orchestrates liver lipid metabolism and CD8+ T cells to suppress antitumor immunity [Hepatocytes] 18 samples shares cd8, immunity
- GSE276107 Host MTDH orchestrates liver lipid metabolism and CD8+ T cells to suppress antitumor immunity 44 samples shares cd8, immunity
- GSE270050 Expansion of Tumor-Infiltrating CD8+ T Cell Clonotypes Occurs in the Spleen in Response to Immune Checkpoint Blockade 29 samples shares cd8, tumor-infiltrating
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.