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α2,6-Sialoglycan-regulated anti-tumor immunity of tumor-infiltrating CD8+ T cells in the tumor microenvironment [CD8+T]

GSE316541 Mus musculus (mouse) Single-cell RNA-seq 27 samples Submitted 2026/08/01 Platform GPL24247
At a glance

Single-cell RNA-seq · mouse · 27 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
27 samples: 9 conditions, mostly in triplicateGroups 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.
Summary (written by the submitters)
Cell-surface sialoglycans overexpressed on cancer cells suppress the activation of tumor-infiltrating immune cells (TIICs), and have emerged as a promising target for cancer immunotherapy. However, the functional roles of sialylation in TIICs remain incompletely understood. Here, we develop the single-cell correlative analysis of α2,3- and α2,6-linked sialoglycans and transcriptomes (scCAST_3&6) strategy to correlate cell-surface sialylation in a linkage-specific manner with gene expression of the same cells by single-cell RNA sequencing.
Read the full summary ↓
Applying scCAST_3&6, we discover that α2,3- and α2,6-sialoglycans are distinctively regulated in specific TIIC subpopulations. Importantly, downregulated α2,6-sialoglycan is demonstrated as a cell-surface marker for labeling and isolating CD8+ T cells with high reactivity to tumor-specific antigens (TSAs) from the tumor. Mechanistically, α2,6-sialyltransferase ST6Gal-I is transcriptionally suppressed upon the activation of intratumoral CD8+ T cells with high-avidity T cell receptors towards tumor antigens, which downregulates α2,6-sialylation and exposes galectin-1 ligands. Functionally, increased galectin-1 binding to TSA-reactive CD8+ T cells promotes T cell apoptosis and cancer immune evasion. This work underscores the functional significance and therapeutic promise of specific sialoglycans on TIICs.
This dataset
Open GSE316541 in finder → Find more mouse RNA-seq datasets →
Download · which file do I need?

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.

1 · Just have a look

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.

Series matrix ↓
2 · Re-analyse it

Supplementary files

The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE316541_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
3 · Start from the raw reads

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.

Raw reads on ENA ↗

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 PRJNA1403296 and SRA study SRP662662. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
9 conditions, mostly in triplicate
OT1 CD8+T, day0, ×3 OVA stimulated, day2, ×3 Q4 stimulated, day2, ×3 V4 stimulated, day2, ×3 OVA stimulated, day1, ×3 Q4 stimulated, day1, ×3 V4 stimulated, day1, ×3 CD3/CD28 Dynabeads stimulated, day1, ×3 +1 more

Supports a between-group comparison across 27 samples.

How we read this: 9 replicated groups read from 27 sample titles; they account for 27 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.

Samples in this study
Datasets on a similar topic

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