Clonal CD8+ T Cells Populate the Leptomeninges and Coordinate with Immune Cells in Human Degenerative Brain Diseases
Single-cell RNA-seq · human · 113 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
- Homo sapiens (human)
- Samples
- 113 samples: 113 samples, each with a distinct title — no replicated groupsGroups 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.
- Paper
- Clonal CD8(+) T cells populate the leptomeninges and coordinate with immune cells in human degenerative brain diseasesNature immunology · 2026
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 GSE288856_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 PRJNA1219638 and SRA study SRP561816. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 113 sample titles: 113 distinct titles with little repetition. 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.
- GSM8776832 leptomeninges, patient 1, RNA
- GSM8776833 leptomeninges, patient 2, RNA
- GSM8776834 leptomeninges, patient 3, RNA
- GSM8776835 leptomeninges, patient 4, RNA
- GSM8776836 leptomeninges, patient 5, RNA
- GSM8776837 leptomeninges, patient 6, RNA
- GSM8776838 leptomeninges, patient 7, RNA
- GSM8776839 leptomeninges, patient 8, RNA
- GSM8776840 leptomeninges, patient 9, RNA
- GSM8776841 leptomeninges, patient 10, RNA
- GSM8776842 leptomeninges, patient 11, RNA
- GSM8776843 leptomeninges, patient 12, RNA
- GSM8776844 leptomeninges, patient 13, RNA
- GSM8776845 leptomeninges, patient 14, RNA
- GSM8776846 leptomeninges, patient 15, RNA
- GSM8776847 leptomeninges, patient 16, RNA
- GSM8776848 leptomeninges, patient 17, RNA
- GSM8776849 leptomeninges, patient 18, RNA
- GSM8776850 leptomeninges, patient 19, RNA
- GSM8776851 leptomeninges, patient 21, RNA
- GSM8776852 leptomeninges, patient 22, RNA
- GSM8776853 leptomeninges, patient 23, RNA
- GSM8776854 leptomeninges, patient 24, RNA
- GSM8776855 leptomeninges, patient 25, RNA
- GSM8776856 leptomeninges, patient 26, RNA
- GSM8776857 leptomeninges, patient 27, RNA
- GSM8776859 leptomeninges, patient 28, RNA
- GSM8776861 leptomeninges, patient 29, RNA
- GSM8776863 motor cortex, patient 2, RNA
- GSM8776865 hippocampus, patient 3, RNA
- GSM8776867 parietal, patient 3, RNA
- GSM8776869 hippocampus, patient 4, RNA
- GSM8776870 hippocampus, patient 6, RNA
- GSM8776871 hippocampus, patient 7, RNA
- GSM8776872 hippocampus, patient 8, RNA
- GSM8776873 parietal, patient 8, RNA
- GSM8776874 motor cortex, patient 10, RNA
- GSM8776875 hippocampus, patient 13, RNA
- GSM8776876 motor cortex, patient 15, RNA
- GSM8776877 hippocampus, patient 16, RNA
+ 73 more — browse all 113 samples with per-sample file links →
- GSE210231 CD8+ T cell memory induced by successive SARS-CoV-2 mRNA vaccinations is characterized by shifts in clonal dominance 931 samples shares cd8, clonal
- GSE272993 Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8 T cells [dataset 1] 360 samples shares cd8, clonal
- GSE279781 CD137 agonism enhances anti-PD1 induced activation of clonally expanded CD8+ T cells in a neoadjuvant pancreatic cancer clinical trial 30 samples shares cd8, clonal
- GSE291804 Multi-omics analysis of brain metastasis elucidates obesity induced prostaglandin crosstalk in tumor microenvironment restrain CD8T cell expansion 18 samples shares cd8, brain
- GSE316096 Clonal expansion of cytotoxic CD8+ T cells in lecanemab-associated ARIA 18 samples shares cd8, clonal
- GSE280113 Progenitor effects and unique transcriptomic signatures linked to differentiation phenotype in clonally expanded antigen-specific CD8 T memory stem cells (TSCM) 509 samples shares cd8, clonal
- GSE272734 Combination anti-PD-1 and anti-CTLA-4 therapy generates waves of clonal responses that include progenitor-exhausted CD8 T cells [dataset 2] 40 samples shares cd8, clonal
- GSE225063 Blockade of LAG-3 and PD-1 leads to co-expression of cytotoxic and exhaustion gene modules in CD8+ T cells to promote antitumor immunity 256 samples shares cd8
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.