GEO series
Tumor-reactive heterotypic CD8 T cell clusters from clinical samples
GSE283942
Homo sapiens (human)
Single-cell RNA-seq
28 samples
Submitted 2025/09/15
Platform GPL24676
At a glance
Single-cell RNA-seq · human · 28 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
- 28 samples: 6 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.
- Paper
- Tumour-reactive heterotypic CD8 T cell clusters from clinical samplesNature · 2026
Summary (written by the submitters)
Emerging evidence suggests a correlation between CD8+ T cell-tumor cell proximity and immunotherapy response1–3. However, it is unknown whether these cells can be captured as functional clusters from clinical samples. In defined human co-cultures, tumor antigen-recognizing T cells outcompeted unmatched T cells in forming clusters with tumor cells, prompting us to investigate whether this feature could be used to isolate tumor-reactive T cells directly from cancer specimens.
Read the full summary ↓
By conventional and imaging flow cytometry, we show here that from 21/21 human melanoma metastases, we were able to isolate heterotypic clusters, comprising CD8+ T cells interacting with one or more tumor cells and/or antigen-presenting cells (APCs). Single cell RNA-sequencing revealed that CD8+ T cells from clusters were enriched for tumor-reactive and exhausted gene signatures. Integration with T cell receptor (TCR)-sequencing showed increased clonality of clustered T cells, indicative of expansion. In-depth analyses revealed that these T cells had conjugated with tumor cells and various APCs, each exhibiting specific enriched cell states, which were linked to distinct patterns of cell-cell communication. CD8+ T cells expanded from clusters ex vivo exerted on average 9-fold increased killing activity towards autologous melanomas, accompanied by enhanced cytokine production. Also upon adoptive cell transfer (ACT) into mice, T cells from clusters showed superior patient-derived xenograft (PDX) killing associated with more T cell infiltration and activation. Together, these results demonstrate that tumor-reactive CD8+ T cells are enriched in functional clusters with tumor cells and/or APCs, and that they can be isolated and expanded from clinical samples. Typically excluded during single-cell sorting by flow cytometry, these distinct heterotypic CD8+ T cell clusters serve as a valuable source amenable to deciphering functional tumor-immune cell interactions, while they may also be therapeutically explored.
Published in
Ibáñez-Molero S, Veldman J, Simon Nieto J et al.
· Nature 2026
· PMID 41261135
· doi:10.1038/s41586-025-09754-w
This dataset
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.
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 GSE283942_RAW.tar (it can run to tens of gigabytes).
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.
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 PRJNA1196361. Searching any of these in the dataset finder brings you back here.
Study design
6 conditions, mostly in triplicate
tumor cell clusters GEX ×3
tumor cell clusters TCR ×3
APC clusters GEX ×3
APC clusters TCR ×3
tumor cell, CD8+ T cell:APC clusters GEX ×2
tumor cell, CD8+ T cell:APC clusters TCR ×2
Patient 1 (AKB460) APC,tumor, and CD8+ T cell… ×1
Patient 1 (AKB460) APC,tumor, and CD8+ T cell… ×1
+10 more
Supports a between-group comparison across 16 samples.
How we read this: 6 replicated groups read from 28 sample titles; they account for 16 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
- GSM8674578 Patient 1 (AKB460) CD8+ T cell:tumor cell clusters GEX tumor cell clusters GEX
- GSM8674579 Patient 1 (AKB460) CD8+ T cell:tumor cell clusters TCR tumor cell clusters TCR
- GSM8674580 Patient 1 (AKB460) CD8+ T cell:APC clusters GEX APC clusters GEX
- GSM8674581 Patient 1 (AKB460) CD8+ T cell:APC clusters TCR APC clusters TCR
- GSM8674582 Patient 1 (AKB460) APC,tumor, and CD8+ T cell singlets GEX
- GSM8674583 Patient 1 (AKB460) APC,tumor, and CD8+ T cell singlets TCR
- GSM8674584 Patient 2 (SJ2) CD8+ T cell:tumor cell, CD8+ T cell:APC clusters GEX tumor cell, CD8+ T cell…
- GSM8674585 Patient 2 (SJ2) CD8+ T cell:tumor cell, CD8+ T cell:APC clusters TCR tumor cell, CD8+ T cell…
- GSM8674586 Patient 2 (SJ2) APC,tumor, and CD8+ T cell singlets GEX
- GSM8674587 Patient 2 (SJ2) APC,tumor, and CD8+ T cell singlets TCR
- GSM8674588 Patient 8 (SJ18) CD8+ T cell:tumor cell, CD8+ T cell:APC clusters GEX tumor cell, CD8+ T cell…
- GSM8674589 Patient 8 (SJ18) CD8+ T cell:tumor cell, CD8+ T cell:APC clusters TCR tumor cell, CD8+ T cell…
- GSM8674590 Patient 8 (SJ18) APC,tumor, and CD8+ T cell singlets GEX
- GSM8674591 Patient 8 (SJ18) APC,tumor, and CD8+ T cell singlets TCR
- GSM8674592 Patient 9 (SJ20) CD8+ T cell:tumor cell clusters GEX tumor cell clusters GEX
- GSM8674593 Patient 9 (SJ20) CD8+ T cell:tumor cell clusters TCR tumor cell clusters TCR
- GSM8674594 Patient 9 (SJ20) CD8+ T cell:APC clusters GEX APC clusters GEX
- GSM8674595 Patient 9 (SJ20) CD8+ T cell:APC clusters TCR APC clusters TCR
- GSM8674596 Patient 9 (SJ20) APC,tumor, and CD8+ T cell singlets GEX
- GSM8674597 Patient 9 (SJ20) APC,tumor, and CD8+ T cell singlets TCR
- GSM8674598 Patient 15 (SJ32) CD8+ T cell:tumor cell clusters GEX tumor cell clusters GEX
- GSM8674599 Patient 15 (SJ32) CD8+ T cell:tumor cell clusters TCR tumor cell clusters TCR
- GSM8674600 Patient 15 (SJ32) CD8+ T cell:APC clusters GEX APC clusters GEX
- GSM8674601 Patient 15 (SJ32) CD8+ T cell:APC clusters TCR APC clusters TCR
- GSM8674602 Patient 15 (SJ32) APC,tumor, and CD8+ T cell singlets GEX
- GSM8674603 Patient 15 (SJ32) APC,tumor, and CD8+ T cell singlets TCR
- GSM9105214 Patient 8 & 15 (SJ18 & SJ32) CD39+ CD8+ T cells GEX
- GSM9105215 Patient 8 & 15 (SJ18 & SJ32) CD39+ CD8+ T cells TCR
Datasets on a similar topic
- 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, clinical
- GSE210231 CD8+ T cell memory induced by successive SARS-CoV-2 mRNA vaccinations is characterized by shifts in clonal dominance 931 samples shares cd8
- 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
- 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
- GSE288199 Distinct CD8+ T cell dynamics associate with response to neoadjuvant cancer immunotherapies 180 samples shares cd8
- GSE288856 Clonal CD8+ T Cells Populate the Leptomeninges and Coordinate with Immune Cells in Human Degenerative Brain Diseases 113 samples shares cd8
- GSE308745 The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment.[PB cohort2] 87 samples shares cd8
- GSE298811 Immune dysregulation and stem-like CD8+ T cell enrichment in type 1 diabetes pancreatic lymph nodes 57 samples shares cd8
Share this dataset
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.