The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment.[S1-S3]
Single-cell RNA-seq · human · 24 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
- 24 samples: 24 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
- The CD4(+) T cell population partners with Tpex CD8(+) T cells to mediate antitumor immunity in the tumor microenvironmentNature communications · 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 GSE267026_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 PRJNA1109362 and SRA study SRP506586. 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 24 sample titles: 24 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.
- GSM8258650 S1 Th1CD62LlowCD4+ T cell, scRNA-seq
- GSM8258651 S1 CXCR3+Th7RCD62LlowCD4+ T cell, scRNA-seq
- GSM8258652 S1 CXCR3-Th7RCD62LlowCD4+ T cell, scRNA-seq
- GSM8258653 S1 Th17CD62LlowCD4+ T cell, scRNA-seq
- GSM8258654 S2 Th1CD62LlowCD4+ T cell, scRNA-seq
- GSM8258655 S2 CXCR3+Th7RCD62LlowCD4+ T cell, scRNA-seq
- GSM8258656 S2 CXCR3-Th7RCD62LlowCD4+ T cell, scRNA-seq
- GSM8258657 S2 Th17CD62LlowCD4+ T cell, scRNA-seq
- GSM8258658 S3 Th1CD62LlowCD4+ T cell, scRNA-seq
- GSM8258659 S3 CXCR3+Th7RCD62LlowCD4+ T cell, scRNA-seq
- GSM8258660 S3 CXCR3-Th7RCD62LlowCD4+ T cell, scRNA-seq
- GSM8258661 S3 Th17CD62LlowCD4+ T cell, scRNA-seq
- GSM8258662 S1 Th1CD62LlowCD4+ T cell, scTCR-seq
- GSM8258663 S1 CXCR3+Th7RCD62LlowCD4+ T cell, scTCR-seq
- GSM8258664 S1 CXCR3-Th7RCD62LlowCD4+ T cell, scTCR-seq
- GSM8258665 S1 Th17CD62LlowCD4+ T cell, scTCR-seq
- GSM8258666 S2 Th1CD62LlowCD4+ T cell, scTCR-seq
- GSM8258667 S2 CXCR3+Th7RCD62LlowCD4+ T cell, scTCR-seq
- GSM8258668 S2 CXCR3-Th7RCD62LlowCD4+ T cell, scTCR-seq
- GSM8258669 S2 Th17CD62LlowCD4+ T cell, scTCR-seq
- GSM8258670 S3 Th1CD62LlowCD4+ T cell, scTCR-seq
- GSM8258671 S3 CXCR3+Th7RCD62LlowCD4+ T cell, scTCR-seq
- GSM8258672 S3 CXCR3-Th7RCD62LlowCD4+ T cell, scTCR-seq
- GSM8258673 S3 Th17CD62LlowCD4+ T cell, scTCR-seq
- 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, microenvironment, population, antitumor, partners, immunity, mediate
- GSE295601 The Cd4+ T cell population Partners with Tpex CD8 T cells to mediate Antitumor Immunity in the Tumor Microenvironment. [P6] 18 samples shares cd8, microenvironment, population, antitumor, partners, immunity, mediate
- 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, antitumor, immunity
- GSE284015 GZMK-expressing tissue-resident memory CD8+ T cells mediate human intestinal acute graft-versus-host disease 26 samples shares cd8, mediate
- GSE291804 Multi-omics analysis of brain metastasis elucidates obesity induced prostaglandin crosstalk in tumor microenvironment restrain CD8T cell expansion 18 samples shares cd8, microenvironment
- GSE235090 Pre-existing skin-resident CD8 and γδ T cell circuits mediate immune response in Merkel cell carcinoma and Predict immunotherapy efficacy [scRNA_tissue] 192 samples shares cd8, mediate
- GSE280318 Characterization of immune cell populations in the tumor microenvironment of colorectal cancer using high definition spatial profiling 39 samples shares microenvironment, population
- GSE210231 CD8+ T cell memory induced by successive SARS-CoV-2 mRNA vaccinations is characterized by shifts in clonal dominance 931 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.