In vitro PI3Kδ inhibition skews CD8 T cell differentiation towards progenitor exhaustion in vivo and reprograms tumor microenvironment metabolism, immune composition, and inflammation [scRNA-seq]
Single-cell RNA-seq · mouse · 12 samples
- What it is
- Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
- Organism
- Mus musculus (mouse)
- Samples
- 12 samples
- 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
- PI3Kδ inhibition alters CD8 T cell differentiation and reprograms the tumor microenvironment following adoptive immunotherapyJournal of immunology (Baltimore, Md. : 1950) · 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 GSE286925_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 PRJNA1210553 and SRA study SRP557243. Searching any of these in the dataset finder brings you back here.
The sample list for this study is not cached yet. Press Load samples and it will be fetched from NCBI.
+ 12 more — browse all 12 samples with per-sample file links →
- GSE307051 Active aldehydes accelerate CD8+ T cell exhaustion by metabolic alteration in the tumor microenvironment 3 samples shares cd8, microenvironment, exhaustion
- GSE291447 Targeting CD11b+ regulatory B cells via RAS/RAF/PI3K pathway inhibition augments response to immune checkpoint blockade or CD40 agonism in metastatic melanoma 60 samples shares pi3k, inhibition
- GSE223164 Osr2 functions as a biomechanical checkpoint to aggravate CD8+ T cell exhaustion in tumor 49 samples shares cd8, exhaustion
- GSE316541 α2,6-Sialoglycan-regulated anti-tumor immunity of tumor-infiltrating CD8+ T cells in the tumor microenvironment [CD8+T] 27 samples shares cd8, microenvironment
- GSE262842 Antitumor progenitor exhausted CD8 T cells are sustained with TCR engagement [ATACseq] 24 samples shares cd8, progenitor
- GSE269676 3D genome of CD8+ T cells reveals IRF8-mediated exhaustion in cancer 18 samples shares cd8, exhaustion
- GSE277610 Endothelial PD-L1 brakes CD8+ T cell exhaustion, empowering anti-tumor immunity in non-small cell lung cancer 17 samples shares cd8, exhaustion
- GSE310452 Sustained A2AR expression and loss paradoxically promote CD8+ T cell exhaustion 12 samples shares cd8, exhaustion
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.