PD-1 regulates latent effector differentiation of thymic cytotoxic CD8+ T cells
RNA-seq (gene expression) · human · 74 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Samples
- 74 samples: 67 distinct titles, 1 of them repeatedGroups 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
- PD-1 regulates latent effector differentiation of thymic cytotoxic CD8(+) T cellsNature communications · 2026
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 GSE333858_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: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1472703 and SRA study SRP693098. Searching any of these in the dataset finder brings you back here.
How we read this: Read from 74 sample titles: 67 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.
- GSM9683361 Multiplexed_1
- GSM9683362 Multiplexed_2
- GSM9683363 Multiplexed_3
- GSM9683364 Multiplexed_4
- GSM9683365 Multiplexed_5
- GSM9683366 Multiplexed_6
- GSM9683367 Multiplexed_7
- GSM9683368 Multiplexed_8
- GSM9686182 Pdcd1fl/fl, thymic CD8+ T cells baseline scRNA seq
- GSM9686183 Pdcd1 cKO, thymic CD8+ T cells baseline scRNA seq
- GSM9686184 Pdcd1fl/fl, splenic CD8+ T cells baseline scRNA seq
- GSM9686185 Pdcd1 cKO, splenic CD8+ T cells baseline scRNA seq
- GSM9686186 Pdcd1fl/fl, CD8+ TIL scRNA seq
- GSM9686187 Pdcd1 cKO, CD8+ TIL scRNA seq
- GSM9686886 JR-6989_E5 | JR_6989_E5_001 | NKG7+ CD8+
- GSM9686887 JR-6989_E5 | JR_6989_E5_001 | NKG7- CD8+
- GSM9686888 JR-6989_E5 | JR_6989_E5_002 | NKG7+ CD8+
- GSM9686889 JR-6989_E5 | JR_6989_E5_002 | NKG7- CD8+
- GSM9686890 JR-6989_E5 | JR_6989_E5_003 | NKG7+ CD8+
- GSM9686891 JR-6989_E5 | JR_6989_E5_004 | NKG7+ CD8+
- GSM9686892 JR-6989_E5 | JR_6989_E5_004 | NKG7- CD8+
- GSM9686893 JR-6989_E5 | JR_6989_E5_005 | NKG7+ CD8+
- GSM9686894 JR-6989_E5 | JR_6989_E5_006 | NKG7+ CD8+
- GSM9686895 JR-6989_E5 | JR_6989_E5_006 | NKG7- CD8+
- GSM9686896 JR-6989_E5 | JR_6989_E5_007 | NKG7+ CD8+
- GSM9686897 JR-6989_E5 | JR_6989_E5_007 | NKG7- CD8+
- GSM9686898 JR-6989_E5 | JR_6989_E5_008 | NKG7+ CD8+
- GSM9686899 JR-6989_E5 | JR_6989_E5_008 | NKG7- CD8+
- GSM9686900 JR19_1207_D12 | JR191207_D12_001 | NKG7+ CD8+
- GSM9686901 JR19_1207_D12 | JR191207_D12_001 | NKG7- CD8+
- GSM9686902 JR19_1207_D12 | JR191207_D12_002 | NKG7+ CD8+
- GSM9686903 JR19_1207_D12 | JR191207_D12_002 | NKG7- CD8+
- GSM9686904 JR19_1207_D12 | JR191207_D12_003 | NKG7+ CD8+
- GSM9686905 JR19_1207_D12 | JR191207_D12_004 | NKG7+ CD8+
- GSM9686906 JR19_1207_D12 | JR191207_D12_004 | NKG7- CD8+
- GSM9686907 JR19_1207_D12 | JR191207_D12_005 | NKG7+ CD8+
- GSM9686908 JR19_1207_D12 | JR191207_D12_005 | NKG7- CD8+
- GSM9686909 JR19_1207_D12 | JR191207_D12_006 | NKG7+ CD8+
- GSM9686910 JR19_1207_D12 | JR191207_D12_007 | NKG7+ CD8+
- GSM9686911 JR19_1207_D12 | JR191207_D12_007 | NKG7- CD8+
+ 34 more — browse all 74 samples with per-sample file links →
- GSE261093 The TET2 methylcytosine dioxygenase regulates early and late transitions in exhausted CD8+ T-cell differentiation 51 samples shares cd8
- GSE260599 Anti-tumor activity of a novelLAIR1antagonist in combination with anti-PD-1to treat collagen-rich solid tumors 61 samples shares pd-1
- GSE89308 Epigenetic analysis of tumor-specific CD8 T cells in murine and solid tumors 59 samples shares cd8
- GSE235246 Senescent cancer-associated fibroblasts in pancreatic adenocarcinoma impair CD8+ T cell activation and responsiveness to immunotherapy in mice 38 samples shares cd8
- GSE242839 PD-1 is induced on tumor-associated macrophages in obesity to directly restrain anti-tumor immunity 29 samples shares pd-1
- GSE264352 Enfortumab Vedotin Induces Immunogenic Cell Death and Shows Enhanced Preclinical Antitumor Activity When Combined With a PD-1 Inhibitor 21 samples shares pd-1
- GSE255177 Inhibiting CXCR4 Attenuates TOX-Programmed Exhausted Phenotype of CD8+ T cells via Regulating JAK2/STAT3 Pathway [ChIP-Seq] 20 samples shares cd8
- GSE314446 Human GPR15 deficiency reveals CD8+ T regulatory cell-macrophage crosstalk in intestinal inflammation 16 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.