← BioTransfer GEO Dataset Finder
GEO series

Epigenetic regulators of clonal hematopoiesis control CD8 T cell stemness during immunotherapy [ATAC-seq]

GSE274863 Mus musculus (mouse) ChIP-seq / ATAC-seq (genome binding and open chromatin) 16 samples Submitted 2024/10/10 Platform GPL24247
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · mouse · 16 samples

What it is
ChIP-seq / ATAC-seq (genome binding and open chromatin)Where proteins bind the genome, or which regions are open and active.
Organism
Mus musculus (mouse)
Samples
16 samples: 16 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
Epigenetic regulators of clonal hematopoiesis control CD8 T cell stemness during immunotherapyScience (New York, N.Y.) · 2024
Summary (written by the submitters)
Epigenetic reinforcement of T cell exhaustion is a major barrier limiting durability of T cell responses during immunotherapy, however the central epigenetic regulators restricting therapy-enabling T cell stemness in settings of prolonged antigen exposure remain to be fully resolved. Here we investigated DNMT3A, TET2, and ASXL1, the three most commonly mutated epigenetic regulators promoting clonal hematopoiesis (CH), to determine if they control the cardinal features of T cell stemness.
Read the full summary ↓
Using a canonical murine model of exhaustion, we show that CD8 T cells lacking Dnmt3a, Tet2, or Asxl1 are able to preserve an immune checkpoint blockade (ICB) responsive progenitor-exhausted (Tpex) population for over a year during chronic antigen exposure without undergoing malignant transformation. Specific investigation into the lesser-studied regulator, Asxl1, revealed that this unprecedented maintenance of Tpex was achieved through preservation of the cell’s self-renewal capacity with less terminal differentiation. Mechanistic investigation into the role of Asxl1 during CD8 T cell differentiation revealed epigenetic modification of the PR-DUB pathway involving H2AK119-ubiquitination. Extending this Tpex-preserving mechanism to immunotherapy, we report synergy between Asxl1 deficient T cells and anti-PDL1, resulting in heightened tumor control in murine tumor models and a survival advantage to the mutated T cells in treated patients. These data collectively define a core set of epigenetic regulators that control longevity of the stem-like T cell population responsible for clinical success during cancer immunotherapy.
Published in
Epigenetic regulators of clonal hematopoiesis control CD8 T cell stemness during immunotherapy
Kang TG, Lan X, Mi T et al. · Science (New York, N.Y.) 2024 · PMID 39388542 · doi:10.1126/science.adl4492
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 GSE274863_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: Look for peak files (.bed, .narrowPeak) and signal tracks (.bigWig) among the supplementary files; the raw reads are on ENA.

Also filed as BioProject PRJNA1148210 and SRA study SRP526442. Searching any of these in the dataset finder brings you back here.

Study design
16 samples, each with a distinct title — no replicated groups

Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.

How we read this: Read from 16 sample titles: 16 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.

Samples in this study
Datasets on a similar topic

Search all mouse ChIP / ATAC / CUT&Tag datasets in GEO →

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.