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Mezigdomide reverses T cell exhaustion through degradation of Aiolos/Ikaros and reinvigoration of cytokine production pathways [ChIP-seq]

GSE301715 Homo sapiens (human) ChIP-seq / ATAC-seq (genome binding and open chromatin) 37 samples Submitted 2026/07/04 Platform GPL20301
At a glance

ChIP-seq / ATAC-seq (genome binding and open chromatin) · human · 37 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
Homo sapiens (human)
Samples
37 samples: 37 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.
Summary (written by the submitters)
Given the well-established notion that T cells undergo significant changes in their nuclear architecture and chromatin accessibility between different stages of differentiation or phenotypic stage such as activation and exhaustion, we aimed to investigate the chromatin binding patterns of the Ikaros transcription factor, which plays a crucial role in T cell biology and gene regulation, including development, differentiation and activation in response to TCR stimulation.
Read the full summary ↓
However, a thorough genome-wide analysis of its occupancy and transcriptional regulatory activity between T cell activation and exhaustion has not been performed. To address this, we conducted an integrated epigenomic investigation utilizing Hi-C, ATAC-seq, RNA-seq and ChIP-seq, focusing on Ikaros and histone modifications, including H3K27ac, H3K4me1, and H3K4me3. This approach allows us to understand Ikaros-specific regulation of transcription by characterizing the epigenome in Tact versus Tex cells.
This dataset
Open GSE301715 in finder → Find more human ChIP / ATAC / CUT&Tag datasets →
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.

Series matrix ↓
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 GSE301715_RAW.tar (it can run to tens of gigabytes).

All supplementary files ↗ Whole study · RAW.tar ↓
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.

Raw reads on ENA ↗

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 PRJNA1287468 and SRA study SRP598559. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
37 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 37 sample titles: 37 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

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