GEO series

Degradation of Ikaros prevents epigenetic progression of T cell exhaustion in novel antigen-specific assay [scRNA-seq]

GSE244180 Homo sapiens (human) Single-cell RNA-seq 2 samples Submitted 2024/09/02 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 2 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 2 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.

Summary (written by the submitters)

Epigenetic regulation drives the differentiation of T cells into phenotypically stable subsets including a dysfunctional state termed exhaustion, the presence of these epigenetically distinct T cells in tumors make them non-responsive to checkpoint blockade. Cancer immunotherapies restoring T cell function have transformed cancer treatment by preventing immune evasion of tumor cells allowed by T cell exhaustion.

Read the full summary ↓

However, some patients develop resistance to immunotherapy or do not respond. Recent literature has demonstrated that epigenetic regulation governs the transition from effector to exhausted T cells. Here, we describe a novel antigen-specific assay for T-cell exhaustion that produces T cells biologically and epigenetically similar to their in vivo exhausted counterpart. We perform a CRISPR KO screen for epigenetic regulators of the human genome and validate Ikaros as a driver of T-cell exhaustion. We determined that the Ikaros degrader iberdomide prevents exhaustion by blocking chromatin remodeling at T cell effector enhancers by preserving activity of key transcription factors AP-1, NF-κB and NFAT using transcription factor footprinting analysis. Thus, our study uncovers a role for Ikaros, degraded by the drug iberdomide, as a driver of T-cell exhaustion.

This dataset

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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 GSE244180_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: 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 PRJNA1021609 and SRA study SRP463550. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

Datasets on a similar topic

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GSE268599 Astrocyte transcriptomic changes along the spatiotemporal progression of Alzheimer’s disease 146 samples shares progression

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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.