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Sustained and specific multiplexed immune checkpoint modulation in CAR T cells induced by targeted epigenome editing

GSE273682 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2025/06/30 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 15 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
15 samples: 15 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
Sustained and specific multiplexed immune checkpoint modulation in CAR T cells induced by targeted epigenome editingMolecular therapy. Nucleic acids · 2025
Summary (written by the submitters)
Engineered T cells equipped with a chimeric antigen receptor (CAR) have shown tremendous clinical success but tumor-mediated stimulation of T cell inhibitory receptors leads to exhaustion, hampering durable remission in patients. Mitigation of this effect via checkpoint inhibition or genome editing to knockout the genes encoding for these receptors has shown promise.
Read the full summary ↓
Yet, the side effects of these procedures require alternatives. Targeted epigenome editing is a potent strategy to alter gene expression in the absence of DNA modifications. The hit-and-run feature enables durable multiplexed modulation of gene expression with greater safety. Here we describe multiplexed epigenome editing inactivation of two critical exhaustion-related genes, PDCD1 and LAG3, both in primary human T cells and in prostate cancer specific CAR T cells. Epigenetically modified CAR T cells are fully functional and nearly indistinguishable from parental cells in a variety of functional assays. Target gene silencing is durable over multiple cell divisions and repeated CAR-mediated stimulations. Furthermore, transcriptomic analysis revealed minimal off-target effects not directly attributable to the effectors used. We demonstrate that targeted epigenome editing is an effective and safe procedure for multiplexed gene inhibition and that this strategy can be used to engineer CAR T cells with novel desirable features.
Published in
Sustained and specific multiplexed immune checkpoint modulation in CAR T cells induced by targeted epigenome editing
Roman Azcona MS, Monaco G, Whitehead M et al. · Molecular therapy. Nucleic acids 2025 · PMID 40686859 · doi:10.1016/j.omtn.2025.102618
This dataset
Open GSE273682 in finder → Find more human RNA-seq 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 GSE273682_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: 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 PRJNA1142611 and SRA study SRP523448. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40686859) ↗
Study design
15 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 15 sample titles: 15 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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