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Chimeric antigen receptor with novel intracellular modules improves antitumor performance of T cells

GSE281230 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2025/01/22 Platform GPL16791
At a glance

RNA-seq (gene expression) · human · 24 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
24 samples: 24 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
Chimeric antigen receptor with novel intracellular modules improves antitumor performance of T cellsSignal transduction and targeted therapy · 2025
Summary (written by the submitters)
The excessive cytokine release and limited persistence represent major obstacles to successful chimeric antigen receptor T (CAR-T) cell therapy in solid tumors. Conventional CARs employ an intracellular domain (ICD) from the ζ chain of CD3 as a signaling module, and it is largely unknown how alternative CD3 chains potentially contribute to CAR design.
Read the full summary ↓
Here, we obtained a series of CAR-T cells against HER2 and mesothelin using a domain containing one immunoreceptor tyrosine-based activation motif from different CD3 subunits as the ICD of CARs. While these reconstituted CARs conferred sufficient antigen-specific cytolytic activity on equipped T cells, they elicited low tonic signal, ameliorated CAR-T cell exhaustion and facilitated memory differentiation. Intriguingly, the CD3ε-derived ICD outperformed others in generation of CAR-T cells that produced minimized cytokines. Mechanistically, CD3ε-based CARs displayed a restrained cytomembrane expression on engineered T cells, which was ascribed to endoplasmic reticulum retention mediated by the carboxyl terminal basic residues. The present study demonstrated the applicability of CAR reconstitution using signaling modules from different CD3 subunits, and depicted a novel pattern of CAR expression that reduces cytokine release, thus paving a way for generation of CAR-T cells with improved safety and persistence against diverse tumor antigens.
Published in
Chimeric antigen receptor with novel intracellular modules improves antitumor performance of T cells
Wang P, Wang Y, Zhao X et al. · Signal transduction and targeted therapy 2025 · PMID 39809749 · doi:10.1038/s41392-024-02096-5
This dataset
Open GSE281230 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 GSE281230_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 PRJNA1182774 and SRA study SRP543565. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39809749) ↗
Study design
24 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 24 sample titles: 24 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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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.