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Supplementing CD2 expression enhances CAR-T Cell Efficacy through Optimizing CAR-immunological Synapse formation

GSE291458 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2025/08/05 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 18 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
18 samples: 18 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
CD2 augmentation enhances CAR-T-cell efficacy via immunological synapse remodeling and T-cell exhaustion mitigationCellular & molecular immunology · 2025
Summary (written by the submitters)
CAR-T cell therapy has made significant strides in treating hematological malignancies, yet its efficacy is often hampered by T cells' suboptimal functionality, marked by weak antitumor capabilities and lack of durability. The immunological synapse, a key determinant of T cell function, is influenced by the CD58-CD2 axis. The dynamic regulation of CD2 expression on T cells impacts the quality of CAR-mediated synapses, affecting CAR-T cells' functional outcomes and differentiation.
Read the full summary ↓
Our study confirmed that CD2 expression levels are closely linked to the quality of immunological synapses formed by CAR-T cells and their antitumor potency. Exogenous CD2 supplementation enhances CAR-T cells' ability to form high-quality synapses, reduces T cell exhaustion, and boosts sustained antitumor efficacy. Additionally, ectopic CD2 expression increases CAR-T cells' sensitivity to low-density antigens. Thus, replenishing CD2 in CAR-T cells is a promising strategy to enhance the therapeutic efficacy of CAR-T cell therapy.
Published in
CD2 augmentation enhances CAR-T-cell efficacy via immunological synapse remodeling and T-cell exhaustion mitigation
Zhu Q, Li J, Liu N et al. · Cellular & molecular immunology 2025 · PMID 40615696 · doi:10.1038/s41423-025-01314-6
This dataset
Open GSE291458 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 GSE291458_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 PRJNA1233798 and SRA study SRP568976. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40615696) ↗
Study design
18 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 18 sample titles: 18 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.