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4-1BB causes CAR-T cell death via sequestration of the ubiquitin-modifying enzyme A20

GSE267821 Homo sapiens (human) RNA-seq (gene expression) 22 samples Submitted 2026/05/18 Platform GPL30173
At a glance

RNA-seq (gene expression) · human · 22 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
22 samples: 8 conditions, mostly in triplicateGroups 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)
CD28 and 4-1BB costimulatory endodomains included in chimeric antigen receptor (CAR) molecules play a critical role in promoting sustained antitumor activity of CAR-T cells. However, the molecular events associated with the ectopic and constitutive display of either CD28 or 4-1BB in CAR-T cells have been only partially explored. In the current study, we demonstrated that 4-1BB incorporated within the CAR leads to cell apoptosis and necroptosis in the absence of CAR tonic signaling.
Read the full summary ↓
Additionally, we found that cell death induced by 4-1BB co-stimulation is TRAF and RIPK1-dependent. At the molecular level, 4-1BB endodomain causes functional deficiency of the A20 protein in CAR-T cells that appears to be sequestered at the plasma membrane through its binding to the 4-1BB in a TRAF-dependent manner. Genetic modulations of the A20 interplay with 4-1BB obtained by deletion of the TRAF binding motifs of 4-1BB rescue the cell death and enhance the antitumor ability of 4-1BB-costimulated CAR-T cells.
This dataset
Open GSE267821 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 GSE267821_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 PRJNA1113315 and SRA study SRP508555. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
CD19.CD28_Dono ×3 CD19.BB_Dono ×3 CD19.BB.A20_Dono ×3 CD19.CD28.Ab activation_Dono ×3 CD19.BB.Ab activation_Dono ×3 CD19.BB.A20.Ab activation_Dono ×3 CD19.BBdeltaC_Dono ×2 CD19.BBdeltaC.Ab activation_Dono ×2

Supports a between-group comparison across 22 samples.

How we read this: 8 replicated groups read from 22 sample titles; they account for 22 of them. 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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