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pTα enhances mRNA translation and potentiates CAR T cells for solid tumor eradication [bulk RNA-seq]

GSE289390 Homo sapiens (human) RNA-seq (gene expression) 25 samples Submitted 2026/01/22 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 25 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
25 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)
Current chimeric antigen receptor (CAR) therapies are effective against a range of hematological malignancies and autoimmune disorders but have shown limited activity against solid tumors. In searching for effective means to enhance the functional persistence and potency of CAR T cells, we explored the potential of integrating pre-T cell features into canonical CD28-based CARs.
Read the full summary ↓
Thymocytes undergo a proliferation burst during the β-selection developmental stage, which is driven by the pre-T cell receptor and its unique pTα chain. CARs harboring the pTα 1A domain imparted greater expansion, cytokine production, and in vivo persistence to T cells, accompanied by lowered exhaustion and greater long-term tumor control in multiple liquid and solid tumor models. CARs incorporating the 1A domain showed sustained phosphorylation of the mRNA translation master regulator YBX1, which was required for enhanced tumor eradication. The programing of mRNA translation in T cells opens another avenue for regulating and potentiating immunotherapy.
This dataset
Open GSE289390 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 GSE289390_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 PRJNA1222835 and SRA study SRP563426. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
19-28z-preinfusion ×3 19-28z-1A-preinfusion ×3 19-1XX-preinfusion ×3 19-28z-week1 ×3 19-28z-1A-week1 ×3 19-1XX-week1 ×3 19-28z-1A-week2 ×3 19-1XX-week2 ×3 +1 more

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 25 sample titles; they account for 24 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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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.