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Tonic Signaling Shaped by Epitope Targeting Governs CAR-T Cell Fitness and Antitumor Activity in Diffuse Midline Glioma [RNA-Seq]

GSE302514 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2025/12/04 Platform GPL34281
At a glance

RNA-seq (gene expression) · human · 10 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
10 samples: 5 conditions, mostly in duplicateGroups 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
A Tonic Signaling Code Predicts CAR-T Cell Efficacy in Diffuse Midline GliomabioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
We systematically evaluated B7-H3–targeting CAR-T cells derived from three monoclonal antibodies (376.96, MGA271, and Hu8H9) in diffuse midline glioma (DMG or DIPG), a fatal pediatric brain tumor. Among these, 376.96 CAR-T cells had markedly lower tonic signaling, diminished expression of exhaustion markers, and enhanced tumor killing, cytokine production, and persistence.
Read the full summary ↓
Transcriptomic and epigenomic profiling revealed a restrained activation state with reduced tonic signaling pathways and elevated stemness properties, oxidative metabolism, and innate immune sensing in these cells. In patient-derived spheroids and orthotopic DIPG xenografts, mRNA-based 376.96 CAR-T cells achieved robust tumor control and extended survival. By leveraging epitope selection, we reveal a mechanistic link between tonic signaling and CAR-T cell exhaustion, and provide a rational framework for optimizing CAR-T cell design to achieve improved efficacy and durability in pediatric brain tumor therapy.
Published in
A Tonic Signaling Code Predicts CAR-T Cell Efficacy in Diffuse Midline Glioma
Deng EB, Zhong X, Xin D et al. · bioRxiv : the preprint server for biology 2025 · PMID 41256549 · doi:10.1101/2025.09.29.679095
This dataset
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.

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 GSE302514_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1291110 and SRA study SRP600728. Searching any of these in the dataset finder brings you back here.

Study design
5 conditions, mostly in duplicate
Untransduced T ×2 Control T ×2 376 ×2 MGA271 ×2 Hu8H9 ×2

Supports a between-group comparison across 10 samples.

How we read this: 5 replicated groups read from 10 sample titles; they account for 10 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
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