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Brain-sensing synNotch-CAR T-cells enable precise targeting and clearance of diffuse midline glioma in multiple preclinical models

GSE337350 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/07/09 Platform GPL34284
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: 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)
Diffuse midline glioma (DMG) is a lethal pediatric brain tumor with limited therapeutic options and a poor prognosis. The ultimate success of chimeric antigen receptor (CAR) T-cell therapy requires improving T-cell tumor infiltration, and persistence, and reducing the risk of on-target/off-tumor toxicity. Here, we adapt and advance a brain-restricted CAR T-cell platform, previously validated in glioblastoma, to address the distinct anatomical and biological challenges of DMG.
Read the full summary ↓
We engineer we test whether a strategy developed for glioblastoma can also be effective against DMG. We evaluated a T- cell circuit in which a brain-specific sensor -- the synthetic Notch (synNotch) receptor recognizingagainst Brevican (BCAN) -- induces CAR the expression against of a CAR targeting either EphA2 or IL-13Rα2 (“B-SYNC”), enabling multi-antigen tumor recognition tumor recognition through multiple antigens while restricting CAR expression to the CNS. In immunodeficient DMG models, a single infusion of B-SYNC T- cells, either by intravenousintravenously (IV) or intracerebroventricularly (ICV) infusion, led to tumor infiltration, sustained persistence, robust anti-tumor activity, and significantly extended survival. An alternative BCAN-primed circuit CAR inducing a CAR targeting eithertargeting B7-H3 or IL-13Rα2 (“B-SYNC-B/I”) similarly improved therapeutic efficacy when delivered IV. However, ICV administration triggered fatal neurotoxicity due to low-level B7-H3 expression in non-tumor CNS regions, indicating that rapid CNS exposure via ICV delivery can amplify off-tumor toxicity. In contrast, in an immunocompetent syngeneic DMG model, both IV and ICV delivery of a murinized BCAN-gated B7-H3 CAR (mB-SYNC-B7-H3) achieved durable tumor clearance and resistance to rechallenge, without any detectable neurotoxicity. Mechanistically, synNotch-primed CAR T--cells exhibited reduced exhaustion, enhanced activation, and enrichment of naïve and stem- cell memory-like subsets. , supporting superior functional durability in the DMG microenvironment. These findings demonstrate that brain-sensing synNotch CAR T circuits represent a generalizable and translatable strategy for targeting multiple CNS malignancies, including DMG.
This dataset
Open GSE337350 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 GSE337350_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 PRJNA1484923 and SRA study SRP714631. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
8 conditions, mostly in triplicate
CD8, BCAN synNotch - anti-EphA2/IL13RA2 CAR, … ×3 CD4, BCAN synNotch - anti-EphA2/IL13RA2 CAR, … ×3 CD8, Constitutive anti-EphA2/IL13RA2 CAR, don… ×3 CD4, Constitutive anti-EphA2/IL13RA2 CAR, don… ×3 CD8, BCAN synNotch - anti-EphA2/IL13RA2 CAR, … ×3 CD4, BCAN synNotch - anti-EphA2/IL13RA2 CAR, … ×3 CD8, Constitutive anti-EphA2/IL13RA2 CAR, don… ×3 CD4, Constitutive anti-EphA2/IL13RA2 CAR, don… ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 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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