← BioTransfer GEO Dataset Finder
GEO series

Development of CAR T cells Targeting U5 snRNP200 for the Treatment of Acute Myeloid and B-Lymphoid Leukemias

GSE297441 Mus musculus (mouse) RNA-seq (gene expression) 19 samples Submitted 2025/11/30 Platform GPL34328
At a glance

RNA-seq (gene expression) · mouse · 19 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
Mus musculus (mouse)
Samples
19 samples: 19 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
Development of CAR T cells Targeting a Surface RNA Binding Protein for the Treatment of Acute LeukemiasCancer discovery · 2026
Summary (written by the submitters)
Developing chimeric antigen receptor (CAR) T cells for acute myeloid leukemia (AML) has been challenging due to a lack of known AML-associated antigens which spare normal hematopoietic precursor cells. Here we reasoned that donor auto-antibodies from AML recipients cured following allogeneic transplant and responsible for graft-versus-leukemia effect could be engineered to create effective CAR-T cells.
Read the full summary ↓
We generated CAR-T cells against one such antigen - U5 snRNP200, an RNA helicase localized to the surface of AML cells and absent from normal hematopoietic precursors. Anti-U5 snRNP200 CAR T cells were effective in human and syngeneic models of AML as well as B acute lymphoblastic leukemia (B-ALL), a setting where surface U5 snRNP200 was also present. IL-18 armoring augmented target antigen expression due to cell surface trafficking of U5 snRNP200 with CD32A. These data thereby identify a CAR-T cell platform which addresses prior limitations in tumor-selectivity and safety for patients with acute leukemias.
Published in
Development of CAR T cells Targeting a Surface RNA Binding Protein for the Treatment of Acute Leukemias
Fujino T, Lewis J, Chen B et al. · Cancer discovery 2026 · PMID 42059863 · doi:10.1158/2159-8290.CD-25-0920
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 GSE297441_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 PRJNA1263852 and SRA study SRP585965. Searching any of these in the dataset finder brings you back here.

Study design
19 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 19 sample titles: 19 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

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.