← BioTransfer GEO Dataset Finder
GEO series

Expression of the CXCR4 S338X variant improves anti-leukemia efficacy of anti-CD19 CAR-T cells

GSE314992 Homo sapiens (human) RNA-seq (gene expression) 20 samples Submitted 2025/12/28 Platform GPL34284
At a glance

RNA-seq (gene expression) · human · 20 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)
Topic
Acute lymphoblastic leukemiaThis series is part of our curated briefing on it.
Samples
20 samples: 20 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
Expression of the CXCR4 S338X Variant Improves Anti-Leukemia Efficacy of Anti-CD19 CAR-T CellsCancer science · 2026
Summary (written by the submitters)
Chimeric antigen receptor T (CAR-T) cell therapy has demonstrated remarkable success in treating hematological malignancies; however, antigen-positive relapse remains a significant obstacle to achieving sustained remission in B-cell acute lymphoblastic leukemia (B-ALL). To enhance the therapeutic efficacy of anti-CD19 CAR (CAR19)-T cells, we overexpressed CXCR4 in CAR19-T cells to improve their trafficking to bone marrow (BM), a key sanctuary for minimal residual disease.
Read the full summary ↓
We engineered CAR19-T cells with overexpression of wild-type CXCR4 (CAR19/CXCR4WT-T) or gain-of-function CXCR4 S338X mutant (CAR19/CXCR4S338X-T). Both CAR19/CXCR4WT-T and CAR19/CXCR4S338X-T cells exhibited enhanced CXCR4 surface expression in vitro and in vivo compared to control CAR19-T cells, with the latter showing significantly superior improvements under all tested conditions, including engagement with CAR-specific antigens or CXCR4 ligand CXCL12. Upon engagement with CXCL12, CAR19/CXCR4S338X-T cells, but not CAR19/CXCR4WT-T cells, displayed significantly increased activation of ERK1/2 and AKT signaling pathways, as well as elevated transcription of TNF-α, IFN-γ, granzyme B, CDK6, and BCL2A1, along with strengthened effector functions, chemotaxis, and activation of anti-apoptotic pathways. Furthermore, CAR19/CXCR4S338X-T cells demonstrated significantly improved migration to and retention in the BM accompanied by increased CD45RA+CCR7+ memory T cell populations, which correlated with enhanced anti-leukemic effects following injection into B-ALL-bearing mice. This study offers a potentially effective strategy to improve the functionality and durability of CAR-T cell responses in hematological malignancies.
Published in
Expression of the CXCR4 S338X Variant Improves Anti-Leukemia Efficacy of Anti-CD19 CAR-T Cells
Mao Y, Wang X, Jin CH et al. · Cancer science 2026 · PMID 41467552 · doi:10.1111/cas.70313
This dataset
Open GSE314992 in finder → Find more human RNA-seq datasets → Acute lymphoblastic leukemia landscape →
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 GSE314992_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 PRJNA1394210 and SRA study SRP659849. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41467552) ↗
Study design
20 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 20 sample titles: 20 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
More Acute lymphoblastic leukemia datasets

Search all human 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.