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VLA-4 Agonist Promote Engraftment and Cell Immune Reconstitution of Allogeneic Hematopoietic Stem Cells

GSE264056 Homo sapiens (human) RNA-seq (gene expression) 10 samples Submitted 2026/03/23 Platform GPL24247Platform GPL24676
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: 10 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
VLA-4 agonist promotes engraftment and immune reconstitution of allogeneic hematopoietic stem cellsBlood advances · 2026
Summary (written by the submitters)
Successful engraftment and early immune reconstitution of donor hematopoietic stem cells (HSCs) are crucial for allogeneic hematopoietic stem cell transplantation (allo-HSCT). However, little is known about how to promote implantation and early immune reconstitution of HSCs through regulating its own functions. Here, we identified very-late antigen (VLA-4) as a pivotal target in regulating HSC implantation.
Read the full summary ↓
Critically, we screened out a VLA-4 agonist, which could promote the implantation and long-term hematopoietic reconstitution of donor HSCs in a mixed donor chimerism (MDC) mouse model and serial xenotransplantation model of human CD34+ cells from umbilical cord blood (UCB). Competitive transplantation mouse model and limited dilution assay for UCB CD34+ cells revealed that VLA-4 agonist could enhance the self-renewal capacity of HSCs and increase the number of severe combined immunodeficient (SCID)-repopulating cells (SRCs) to five-fold in vivo. Furthermore, the VLA-4 agonist could facilitate early post-transplant cell immune reconstitution by enhancing T cell output of HSCs. VLA-4 agonist regulates HSC functions and lymphoid progenitor differentiation through affecting the ERK1/2 phosphorylation pathway, whereas may not increase the risk of leukemia transformation. These findings indicate that the VLA-4 agonist holds a great clinical translational potential in enhancing engraftment of HSCs and early cellular immune reconstitution following allo-HSCT.
Published in
VLA-4 agonist promotes engraftment and immune reconstitution of allogeneic hematopoietic stem cells
He Q, Sun X, Chen LV et al. · Blood advances 2026 · PMID 41758999 · doi:10.1182/bloodadvances.2025017456
This dataset
Open GSE264056 in finder → Find more 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 GSE264056_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 PRJNA1100619 and SRA study SRP501941. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41758999) ↗
Study design
10 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 10 sample titles: 10 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

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