GEO series

POISONING OF HEALTHY HEMATOPOIESIS IS AN UNANTICIPATED MECHANISM DRIVING CLONAL DOMINANCE IN VEXAS SYNDROME [scRNA-seq]

GSE272816 Homo sapiens (human) Single-cell RNA-seq 14 samples Submitted 2025/02/06 Platform GPL24247Platform GPL24676

At a glance

Single-cell RNA-seq · human · 14 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart.
Organism: Homo sapiens (human)
Samples: 14 samples
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: Mechanisms of hematopoietic clonal dominance in VEXAS syndromeNature medicine · 2025

Summary (written by the submitters)

Clonal dominance characterizes hematopoiesis during aging and increases susceptibility to blood cancers and common non-malignant disorders. VEXAS syndrome is a recently discovered adult-onset autoinflammatory disease burdened by a high mortality rate and caused by dominant hematopoietic clones bearing somatic mutations in the UBA1 gene.

Read the full summary ↓

However, pathogenic mechanisms fueling clonal dominance are unknown. Moreover, the lack of disease models hampers the development of disease-modifying therapies. Here, we performed immunophenotypic dissection of hematopoiesis and single-cell transcriptomics in a VEXAS patient cohort revealing pervasive inflammation across all lineages. Hematopoietic stem/progenitor cells (HSPCs) in VEXAS patients proliferate less, are mostly committed toward myelopoiesis, and prone to egress from the bone marrow. Humanized xenograft models of VEXAS syndrome, generated by inserting the causative mutation in healthy HSPCs through base editing, fully recapitulated patients’ hematologic and inflammatory hallmarks. Competitive transplants of VEXAS-like and normal HSPCs showed that while mutant cells are resilient to the inflammatory milieu, wild-type ones are poisoned and progressively overwhelmed by VEXAS clones, becoming unable to support functional multilineage hematopoiesis. Our study unveils an unanticipated mechanism of clonal dominance, provides new models for preclinical investigation of therapeutic strategies, and has relevant implications for clinical management of VEXAS patients.

Published in

Mechanisms of hematopoietic clonal dominance in VEXAS syndrome

Molteni R, Fiumara M, Campochiaro C et al. · Nature medicine 2025 · PMID 40195449 · doi:10.1038/s41591-025-03623-9

This dataset

Open GSE272816 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 GSE272816_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1138789 and SRA study SRP521454. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40195449) ↗

Samples in this study

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+ 14 more — browse all 14 samples with per-sample file links →

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