GEO series

Distinct routes of clonal progression in SF3B1-mutant myelodysplastic syndromes

GSE290183 Homo sapiens (human) RNA-seq (gene expression) 15 samples Submitted 2025/03/21 Platform GPL20795

At a glance

RNA-seq (gene expression) · human · 15 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: Myelodysplastic syndromesThis series is part of our curated briefing on it.
Samples: 15 samples: 7 conditions, mostly in duplicateGroups 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: Distinct routes of clonal progression in SF3B1-mutant myelodysplastic syndromesBlood advances · 2025

Summary (written by the submitters)

Myelodysplastic syndromes (MDS) are clonal stem cell disorders driven by heterogeneous genetic alterations leading to variable clinical course. MDS with splicing factor SF3B1 mutations is a distinct subtype with a favorable outcome. However, selected co-mutations induce poor prognosis and how these genetic lesions cooperate in human hematopoietic stem and progenitor cells (HSPCs) during disease progression is still unclear.

Read the full summary ↓

Here, we integrated clinical and molecular profiling of patients with SF3B1 mutations with gene editing of primary and iPSC-derived human HSPCs to show that high-risk co-mutations impart distinct effects on lineage programs of SF3B1-mutant HSPCs. Secondary RUNX1 or STAG2 mutations were clinically associated with advanced disease and reduced survival. However, RUNX1 and STAG2 mutations induced opposing regulation of myeloid transcriptional programs and differentiation in SF3B1-mutant HSPCs. Moreover, high-risk RUNX1 and STAG2, but not low-risk TET2, mutations expanded distinct SF3B1-mutant HSPC subpopulations. These findings provide evidence that progression from low- to high-risk MDS involves distinct molecular and cellular routes depending on co-mutation patterns.

Published in

Distinct routes of clonal progression in SF3B1-mutant myelodysplastic syndromes

Sarchi M, Clough CA, Gallì A et al. · Blood advances 2025 · PMID 40188457 · doi:10.1182/bloodadvances.2024014965

This dataset

Open GSE290183 in finder → Find more human RNA-seq datasets → Myelodysplastic syndromes 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 GSE290183_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 PRJNA1226528 and SRA study SRP565477. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40188457) ↗

Study design

7 conditions, mostly in duplicate

SF3B1-WT AAVS1-edited ×2 SF3B1-WT RUNX1-edited ×2 SF3B1-WT STAG2-edited ×2 SF3B1-MUT AAVS1-edited ×2 SF3B1-MUT RUNX1-edited ×2 SF3B1-MUT STAG2-edited ×2 K562 SF3B1-MUT STAG2-MUT ×2 K562 SF3B1-MUT RUNX1-MUT ×1

Supports a between-group comparison across 14 samples.

How we read this: 7 replicated groups read from 15 sample titles; they account for 14 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

GSM8807870 SF3B1-WT AAVS1-edited replicate 1 SF3B1-WT AAVS1-edited
GSM8807871 SF3B1-WT AAVS1-edited replicate 2 SF3B1-WT AAVS1-edited
GSM8807872 SF3B1-WT RUNX1-edited replicate 1 SF3B1-WT RUNX1-edited
GSM8807873 SF3B1-WT RUNX1-edited replicate 2 SF3B1-WT RUNX1-edited
GSM8807874 SF3B1-WT STAG2-edited replicate 1 SF3B1-WT STAG2-edited
GSM8807875 SF3B1-WT STAG2-edited replicate 2 SF3B1-WT STAG2-edited
GSM8807876 SF3B1-MUT AAVS1-edited replicate 1 SF3B1-MUT AAVS1-edited
GSM8807877 SF3B1-MUT AAVS1-edited replicate 2 SF3B1-MUT AAVS1-edited
GSM8807878 SF3B1-MUT RUNX1-edited replicate 1 SF3B1-MUT RUNX1-edited
GSM8807879 SF3B1-MUT RUNX1-edited replicate 2 SF3B1-MUT RUNX1-edited
GSM8807880 SF3B1-MUT STAG2-edited replicate 1 SF3B1-MUT STAG2-edited
GSM8807881 SF3B1-MUT STAG2-edited replicate 2 SF3B1-MUT STAG2-edited
GSM8807882 K562 SF3B1-MUT RUNX1-MUT
GSM8807883 K562 SF3B1-MUT STAG2-MUT replicate 1 K562 SF3B1-MUT STAG2-MUT
GSM8807884 K562 SF3B1-MUT STAG2-MUT replicate 2 K562 SF3B1-MUT STAG2-MUT

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GSE292039 Splicing of erythroid transcription factor is associated with therapeutic response in myelodysplastic syndromes 27 samples same disease briefing · shares myelodysplastic, syndromes
GSE237148 Targeting IL-1b–mediated inflammatory signaling overcomes transfusion dependence in early-stage myelodysplastic syndromes 26 samples same disease briefing · shares myelodysplastic, syndromes
GSE280881 Rapid Disease Progression of Myelodysplastic Syndrome is Reflected in Transcriptomic and Functional Abnormalities of Bone Marrow MSCs 22 samples same disease briefing · shares myelodysplastic, progression
GSE293014 Identifying clones in myelodysplastic syndromes by using single-cell RNA sequencing 11 samples same disease briefing · shares myelodysplastic, syndromes
GSE245452 Single-cell transcriptional profile of CD34+ hematopoietic progenitor cells from del(5q) Myelodysplastic Syndromes and impact of lenalidomide 7 samples same disease briefing · shares myelodysplastic, syndromes
GSE256396 Somatic mutations and DNA methylation identify a subgroup of poor prognosis within lower risk myelodysplastic syndromes 374 samples same disease briefing · shares myelodysplastic, syndromes

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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.