GEO series

Stromal Cell Senescence Augments Hematopoietic Cell Fitness in Clonal Hematopoiesis

GSE299122 Homo sapiens (human) Single-cell RNA-seq 15 samples Submitted 2026/05/14 Platform GPL24676

At a glance

Single-cell RNA-seq · human · 15 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 15 samples: 6 × human healthy BM-MSC co-cultured with high-risk CHIP HSPC, vs 5 × human healthy BM-MSC co-cultured with non-CHIP HSPC, vs 4 × human healthy BM-MSC co-cultured with low-risk CHIP HSPC,Groups 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.

Summary (written by the submitters)

Non-cell-autonomous mechanisms impact tumor growth and metastasis, including remodeling of the tissue microenvironment. The extent to which remodeling of the microenvironment promotes pre-malignant clonal fitness remains unknown. Here, using single-cell RNA sequencing of the bone marrow microenvironment in a mouse model of DNMT3A-mutant clonal hematopoiesis, we identify subsets of mesenchymal stromal cells (MSCs) in a molecular state of cellular senescence.

Read the full summary ↓

Using in vivo and ex vivo approaches, we find MSC senescence is induced by Dnmt3a-mutant hematopoietic cells in a cell contact-independent manner through soluble factors, including the cytokines IL-6 and TNF. Mechanistically, these cytokines activate a STAT3-driven senescence induction pathway selectively in MSCs and not in endothelial cells, underscoring cell context specificity. Depletion of senescent MSCs using genetic or pharmacological methods reduces the fitness of Dnmt3a-mutant hematopoietic stem and progenitor cells, and delays development of myeloproliferation which is a precursor to myeloid malignancy. Together, our work identifies that remodeling of the tissue microenvironment modifies pre-malignant clonal fitness and suggests disruption of the crosstalk between pre-malignant cells and their niche as a cancer prevention strategy.

This dataset

Open GSE299122 in finder → Find more human 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 GSE299122_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 PRJNA1272610 and SRA study SRP590231. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 × human healthy BM-MSC co-cultured with high-risk CHIP HSPC, vs 5 × human healthy BM-MSC co-cultured with non-CHIP HSPC, vs 4 × human healthy BM-MSC co-cultured with low-risk CHIP HSPC,

Supports a between-group comparison across 15 samples.

How we read this: 3 replicated groups read from 15 sample titles; they account for 15 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

GSM9033815 human healthy BM-MSC co-cultured with non-CHIP HSPC, biological replicate 1 human healthy BM-MSC co…
GSM9033816 human healthy BM-MSC co-cultured with non-CHIP HSPC, biological replicate 2 human healthy BM-MSC co…
GSM9033817 human healthy BM-MSC co-cultured with non-CHIP HSPC, biological replicate 3 human healthy BM-MSC co…
GSM9033818 human healthy BM-MSC co-cultured with non-CHIP HSPC, biological replicate 4 human healthy BM-MSC co…
GSM9033819 human healthy BM-MSC co-cultured with non-CHIP HSPC, biological replicate 5 human healthy BM-MSC co…
GSM9033820 human healthy BM-MSC co-cultured with low-risk CHIP HSPC, biological replicate 1 human healthy BM-MSC co…
GSM9033821 human healthy BM-MSC co-cultured with high-risk CHIP HSPC, biological replicate 1 human healthy BM-MSC co…
GSM9033822 human healthy BM-MSC co-cultured with low-risk CHIP HSPC, biological replicate 2 human healthy BM-MSC co…
GSM9033823 human healthy BM-MSC co-cultured with high-risk CHIP HSPC, biological replicate 2 human healthy BM-MSC co…
GSM9033824 human healthy BM-MSC co-cultured with low-risk CHIP HSPC, biological replicate 3 human healthy BM-MSC co…
GSM9033825 human healthy BM-MSC co-cultured with high-risk CHIP HSPC, biological replicate 3 human healthy BM-MSC co…
GSM9033826 human healthy BM-MSC co-cultured with high-risk CHIP HSPC, biological replicate 4 human healthy BM-MSC co…
GSM9033827 human healthy BM-MSC co-cultured with high-risk CHIP HSPC, biological replicate 5 human healthy BM-MSC co…
GSM9033828 human healthy BM-MSC co-cultured with low-risk CHIP HSPC, biological replicate 4 human healthy BM-MSC co…
GSM9033829 human healthy BM-MSC co-cultured with high-risk CHIP HSPC, biological replicate 6 human healthy BM-MSC co…

Datasets on a similar topic

GSE326276 Inhibition of inflammation and senescence with azole compound C7 enables expansion of hematopoietic stem and progenitor cells 45 samples shares hematopoietic, senescence
GSE216842 Transcriptomic landscape of human primary stromal cells (fibroblasts, endothelial cells and mesenchymal stem cells) upon therapy-induced senescence (genotoxic chemotherapy） 24 samples shares senescence, stromal
GSE320375 On-demand GLUT3 expression augments CAR-T cell metabolic fitness and antitumor efficacy whereas preventing toxicity in glioblastoma 16 samples shares augments, fitness
GSE309534 Single-cell profiling of the human bone marrow niche remodeling in clonal hematopoiesis and myelodysplasia 10 samples shares hematopoiesis, clonal
GSE318863 Ex vivo long-term expansion of human hematopoietic stem and progenitor cells as a tool for modeling vector integration sites and clonality 10 samples shares hematopoietic, clonal
GSE244257 Senescence and inflammation are unintended adverse consequences of CRISPR-Cas9/AAV6 mediated gene editing in hematopoietic stem cells 83 samples shares hematopoietic, senescence
GSE210435 TET2 Mutant Clonal Hematopoiesis Enhances Severity of COVID-19 Related Cytokine Release Syndrome and is Associated with Increased Mortality. 363 samples shares hematopoiesis, clonal
GSE285943 A reference model for circulating hematopoietic stem cells with applications to diagnostics 299 samples shares hematopoietic

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.