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Bone marrow immunosuppressive states associate with survival after guadecitabine and atezolizumab therapy in HMA-R/R MDS

GSE326589 Homo sapiens (human) Single-cell RNA-seq 58 samples Submitted 2026/05/18 Platform GPL24676
At a glance

Single-cell RNA-seq · human · 58 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)
Topic
Myelodysplastic syndromesThis series is part of our curated briefing on it.
Samples
58 samples: 51 distinct titles, 7 of them repeatedGroups 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
Bone marrow immunosuppressive states associate with survival after guadecitabine and atezolizumab therapy in HMA-R/R MDSBlood neoplasia · 2026
Summary (written by the submitters)
Approximately half of patients with myelodysplastic syndromes (MDS) relapse or are refractory to hypomethylating agents (HMAs) and experience poor clinical outcomes. We previously reported improved survival in a Phase I/II clinical trial combining the HMA guadecitabine with PD-L1 blockade (atezolizumab) in HMA-relapsed or -refractory MDS, yet the biological features associated with durable responses to this combined epigenetic and immunotherapy approach remain unclear.
Read the full summary ↓
Here, we performed integrated bulk and single-cell transcriptomic profiling of bone marrow samples from patients treated on this trial to identify molecular and cellular features associated with survival. Long-term survival was associated with the presence of immunosuppressive myeloid cells and primed dendritic cells at baseline, together with therapy-induced immune reinvigoration characterized by interferon pathway activation and expansion of effector lymphocytes. In contrast, short-term survival was associated with persistent senescence-associated inflammatory programs in CD34⁺ bone marrow cells and elevated expression of immunosuppressive immune checkpoint molecules. These findings suggest that chronic inflammatory and senescent microenvironmental states constrain effective immune activation despite combined epigenetic and immune checkpoint therapy. Here, we reveal distinct bone marrow microenvironments associated with patient survival after combined epigenetic and immune checkpoint therapy and suggest candidate biomarkers to guide patient stratification in high-risk MDS.
Published in
Bone marrow immunosuppressive states associate with survival after guadecitabine and atezolizumab therapy in HMA-R/R MDS
Jang HJ, Urrutia G, Ørskov AD et al. · Blood neoplasia 2026 · PMID 42305767 · doi:10.1016/j.bneo.2026.100243
This dataset
Open GSE326589 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 GSE326589_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 PRJNA1402330 and SRA study SRP662483. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42305767) ↗
Study design
51 distinct titles, 7 of them repeated
CD34+ cells, 113446P ×2 CD34+ cells, 114152P ×2 CD34+ cells, 116467P ×2 CD34+ cells, 117494P ×2 CD34+ cells, 119837P ×2 CD34+ cells, 121015P ×2 CD34+ cells, 121535P ×2

How we read this: Read from 58 sample titles: 51 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

+ 18 more — browse all 58 samples with per-sample file links →

More Myelodysplastic syndromes datasets

Search all human RNA-seq datasets in GEO →

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