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Inhibition of inflammation and senescence with azole compound C7 enables expansion of hematopoietic stem and progenitor cells

GSE326276 Homo sapiens (human) RNA-seq (gene expression) 45 samples Submitted 2026/04/03 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 45 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
45 samples: 45 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.
Summary (written by the submitters)
Human hematopoietic stem and progenitor cells (HSPCs) derived from umbilical cord blood (UCB) are often insufficient in quantity for transplantation, necessitating efforts for ex vivo expansion. We previously developed a novel azole-based small molecule, C7, as a structural analog of the p38 mitogen-activated protein kinase inhibitor SB203580.
Read the full summary ↓
C7 mediated robust ex vivo expansion of UCB HSPCs from unselected mononuclear cells, compared to its structural analogs and other published compounds. However, the molecular underpinnings of C7’s potency remained unclear. In this work, we demonstrate that C7 preferentially enhances the proliferation and viability of early HSPC subsets upon direct culture with pre-isolated HSPCs, while limiting mitochondrially-derived reactive oxygen species production linked to oxidative stress. C7 treatment enhances hematopoietic stem cell self-renewal and in vivo multilineage reconstitution without T- or myeloid lineage bias. Unlike existing p38 inhibitors, C7 targets multiple kinases and pathways to achieve superior HSPC expansion through suppression of NFκB and IL-10 inflammatory signaling and attenuation of stress/senescence‑associated markers (e.g., SERPINB2 and CDKN1A/p21). This mechanism of action of C7 is distinct from those of other existing compounds used for ex vivo HSPC expansion and has implications for application in other ex vivo culture platforms and clinical settings.
This dataset
Open GSE326276 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 GSE326276_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 PRJNA1445057 and SRA study SRP687686. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
45 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 45 sample titles: 45 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

+ 5 more — browse all 45 samples with per-sample file links →

Datasets on a similar topic

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.