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DDO1002, an Nrf2–Keap1 inhibitor, improves impairedhaematopoiesis by reducing ROS production and promoting Nrf2-mediated antioxidative response

GSE275533 Mus musculus (mouse) Single-cell RNA-seq 2 samples Submitted 2025/01/29 Platform GPL24247

At a glance

Single-cell RNA-seq · mouse · 2 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: Mus musculus (mouse)
Samples: 2 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: DDO1002, an NRF2-KEAP1 inhibitor, improves hematopoietic stem cell aging and stress responseLife medicine · 2024

Summary (written by the submitters)

Oxidative stress reduces haematopoietic stem cell (HSC) function with age, and increased reactive oxygen species (ROS) levels promote DNA damage, cell senescence, and haematopoietic dysfunction. DDO1002, an effective Keap1–Nrf2 inhibitor, may regulate antioxidant gene expression, however, its ability to alleviate impaired haematopoiesis following total body irradiation (TBI) or ageing remains unclear.

Read the full summary ↓

Through both cellular and mouse models, we showed that DDO1002 upregulated Nrf2, activated the Nrf2-mediated antioxidant response element (ARE) signalling pathway, reduced intracellular ROS levels and delayed cellular senescence. Moreover, DDO1002 reduced DNA damage and HSC apoptosis, thereby increasing the number of HSCs, lymphoid-primed MPP4 cells, and B cells in peripheral blood. Therefore, DDO1002 alleviates TBI-induced haematopoietic injury. Similarly, DDO1002 treatment activated the expression of Nrf2 and Nrf2-mediated ARE signalling pathways in the bone marrow cells of naturally ageing mice. B and T cell proportions in the spleen were increased, as was the colony-forming ability of bone marrow cells. Single-cell sequencing analysis revealed that DDO1002 treatment attenuated intracellular inflammatory signalling pathways and reduced the ROS pathway in aged HSCs, suggesting an ability to restore aged-HSC viability. Thus, DDO1002 effectively activated Nrf2 to delay cell senescence and improved impaired haematopoiesis via the Nrf2–ARE pathway, showing potential for treating age-related haematopoietic disorders.

Published in

DDO1002, an NRF2-KEAP1 inhibitor, improves hematopoietic stem cell aging and stress response

Li Y, Wu A, Jin X et al. · Life medicine 2024 · PMID 39872153 · doi:10.1093/lifemedi/lnae043

This dataset

Open GSE275533 in finder → Find more mouse 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 GSE275533_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 PRJNA1151641 and SRA study SRP528310. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39872153) ↗

Samples in this study

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+ 2 more — browse all 2 samples with per-sample file links →

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