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Impact of Hydroxycarbamide Treatment on the Whole Blood Transcriptome in Sickle Cell Disease

GSE254951 Homo sapiens (human) RNA-seq (gene expression) 50 samples Submitted 2024/10/20 Platform GPL20301
At a glance

RNA-seq (gene expression) · human · 50 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
50 samples: 25 × Blood, HU-MTD, HU vs 23 × Blood, pre-HU, HU vs 2 × Blood, HU-Washout, HUGroups 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
Impact of hydroxycarbamide treatment on the whole-blood transcriptome in sickle cell diseaseBritish journal of haematology · 2025
Summary (written by the submitters)
Hydroxycarbamide (HC, also known as hydroxyurea) is the most widely used therapeutic for individuals with sickle cell disease (SCD). HC’s clinical benefits are primarily associated with its ability to induce fetal hemoglobin (HbF). However, much remains unknown about the non-HbF related impact of HC on genes and pathways relevant to SCD pathophysiology.
Read the full summary ↓
In this study, we performed bulk RNA-Seq on whole blood samples collected from a cohort of 25 pediatric patients with SCD to identify genes and pathways that are affected by treatment with HC. The results illustrate the range of effects exerted by HC during therapy for SCD and pave the way for an improved understanding of the HbF induction-independent benefits of HC.
Published in
Impact of hydroxycarbamide treatment on the whole-blood transcriptome in sickle cell disease
Bhat V, Potdar AA, Yu GK et al. · British journal of haematology 2025 · PMID 39552261 · doi:10.1111/bjh.19839
This dataset
Open GSE254951 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 GSE254951_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 PRJNA1072682 and SRA study SRP487803. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39552261) ↗
Study design
25 × Blood, HU-MTD, HU vs 23 × Blood, pre-HU, HU vs 2 × Blood, HU-Washout, HU

Supports a between-group comparison across 50 samples.

How we read this: 3 replicated groups read from 50 sample titles; they account for 50 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

+ 10 more — browse all 50 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.