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Nanoengineered 3D culture substrate enables superior long-term and polyclonal engraftment of genetically engineered hematopoietic stem and progenitor cells

GSE280536 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/12/09 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 12 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
12 samples: 3 × 2D - Day4 vs 3 × 2D - Day7 vs 3 × 3D - Day4 vs 3 × 3D - Day7Groups 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)
Ex vivo culture of hematopoietic stem and progenitor cells is crucial for gene therapy applications but inadvertently triggers detrimental cellular responses, potentially threatening clinical success. In this study, we employ a biocompatible 3D scaffold with cell-scale resolution to provide mechanical support during ex vivo manipulation.
Read the full summary ↓
This innovative 3D culture system improves multi-lineage differentiation and engraftment capacity by leveraging mechanobiological control over nuclear morphology, cytoskeleton organization, metabolism, and DNA integrity. Notably, 3D culture enables efficient genetic engineering across multiple platforms, including long-range gene editing, base- and prime-editing, and lentiviral gene addition. Moreover, this scaffold increases the clonal output and the long-term persistence of genetically engineered cells in xenotransplantation experiments and outperforms traditional 2D culture in a clinical protocol for Wiskott-Aldrich Syndrome. Overall, we propose a transformative approach to enhance the efficacy and safety of hematopoietic stem cell-based gene therapies within emerging and pre-existing clinical workflows.
This dataset
Open GSE280536 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 GSE280536_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 PRJNA1179370 and SRA study SRP541766. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × 2D - Day4 vs 3 × 2D - Day7 vs 3 × 3D - Day4 vs 3 × 3D - Day7

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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
Datasets on a similar topic

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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.