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In vivo engineering of hematopoietic stem cells by targeted lipid nanoparticles within humanized mice

GSE318716 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2026/06/20 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples: 7 conditions, mostly in triplicateGroups 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)
In vivo genetic engineering of hematopoietic stem and progenitor cells (HSPCs) holds the potential to revolutionize the treatment landscape for numerous diseases with unmet clinical needs. An optimal delivery system for genetic medicines must target quiescent human HSCs to ensure long-term therapeutic efficacy. Here, we screened 15 lipid nanoparticles (LNPs) with different PEG-lipid structures and reported an LNP named LNPDP that demonstrated efficient delivery of reporter mRNA to human HSPCs both in ex vivo and in vivo settings, when conjugated with the anti-CD34 antibody (CD34/LNPDP).
Read the full summary ↓
Using CRISPR/Cas editing cargos, CD34/LNPDP achieved high editing efficiency in human HSPCs ex vivo. Subtle transcriptomic alterations were detected following LNP treatment, primarily attributed to the cellular uptake of exogenous cholesterol. Intrafemoral administration of CD34/LNPDP in humanized mice resulted in efficient editing of the erythroid-specific BCL11A enhancer within human HSPCs, which enables the sustained long-term reactivation of fetal hemoglobin (HbF) expression in erythroid cells. Furthermore, utilizing an additional humanized neutropenia model harboring an ELANE mutation, we demonstrated that intrafemoral administration of CD34/LNPDP can achieve robust editing targeting exon 2 of ELANE in human HSPCs, thereby attenuating the expression of mutant ELANE and partially restoring neutrophil development impairment under long-term observation. Notably, the genetically modified HSPCs exhibited unbiased repopulation of the entire hematopoietic hierarchy following LNP administration. Collectively, targeting CD34 on human HSPCs provides a novel platform to modify HSPCs for in vivo gene therapy without perturbing normal hematopoietic output, making it a promising candidate for clinical translation.
This dataset
Open GSE318716 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 GSE318716_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 PRJNA1419830 and SRA study SRP675258. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
7 conditions, mostly in triplicate
CD34+ HSPCs-RNA_Mock-1 ×3 CD34+ HSPCs-RNA_IgG/LNPDP-1 ×3 CD34+ HSPCs-RNA_CD34/LNPDP-1 ×3 CD34+ HSPCs-RNA_Mock-2 ×3 CD34+ HSPCs-RNA_LNPDP-2 ×3 CD34+ HSPCs-RNA_IgG/LNPDP-2 ×3 CD34+ HSPCs-RNA_CD34/LNPDP-2 ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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
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