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Custom-designed lipid-based nanoparticles efficiently deliver mRNA to reverse the pathogenesis of LAL deficiency in a preclinical model

GSE280933 Mus musculus (mouse) RNA-seq (gene expression) 28 samples Submitted 2024/12/06 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 28 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
Mus musculus (mouse)
Samples
28 samples: 28 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)
Lysosomal acid lipase (LAL) is a crucial enzyme responsible for the hydrolysis of triglycerides (TGs) and cholesteryl esters (CEs) in the lysosomes. LAL deficiency results in the extensive storage of CEs and TGs in the liver and the spleen, inducing hepatosplenomegaly, and can be a life-threatening condition with patients rarely surviving beyond 6 months of age in the most aggressive form.
Read the full summary ↓
Using messenger ribonucleic acid (mRNA) for protein replacement is an innovative approach to treating LAL deficiency. Here, we describe the development of a new lipid-based nanoparticle (LNP) formulation capable of efficiently delivering LAL mRNA and restoring LAL activity in affected organs mediating significant reversal of the pathological progression in a highly predictive preclinical model. A combinatorial library of mRNA-LNPs was generated and screened both in vitro and in vivo to yield a new formulation with a higher potency than an FDA-approved MC3-based nano-formulation. In vivo evaluation revealed that the new formulation could promote a more sustained and superior LAL expression. Multiple injection regimen was able to mitigate hepatosplenomegaly and reduce the lipid accumulation of CEs and TGs by 20-30% in the liver and 50% in the spleen. Furthermore, liver inflammation processes and development of fibrosis were significantly diminished. These findings provide strong evidence that mRNA-LNP is a very promising approach for the chronic treatment of LAL deficiency and support the clinical translation of mRNA therapy to overcome side effects and challenges encountered with traditional enzyme replacement therapies.
This dataset
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.

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 GSE280933_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1181265 and SRA study SRP542772. Searching any of these in the dataset finder brings you back here.

Study design
28 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 28 sample titles: 28 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
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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.