GEO series

Liver-specific delivery of MDM2 antisense oligonucleotides counteracts diet-induced metabolic dysfunction-associated steatotic liver diseases

GSE312061 Mus musculus (mouse) RNA-seq (gene expression) 18 samples Submitted 2026/01/13 Platform GPL13112Platform GPL28457

At a glance

RNA-seq (gene expression) · mouse · 18 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: 18 samples: 5 × GalNAc‐conASO_CDAHFD vs 5 × GalNAc‐Mdm2ASO_CDAHFD vs 4 × GalNAc‐conASO_HFHC vs 4 × GalNAc‐Mdm2ASO_HFHCGroups 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: Liver-specific delivery of MDM2 antisense oligonucleotides counteracts diet-induced metabolic-dysfunction-associated steatotic liver diseasesMolecular therapy. Nucleic acids · 2026

Summary (written by the submitters)

Metabolic dysfunction-associated steatotic liver disease (MASLD) encompasses a spectrum of pathogenic conditions ranging from steatosis, inflammation and fibrosis with limited treatment options. We previously demonstrated an upregulation of hepatic murine double minute 2 (MDM2) in human subjects with MASLD. Genetic deletion of hepatic MDM2 and pharmacological inhibition of systemic MDM2 improves steatosis and fibrosis in mouse models.

Read the full summary ↓

In this study, we further developed and investigated the therapeutic potential of a hepatocyte-specific triantennary N-acetylgalactosamine (GalNAc)-conjugated antisense oligonucleotide targeting MDM2 (GalNAc-Mdm2ASO) in two distinct dietary-induced mouse models of MASLD: a high-fat-high-cholesterol (HFHC) diet and a choline-deficient L-amino acid-defined high-fat diet (CDAHFD). In the HFHC-induced MASLD model, GalNAc‐Mdm2ASO not only alleviated liver injury, steatosis, and fibrosis but also improved obesity-related insulin resistance and hyperlipidaemia. The hepatoprotective effects of GalNAc-Mdm2ASO treatment were associated with a reduced accumulation of hepatic cholesterol and ceramide, both of which are known to trigger MASLD. In CDAHFD-induced MASLD mouse model, GalNAc‐Mdm2ASO significantly mitigated hepatic inflammation, cholesterol accumulation, and fibrosis but not triglyceride accumulation. Overall, we prove hepatic inhibition of MDM2 using GalNAc-Mdm2ASO as a promising therapeutic agent for MASLD in two rodent models with distinct pathogenesis.

Published in

Liver-specific delivery of MDM2 antisense oligonucleotides counteracts diet-induced metabolic-dysfunction-associated steatotic liver diseases

Hoque MM, Kong M, Yuan X et al. · Molecular therapy. Nucleic acids 2026 · PMID 41646884 · doi:10.1016/j.omtn.2026.102837

This dataset

Open GSE312061 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 GSE312061_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 PRJNA1372128 and SRA study SRP650344. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41646884) ↗

Study design

5 × GalNAc‐conASO_CDAHFD vs 5 × GalNAc‐Mdm2ASO_CDAHFD vs 4 × GalNAc‐conASO_HFHC vs 4 × GalNAc‐Mdm2ASO_HFHC

Supports a between-group comparison across 18 samples.

How we read this: 4 replicated groups read from 18 sample titles; they account for 18 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

GSM9337053 GalNAc‐conASO_HFHC-01 GalNAc‐conASO_HFHC
GSM9337054 GalNAc‐conASO_HFHC-02 GalNAc‐conASO_HFHC
GSM9337055 GalNAc‐conASO_HFHC-04 GalNAc‐conASO_HFHC
GSM9337056 GalNAc‐conASO_HFHC-05 GalNAc‐conASO_HFHC
GSM9337057 GalNAc‐Mdm2ASO_HFHC-06 GalNAc‐Mdm2ASO_HFHC
GSM9337058 GalNAc‐Mdm2ASO_HFHC-07 GalNAc‐Mdm2ASO_HFHC
GSM9337059 GalNAc‐Mdm2ASO_HFHC09 GalNAc‐Mdm2ASO_HFHC
GSM9337060 GalNAc‐Mdm2ASO_HFHC-10 GalNAc‐Mdm2ASO_HFHC
GSM9337061 GalNAc‐conASO_CDAHFD-01 GalNAc‐conASO_CDAHFD
GSM9337062 GalNAc‐conASO_CDAHFD-02 GalNAc‐conASO_CDAHFD
GSM9337063 GalNAc‐conASO_CDAHFD-03 GalNAc‐conASO_CDAHFD
GSM9337064 GalNAc‐conASO_CDAHFD-04 GalNAc‐conASO_CDAHFD
GSM9337065 GalNAc‐conASO_CDAHFD-05 GalNAc‐conASO_CDAHFD
GSM9337066 GalNAc‐Mdm2ASO_CDAHFD-06 GalNAc‐Mdm2ASO_CDAHFD
GSM9337067 GalNAc‐Mdm2ASO_CDAHFD-07 GalNAc‐Mdm2ASO_CDAHFD
GSM9337068 GalNAc‐Mdm2ASO_CDAHFD-08 GalNAc‐Mdm2ASO_CDAHFD
GSM9337069 GalNAc‐Mdm2ASO_CDAHFD-09 GalNAc‐Mdm2ASO_CDAHFD
GSM9337070 GalNAc‐Mdm2ASO_CDAHFD-10 GalNAc‐Mdm2ASO_CDAHFD

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