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ClinASO: a guideline for rapid drug discovery of gapmer antisense oligonucleotidess

GSE307517 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/11/03 Platform GPL35109Platform GPL35959
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 × HFD vs 3 × HFD-SG34-48 vs 3 × Hep-G2 vs 3 × Hep-G2_SG34-48Groups 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)
Metabolic dysfunction-associated steatotic liver disease (MASLD) is a chronic disorder that threatens global health, yet current treatments lack efficacy and patient compliance. Antisense oligonucleotides (ASOs) offer advantages for chronic metabolic diseases through precision targeting and long-acting effects; however, rational design remains a key barrier to drug development.
Read the full summary ↓
Here, we established an integrated Gapmer ASO design platform that incorporates SNP filtering, secondary structure prediction, off-target minimization, RNase H cleavage efficiency, and animal model compatibility to systematically identify potent ASO candidates. Targeting acyl-CoA synthetase long-chain family member 4 (ACSL4), we screened a focused panel of candidates and identified a highly efficient ASO that suppressed ACSL4 expression and reduced lipid droplet accumulation in HepG2 cells. Conjugation with N-acetylgalactosamine (GalNAc) yielded gA-28c, which achieved efficient hepatocyte uptake and robust ACSL4 knockdown at low doses (2.5 mg/kg) in vivo, with durable activity for at least 14 days and no detectable hepatotoxicity. In a chronic high-fat diet (HFD) mouse model, gA-28c markedly suppressed hepatic ACSL4, ameliorated steatosis, and restored near-normal liver histology, phenocopying ACSL4 knockout. Unexpectedly,gA-28c also normalized dyslipidemia, significantly lowering circulating cholesterol and lipoproteins, a therapeutic effect not previously observed with genetic ACSL4 depletion. Mechanistically, ACSL4 silencing by gA-28c downregulated lipid metabolic pathways and enhanced triglyceride turnover. Collectively, these findings establish gA-28c as a potent, liver-targeted, and long-acting therapeutic candidate that not only alleviates hepatic steatosis but also improves systemic lipid metabolism, underscoring the promise of ASO therapy for MASLD and hyperlipidemia
This dataset
Open GSE307517 in finder → Find more 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 GSE307517_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 PRJNA1321903 and SRA study SRP618446. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
3 × HFD vs 3 × HFD-SG34-48 vs 3 × Hep-G2 vs 3 × Hep-G2_SG34-48

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
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