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Cell Delivery Agent as Drug. A Multitarget Agent Delivers an Antisense Oligonucleotide for Synergistic Activity in Myotonic Dystrophy Type 1

GSE157861 Homo sapiens (human) RNA-seq (gene expression) 12 samples Submitted 2025/08/06 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: 10 distinct titles, 1 of them repeatedGroups 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
Drug delivery agent that acts as a drug for synergistic activityiScience · 2025
Summary (written by the submitters)
Drug delivery vehicles are hoped to be inert, although many suffer toxicity issues that limit their use. In developing potential agents to treat myotonic dystrophy type 1 (DM1), we wondered if a delivery vehicle might be designed to be a direct acting drug. DM1 is an incurable neurodegenerative disease that originates from expanded (CTG)·(CAG) repeats in the 3'-UTR of the DMPK gene.
Read the full summary ↓
The majority of drug discovery efforts have been focused on development of small molecules that inhibit MBNL1 protein sequestration by the expanded RNA transcript, r(CUG)exp. Antisense oligonucleotides (ASOs) have also been utilized to treat DM1. However, ASOs normally exhibit poor cell penetration so considerable effort has focused on their delivery. Herein, we report a series of multitargeting oligomeric ligands that have been developed to serve both as drug molecules and as antisense delivery vehicles for DM1. As a result of multivalency, the longer oligomers bound the target DNA and RNA with nanomolar affinities, in vitro, and exhibited improved disease outcomes in DM cell culture model and DM1 patient myotubes. The oligomers form polyplexes with a locked nucleic acid (LNA) CAG16 gapmer, facilitating its cell uptake in both HeLa cells and DM1 patient myotubes decreasing the level of toxic r(CUG)exp significantly. RNA-seq analysis indicated that the oligomeric ligand and its polyplex can rescue DM1 associated splicing defects and gene expression changes transcriptome-wide in DM1 patient myotubes.
Published in
Drug delivery agent that acts as a drug for synergistic activity
Li K, Chembazhi UV, Krueger SB et al. · iScience 2025 · PMID 40727942 · doi:10.1016/j.isci.2025.112890
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 GSE157861_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 PRJNA662996 and SRA study SRP282152. Searching any of these in the dataset finder brings you back here.

Study design
10 distinct titles, 1 of them repeated
mRNA_LG ×3

How we read this: Read from 12 sample titles: 10 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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