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High-Throughput Drug Discovery for a Rare Neurological Disorder: Uncovering a Novel Therapeutic Opportunity for the 19q12 Autism Spectrum Disorder [DRUGseq]

GSE292759 Homo sapiens (human) RNA-seq (gene expression) 68 samples Submitted 2025/03/24 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 68 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
68 samples: 11 conditions, mostly with about 4 replicates eachGroups 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
High-throughput transcriptomic screening reveals entrectinib as a repositioning opportunity in 19q12 autism spectrum disorderScientific reports · 2025
Summary (written by the submitters)
Discovering new and viable therapies for genetic diseases is a time consuming and cost intensive process. This is even more challenging for rare disorders that affect a small fraction of the population and do not incentivise research and development in the traditional drug discovery lifecycle. There is therefore a need for scalable and efficient solutions for discovering novel therapies for these rare disorders.
Read the full summary ↓
In this study, we highlight how a high-throughput drug discovery engine was utilized to uncover drugs at scale that normalized the signature for a rare neurological neurodevelopmental disease, 19q12 autism spectrum disorder associated with deficiencies in ZNF536 and TSHZ3. We do this by uncovering and understanding the full 360o view of the biological impact of the drug in a relevant cell line via transcriptomics. This platform, in combination with a statistically viable n-of-1 trial, was able to quickly uncover and utilize a novel therapeutic potential of a previously approved drug for a patient living with from 19q12 autism spectrum disorder.
Published in
High-throughput transcriptomic screening reveals entrectinib as a repositioning opportunity in 19q12 autism spectrum disorder
Guin D, Haditsch U, Bellucci JJ et al. · Scientific reports 2025 · PMID 41290998 · doi:10.1038/s41598-025-26015-y
This dataset
Open GSE292759 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 GSE292759_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 PRJNA1241214 and SRA study SRP572669. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41290998) ↗
Study design
11 conditions, mostly with about 4 replicates each
DMSO control well, biol ×28 Entrectinib treated well at 0.005 µM, biol ×4 Entrectinib treated well at 0.002 µM, biol ×4 Entrectinib treated well at 0.0005 µM, biol ×4 Entrectinib treated well at 10.0 µM, biol ×4 Entrectinib treated well at 3.33 µM, biol ×4 Entrectinib treated well at 1.11 µM, biol ×4 Entrectinib treated well at 0.37 µM, biol ×4 +3 more

Supports a case/control comparison: 40 samples read as cases, 28 as controls.

How we read this: 11 replicated groups read from 68 sample titles; they account for 68 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

+ 28 more — browse all 68 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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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.