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Transcriptional profiling of Hutchinson-Gilford Progeria patients identifies primary target pathways of the disease-causing progerin protein

GSE306264 Homo sapiens (human) RNA-seq (gene expression) 96 samples Submitted 2025/11/13 Platform GPL24676
At a glance

RNA-seq (gene expression) · human · 96 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
96 samples: 96 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.
Paper
Transcriptional profiling of Hutchinson-Gilford Progeria patients identifies primary target pathways of progerinbioRxiv : the preprint server for biology · 2025
Summary (written by the submitters)
Hutchinson Gilford Progeria Syndrome (HGPS) is an ultra-rare pediatric premature aging disorder. The disease is caused by a point mutation in the LMNA gene leading to the production of the dominant-negative progerin isoform of the nuclear envelope protein lamin A. Disease severity and progression amongst the population of ~140 known patients is variable.
Read the full summary ↓
Numerous cellular pathways have been implicated in the disease mechanism, including mTOR signaling, stem cell differentiation and the oxidative stress response. Most of mechanistic insights into the disease have come from studies using cellular or mouse models of HGPS. To probe the clinical relevance of previously implicated cellular pathways and to address the extent of gene expression heterogeneity between patients, we have performed transcriptomic analysis of a comprehensive set of HGPS patients. We find misexpression of several of the major HGPS-associated cellular pathways across the patient population, particularly of multiple signaling pathways as well as the Unfolded Protein Response (UPR) and mesodermal cell fate specification. Variability amongst individual patients was limited with misregulation of the major pathways observed in most patients. Comparing the transcriptome of patients with an inducible HGPS cell model, we distinguished immediate-early cellular response pathways from secondary adaptive pathways and identify mTOR, the UPR, UV response, apoptosis and TNFa signaling via NFkB as primary targets of the disease-causing progerin protein.
Published in
Transcriptional profiling of Hutchinson-Gilford Progeria patients identifies primary target pathways of progerin
Vidak S, Kim S, Misteli T · bioRxiv : the preprint server for biology 2025 · PMID 41000886 · doi:10.1101/2025.09.18.677125
This dataset
Open GSE306264 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 GSE306264_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 PRJNA1310322 and SRA study SRP612248. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41000886) ↗
Study design
96 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 96 sample titles: 96 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

+ 56 more — browse all 96 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.