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Comparative analysis of replicative and doxorubicin-induced senescence identifies conserved transcriptomic signatures in aging fibroblasts [RNA-Seq1]

GSE301164 Homo sapiens (human) RNA-seq (gene expression) 21 samples Submitted 2025/12/02 Platform GPL29480
At a glance

RNA-seq (gene expression) · human · 21 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
21 samples: 7 conditions, mostly in triplicateGroups 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
Targeting PURPL RNA enabled rejuvenation of senescence cells via epigenetic reprogrammingJournal of translational medicine · 2025
Summary (written by the submitters)
We established parallel replicative and doxorubicin-induced senescence models in human BJ fibroblasts, demonstrating progressive morphological changes and SA-β-gal activity increases across passages (P3-P33). Molecular analyses confirmed expected senescence markers: p21/p53 upregulation and LMNB1 downregulation at RNA/protein levels. Transcriptomic profiling identified 734 upregulated (extracellular matrix organization) and 195 downregulated (cell cycle) genes.
Read the full summary ↓
Comparative lncRNA analysis revealed 23 consistently upregulated candidates, with PURPL showing the most dramatic senescence-associated induction. These validated models provide a robust platform for mechanistic aging studies, with PURPL emerging as a key regulator of cellular senescence.
Published in
Targeting PURPL RNA enabled rejuvenation of senescence cells via epigenetic reprogramming
Wang J, Yang X, Su X et al. · Journal of translational medicine 2025 · PMID 41107828 · doi:10.1186/s12967-025-07208-5
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 GSE301164_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 PRJNA1284213 and SRA study SRP596169. Searching any of these in the dataset finder brings you back here.

Study design
7 conditions, mostly in triplicate
BJ P3, ×3 BJ P11, ×3 BJ P24, ×3 BJ P30, ×3 BJ P33, ×3 BJ P11_DOX_50ngml, ×3 BJ P11_DMSO, ×3

Supports a between-group comparison across 21 samples.

How we read this: 7 replicated groups read from 21 sample titles; they account for 21 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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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.