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Progressive suppression of DNA repair genes with persistent p53 activation in Doxorubicin-treated cardiomyocytes

GSE313746 Homo sapiens (human) RNA-seq (gene expression) 42 samples Submitted 2026/05/26 Platform GPL34295
At a glance

RNA-seq (gene expression) · human · 42 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
42 samples: 6 conditions, mostly with about 6 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.
Summary (written by the submitters)
Doxorubicin (DOX) is an effective anti-cancer drug; however it can cause cardiotoxicity by inducing DNA double strand breaks in cardiomyocytes. Cardiotoxicity can present immediately or years following treatment. Most human in vitro models of DOX-induced cardiotoxicity (DIC) focus on the acute effects of DOX treatment. To understand the long-term effects, we profiled the global gene expression response to DOX exposure over time.
Read the full summary ↓
We treated iPSC-derived cardiomyocytes from six individuals with DOX for 24 hours and assayed responses after 0, 24 and 144 hours of recovery. DNA damage, determined by γH2AX expression, is induced following DOX treatment and is resolved by the last recovery timepoint. We identified both acute and chronic gene expression response signatures. The chronic signature, representing 501 genes, is enriched for p53 target genes and DNA damage response genes compared to acute response genes. P53 target genes are persistently activated, and DNA damage response genes are progressively downregulated over time. Our results suggest an altered cell state following repair of double strand breaks that is distinct from pre-exposed cells. DOX response genes with persistent changes in expression can be applied to the design of toxicity biomarkers or therapeutic targets.
This dataset
Open GSE313746 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 GSE313746_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 PRJNA1381534 and SRA study SRP655255. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
6 conditions, mostly with about 6 replicates each
iPSC-CM_DOX_tx0 ×6 iPSC-CM_VEH_tx0 ×6 iPSC-CM_DOX_tx24 ×6 iPSC-CM_VEH_tx24 ×6 iPSC-CM_DOX_tx144 ×6 iPSC-CM_VEH_tx144 ×6 iPSC-CM_DOX_tx0_6R ×1 iPSC-CM_VEH_tx0_6R ×1 +4 more

Supports a between-group comparison across 36 samples.

How we read this: 6 replicated groups read from 42 sample titles; they account for 36 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

+ 2 more — browse all 42 samples with per-sample file links →

Datasets on a similar topic

Search all human RNA-seq datasets in GEO →

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