GEO series

A p53-CCF circuit integrates genome integrity with senescence phenotypes [RNA-Seq 1]

GSE259291 Homo sapiens (human) Single-cell RNA-seq 12 samples Submitted 2025/02/11 Platform GPL18573

At a glance

Single-cell RNA-seq · human · 12 samples

What it is: Single-cell RNA-seqGene activity measured in thousands of individual cells, so cell types can be told apart. Read from the summary: GEO's own type field only says 'expression profiling by sequencing', so confirm it in the paper.
Organism: Homo sapiens (human)
Samples: 12 samples: 3 × IMR90 cells, proliferating, empty vector, vs 3 × IMR90 cells, proliferating, 53BP1 OE, vs 3 × IMR90 cells, IR, empty vector, vs 3 × IMR90 cells, IR, 53BP1 OE,Groups 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: p53 enhances DNA repair and suppresses cytoplasmic chromatin fragments and inflammation in senescent cellsNature communications · 2025

Summary (written by the submitters)

Genomic instability and inflammation are distinct hallmarks of aging, but the connection between them is poorly understood. Understanding their interrelationship will help unravel new mechanisms and therapeutic targets of aging and age-associated diseases. Here we report a novel mechanism directly linking genomic instability and inflammation in senescent cells, through a mitochondria-regulated molecular circuit that connects the p53 tumor suppressor and cytoplasmic chromatin fragments (CCF), a driver of inflammation through the cGAS-STING pathway.

Read the full summary ↓

Activation or inactivation of p53 by genetic and pharmacologic approaches showed that p53 suppresses CCF accumulation and the downstream inflammatory senescence-associated secretory phenotype (SASP), independent of its effects on cell cycle arrest. p53 activation suppressed CCF formation by promoting DNA repair, reflected in maintenance of genomic integrity, particularly in subtelomeric regions, as shown by single cell genome resequencing. Activation of p53 by pharmacological inhibition of MDM2 in old mice decreased features of SASP in liver, indicating a senomorphic role in vivo. Remarkably, mitochondria in senescent cells suppressed p53 activity by promoting CCF formation and thereby restricting ATM-dependent nuclear DNA damage signaling. These data provide evidence for a mitochondria-regulated p53-CCF circuit in senescent cells that controls DNA repair, genome integrity and inflammatory SASP, and is a potential target for senomorphic healthy aging interventions.

Published in

p53 enhances DNA repair and suppresses cytoplasmic chromatin fragments and inflammation in senescent cells

Miller KN, Li B, Pierce-Hoffman HR et al. · Nature communications 2025 · PMID 40044657 · doi:10.1038/s41467-025-57229-3

This dataset

Open GSE259291 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 GSE259291_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: Single-cell studies usually ship their counts as 10x files (matrix.mtx, barcodes.tsv, features.tsv), an .h5 file, or an .rds / .h5ad object that Seurat or Scanpy can open. Look for those among the supplementary files.

Also filed as BioProject PRJNA1080591 and SRA study SRP491849. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40044657) ↗

Study design

3 × IMR90 cells, proliferating, empty vector, vs 3 × IMR90 cells, proliferating, 53BP1 OE, vs 3 × IMR90 cells, IR, empty vector, vs 3 × IMR90 cells, IR, 53BP1 OE,

Supports a between-group comparison across 12 samples.

How we read this: 4 replicated groups read from 12 sample titles; they account for 12 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

GSM8113395 IMR90 cells, proliferating, empty vector, rep 1 IMR90 cells, proliferat…
GSM8113396 IMR90 cells, proliferating, empty vector, rep 2 IMR90 cells, proliferat…
GSM8113397 IMR90 cells, proliferating, empty vector, rep 3 IMR90 cells, proliferat…
GSM8113398 IMR90 cells, proliferating, 53BP1 OE, rep 1 IMR90 cells, proliferat…
GSM8113399 IMR90 cells, proliferating, 53BP1 OE, rep 2 IMR90 cells, proliferat…
GSM8113400 IMR90 cells, proliferating, 53BP1 OE, rep 3 IMR90 cells, proliferat…
GSM8113401 IMR90 cells, IR, empty vector, rep 1 IMR90 cells, IR, empty …
GSM8113402 IMR90 cells, IR, empty vector, rep 2 IMR90 cells, IR, empty …
GSM8113403 IMR90 cells, IR, empty vector, rep 3 IMR90 cells, IR, empty …
GSM8113404 IMR90 cells, IR, 53BP1 OE, rep 1 IMR90 cells, IR, 53BP1 …
GSM8113405 IMR90 cells, IR, 53BP1 OE, rep 2 IMR90 cells, IR, 53BP1 …
GSM8113406 IMR90 cells, IR, 53BP1 OE, rep 3 IMR90 cells, IR, 53BP1 …

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