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Endogenous p53 Inhibitor TIRR Dissociates Systemic Metabolic Health from Oncogenic Activity - RNAseq data

GSE210900 Mus musculus (mouse) RNA-seq (gene expression) 82 samples Submitted 2024/06/10 Platform GPL23479
At a glance

RNA-seq (gene expression) · mouse · 82 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
Mus musculus (mouse)
Samples
82 samples: 82 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
Endogenous p53 inhibitor TIRR dissociates systemic metabolic health from oncogenic activityCell reports · 2024
Summary (written by the submitters)
It is unclear whether metabolic health corresponds to reduced oncogenesis or vice versa. We study Tudor-interacting repair regulator (TIRR), an inhibitor of p53 binding protein 1 (53BP1)-mediated p53 activation, and the physiological consequences of enhancing tumor suppressor activity. Deleting TIRR selectively activates p53, significantly protecting against cancer but leading to a systemic metabolic imbalance in mice.
Read the full summary ↓
TIRR-deficient mice are overweight and insulin resistant, even under normal chow diet. Similarly, reduced TIRR expression in human adipose tissue correlates with higher BMI and insulin resistance. Despite the metabolic challenges, TIRR loss improves p53 heterozygous (p53HET) mouse survival and correlates with enhanced progression-free survival in patients with various p53HET carcinomas. Finally, TIRR’s oncoprotective and metabolic effects are dependent on p53 and lost upon p53 deletion in TIRR-deficient mice, with glucose homeostasis and orexigenesis being primarily regulated by TIRR expression in the adipose tissue and the CNS, respectively, as evidenced by tissue-specific models. In summary, TIRR deletion provides a paradigm of metabolic deregulation accompanied by reduced oncogenesis.
Published in
Endogenous p53 inhibitor TIRR dissociates systemic metabolic health from oncogenic activity
Tsaousidou E, Chrzanowski J, Drané P et al. · Cell reports 2024 · PMID 38861384 · doi:10.1016/j.celrep.2024.114337
This dataset
Open GSE210900 in finder → Find more mouse 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 GSE210900_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 PRJNA868216 and SRA study SRP390859. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 38861384) ↗
Study design
82 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 82 sample titles: 82 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

+ 42 more — browse all 82 samples with per-sample file links →

Datasets on a similar topic

Search all mouse 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.