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Senescence-associated dysregulation of translation inhibits activation of the integrated stress response

GSE223762 Homo sapiens (human) RNA-seq (gene expression) 54 samples Submitted 2024/09/18 Platform GPL24106Platform GPL26167
At a glance

RNA-seq (gene expression) · human · 54 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
54 samples: 42 distinct titles, 12 of them repeatedGroups 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
Senescence suppresses the integrated stress response and activates a stress-enhanced secretory phenotypebioRxiv : the preprint server for biology · 2023
Summary (written by the submitters)
Senescence is a state of indefinite cell cycle arrest associated with aging, cancer, and age-related diseases. Here we find that translational deregulation and a corresponding maladaptive integrated stress response (ISR) is a hallmark of senescence that desensitizes senescent cells to stress. We present evidence that senescent cells maintain high levels of eIF2?
Read the full summary ↓
phosphorylation, typical of ISR activation, but translationally repress production of the stress response transcription factor 4 (ATF4) by ineffective bypass of the inhibitory upstream open reading frames (uORFs). Surprisingly, ATF4 translation remains inhibited even after acute proteotoxic and amino acid starvation stressors, resulting in a highly diminished stress response. We also find that stress augments the senescence associated secretory phenotype with sustained remodeling of inflammatory factors expression that is suppressed by non-uORF carrying ATF4 mRNA expression. Our results thus show that senescent cells possess a unique response to stress that entails an increase in their inflammatory profile.
Published in
Senescence suppresses the integrated stress response and activates a stress-enhanced secretory phenotype
Payea MJ, Dar SA, Anerillas C et al. · bioRxiv : the preprint server for biology 2023 · PMID 37609272 · doi:10.1101/2023.04.12.536613
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 GSE223762_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 PRJNA928344 and SRA study SRP419253. Searching any of these in the dataset finder brings you back here.

Study design
42 distinct titles, 12 of them repeated
Cycling cells, ×2 Etoposide-induced senecent cells, ×2 Cycling cells starved for Methionine and Cyst… ×2 Cycling cells treated with 25 nM thapsigargin… ×2 Etoposide-induced senescent cells cells starv… ×2 Etoposide-induced senescent cells cells treat… ×2 Sen-Etop mock treat rep 1, expt ×2 Sen-Etop mock treat rep 2, expt ×2 +4 more

Supports a case/control comparison: 8 samples read as cases, 17 as controls.

How we read this: Read from 54 sample titles: 42 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

+ 14 more — browse all 54 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.