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Maintenance of p-eIF2 alpha levels by the eIF2B complex is vital for colorectal cancer

GSE249128 Homo sapiens (human) RNA-seq (gene expression) 48 samples Submitted 2025/01/09 Platform GPL18573
At a glance

RNA-seq (gene expression) · human · 48 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)
Topic
Colorectal cancerThis series is part of our curated briefing on it.
Samples
48 samples: 48 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
Maintenance of p-eIF2α levels by the eIF2B complex is vital for colorectal cancerThe EMBO journal · 2025
Summary (written by the submitters)
Protein synthesis is an essential cellular process highly deregulated in multiple tumour types, where control of several translation factors is hijacked to benefit oncogenic growth. Here we show that colorectal cancer (CRC) is characterized specifically by elevated levels of phosphorylated eukaryotic initiation factor 2 alpha (p-eIF2alpha).
Read the full summary ↓
In contrast to its canonical association with reduced translation rates, we reveal that CRC with high p-eIF2alpha has increased protein synthesis rates. Thus, we hypothesize that eIF2B, the sensor of p-eIF2 alpha, plays a central role in cells’ inability to relay this inhibitory signal. Using a combination of in cellulo biochemistry, phenotypic assays, and analysis of translation upon modulation of eIF2B subunits alpha and delta, the two eIF2B subunits responsible for sensing p-eIF2 alpha, we demonstrate that CRC cells require an intact eIF2B complex to sense p-eIF2 alpha. Crucially, we show that the alpha subunit of eIF2B is necessary to translate the oncogenic programs driven by APC loss, highlighting its central role in oncogenic transformation. To conclude, we demonstrate that whilst normal cells do not depend on eIF2B alpha, CRC cells require this eIF2B subunit for correct sensing of p-eIF2 alpha and regulation of their proteostasis, thus validating eIF2B alpha as a target for therapeutic intervention in CRC.
Published in
Maintenance of p-eIF2α levels by the eIF2B complex is vital for colorectal cancer
Škapik IP, Giacomelli C, Hahn S et al. · The EMBO journal 2025 · PMID 40016419 · doi:10.1038/s44318-025-00381-9
This dataset
Open GSE249128 in finder → Find more human RNA-seq datasets → Colorectal cancer landscape →
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 GSE249128_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 PRJNA1047524 and SRA study SRP475305. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 40016419) ↗
Study design
48 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 48 sample titles: 48 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

+ 8 more — browse all 48 samples with per-sample file links →

More Colorectal cancer datasets

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.