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eIF4G2-dependent translation restrains pancreatic cancer progression

GSE308769 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/04/13 Platform GPL30172
At a glance

RNA-seq (gene expression) · mouse · 12 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
12 samples: 12 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.
Summary (written by the submitters)
Pancreatic ductal adenocarcinoma (PDA) is among the most lethal cancers, driven by cellular plasticity that fuels therapeutic resistance and early dissemination. The contribution of translational control to this plasticity remains poorly understood. Through an in vivo CRISPR/Cas9 screen, we identify the non-canonical initiation factor eIF4G2 (DAP5/NAT1) as a translational checkpoint restraining PDA progression.
Read the full summary ↓
Loss of eIF4G2 accelerated tumor growth, induced poorly differentiated, basal-like histology, and triggered widespread metastatic spread. Ribosome profiling revealed that eIF4G2 loss did not increase bulk protein synthesis but instead suppressed translation of a selective regulon, including tumor suppressors such as PTEN and CREBBP. Functional studies confirmed that PTEN loss was sufficient to drive dedifferentiation but insufficient to promote metastasis, implicating the broader eIF4G2-dependent program—including translational control of transcriptional regulators like CREBBP—in limiting dissemination. Consistently, eIF4G2-deficient tumors showed transcriptomic enrichment of migratory and stemness programs. Computational inference from human PDA datasets demonstrated reduced eIF4G2 activity in metastases, aligning with basal-like features and predicting poorer survival. These results define eIF4G2 as a translational regulator that maintains epithelial identity and restrains metastatic potential, highlighting selective translation as a determinant of PDA subtype and clinical outcome.
This dataset
Open GSE308769 in finder → Find more mouse 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 GSE308769_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 PRJNA1332697 and SRA study SRP625068. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗
Study design
12 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 12 sample titles: 12 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
Datasets on a similar topic

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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.