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Increased mRNA translation delays tumor initiation and exposes a therapeutic vulnerability in lung cancer

GSE327213 Mus musculus (mouse) RNA-seq (gene expression) 16 samples Submitted 2026/07/22 Platform GPL19057
At a glance

RNA-seq (gene expression) · mouse · 16 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
16 samples: 16 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
Increased mRNA translation delays tumour initiation and exposes a therapeutic vulnerability in lung cancerMolecular cancer · 2026
Summary (written by the submitters)
Although protein synthesis inhibitors are being evaluated as anti-cancer agents, the dynamics of mRNA translation in early tumorigenesis are still poorly understood. We report that deletion of the mRNA-translation repressor, eIF4A2 in early KRAS-driven lung adenocarcinoma leads to a dysregulated protein synthesis landscape characterised by a strongly upregulated secretome, enlarged secretory compartments, increased oxidative metabolism and acquisition of senescence-like characteristics.
Read the full summary ↓
Paradoxically, this overdriven protein synthesis landscape delays tumorigenesis and leads to appearance of clusters of non-proliferative, p21-positive KRAS-expressing cells in the lung. Administration of rapamycin to reduce mRNA translation, suppresses senescence and restores tumorigenesis following eIF4A2 deletion. Importantly, some eIF4A2 deleted cells overcome senescence to form tumors that growth aggressively. Analysis of these eIF4A2-deleted tumors through a combination of multiplex imaging and spatial transcriptomics pointed to a rewiring of KRAS downstream pathways through enhanced MAP-kinase and reduced PI3K signalling. Consequently, these tumors may be eradicated by administration of a MEK inhibitor, in contrast to eIF4A2 positive lesions. Thus, dysregulated mRNA translation exposes a potential therapeutic vulnerability in KRAS-driven lung adenocarcinoma by forcing cancer cells to rely on MEK signalling.
Published in
Increased mRNA translation delays tumour initiation and exposes a therapeutic vulnerability in lung cancer
Pardo L, Moore M, Deshmukh R et al. · Molecular cancer 2026 · PMID 42163342 · doi:10.1186/s12943-026-02680-z
This dataset
Open GSE327213 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 GSE327213_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 PRJNA1449980 and SRA study SRP689847. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42163342) ↗
Study design
16 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 16 sample titles: 16 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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