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GATA4 loss promotes mutant Kras-driven pancreatic ductal adenocarcinoma in the absence of canonical precursor lesions [Epithelial RNA-seq]

GSE330245 Mus musculus (mouse) RNA-seq (gene expression) 12 samples Submitted 2026/05/12 Platform GPL24247
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)
GATA6 and GATA4 play key roles in pancreatic development and are essential to maintain the classical transcriptional program in pancreatic ductal adenocarcinoma (PDAC). Using genetic mouse models we show that, in contrast to GATA6, GATA4 is dispensable for the maintenance of acinar homeostasis in the adult pancreas.
Read the full summary ↓
Deletion of Gata4 in mice expressing mutant Kras in the embryonic pancreas (KG4C) leads to PDAC development in the absence of acinar-to-ductal metaplasia (ADM), pancreatic intraepithelial neoplasias (PanINs), or other canonical precursor lesions present in Gata4-proficient (KC) mice. Similar observations were made when Gata4 was selectively inactivated in adult, Kras-mutant, acinar cells, We identify Pale Acinar Lesions (PALes) as a previously unrecognized pancreatic lesion, distinct from ADM and PanINs, present in KC and KG4C mice but not in control mice. PALes display weak expression of acinar and ductal markers and lack mucins; they have lower proliferation rates than PanINs. RNA-seq and ChIP-seq reveal that GATA4 and GATA6 partially share genomic binding sites and transcriptomic effects, but they exert opposing influences on mutant Kras–induced, hematopoietic cell–dependent, transcriptional inflammatory signatures. Adenoviral-mediated pancreatic expression of IL17 restored the formation of ductal lesions in KG4C mice but failed to rescue PanIN development. Our data suggest that GATA4 functions through the coordinated action of multiple inflammatory factors that are required for ADM/PanIN formation but are dispensable for PDAC development. Collectively, these findings challenge current paradigms of PDAC initiation and progression.
This dataset
Open GSE330245 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 GSE330245_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 PRJNA1463230 and SRA study SRP698352. 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.