← BioTransfer GEO Dataset Finder
GEO series

Inactivation of CDKN2A-ARF Promotes p53-Independent Remodeling of the PDAC Tumor Microenvironment [RNA-Seq]

GSE319318 Mus musculus (mouse) RNA-seq (gene expression) 20 samples Submitted 2026/02/18 Platform GPL21103
At a glance

RNA-seq (gene expression) · mouse · 20 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
20 samples: 20 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
Inactivation of CDKN2AARF Promotes p53-Independent Remodeling of the PDAC Tumor MicroenvironmentCancer research · 2026
Summary (written by the submitters)
The CDKN2A locus, which is frequently deleted in pancreatic ductal adenocarcinoma (PDAC), encodes two tumor suppressors, ARF and INK4A, that may influence tumorigenesis through distinct mechanisms. Distinguishing their individual contributions to cancer could help improve the understanding of PDAC pathogenesis and potentially uncover targetable vulnerabilities.
Read the full summary ↓
Moreover, while ARF is known to enhance p53 function, defining its p53-independent activities could elucidate new processes that drive PDAC development. Here, we sought to understand ARF function in PDAC suppression. Analysis of gene expression and mutational patterns in human PDAC TCGA data indicated that CDKN2AARF and CDKN2AINK4A are commonly both affected by point mutations and/or deletions, suggesting that their combined inactivation contributes to PDAC development. In genetically engineered mouse models (GEMMs), Arf inactivation accelerated KRASG12D-driven PDAC development, both in the presence and absence of Trp53, demonstrating that ARF is a PDAC suppressor and can act in a p53-independent manner. Transcriptomic analyses of PDACs supported a p53-independent role for ARF, with ARF deficiency promoting extracellular matrix, collagen synthesis/assembly, and epithelial-mesenchymal transition gene expression programs. Accordingly, ARF-deficient PDACs displayed extensive remodeling of the tumor microenvironment (TME), associated with collagen deposition, increased tissue stiffness, and higher fibroblast content – hallmarks of aggressive and treatment-resistant PDAC stroma. Together, this study shows how ARF deficiency associated with CDKN2A inactivation sculpts the PDAC TME in a p53-independent fashion. Given the central role of the TME in PDAC progression and therapeutic resistance, these findings may provide insight critical for improving therapeutic interventions for PDAC.
Published in
Inactivation of CDKN2AARF Promotes p53-Independent Remodeling of the PDAC Tumor Microenvironment
Ferreira S, Flowers BM, Choi WY et al. · Cancer research 2026 · PMID 41811433 · doi:10.1158/0008-5472.CAN-25-1969
This dataset
Open GSE319318 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 GSE319318_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 PRJNA1422818 and SRA study SRP676610. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 41811433) ↗
Study design
20 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 20 sample titles: 20 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

Search all mouse RNA-seq datasets in GEO →

Share this dataset

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.