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RNA-sea of Smad4 wild-type or Smad4 knockout KPC PDAC organoids from monocultures or co-cultures with pancreatic stellate cells and RNA-seq of flow-sorted PSCs from the same co-cultures.

GSE263080 Mus musculus (mouse) RNA-seq (gene expression) 44 samples Submitted 2024/12/02 Platform GPL24247
At a glance

RNA-seq (gene expression) · mouse · 44 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
44 samples: 44 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
SMAD4 and KRAS Status Shapes Cancer Cell-Stromal Cross-Talk and Therapeutic Response in Pancreatic CancerCancer research · 2025
Summary (written by the submitters)
RNA-sequencing of flow-sorted Smad4 wild-type (WT) or Smad4 knockout (KO) KPC (i.e. KRASG12D; p53 mutant) pancreatic ductal adenocarcinoma (PDAC) organoids from monocultures or co-cultures with pancreatic stellate cells (PSCs) and RNA-sequencing of flow-sorted PSCs from the same co-cultures. We investigated changes in transcriptome in Smad4 KO KPC PDAC organoids compared to Smad4 WT KPC PDAC organoids in monoculture or in co-culture with PSCs. We also investigated the changes in transcriptome in PSCs co-cultured with Smad4 WT or Smad4 KO KPC PDAC organoids.
Published in
SMAD4 and KRAS Status Shapes Cancer Cell-Stromal Cross-Talk and Therapeutic Response in Pancreatic Cancer
Lloyd EG, Jihad M, Manansala JS et al. · Cancer research 2025 · PMID 39841099 · doi:10.1158/0008-5472.CAN-24-2330
This dataset
Open GSE263080 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 GSE263080_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 PRJNA1095551 and SRA study SRP499390. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 39841099) ↗
Study design
44 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 44 sample titles: 44 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

+ 4 more — browse all 44 samples with per-sample file links →

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.