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Transcriptomic profiling of pancreatic cancer cells and tissues from genetically engineered mouse models

GSE301904 Mus musculus (mouse) RNA-seq (gene expression) 19 samples Submitted 2026/04/30 Platform GPL28457
At a glance

RNA-seq (gene expression) · mouse · 19 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
19 samples
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
NF-κB inducing kinase (NIK) deletion accelerates KRAS-driven pancreatic cancer in association with tumor microenvironment remodelingCell death & disease · 2026
Summary (written by the submitters)
This study investigates transcriptomic alterations associated with pancreatic ductal adenocarcinoma (PDAC) progression in genetically engineered mouse models. Total RNA was extracted from two types of samples: (1) pancreatic cancer cells isolated from KPC and KPNiC tumors, and (2) whole pancreatic tissue lysates from WT, NiC, KC, and KNiC mice.
Read the full summary ↓
RNA-seq libraries were polyA-selected and strand-specific, sequenced on the DNBSEQ-G400 platform (BGI Genomics). Bioinformatic analyses included read alignment (HISAT2), quantification (RSEM), differential gene expression (DESeq2), and gene set enrichment analysis (GSEA). This dataset provides insights into the impact of NIK deletion on pancreatic tumor biology.
Published in
NF-κB inducing kinase (NIK) deletion accelerates KRAS-driven pancreatic cancer in association with tumor microenvironment remodeling
Du Z, Büttner UFG, Wirth HL et al. · Cell death & disease 2026 · PMID 42203767 · doi:10.1038/s41419-026-08877-w
This dataset
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.

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 GSE301904_RAW.tar (it can run to tens of gigabytes).

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.

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 PRJNA1287719 and SRA study SRP599302. Searching any of these in the dataset finder brings you back here.

Samples in this study

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+ 19 more — browse all 19 samples with per-sample file links →

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