← BioTransfer GEO Dataset Finder
GEO series

Exploring the mechanism of AGR2 regulating the progression of pancreatic ductal adenocarcinoma and remodeling of the tumor microenvironment

GSE267820 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2024/11/26 Platform GPL23227
At a glance

RNA-seq (gene expression) · human · 24 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
Homo sapiens (human)
Topic
Pancreatic cancerThis series is part of our curated briefing on it.
Samples
24 samples: 8 conditions, mostly in triplicateGroups 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
Disrupting AGR2/IGF1 paracrine and reciprocal signaling for pancreatic cancer therapyCell reports. Medicine · 2025
Summary (written by the submitters)
Pancreatic ductal adenocarcinoma (PDAC) is a highly invasive and lethal malignant tumor characterized by extensive desmoplasia. We found that AGR2 deletion reshapes the tumor microenvironment by affecting the activation of the IGF1 signaling pathway. On the one hand, AGR2, as an endoplasmic reticulum protein, promoted correct folding and cell surface distribution of IGF1R.
Read the full summary ↓
On the other hand, AGR2 was secreted into the extracellular space, promoting IGF1 transcription by activating the WNT pathway in cancer-associated fibroblasts (CAFs). Through these mechanisms, AGR2 significantly enhanced the IGF1 signal in the PDAC tumor microenvironment, accelerating the formation of desmoplasia and an immunosuppressive microenvironment.
Published in
Disrupting AGR2/IGF1 paracrine and reciprocal signaling for pancreatic cancer therapy
Li H, Zhang Z, Shi Z et al. · Cell reports. Medicine 2025 · PMID 39914384 · doi:10.1016/j.xcrm.2024.101927
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 GSE267820_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 PRJNA1113316 and SRA study SRP508558. Searching any of these in the dataset finder brings you back here.

Study design
8 conditions, mostly in triplicate
Panc1 cells, sgControl, ×3 Panc1 cells, sgAGR2, ×3 Capan2 cells, sgControl, ×3 Capan2 cells, sgAGR2, ×3 CAF, Control, ×3 CAF, AGR2, ×3 CAF, TGFb, ×3 CAF, IL1A, ×3

Supports a between-group comparison across 24 samples.

How we read this: 8 replicated groups read from 24 sample titles; they account for 24 of them. 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
More Pancreatic cancer datasets

Search all human 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.