GEO series

Mitophagy Competent Cancer Associated Fibroblasts fuel Chemoresistance by Rewiring Pyrimidine Metabolism in Pancreatic Cancer [RNA-Seq]

GSE330683 Homo sapiens (human) RNA-seq (gene expression) 18 samples Submitted 2026/05/13 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 18 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: 18 samples: 6 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.

Summary (written by the submitters)

Pancreatic cancer remains one of the deadliest malignancies, with gemcitabine-based chemotherapy as the mainstay treatment for most patients, yet resistance emerges almost universally. A defining feature of pancreatic cancer is its dense, fibroblast-rich stroma, where heterogeneous cancer-associated fibroblasts (CAFs) actively shape tumor biology and therapeutic response.

Read the full summary ↓

Here, we elucidated a stromal–metabolic mechanism through which chemoresistant CAFs confer gemcitabine resistance. We identified a subset of mitophagy-competent CAFs that enhanced pancreatic cancer gemcitabine resistance. The EMT transcription factor ZEB1 acts as a master regulator of this CAF-driven chemoresistance program, being upregulated and epigenetically activated via SETD1A-mediated H3K4 methylation in gemcitabine-resistant CAFs. ZEB1 promotes BNIP3-mediated mitophagy in CAFs, leading to increased nucleotides secretion, which competitively inhibited gemcitabine incorporation into cancer cells while simultaneously supplying pyrimidine metabolism substrates for pyrimidine metabolism. Concurrently, ZEB1 transcriptionally activated CXCL8, engaging the CXCR1/2–MEK/ERK pathway in tumor cells and further augmenting pyrimidine metabolism via the RRM1/E2F1/G6PD axis, collectively diminishing gemcitabine cytotoxicity. Notably, combined inhibition of CXCR1/2 or G6PD with gemcitabine robustly suppressed tumor growth and restored chemosensitivity both in vitro and in vivo. These findings uncover a key stromal–metabolic axis in pancreatic cancer, linking mitophagy CAF activity to metabolic remodeling in tumor cells, and identifying ZEB1 and its downstream network as actionable targets to overcome chemoresistance.

This dataset

Open GSE330683 in finder → Find more human RNA-seq datasets → Pancreatic cancer landscape →

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 GSE330683_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 PRJNA1465225 and SRA study SRP699653. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

6 conditions, mostly in triplicate

RNA-seq,hCAF_1, ×3 RNA-seq,hCAF_2, ×3 RNA-seq,hCAF_3, ×3 RNA-seq,hCAF_4, ×3 RNA-seq,hCAF_5, ×3 RNA-seq,hCAF_6, ×3

Supports a between-group comparison across 18 samples.

How we read this: 6 replicated groups read from 18 sample titles; they account for 18 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

GSM9730374 RNA-seq,hCAF_1,rep1 RNA-seq,hCAF_1,
GSM9730375 RNA-seq,hCAF_1,rep2 RNA-seq,hCAF_1,
GSM9730376 RNA-seq,hCAF_1,rep3 RNA-seq,hCAF_1,
GSM9730377 RNA-seq,hCAF_2,rep1 RNA-seq,hCAF_2,
GSM9730378 RNA-seq,hCAF_2,rep2 RNA-seq,hCAF_2,
GSM9730379 RNA-seq,hCAF_2,rep3 RNA-seq,hCAF_2,
GSM9730380 RNA-seq,hCAF_3,rep1 RNA-seq,hCAF_3,
GSM9730381 RNA-seq,hCAF_3,rep2 RNA-seq,hCAF_3,
GSM9730382 RNA-seq,hCAF_3,rep3 RNA-seq,hCAF_3,
GSM9730383 RNA-seq,hCAF_4,rep1 RNA-seq,hCAF_4,
GSM9730384 RNA-seq,hCAF_4,rep2 RNA-seq,hCAF_4,
GSM9730385 RNA-seq,hCAF_4,rep3 RNA-seq,hCAF_4,
GSM9730386 RNA-seq,hCAF_5,rep1 RNA-seq,hCAF_5,
GSM9730387 RNA-seq,hCAF_5,rep2 RNA-seq,hCAF_5,
GSM9730388 RNA-seq,hCAF_5,rep3 RNA-seq,hCAF_5,
GSM9730389 RNA-seq,hCAF_6,rep1 RNA-seq,hCAF_6,
GSM9730390 RNA-seq,hCAF_6,rep2 RNA-seq,hCAF_6,
GSM9730391 RNA-seq,hCAF_6,rep3 RNA-seq,hCAF_6,

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GSE273492 Selective NSD2 Inhibition Reveals an Epigenetic Vulnerability of KRAS-Driven Cancers [RNA-Seq] 36 samples same disease briefing · shares rna-seq
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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.