GEO series

Matrix Stiffness-Sensitive LDHA Drives Autophagy of Pancreatic Ductal Adenocarcinoma via Lactate-Induced FOXO3 Expression and Lactylation

GSE292751 Homo sapiens (human) RNA-seq (gene expression) 6 samples Submitted 2026/08/06 Platform GPL24676

At a glance

RNA-seq (gene expression) · human · 6 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: 6 samples: 6 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: Target FADS1-arachidonic acid-ferroptosis axis: A metabolic bridge linking matrix stiffness to PDAC stemnessMaterials today. Bio · 2026

Summary (written by the submitters)

Pancreatic ductal adenocarcinoma (PDAC), a highly aggressive tumor within the digestive system, is characterized by the high stiffness of the extracellular matrix (ECM), which has fundamental influences on biological processes and malignant phenotypes of PDAC. Autophagy, as a key process of PDAC, significantly accelerates malignant progression and ultimately leads to adverse prognosis.

Read the full summary ↓

Consequently, it is crucial to comprehend the underlying mechanisms of the interplay between matrix stiffness and PDAC autophagy. To serve the intent, Polyacrylamide (PA) hydrogels with adjustable stiffness were utilized to cultivate MIA PaCa-2 and PANC-1 cells. The outcomes established that high stiffness induced lactate production via the activation of lactate dehydrogenase A (LDHA), resulting in the upregulation of transcription factor FOXO3 and subsequent induction of autophagy. Interestingly, in vivo experiments, the MIA PaCa-2 cells educated by stiff PA hydrogels exhibited not only higher tumorigenicity, but also persistent phenotype maintenance and gene expression, which implied the potential epigenetic modulation of matrix stiffness. Through DeepKla analysis, Co-Immunoprecipitation (Co-IP) and Western Blot (WB), we identified that matrix stiffness drives FOXO3 lysine lactylation (Kla) modification by promoting LDHA-dependent lactate production, thereby sustaining the persistent activation of autophagy. In conclusion, we revealed the key role of matrix stiffness in lactate metabolism, lactylation modification and autophagy activation of PDAC, offering both foundational theory and potential therapeutic targets for precision medicine in PDAC.

Published in

Target FADS1-arachidonic acid-ferroptosis axis: A metabolic bridge linking matrix stiffness to PDAC stemness

Gong T, Yan J, Zhu H et al. · Materials today. Bio 2026 · PMID 42540354 · doi:10.1016/j.mtbio.2026.103455

This dataset

Open GSE292751 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 GSE292751_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 PRJNA1241192 and SRA study SRP572636. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗ Paper (PMID 42540354) ↗

Study design

6 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 6 sample titles: 6 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

GSM8864648 MIA PaCa-2, soft matrix, 5 days (1)
GSM8864649 MIA PaCa-2, soft matrix, 5 days (2)
GSM8864650 MIA PaCa-2, soft matrix, 5 days (3)
GSM8864651 MIA PaCa-2, stiff matrix, 5 days (1)
GSM8864652 MIA PaCa-2, stiff matrix, 5 days (2)
GSM8864653 MIA PaCa-2, stiff matrix, 5 days (3)

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Search all human RNA-seq datasets in GEO →

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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.