GEO series

Metabolic Plasticity Underlies Ferroptosis Resistance Driven by Mutant p53 in Pancreatic Ductal Adenocarcinoma

GSE319384 Homo sapiens (human) RNA-seq (gene expression) 24 samples Submitted 2026/07/31 Platform GPL30173

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.

Summary (written by the submitters)

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy characterized by late diagnosis, rapid progression, and resistance to conventional therapies. Mutations in the tumor suppressor gene TP53 are prevalent in this cancer and have been associated with gain-of-function activities that promote tumor survival. Ferroptosis, an iron-dependent form of regulated cell death driven by lipid peroxidation, represents a potential therapeutic vulnerability.

Read the full summary ↓

However, the influence of mutant p53 on ferroptosis susceptibility remains poorly understood.We employed isogenic pancreatic cancer cell models, including CRISPR-Cas9-mediated TP53 knockout and transient overexpression of common mutant TP53 variants, to examine ferroptosis sensitivity. Cell viability, reactive oxygen species accumulation, lipid peroxidation, mitochondrial integrity, and metabolic profiling were assessed following treatment with ferroptosis inducers. Transcriptional changes were analysed by RNA sequencing, and functional contributions of glycolysis and mitochondrial respiration were evaluated using metabolic flux assays. Pharmacological reactivation of wild-type p53 was tested in combination with ferroptosis inducers in vitro and in orthotopic murine models.Deletion of mutant TP53 sensitized pancreatic cancer cells to ferroptosis, accompanied by increased oxidative stress, lipid peroxidation, and mitochondrial dysfunction. Mutant TP53 expression preserved mitochondrial integrity and sustained bioenergetic flexibility under ferroptotic stress. Transcriptomic analyses revealed a multi-layered adaptive program, including upregulation of antioxidant and metabolic genes, and activation of PI3K–AKT signaling, which is associated to a selective glycolytic shift to maintain ATP levels. Functional modulation confirmed that glucose supplementation enhanced, whereas glycolytic inhibition impaired, survival under ferroptotic conditions in mutant TP53-expressing cells, but not in TP53 KO cells. Pharmacological reactivation of wild-type p53 disrupted this adaptive network, abrogating glycolytic reprogramming and significantly increasing ferroptotic cell death both in vitro and in vivo. Mutant p53 orchestrates transcriptional and metabolic plasticity that confers ferroptosis resistance in pancreatic cancer. Reactivating wild-type p53 in combination with ferroptosis induction overcomes this resistance, highlighting a therapeutically actionable vulnerability and supporting the development of combinatorial strategies for this aggressive malignancy.

This dataset

Open GSE319384 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 GSE319384_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 PRJNA1423215 and SRA study SRP676802. Searching any of these in the dataset finder brings you back here.

NCBI GEO page ↗

Study design

8 conditions, mostly in triplicate

PANC-1,DMSO, ×3 PANC-1,Erastin, ×3 PANC-1,RSL3, ×3 PANC-1,Ferroptocide, ×3 PANC-1 TP53-KO, DMSO, ×3 PANC-1 TP53-KO, Erastin, ×3 PANC-1 TP53-KO, RSL3, ×3 PANC-1 TP53-KO, Ferroptocide, ×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

GSM9517085 PANC-1,DMSO, 2778 PANC-1,DMSO,
GSM9517086 PANC-1,Erastin, 2779 PANC-1,Erastin,
GSM9517087 PANC-1,RSL3, 2780 PANC-1,RSL3,
GSM9517088 PANC-1,Ferroptocide, 2781 PANC-1,Ferroptocide,
GSM9517089 PANC-1,DMSO, 2782 PANC-1,DMSO,
GSM9517090 PANC-1,Erastin, 2783 PANC-1,Erastin,
GSM9517091 PANC-1,RSL3, 2784 PANC-1,RSL3,
GSM9517092 PANC-1,Ferroptocide, 2785 PANC-1,Ferroptocide,
GSM9517093 PANC-1,DMSO, 2786 PANC-1,DMSO,
GSM9517094 PANC-1,Erastin, 2787 PANC-1,Erastin,
GSM9517095 PANC-1,RSL3, 2788 PANC-1,RSL3,
GSM9517096 PANC-1,Ferroptocide, 2789 PANC-1,Ferroptocide,
GSM9517097 PANC-1 TP53-KO, DMSO, 2790 PANC-1 TP53-KO, DMSO,
GSM9517098 PANC-1 TP53-KO, Erastin, 2791 PANC-1 TP53-KO, Erastin,
GSM9517099 PANC-1 TP53-KO, RSL3, 2792 PANC-1 TP53-KO, RSL3,
GSM9517100 PANC-1 TP53-KO, Ferroptocide, 2793 PANC-1 TP53-KO, Ferropt…
GSM9517101 PANC-1 TP53-KO, DMSO, 2794 PANC-1 TP53-KO, DMSO,
GSM9517102 PANC-1 TP53-KO, Erastin, 2795 PANC-1 TP53-KO, Erastin,
GSM9517103 PANC-1 TP53-KO, RSL3, 2796 PANC-1 TP53-KO, RSL3,
GSM9517104 PANC-1 TP53-KO, Ferroptocide, 2797 PANC-1 TP53-KO, Ferropt…
GSM9517105 PANC-1 TP53-KO, DMSO, 2798 PANC-1 TP53-KO, DMSO,
GSM9517106 PANC-1 TP53-KO, Erastin, 2799 PANC-1 TP53-KO, Erastin,
GSM9517107 PANC-1 TP53-KO, RSL3, 2800 PANC-1 TP53-KO, RSL3,
GSM9517108 PANC-1 TP53-KO, Ferroptocide, 2801 PANC-1 TP53-KO, Ferropt…

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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.