ArticleScientific reports2025
Identification of ferroptosis-related signature predicting prognosis and therapeutic responses in pancreatic cancer.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Translating ferroptosis into oncology: challenges, opportunities and future directions.Nature reviews. Clinical oncology · 2026Review
- Ferroptosis-based therapeutic strategy targeting iron metabolism and SLC7A11 overcomes oxaliplatin resistance in patient-derived pancreatic cancer organoids.Journal of experimental & clinical cancer research : CR · 2026Article
- AURKA suppresses NCOA4-mediated ferritinophagy to enhance sorafenib resistance in hepatocellular carcinoma.Cell death & disease · 2026Article
- Predicting DNA damage response using synthetic cell painting profiles and experimental analysis.iScience · 2026Article
- Selenium-Thioredoxin Axis Contributes to Ferroptosis Resistance in Pancreatic Cancer Cells.International journal of molecular sciences · 2026Article
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Authors and funding
3 authors.
Funding
Abstract
Ferroptosis plays a role in tumorigenesis by affecting lipid peroxidation and metabolic pathways; however, its prognostic or therapeutic relevance in pancreatic adenocarcinoma (PAAD) remains poorly understood. In this study, we developed a prognostic ferroptosis-related gene (FRG)-based risk model using cohorts of The Cancer Genome Atlas (TCGA) and the International Cancer Genome Consortium (ICGC), proposing plausible therapeutics. Differentially expressed FRGs between tumors from TCGA-PAAD and normal pancreatic tissues from Genotype-Tissue Expression were analyzed to construct a prognostic risk model using univariate and multivariate Cox regression and LASSO analyses. A model incorporating AURKA, CAV1, and PML gene expression effectively distinguished survival differences between high- and low-risk groups among TCGA-PAAD patients, with validation in two ICGC cohorts. The high-risk group was enriched in gene sets involving mTOR, MAPK, and E2F signaling. The immune and stromal cells infiltration score did not differ between the groups. Analysis of PRISM datasets using our risk model to classify pancreatic cell lines suggested the dasatinib's efficacy in the high-risk group, which was experimentally confirmed in four cell lines with a high- or low-risk signature. In conclusion, this study proposed a robust FRG-based prognostic model that may help stratify PAAD patients with poor prognoses and select potential therapeutic avenues.
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