ArticleJournal of gastrointestinal oncology2022
Construction and validation of a m6A RNA methylation and ferroptosis-related prognostic model for pancreatic cancer by integrated bioinformatics analysis.
Article in Journal of gastrointestinal oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
7 citing papers in PubMed, 10 citations in OpenAlex.
- Ferroptosis in cancer toward molecular insights and clinical translation in pancreatic cancer.Molecular cancer · 2026Review
- Mechanism and therapeutic prospects of ferroptosis regulation through m6A in cancer.Frontiers in cell and developmental biology · 2026Review
- Article
- Summary of the mechanism of ferroptosis regulated by m6A modification in cancer progression.Frontiers in cell and developmental biology · 2025Review
- Article
- Article
- Effects of DNA, RNA, and Protein Methylation on the Regulation of Ferroptosis.International journal of biological sciences · 2023Review
Corrections and comments
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Authors and funding
13 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Both N6-methyladenosine (m6A) ribonucleic acid (RNA) methylation and ferroptosis regulators are demonstrated to have significant effects on the malignant clinicopathological characteristics of pancreatic adenocarcinoma (PAAD) patients. However, the currently available clinical indexes are not sufficient to predict precise prognostic outcomes pf PAAD patients accurately. This study aims to examine the clinicopathologic features of m6A RNA methylation and ferroptosis regulators in predicting the outcomes of different types of cancer. Methods: As the foundation for this research, the differentially expressed genes (DEGs) between PAAD tissues and adjacent normal tissues were first identified. Next, dimensional reduction analysis (DCA) based on m6A RNA methylation regulators and ferroptosis regulators were performed and DEGs between good/poor prognosis PAAD patient clusters were identified. DEGs were then screened by Cox analysis, and finally a risk signature was established by least absolute shrinkage and selection operator (LASSO) analyses. The prediction model based on risk score was further evaluated by a validation set from Gene Expression Omnibus (GEO) database. Results: In total, 4 m6A RNA methylation regulator genes and 29 ferroptosis regulator genes were found to have close causal relationships with the prognosis of PAAD, and a risk score with 3 m6A methylation regulators (i.e., Conclusions: The combined prediction model, composed of seven regulators of m6A methylation and ferroptosis, in this study more effectively reflects the progression and prognosis of PAAD than previous single genome or epigenetic analysis. Our study provides a broader perspective for the subsequent establishment of prognostic models and the patients may benefit from more precision management.
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