ArticleHereditas2025
Identification of N6-methyladenosine-associated ferroptosis biomarkers in cervical cancer.
Article in Hereditas, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed.
- Research progress of ferroptosis in gynecological diseases.Annals of medicine · 2026Review
- miR-1229-3p promotes epithelial-mesenchymal transition and metastasis of cervical cancer cells by targeting FBXL5.Hereditas · 2026Article
- Mechanism and therapeutic prospects of ferroptosis regulation through m6A in cancer.Frontiers in cell and developmental biology · 2026Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
backgroundCervical cancer (CC) stands as a major contributor to female mortality. The pathogenesis of CC is linked with various factors. Our research aimed to unravel the underlying mechanisms of ferroptosis and m6A RNA methylation in CC through bioinformatics analysis.
methodsThree CC datasets, including GSE9750, GSE63514, and TCGA-CESC, were incorporated. m6A-related genes were derived from published sources, while ferroptosis-related genes were obtained from the FerrDb database. Differential expression and correlation analyses were performed to identify differentially expressed m6A-related ferroptosis genes (DE-MRFGs) in CC. Subsequently, the biomarkers were further identified using machine learning techniques. Gene Set Enrichment Analysis (GSEA) and Kaplan-Meier (KM) survival analysis were also performed to comprehend these biomarkers. Furthermore, a competing endogenous RNAs (ceRNA) network involving biomarkers was established. Finally, biomarkers expression were verified by real-time quantitative polymerase chain reaction (RT-qPCR).
resultsFrom the DE-MRFGs, six genes, including ALOX12, EZH2, CA9, CDCA3, CDC25A, HSPB1, were selected. A nomogram constructed based on these biomarkers exhibited potential clinical diagnostic value for CC, with good diagnostic accuracy confirmed through calibration curves. GSEA unveiled associations of these biomarkers with cell proliferation, spliceosome, and base excision repair. KM survival analysis demonstrated significant differences in survival outcomes between high and low expressions of HSPB1, EZH2, and CA9 samples. A ceRNA network was constructed involving three biomarkers, such as CDC25A, CDCA3, and EZH2, 29 miRNAs, and 25 lncRNAs. In RT-qPCR verification, the expression of ALOX12, EZH2 and CDC25A was significantly higher in CC samples, while HSPB1 expression was higher in control samples.
conclusionSix genes, namely ALOX12, EZH2, CA9, CDCA3, CDC25A, and HSPB1, were identified as m6A-regulated ferroptosis biomarkers in CC. These findings offer valuable insights into disease pathogenesis and hold promise for advancing CC treatment and prognosis.
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