Identification of N6-methyladenosine-associated ferroptosis biomarkers in cervical cancer

被引：0
作者：
Jinzhe Liu [1 ]
Buwei Han [2 ]
Xijiao Hu [3 ]
Mengke Yuan [4 ]
Zhiwei Liu [5 ]
机构：
[1] Department of Chinese Pharmacy, School of Pharmacy, Guizhou University of Traditional Chinese Medicine, Guizhou, Guiyang
[2] Department of Chinese Pharmacy, School of Pharmacy, Harbin University of Commerce, Heilongjiang, Harbin
[3] Postdoctoral Scientific Research Workstation, Harbin University of Commerce, Heilongjiang, Harbin
[4] Department of Obstetrics and Gynecology, The Second Affiliated Hospital of Heilongjiang University of Chinese Medicine, Heilongjiang, Harbin
[5] Department of Gynaecology and Obstetrics, The First Affiliated Hospital of Zhejiang Chinese Medical University (Zhejiang Provincial Hospital of Chinese Medicine), Zhejiang, Hangzhou
[6] Department of Pediatrics, The Second Affiliated Hospital of Guizhou University of Traditional Chinese Medicine, No. 83, Feishan Road, Guizhou Province, Guiyang
来源：
Hereditas | / 162卷 / 1期
关键词：
Biomarker; Cervical cancer; Ferroptosis; m6A; Nomogram;
D O I：
10.1186/s41065-025-00418-3
中图分类号：
学科分类号：
摘要：
Background: Cervical 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. Methods: Three 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). Results: From 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. Conclusion: Six 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. © The Author(s) 2025.
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