Identification of m6 A-regulated ferroptosis biomarkers for prognosis in laryngeal cancer

Abstract

Abstract Laryngeal cancer (LC) is a malignant tumor that occurs in the larynx. N6-methyladenosine (m6A) RNA methylation, a pivotal and prevalent epigenetic modification in eukaryotic mRNA, intricately intertwines with ferroptosis, and together, they play a crucial role in the development of LC. Accordingly, further research on related molecular mechanisms and pathology of LC is necessary. Weighted gene co-expression network analysis and correlation analysis were used to identify differentially expressed m6A-related ferroptosis genes in LC. The TCGA-HNSC and GSE65858 datasets were obtained from public databases. The TCGA-HNSC dataset consisted of 110 primary tumor oropharynx samples and 12 control oropharynx samples, while the GSE65858 dataset contained forty-eight primary tumor oropharynx samples. Univariate Cox and least absolute shrinkage and selection operator (LASSO) regression were utilized for feature selection and risk model construction in the TCGA-HNSC dataset. The risk model was validated in the GSE65858 dataset. Then, a nomogram was built based on the independent prognostic factor identified using univariate and multivariate Cox regression in the TCGA-HNSC dataset. Mutation analysis, immune-related analysis, and drug sensitivity prediction were applied to analyze the utility of the risk model in the TCGA-HNSC dataset. Additionally, qRT-PCR and western blot were performed to detect the TFRC, RGS4, and FTH1 expression. Three biomarkers were identified to build a risk model using the univariate Cox and LASSO regression algorithms. Receiver operating characteristic (ROC) analysis verified the accuracy of the risk model. Tumor Immune Dysfunction and Exclusion (TIDE) and Estimation of STromal and Immune cells in MAlignant Tumors using the Expression data (ESTIMATE) algorithm showed a positive relationship between risk score and TIDE or ESTIMATE score. Furthermore, drug sensitivity prediction found that 19 chemotherapy drugs were strongly correlated with a risk score. TFRC, RGS4, and FTH1 exhibited high expression levels in 30 laryngeal carcinoma tissues and cell lines. Notably, TFRC and FTH1 expression levels were significantly associated with patient prognosis. In Conclusion, TFRC, RGS4, and FTH1, were identified as m6A-regulated ferroptosis biomarkers in LC, providing insights into LC treatment and prognosis.

Keywords

• Laryngeal cancer
• M6 A
• Ferroptosis
• Biomarker
• Prognosis