Zao Ji1, Zhiyao Fang2, Xue Dong2, Jia Wang3, Xianyao Wan4, Aihui Yan5. 1. Department of Otolaryngology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, China. 2. Department of Critical Care Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China. 3. Department of Critical Care Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China. emily.jia.1987@163.com. 4. Department of Critical Care Medicine, The First Affiliated Hospital of Dalian Medical University, Dalian, 116021, China. 13322210199@163.com. 5. Department of Otolaryngology, The First Hospital of China Medical University, Shenyang, 110001, Liaoning, China. yanmenxueshu@163.com.
Abstract
PURPOSE: Laryngeal cancer (LC) is a common malignant tumor of the head and neck. However, the relationship between ferroptosis and LC is still unclear. The aim of this study was to identify potential ferroptosis-related biomarkers for diagnosis and prognosis in LC. METHODS: We screened differentially expressed genes (DEGs) related to ferroptosis in LC from the TCGA and FerrDb database. DEGs were identified and enrichment by GO/KEGG, GSEA, GSVA analysis. PPI analysis was performed using String and Cytoscape, then hub genes were extracted. Furthermore, ROC analysis, pan-cancer analysis, gene mutation analysis, immune infiltration correlation analysis and clinical correlation analysis of hub genes were performed. RESULTS: A total of 59 DEGs were screened, which were more significantly enriched in biological processes and involved in HIF-1 signaling pathway, serotonergic synapse and ferroptosis. A total of 29 significant gene set pathways of LC data were performed by GSEA analysis. The GSVA analysis obtained 53 significant differential gene set pathways. The top 20 genes were identified by PPI. ROC curves revealed four of the top20 genes had a good performance, which were CA9 (AUC = 0.930), MAPK3 (AUC = 0.915), MUC1 (AUC = 0.945), and NOX4 (AUC = 0.933). Subsequent analysis found that CDKN2A has the highest mutation frequency in the top 20 gene, and IFNG had a significant correlation with age, tumor stage, degree of tumor differentiation and lymphatic clearance surgery. CONCLUSION: Our study identified key genes closely related to ferroptosis in LC, which still need more studies to explore the mechanisms involved and may become effective clinical diagnostic and prognostic biomarkers.
PURPOSE: Laryngeal cancer (LC) is a common malignant tumor of the head and neck. However, the relationship between ferroptosis and LC is still unclear. The aim of this study was to identify potential ferroptosis-related biomarkers for diagnosis and prognosis in LC. METHODS: We screened differentially expressed genes (DEGs) related to ferroptosis in LC from the TCGA and FerrDb database. DEGs were identified and enrichment by GO/KEGG, GSEA, GSVA analysis. PPI analysis was performed using String and Cytoscape, then hub genes were extracted. Furthermore, ROC analysis, pan-cancer analysis, gene mutation analysis, immune infiltration correlation analysis and clinical correlation analysis of hub genes were performed. RESULTS: A total of 59 DEGs were screened, which were more significantly enriched in biological processes and involved in HIF-1 signaling pathway, serotonergic synapse and ferroptosis. A total of 29 significant gene set pathways of LC data were performed by GSEA analysis. The GSVA analysis obtained 53 significant differential gene set pathways. The top 20 genes were identified by PPI. ROC curves revealed four of the top20 genes had a good performance, which were CA9 (AUC = 0.930), MAPK3 (AUC = 0.915), MUC1 (AUC = 0.945), and NOX4 (AUC = 0.933). Subsequent analysis found that CDKN2A has the highest mutation frequency in the top 20 gene, and IFNG had a significant correlation with age, tumor stage, degree of tumor differentiation and lymphatic clearance surgery. CONCLUSION: Our study identified key genes closely related to ferroptosis in LC, which still need more studies to explore the mechanisms involved and may become effective clinical diagnostic and prognostic biomarkers.
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