Identification of ferroptosis-related genes as potential biomarkers of tongue squamous cell carcinoma using an integrated bioinformatics approach

Abstract

Tongue squamous cell carcinoma (TSCC) is one of the deadliest cancers of the head and neck, but the role of the ferroptosis pathway in its development is still unknown. In this study we explored the pathogenetic mechanisms associated with ferroptosis in TSCC. We identified differentially expressed genes (DEGs) of TSCC patients and used gene ontology (GO), the Kyoto Encyclopedia of Genes and Genomes (KEGG), and gene set enrichment analysis (GSEA) to annotate, visualize, and integrate these DEGs. Receiver operating characteristic curve (ROC) analysis was performed, and the STRING database was used to construct a protein–protein interaction network to evaluate the predictive value of ferroptosis-related DEGs. A total of 219 DEGs were identified and GO, KEGG, and GSEA showed that extracellular matrix (ECM)-receptor interaction and interleukin (IL)-17 signaling pathways were substantially upregulated in TSCC. Univariate Cox analysis revealed that high expression of CA9, TNFAIP3, and NRAS were predictive of a worse outcome. We then constructed a prognostic model that predicted survival in the validation cohort at 1 year and 32 months. Finally, 60 cases of tongue carcinoma and normal tissues were collected, and immunohistochemistry was used to detect the expression of CA9. We found that CA9 was strongly expressed in tongue carcinoma tissues and absent in adjacent tissues. Overall, we found that ferroptosis-related genes may affect TSCC prognosis through the ECM-receptor interaction and IL-17 signaling pathways. Additionally, immunohistochemistry confirmed that CA9 was highly expressed in tongue carcinoma tissues, and a model based on ferroptosis-related genes showed a good ability to predict overall survival in TSCC.