3622 - Iron Metabolism in Nasopharyngeal Carcinoma: Multi-Omics Exploration of Tumor Progression, Immune Microenvironment, and Radiotherapy Efficacy

Purpose/Objective(s):

Nasopharyngeal carcinoma (NPC), a malignant tumor prevalent in southern China and Southeast Asia, is primarily associated with Epstein-Barr virus (EBV) infection as a key etiological factor. Given the aggressive nature of NPC and the high frequency of late-stage diagnosis, radiotherapy remains the cornerstone of treatment. Ferroptosis, an iron-dependent form of regulated cell death, has been strongly implicated in mediating tumor resistance to radiotherapy. However, the relationship between iron metabolism-related genes (IMRGs) and the clinical prognosis of NPC patients remains poorly understood.

Materials/Methods:

In this study, we systematically investigated the functional roles of iron metabolism-related genes (IMRGs) in NPC by integrating single-cell RNA sequencing (scRNA-seq) and bulk RNA sequencing data, with a particular focus on the expression dynamics of four IMRGs—PTGS2, DUOX1, MT3, and MUC1—and their contributions to radiotherapy response.

Results:

We integrated the GSE12452 and GSE13597 datasets to construct a robust training cohort. Differential expression analysis identified 959 significantly dysregulated genes, of which 32 were iron metabolism-related genes (IMRGs) after intersection analysis. Clustering 56 tumor samples of the training set based on their profiles identified two subtypes, characterized by ESTIMATE and ssGSEA. The SVM-REF and random forest (RF) algorithms were employed to screen diagnostic genes, resulting in the identification of 9 overlapping candidate genes. LASSO regression analysis identified 4 key genes, which were subsequently used to construct a diagnostic model and develop a predictive formula. The performance of the diagnostic model was rigorously evaluated using box plots and receiver operating characteristic (ROC) curves. The CIBERSORT and ssGSEA algorithms were utilized to assess the immune cell composition within the high-risk and low-risk groups of the training cohort. Analysis of the IMvigor-210 immunotherapy cohort demonstrated the significant risk stratification capability of the riskScore. Hallmark gene signatures were employed for gene set variation analysis (GSVA) and differential analysis between high-risk and low-risk samples, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses. The expression of key genes was was examined at the single-cell level, and cell communication analysis was conducted on specific cells. Investigation of key gene expression dynamics in the training cohort and post-radiotherapy samples highlighted their diverse roles in radiotherapy response and their critical involvement in NPC pathogenesis and therapeutic outcomes.

Conclusion:

Our findings elucidate the pivotal role of ferroptosis-related mechanisms in NPC, offering a robust theoretical foundation for the development of novel prognostic biomarkers and personalized therapeutic strategies for NPC patients.