Identification of Diagnostic and Prognostic Biomarkers in Nasopharyngeal Carcinoma using Integrated Transcriptomics and Elastic Net Survival Analysis

Introduction: Nasopharyngeal carcinoma (NPC) is a malignant tumor with distinct molecular features, underscoring the need for reliable biomarkers to improve diagnosis, prognosis, and therapeutic strategies. Methods: We analyzed transcriptomic data from Gene Expression Omnibus (GEO) datasets (GSE12452, GSE53819, and GSE102349) to identify diagnostic and prognostic biomarkers. Differential expression analysis was performed to detect potential markers, while survival analysis was conducted using Cox proportional hazards (Cox-PH) modeling and log-rank tests. Elastic Net regression was used to refine the gene signature. RNA-protein expression concordance was validated using the Cancer Cell Line Encyclopedia (CCLE) dataset. Results: Differential expression analysis revealed 591 genes as potential diagnostic markers. Survival analysis identified 54 genes with dual diagnostic and prognostic relevance. Elastic Net regression refined this to an 11-gene signature, which stratified patients into high- and low-risk groups, significantly predicting progression-free survival (log-rank p = 0.0035). Five genes (BUB1B, GAS2L3, NFE2L3, OIP5, and PDGFRL) were identified as potential oncogenic drivers, while six (CD1D, CYP4B1, IL33, KLF2, NAPSB, and VILL) were implicated as tumor suppressors. Six genes (BUB1B, GAS2L3, IL33, OIP5, PDGFRL, and VILL) showed strong RNA-protein expression concordance in the CCLE dataset. Discussion: This study reveals previously unreported cancer-associated genes (NAPSB, GAS2L3, NFE2L3, PDGFRL, CD1D, CYP4B1, KLF2) in NPC while validating established biomarkers (BUB1B, OIP5, IL33, VILL). Our findings expand NPC molecular characterization but require further clinical validation. Conclusion: This study presents a robust gene signature for NPC, offering valuable insights into tumor progression and providing a foundation for advancing diagnostic strategies, improving prognostic stratification, and developing targeted therapies.