Identifying immune cell infiltration and diagnostic biomarkers for nasopharyngeal carcinoma through bioinformatic analysis

Abstract

Abstract Backgrounds: Explore the genomic and signaling pathways contributing to nasopharyngeal carcinoma, a prevalent and multifactorial cancer involving environmental, genetic, and EB virus factors. This study aims to identify potential genes associated with nasopharyngeal cancer and examine their relationship with immune cell infiltration. Methods: The Gene Expression Omnibus (GEO) database provided three sets of nasopharyngeal cancer data: two for training and one for validation. To identify candidate genes, a Protein-Protein Interaction (PPI) network was constructed using a string database and two machine learning algorithms: the Least Absolute Selection and Shrinkage Operator (LASSO) and the Supporting Vector Machine Resource Elimination (SVM-RFE). The external validation dataset assessed the proposed levels of expression of biomarkers and the diagnostic value of the test to evaluate its effectiveness. Receiver Operating Characteristic (ROC) curves were used to measure diagnostic performance, convolutional techniques in CIBERSORT were applied for immune cell infiltration analysis, and correlation analysis was conducted using the training dataset. Results: The GEO database provided GSE12452 and GSE13597 datasets. The limma package filtered 58 differential genes, including 13 upregulated and 35 downregulated genes, which were visualized using volcano maps, heat maps, and PCA. Enrichment analysis results indicated a significant association between inflammation and disease. The Lasso and SVM algorithms were applied to screen 9 and 37 differential genes, respectively. Overlapping genes associated with nasopharyngeal cancer include ATP12A, LAMB1, RAD51AP1, CXCL11, BINSM1, PTGS2, and SAA1. Their diagnostic significance was confirmed using the operational characteristic Receptor of the validation group, and they were found to be highly connected to the degree of immune cell infiltration. Conclusions: These seven genes are considered promising biomarkers for diagnosing nasopharyngeal cancer, paving the way for future research on the immunological mechanisms and therapy of nasopharyngeal carcinoma.