Abstract
PURPOSE: Although considerable progress has been made in basic and clinical research on nasopharyngeal carcinoma (NPC), the biomarkers of the progression of NPC have not been fully studied and described. This study was designed to identify potential novel biomarkers for NPC using integrated analyses and explore the immune cell infiltration in this pathological process. METHODS: Five GEO data sets were downloaded from gene expression omnibus database (GEO) and analysed to identify differentially expressed genes (DEGs), followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses. The four algorithms were adopted for screening of novel and key biomarkers for NPC, including random forest (RF) machine learning algorithm, least absolute shrinkage and selection operator (LASSO) logistic regression, support vector machine-recursive feature elimination (SVM-RFE), and weighted gene co-expression network analysis (WGCNA). Lastly, CIBERSORT was used to assess the infiltration of immune cells in NPC, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. RESULTS: Herein, we identified 46 DEGs, and enrichment analysis results showed that DEGs and several kinds of signaling pathways might be closely associated with the occurrence and progression of NPC. DTL was recognized as NPC-related biomarker. DTL, also known as retinoic acid-regulated nuclear matrix-associated protein (RAMP), or DNA replication factor 2 (CDT2), is reported to be correlated with the cell proliferation, cell cycle arrest and cell invasion in hepatocellular carcinoma, breast cancer and gastric cancer. Immune infiltration analysis demonstrated that macrophages M0, macrophages M1 and T cells CD4 memory activated were linked to pathogenesis of NPC. CONCLUSION: In summary, we adopted a comprehensive strategy to screen DTL as biomarkers related to NPC and explore the critical role of immune cell infiltration in NPC.