Abstract
BACKGROUND: We constructed a nomogram model utilizing key clinical and molecular biological variables to predict the 1-year, 3-year, and 5-year survival probabilities for patients with oral squamous cell carcinoma (OSCC). The model's predictive efficacy was assessed through calibration curves. Additionally, a detailed Spearman correlation analysis of the ZC3H12D gene was executed, with patient data stratified into high and low expression categories based on its expression levels for differential gene analysis. Following this, Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, as well as Gene Set Enrichment Analysis (GSEA), were performed on the identified differentially expressed genes to delineate their specific contributions to biological processes and metabolic pathways. RESULTS: The nomogram model demonstrated a high degree of predictive accuracy, effectively predicting the survival probabilities of oral cancer. patientsThe correlation analysis of the ZC3H12D gene revealed significant correlations with various immune cell types. A total of 439 significantly differentially expressed genes were identified through differential gene analysis. GO and KEGG enrichment analyses, along with GSEA analysis, further elucidated the specific roles of these differentially expressed genes in biological processes and metabolic pathways. Moreover, immune infiltration analysis indicated significant differences between the high and low expression groups of ZC3H12D in terms of immune cell infiltration, immune scores, and ESTIMATE scores. CONCLUSION: The nomogram model constructed in this study provides a practical tool for prognostic assessment in OSCC patients. Additionally, the in-depth analysis of the ZC3H12D gene reveals its significant role in the occurrence and development of oral cancer, providing data support and a theoretical basis for further research.