Background: Lung cancer remains a leading cause of cancer-related mortality globally, underscoring the urgent need for the identification of novel biomarkers and therapeutic targets. This study is aimed at investigating the expression and prognostic significance of NAD+ metabolism-related genes in lung cancer patients. Methods: Gene expression profiles, clinical data, and single nucleotide mutation data were sourced from the The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) databases. Differentially expressed genes (DEGs) were identified utilizing the R package ’limma’ based on a criterion of |log2Fold Change| > 0.5 and an adjusted P-value < 0.05. Gene Set Enrichment Analysis (GSEA) and single-sample GSEA (ssGSEA) were conducted with the aid of the ’clusterProfiler’ R package. Prognostic models were developed through univariate Cox regression and LASSO Cox regression, and their validity was confirmed through Kaplan-Meier survival analysis. A nomogram was constructed by integrating clinical data with risk scores. Furthermore, competing endogenous RNA (ceRNA), RNA-binding protein (RBP)-mRNA, and mRNA-transcription factor (TF) networks were established. Results:Our analyses identified 1743 differentially expressed genes (DEGs) between lung cancer and normal samples, with 945 genes upregulated and 798 genes downregulated. Among the NAD+ metabolism-related DEGs, 324 were upregulated and 15 were downregulated. Intersection analysis revealed 29 key genes, which are involved in processes such as negative regulation of immune system processes. The prognostic model identified four key genes—CENPF and HJURP—as significantly associated with overall survival (OS). The construction of competing endogenous RNA (ceRNA), transcription factor (TF), and RNA-binding protein (RBP) networks elucidated potential regulatory mechanisms involving these genes. Analyses of tumor mutation burden (TMB) and immune checkpoint activity indicated higher TMB and differential expression of immune checkpoints in high-risk groups. Drug sensitivity analysis revealed potential chemotherapeutic agents tailored to different risk groups, and DGIdb identified drug-gene interactions, particularly between SLC34A2 and LIFASTUZUMAB VEDOTIN. Conclusion: This study systematically explored the expression patterns and prognostic significance of NAD+ metabolism-related genes in lung cancer, providing valuable insights for personalized treatment strategies.