Background: Lung cancer stands as the leading cause of cancer-related mortality globally, with non-small cell lung carcinoma (NSCLC) accounting for approximately 85% of all lung cancer cases. Despite advancements in diagnostic techniques and therapeutic interventions, the 5-year survival rate for NSCLC remains low due to the recurrence and dissemination of malignant cells. There is an urgent need to identify novel biomarkers and therapeutic targets to address this challenge. Therefore, this study aims to identify common genes associated with tumor-related immune cells and investigate their potential clinical utility in both early and advanced NSCLC. Methods: Early-stage and advanced NSCLC expression data, mutation data, and associated medical records were obtained and refined for subsequent examination from The Cancer Genome Atlas (TCGA). Differential expression analysis, gene ontology (GO), transcription factors and pathway enrichment analysis, and gene set enrichment analysis (GSEA) were implemented to discern molecular function and regulatory relationship across differentially expressed genes (DEGs). Single-sample gene set enrichment analysis (ssGSEA) was employed to analyze immune cell abundance. Furthermore, the weighted gene co-expression network analysis (WGCNA) of DEGs was utilized to screen out gene modules related to tumor-associated immune cells in early-stage and advanced NSCLC. This was achieved by the tumor immune estimation resource (TIMER) algorithm to assess immune cell abundance. Subsequently, consensus genes associated with drug sensitivity and pathways activity were analyzed using the Gene Set Cancer Analysis Literate (GSCALite) platform. Notably, we also evaluated the correlation between consensus genes expression and TP53 mutant (TP53mut) and TP53 wild-type (TP53wt). Finally, the KMPlotter online tool was used to evaluate the prognostic implications of consensus genes exhibiting different correlation patterns in NSCLC. Results: In early and advanced NSCLC, there were 996 (445 upregulations and 551 downregulations) and 822 (398 upregulations and 424 downregulations) DEGs from lung adenocarcinoma (LUAD) versus lung squamous cell carcinoma (LUSC), respectively, following differential expression analysis. In the interferon signal pathway, functional enrichment analysis showed significant enrichment of DEGs. A correlation between immune infiltration and NSCLC was found using ssGSEA. WGCNA analysis revealed a strong association between tumor-immune infiltration characteristics and the blue and turquoise modules. Notably, a total of 27 consensus genes linked to tumor-related immune cells were identified in both early and advanced NSCLC. Furthermore, differential expression patterns were observed for these consensus genes, such as melanoma-associated antigen A 4 (MAGEA4) and dynein cytoplasmic 1 intermediate chain 1 (DYNC1I1), between TP53 mutant (TP53mut) and TP53 wild-type (TP53wt). Conclusions: This study revealed the crucial role of immune cell infiltration, especially dendritic cells, in the onset and progression of early and advanced NSCLC, providing potential targets for immune therapy.