Introduction: Early diagnosis of lung adenocarcinoma is a clinical priority to reduce global mortality, driving the development of various transcriptomic signatures. However, most lack a mechanistic axis connecting gene expression with external diagnostic signals.

Objective: To characterize the Extended TRIPOD (E-TRIPOD) model, a five-gene signature (COL11A1, CDC20, PSAT1, LDHA, and UCK2) that integrates structural, proliferative, and metabolic drivers as a biological and theoretical foundation for future e-Nose-based screening.

Methods: We analyzed the GSE19188 dataset and performed cross-validation on TCGA real-world data cohorts (n > 500). Kaplan-Meier survival analysis, functional enrichment in g:Profiler, and metabolic mapping via RSEA and KEGG were used to identify potential volatile byproducts.

Results: The model showed exceptional prognostic power with a Hazard Ratio of 2.1 (P=8.8×10−16). Unlike standard models, E-TRIPOD reveals a mechanistic axis based on the pyrimidine salvage pathway. Here, the synergy of UCK2 and PSAT1 leads to urea accumulation and its degradation into volatile ammonia (NH3), as mapped through KEGG pathways.

Conclusion: These results position E-TRIPOD as a robust biomarker that turns genomics into an actionable diagnostic tool. This synergy establishes a theoretical framework for the development of biophysically grounded electronic nose technologies, setting a new potential standard for non-invasive screening.