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 pyrim...