Smoking–genomic discordance in metastatic non–small cell lung cancer.

8543 Background: Smoking is the dominant risk factor for lung cancer, yet clinical smoking history does not consistently align with the presence of tobacco-associated mutational patterns (C > A transversions). We hypothesized that smoking-genomic discordance identifies a biologically distinct subset of tumors arising through endogenous, aging-enriched mutational processes. Methods: We analyzed metastatic NSCLC patients with documented smoking history and tumor sequencing from a discovery cohort (n = 111) and an independent Dana-Farber validation cohort (n = 2,680). Tumors were stratified by presence or absence of C > A tobacco transversions. Endpoints included C > T transition burden as a surrogate for aging-related mutational processes, transition-to-transversion (Ti/Tv) ratio for endogenous mutational contribution, tumor mutational burden (TMB), oncogenic driver distribution, and first line treatment outcomes. Multivariable regression models adjusted for age, sex, smoking intensity, and driver genotype. Results: Among patients with smoking history, 30% of the discovery and 15.2% of the validation cohort lacked detectable C > A transversions, including 29% with > 30 pack-years. Smoking intensity correlated with C > A but not C > T burden, while C > T increased with age in binomial models, consistent with clock-like aging accumulation. C > A negative discordant tumors had higher C > T fractions and Ti/Tv ratios than both concordant smokers and never smokers (p T fractions (β = 0.21, p T quartiles (OR = 9.2, p T high discordant profiles and weak coupling between smoking intensity and C > A burden. Discordance differed by age (p = 7.6×10⁻⁴): among patients T fractions, whereas never smokers showed greatest C > A transversions, suggesting bidirectional smoking-genomic mismatch. C > A negative discordant tumors had lower TMB and depletion of KRAS/STK11/KEAP1 alterations. PD-L1 and TMB predicted immunotherapy PFS only in C > A positive tumors, suggesting limitations of conventional biomarkers in discordant cases. Conversely, C > A presence correlated with shorter targeted therapy PFS across oncogenic drivers. Conclusions: Clinical smoking history alone does not capture the dominant mutational processes shaping NSCLC. Smoking–genomic discordance identifies a biologically coherent phenotype with endogenous aging-associated patterns, driver- and age- related heterogeneity, and distinct therapeutic vulnerabilities. These findings motivate research into germline susceptibility and environmental exposures that may underlie tobacco-independent mutagenesis.