Purpose Cigarette smoking is the major pathogenic factor for lung cancer. The precise mechanisms of tobacco-related carcinogenesis, and its effect on the genomic and transcriptional landscape in lung cancer are not fully understood. Experimental Design 1398 (277 never-smokers, 1121 smokers) genomic and 1449 (370 never-smokers, 1079 smokers) transcriptional profiles were assembled from public lung adenocarcinoma cohorts, including matched next-generation DNA-sequencing data (n=423). Unsupervised and supervised methods were used to identify smoking-related copy number alterations (CNAs), predictors of smoking status, and molecular subgroups. Results Genomic meta-analyses showed that never-smokers and smokers harbored a similar frequency of total CNAs, although, specific regions (5q, 8q, 16p, 19p, and 22q) displayed a 20-30% frequency difference between the two groups. Importantly, supervised classification analyses based on CNAs or gene expression could not accurately predict smoking status (balanced accuracies ~60-80%). However, unsupervised multicohort transcriptional profiling stratified adenocarcinomas into distinct molecular subgroups with specific patterns of CNAs, oncogenic mutations, and mutation transversion frequencies that were independent of the smoking status. One subgroup included ~55-90% of never-smokers and ~20-40% of smokers (both current and former) with molecular and clinical features of a less aggressive and smoking-unrelated disease. Given the considerable intra-group heterogeneity in smoking-defined subgroups, especially among former-smokers, our results emphasize the clinical importance of accurate molecular characterization of lung adenocarcinoma. Conclusions The landscape of smoking-related CNAs and transcriptional alterations in adenocarcinomas is complex, heterogeneous, and with moderate differences. Our results support a molecularly distinct less aggressive adenocarcinoma entity, arising in never-smokers and a subset of smokers.