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1.  Genomic and Transcriptional Alterations in Lung Adenocarcinoma in Relation to EGFR and KRAS Mutation Status 
PLoS ONE  2013;8(10):e78614.
Introduction
In lung adenocarcinoma, the mutational spectrum is dominated by EGFR and KRAS mutations. Improved knowledge about genomic and transcriptional alterations in and between mutation-defined subgroups may identify genes involved in disease development or progression.
Methods
Genomic profiles from 457 adenocarcinomas, including 113 EGFR-mutated, 134 KRAS-mutated and 210 EGFR and KRAS-wild type tumors (EGFRwt/KRASwt), and gene expression profiles from 914 adenocarcinomas, including 309 EGFR-mutated, 192 KRAS-mutated, and 413 EGFRwt/KRASwt tumors, were assembled from different repositories. Genomic and transcriptional differences between the three mutational groups were analyzed by both supervised and unsupervised methods.
Results
EGFR-mutated adenocarcinomas displayed a larger number of copy number alterations and recurrent amplifications, a higher fraction of total loss-of-heterozygosity, higher genomic complexity, and a more distinct expression pattern than EGFR-wild type adenocarcinomas. Several of these differences were also consistent when the three mutational groups were stratified by stage, gender and smoking status. Specific copy number alterations were associated with mutation status, predominantly including regions of gain with the highest frequency in EGFR-mutated tumors. Differential regions included both large and small regions of gain on 1p, 5q34-q35.3, 7p, 7q11.21, 12p12.1, 16p, and 21q, and losses on 6q16.3-q21, 8p, and 9p, with 20-40% frequency differences between the mutational groups. Supervised gene expression analyses identified 96 consistently differentially expressed genes between the mutational groups, and together with unsupervised analyses these analyses highlighted the difficulty in broadly resolving the three mutational groups into distinct transcriptional entities.
Conclusions
We provide a comprehensive overview of the genomic and transcriptional landscape in lung adenocarcinoma stratified by EGFR and KRAS mutations. Our analyses suggest that the overall genomic and transcriptional landscape of lung adenocarcinoma is affected, but only to a minor extent, by EGFR and KRAS mutation status.
doi:10.1371/journal.pone.0078614
PMCID: PMC3812039  PMID: 24205279
2.  Relation between smoking history and gene expression profiles in lung adenocarcinomas 
BMC Medical Genomics  2012;5:22.
Background
Lung cancer is the worldwide leading cause of death from cancer. Tobacco usage is the major pathogenic factor, but all lung cancers are not attributable to smoking. Specifically, lung cancer in never-smokers has been suggested to represent a distinct disease entity compared to lung cancer arising in smokers due to differences in etiology, natural history and response to specific treatment regimes. However, the genetic aberrations that differ between smokers and never-smokers’ lung carcinomas remain to a large extent unclear.
Methods
Unsupervised gene expression analysis of 39 primary lung adenocarcinomas was performed using Illumina HT-12 microarrays. Results from unsupervised analysis were validated in six external adenocarcinoma data sets (n=687), and six data sets comprising normal airway epithelial or normal lung tissue specimens (n=467). Supervised gene expression analysis between smokers and never-smokers were performed in seven adenocarcinoma data sets, and results validated in the six normal data sets.
Results
Initial unsupervised analysis of 39 adenocarcinomas identified two subgroups of which one harbored all never-smokers. A generated gene expression signature could subsequently identify never-smokers with 79-100% sensitivity in external adenocarcinoma data sets and with 76-88% sensitivity in the normal materials. A notable fraction of current/former smokers were grouped with never-smokers. Intriguingly, supervised analysis of never-smokers versus smokers in seven adenocarcinoma data sets generated similar results. Overlap in classification between the two approaches was high, indicating that both approaches identify a common set of samples from current/former smokers as potential never-smokers. The gene signature from unsupervised analysis included several genes implicated in lung tumorigenesis, immune-response associated pathways, genes previously associated with smoking, as well as marker genes for alveolar type II pneumocytes, while the best classifier from supervised analysis comprised genes strongly associated with proliferation, but also genes previously associated with smoking.
Conclusions
Based on gene expression profiling, we demonstrate that never-smokers can be identified with high sensitivity in both tumor material and normal airway epithelial specimens. Our results indicate that tumors arising in never-smokers, together with a subset of tumors from smokers, represent a distinct entity of lung adenocarcinomas. Taken together, these analyses provide further insight into the transcriptional patterns occurring in lung adenocarcinoma stratified by smoking history.
doi:10.1186/1755-8794-5-22
PMCID: PMC3447685  PMID: 22676229
Lung cancer; Smoking; Gene expression analysis; Adenocarcinoma; EGFR; Never-smokers; Immune response

Results 1-2 (2)