Department of Oncology, Lund University, Lund, Sweden.
BMC Med Genomics. 2012 Jun 7;5:22. doi: 10.1186/1755-8794-5-22.
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.
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.
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.
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.
肺癌是全球癌症死亡的主要原因。烟草使用是主要的致病因素，但并非所有肺癌都归因于吸烟。具体而言，与吸烟者相比，非吸烟者的肺癌被认为是一种不同的疾病实体，因为它们在病因、自然史和对特定治疗方案的反应方面存在差异。然而，吸烟者和非吸烟者肺癌之间的遗传异常在很大程度上仍不清楚。
使用 Illumina HT-12 微阵列对 39 例原发性肺腺癌进行无监督基因表达分析。无监督分析的结果在六个外部腺癌数据集（n=687）和六个包含正常气道上皮或正常肺组织标本的数据集（n=467）中进行了验证。在七个腺癌数据集中进行了吸烟者和非吸烟者之间的有监督基因表达分析，并在六个正常数据集中进行了验证。
对 39 例腺癌的初始无监督分析确定了两个亚组，其中一个亚组包含所有非吸烟者。随后生成的基因表达特征可在外部腺癌数据集中以 79-100%的灵敏度识别非吸烟者，在正常材料中以 76-88%的灵敏度识别非吸烟者。相当一部分现吸烟者和前吸烟者被归入非吸烟者。有趣的是，在七个腺癌数据集中对非吸烟者与吸烟者进行有监督分析产生了类似的结果。两种方法的分类重叠率很高，表明这两种方法都将当前/前吸烟者的一组样本识别为潜在的非吸烟者。无监督分析的基因特征包括几个与肺肿瘤发生、免疫反应相关途径、与吸烟相关的基因以及肺泡 II 型肺细胞的标记基因有关的基因，而有监督分析的最佳分类器包括与增殖强烈相关的基因，但也包括与吸烟相关的基因。
基于基因表达谱分析，我们证明在肿瘤材料和正常气道上皮标本中，非吸烟者可以以高灵敏度识别。我们的结果表明，非吸烟者中发生的肿瘤，以及吸烟者中的一部分肿瘤，代表了肺腺癌的一个不同实体。总的来说，这些分析为按吸烟史分层的肺腺癌的转录模式提供了进一步的见解。
