Airway gene expression in smokers: an early diagnostic biomarker for lung cancer

描述(申请人提供)：肺癌是美国男性和女性癌症死亡的主要原因。肺癌患者的高死亡率在一定程度上是由于缺乏有效的工具来在疾病扩散到区域结节或转移到肺外之前对疾病进行早期诊断。我们的长期目标是开发一种相对非侵入性的方法来评估吸烟者呼吸道上皮细胞损伤的程度和患或发展肺癌的风险。这项应用的目的是开发一种胸内(主干支气管)呼吸道基因表达谱，能够作为临床怀疑疾病的吸烟者肺癌的早期诊断生物标志物。这种方法是基于这样一种假设，即吸烟者组织学上皮中的基因表达模式反映了烟草烟雾造成的损害的类型和程度，并可以预测吸烟者患肺癌的风险。利用寡核苷酸微阵列，我们已经在支气管镜检查获得的组织学正常的大气道上皮细胞中确定了一个基因表达特征，它可以作为区分吸烟者患有和不患有肺癌的高度敏感和特异的生物标志物。在这项建议中，我们将1)在怀疑患有肺癌的大型独立吸烟者队列中验证该诊断气道生物标志物；2)评估我们的生物标志物在预测第1期疾病中肺癌存在的准确性；3)将呼吸道基因表达谱与既定的疾病临床风险因素整合，以产生能够指导患者评估和管理的临床基因组预测模型；4)使用新颖的反向工程算法，开发能够区分小细胞肺癌和非小细胞肺癌的正常呼吸道上皮的第二基因表达特征。这些研究将产生一种相对非侵入性的工具，有效地在早期和潜在的可治愈阶段诊断肺癌。这些基于基因表达的生物标记物可能会消除额外的、往往是更具侵入性的诊断测试的需要，这些测试成本高、风险大，并延长了对怀疑患有肺癌的吸烟者的诊断评估。

DESCRIPTION (provided by applicant): Lung cancer is the leading cause of cancer death in both men and women in the United States. The high mortality in patients with lung cancer results, in part, from the lack of effective tools to diagnose the disease at an early stage before it has spread to regional nodes or has metastasized beyond the lung. Our long-term goal is to develop a relatively noninvasive means of assessing the degree of airway epithelial cell damage and the risk for having or developing lung cancer among smokers. The objective of this application is to develop an intrathoracic (mainstem bronchus) airway gene expression profile capable of serving as an early diagnostic biomarker for lung cancer in smokers with clinical suspicion of disease. This approach is based on the hypothesis that patterns of gene expression in the histologically normal airway epithelium of a smoker reflect the types and degree of damage induced by the tobacco smoke and can predict that smoker's risk for having lung cancer. Using oligonucleotide microarrays, we have identified a gene expression signature in histologically normal large airway epithelial cells obtained at bronchoscopy that can serve as a highly sensitive and specific biomarker for distinguishing smokers with and without lung cancer. In this proposal, we will 1) validate this diagnostic airway biomarker in a large independent cohort of smokers with suspicion for lung cancer; 2) evaluate our biomarker's accuracy in predicting the presence of lung cancer in stage 1 disease; 3) integrate airway gene expression profiles with established clinical risk factors for disease to produce a clinicogenomic predictive model that can guide patient evaluation and management; 4) develop a second gene expression signature in normal airway epithelium capable of distinguishing small cell vs. non-small cell lung cancer using novel reverse engineering algorithms. These studies will produce a relatively noninvasive tool effective in diagnosing lung cancer at an early and potentially curable stage. These gene expression-based biomarkers may eliminate the need for additional and often more invasive diagnostic tests that are costly, incur risk, and prolong the diagnostic evaluation of smokers with suspicion of lung cancer.