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

吸烟者气道基因表达：肺癌的早期诊断生物标志物

• 批准号: 8037710
• 负责人: Avrum E Spira
• 金额: $ 29.95万
• 依托单位: BOSTON UNIVERSITY MEDICAL CAMPUS
• 依托单位国家: 美国
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-05-01 至 2013-02-28
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8037710
• 关键词: Age; Algorithms; Biological Markers; Biopsy; Bronchi; Bronchoscopy; Cancer Etiology; Cells; Cessation of life; Clinical; Clinical Data; Collaborations; Computational algorithm; Data; Development; Diagnosis; Diagnostic; Diagnostic tests; Disease; Drug Metabolic Detoxication; Early Diagnosis; Effectiveness; Engineering; Enzymes; Epigenetic Process; Epithelial; Epithelial Cells; Evaluation; Excision; Gene Expression; Gene Expression Profile; Genetic; Goals; Histologic; Interdisciplinary Study; Ireland; Lung; Malignant Neoplasms; Malignant neoplasm of lung; Medical center; Modeling; Molecular Profiling; Neoplasm Metastasis; Non-Small-Cell Lung Carcinoma; Oligonucleotide Microarrays; Operative Surgical Procedures; Outcome; Patients; Pattern; Play; Population; Predictive Value; Probability; Pulmonary Mass; Recruitment Activity; Research Personnel; Risk; Risk Factors; Role; Sampling; Screening procedure; Smoker; Smoking History; Staging; Testing; Therapeutic; Tobacco; Tobacco smoke; Toxin; United States; Voting; Weight; Woman; Work; airway epithelium; base; cell injury; cell type; cigarette smoking; clinically relevant; cohort; computerized tools; disease diagnosis; disorder subtype; experience; innovation; lung carcinogenesis; men; minimally invasive; mortality; non-smoker; novel; predictive modeling; programs; research clinical testing; response; tool

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.

描述（由申请人提供）：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部分是由于缺乏有效的工具来在疾病扩散到区域淋巴结或转移到肺部以外之前的早期诊断疾病。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气道上皮细胞损伤的程度和患肺癌的风险。本申请的目的是开发一种胸内（主支气管）气道基因表达谱，能够作为临床疑似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的假设，即吸烟者的组织学正常气道上皮中的基因表达模式反映了烟草烟雾引起的损伤的类型和程度，并且可以预测吸烟者患肺癌的风险。使用寡核苷酸微阵列，我们已经确定了在支气管镜检查中获得的组织学正常的大气道上皮细胞中的基因表达特征，该基因表达特征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性的生物标志物。在该提案中，我们将1）在怀疑肺癌的吸烟者的大型独立队列中验证这种诊断性气道生物标志物; 2）评估我们的生物标志物在预测1期疾病中肺癌存在的准确性; 3）将气道基因表达谱与疾病的已建立的临床风险因素整合，以产生可以指导患者评估和管理的临床基因组学预测模型; 4）使用新的逆向工程算法开发能够区分小细胞肺癌与非小细胞肺癌的正常气道上皮中的第二基因表达标记。这些研究将产生一种相对非侵入性的工具，有效地诊断肺癌的早期和潜在的可治愈阶段。这些基于基因表达的生物标志物可以消除对额外的和通常更具侵入性的诊断测试的需要，这些测试成本高，风险大，并且延长了对怀疑患有肺癌的吸烟者的诊断评估。

项目成果

Comparison of smoking-induced gene expression on Affymetrix Exon and 3'-based expression arrays.

Affymetrix 外显子和基于 3 的表达阵列上吸烟诱导的基因表达的比较。

• 发表时间: 2007
• 期刊: Genome informatics. International Conference on Genome Informatics
• 作者: Zhang,Xiaoling;Liu,Gang;Lenburg,MarcE;Spira,Avrum
• 通讯作者: Spira,Avrum

Reversible and permanent effects of tobacco smoke exposure on airway epithelial gene expression.

• DOI: 10.1186/gb-2007-8-9-r201
• 发表时间: 2007
• 期刊: Genome biology
• 影响因子: 12.3
• 作者: Beane J;Sebastiani P;Liu G;Brody JS;Lenburg ME;Spira A
• 通讯作者: Spira A

The field of tissue injury in the lung and airway.

• DOI: 10.1158/1940-6207.capr-08-0174
• 发表时间: 2008-11
• 期刊: Cancer prevention research (Philadelphia, Pa.)
• 作者: Steiling K;Ryan J;Brody JS;Spira A
• 通讯作者: Spira A

Smoking-induced gene expression changes in the bronchial airway are reflected in nasal and buccal epithelium.

吸烟引起的基因表达在支气管气道中的变化反映在鼻和颊上皮中。

• DOI: 10.1186/1471-2164-9-259
• 发表时间: 2008-05-30
• 期刊: BMC GENOMICS
• 影响因子: 4.4
• 作者: Sridhar, Sriram;Schembri, Frank;Zeskind, Julie;Shah, Vishal;Gustafson, Adam M.;Steiling, Katrina;Liu, Gang;Dumas, Yves-Martine;Zhang, Xiaohui;Brody, Jerome S.;Lenburg, Marc E.;Spira, Avrum
• 通讯作者: Spira, Avrum

Clinical impact of high-throughput gene expression studies in lung cancer.

• DOI: 10.1097/jto.0b013e31819151f8
• 发表时间: 2009-01
• 期刊: Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
• 作者: Beane J;Spira A;Lenburg ME
• 通讯作者: Lenburg ME