Discovery of Biomarkers for Lung Cancer Metastasis

肺癌转移生物标志物的发现

• 批准号: 6917440
• 负责人: EDWARD F PATZ
• 金额: $ 27.22万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2005
• 资助国家: 美国
• 起止时间: 2005-04-01 至 2009-03-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/6917440
• 关键词: biomarker; blood chemistry; clinical research; human tissue; immunocytochemistry; mass spectrometry; matrix assisted laser desorption ionization; metastasis; molecular oncology; neoplasm /cancer classification /staging; neoplasm /cancer relapse /recurrence; nonsmall cell lung cancer; patient care management; prognosis; protein quantitation /detection; proteomics

DESCRIPTION (provided by applicant): Lung cancer remains a significant public health issue and accounts for 28% of all cancer deaths in the United States. Most patients present with late stage disease, although up to 50% of those with clinical stage I non-small cell lung cancer (NSCLC) will develop metastasis within 5 years of the initial diagnosis. This suggests that many of the patients who undergo resection have undetectable metastasis at the time of presentation, and the only way to determine which patients will recur is with serial radiographs. The identification of specific biomarkers in the primary tumor that predicts metastasis would be an invaluable asset in the management of patients with NSCLC. In addition, identification of protein responsible for the development of metastatic disease has the potential to be a therapeutic target. This proposal is an extension of prior work in our laboratory, using a matrix assisted laser desorption/ionization-time of flight mass spectrometry (MALDI-TOF MS) platform to elucidate protein biomarkers. We will generate protein expression profiles from early stage tumors that recur and compare this to tumors that do not recur. We will mine the data to determine differential expression of ion peaks, identify the proteins, and then validate the markers as biomarkers predictive of metastatic disease in a larger cohort series. This translational project will focus on an essential prognostic issue in lung cancer, but this model can be applied to any other diagnostic question in oncology.

描述（由申请人提供）：肺癌仍然是一个重要的公共卫生问题，占美国所有癌症死亡的28%。大多数患者表现为晚期疾病，尽管高达50%的临床I期非小细胞肺癌（NSCLC）患者将在初次诊断后5年内发生转移。这表明，许多接受切除术的患者在出现时有无法检测到的转移，确定哪些患者会复发的唯一方法是连续X线片。在原发性肿瘤中识别预测转移的特异性生物标志物将是NSCLC患者管理的宝贵资产。此外，鉴定负责转移性疾病发展的蛋白质具有成为治疗靶点的潜力。该建议是我们实验室先前工作的延伸，使用基质辅助激光解吸/电离飞行时间质谱（MALDI-TOF MS）平台来阐明蛋白质生物标志物。我们将从复发的早期肿瘤中生成蛋白质表达谱，并将其与不复发的肿瘤进行比较。我们将挖掘数据以确定离子峰的差异表达，鉴定蛋白质，然后在更大的队列系列中验证标记物作为预测转移性疾病的生物标志物。这个翻译项目将集中在肺癌的一个基本预后问题上，但这个模型可以应用于肿瘤学中的任何其他诊断问题。