Discovery of Biomarkers for Lung Cancer Metastasis

肺癌转移生物标志物的发现

• 批准号: 7027067
• 负责人: EDWARD F PATZ
• 金额: $ 26.58万
• 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/7027067
• 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(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人数的28%。大多数患者存在晚期疾病，尽管临床I期非小细胞肺癌(NSCLC)高达50%的患者在首次诊断后5年内会发生转移。这表明，许多接受切除的患者在出现转移时无法检测到转移，而确定哪些患者会复发的唯一方法是通过连续的X线片。在原发肿瘤中识别预测转移的特定生物标记物在非小细胞肺癌患者的治疗中将是一项宝贵的资产。此外，识别与转移性疾病发展有关的蛋白质有可能成为治疗的靶点。这项建议是我们实验室以前工作的扩展，使用基质辅助激光解吸/电离飞行时间质谱仪(MALDI-TOF MS)平台来阐明蛋白质生物标记物。我们将从复发的早期肿瘤中生成蛋白质表达谱，并将其与未复发的肿瘤进行比较。我们将挖掘这些数据来确定离子峰的差异表达，识别蛋白质，然后在更大的队列序列中验证这些标记作为预测转移性疾病的生物标记。这个翻译项目将专注于肺癌的一个重要的预后问题，但这个模型可以应用于肿瘤学的任何其他诊断问题。