Discovery of Biomarkers for Lung Cancer Metastasis

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人数的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）患者在最初诊断后的5年内会发生转移。这表明，许多接受切除的患者在出现时无法检测到转移，确定哪些患者会复发的唯一方法是连续x线片。在原发肿瘤中识别预测转移的特异性生物标志物将是非小细胞肺癌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有可能成为治疗靶点。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记物。这个转化项目将集中于肺癌的基本预后问题，但这个模型可以应用于任何其他肿瘤学诊断问题。

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.